Demetris Koutsoyiannis

Professor, Civil Engineer, Dr. Engineer
D.Koutsoyiannis@itia.ntua.gr
+30-2107722831
http://www.itia.ntua.gr/dk/

Participation in research projects

Participation as Project Director

  1. Upgrade of the hydraulics laboratory for the modeling of water supply networks & design and operation optimization study
  2. Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO)
  3. DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools
  4. Integrated study for the investigation of the quantity, quality and recovery of the underwater springs of the Stoupa region in Municipality of Lefktros, Messinia
  5. Flood risk estimation and forecast using hydrological models and probabilistic methods
  6. Nonlinear methods in multicriteria water resource optimization problems
  7. Support on the compilation of the national programme for water resources management and preservation
  8. Investigation of management scenarios for the Smokovo reservoir
  9. Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)
  10. Testing of the new measuring system of the aqueduct of Mornos
  11. Modernisation of the supervision and management of the water resource system of Athens
  12. Completion of the classification of quantitative and qualitative parameters of water resources in water districts of Greece
  13. Appraisal of river sediment deposits in reservoirs of hydropower dams
  14. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3
  15. Systematisation of the raw data archive of surface and subsurface waters of the Ministry of Agriculture in Thessalia
  16. Upgrading and updating of hydrological information of Thessalia
  17. Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems
  18. Hydroscope II - Creation of a National Databank for Hydrological and Meteorological Information
  19. Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information

Participation as Principal Investigator

  1. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system
  2. Building the Future of Transnational Cooperation in Water Resources in South East Europe (EDUCATE!)
  3. Investigation of scenarios for the management and protection of the quality of the Plastiras Lake
  4. National databank for hydrological and meteorological information - Hydroscope 2000
  5. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2
  6. AFORISM: A comprehensive forecasting system for flood risk mitigation and control
  7. Development of a relational data base for management and processing of hydrometric information
  8. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 1
  9. A pilot study for the management of the Louros and Arachthos watersheds
  10. Appraisal of existing potential for improving the water supply of greater Athens - Phase 2
  11. Appraisal of existing potential for improving the water supply of greater Athens - Phase 1
  12. Hydrological investigation of the Thessalia water basin

Participation as Researcher

  1. Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information"
  2. Observations, Analysis and Modeling of Lightning Activity in Thunderstorms, for Use in Short Term Forecasting of Flash Floods
  3. Development of a Geographical Information System and an Internet application for the supervision of Kephisos protected areas
  4. EU COST Action C22: Urban Flood Management
  5. Investigation and remedy of the stability problems of the banks and bed of the Philothei Creek using mathematical models and modern environmental methods
  6. Study and research network with applications in Greece and Cyprus
  7. Generation of spatially consistent rainfall data - Refinement and testing of simplified models
  8. Assessment of sediment generation in Thriasio
  9. Development of legislation framework for the drinking water of Athens
  10. Generation of spatially consistent rainfall data
  11. Integrated management of the riparian ecosystem of the Sperhios river
  12. A pilot study for the water resources management of the Epirus water district
  13. Study of the measuring system of the aqueduct network of Athens - Phase 1
  14. Investigation of use of stormwater for irrigation - Application to the area of Archanes municipality
  15. Environmental impacts of the irrigation project in the lake Mikri Prespa, Florina, Phase A
  16. Estimation and integrated management of the water resources and environment of the Aliakmon watershed
  17. Water quality and assimilative capacity investigations of Kalamas river and lake Pamvotis (Ioannina)

Participation in engineering studies

  1. Pleriminary study of Almopaios dam
  2. Investigation of the hydrographic network development in Mavro Vouno, Grammatiko, Attica, Greece
  3. Study of the management of Kephisos
  4. Delineation of the Arachthos River bed in the town of Arta
  5. Specific Technical Study for the Ecological Flow from the Dam of Stratos
  6. Development of tools for the water resource management of the hydrological district of Aegean islands
  7. Water resource management of the Integrated Tourist Development Area in Messenia
  8. Technical consulting for the floods of Lower Acheloos and Edesseos
  9. Expertise for the quality control of engineering studies for the project "Water supply of Patra from Peiros and Parapeiros rivers"
  10. Characterization of the size of Zaravina lake in Delvinaki area of the prefecture of Ioannina
  11. Diversion of the Soulou Stream for the Development of Lignite Exploitations of the Public Power Corporation in the Mine of Southern Field of Region Kozani-Ptolemais
  12. Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina
  13. Study of sewerage and wastewater treatment of the Municipality of Ellomeno in Leukas
  14. Hydraulic study for drainage of the Kanavari-Dombrena-Prodromos road
  15. Hydrological and hydraulic study for the flood protection of the new railway in the region of Sperhios river
  16. Study of the enhancement of water flow in Lethaeos and Ayiaminiotis rivers
  17. Engineering consultant for the project "Water supply of Heracleio and Agios Nicolaos from the Aposelemis dam"
  18. Flood Protection Works of Diakoniaris Stream, Preliminary Study
  19. Study of the Segment Antirrio-Kefalovriso of the Western Road Axis
  20. Preliminary Water Supply Study of the Thermoelectric Livadia Power Plant
  21. Consultative service for the spring "Kephalovriso" in Kaloskope
  22. Engineering study for the licence of positioning of the Valorema Small Hydroelectric Project
  23. Study of the Potamos River, Corfu
  24. Complementary study of environmental impacts from the diversion of Acheloos to Thessaly
  25. Management study of the river Boeoticos Kephisos and the lakes Hylike and Paralimne
  26. Compilation of specifications and requirements for the elaboration of environmental impact studies for various works
  27. Estimation of losses from DXX canal in the irrigation network of Lower Acheloos
  28. Concerted actions for the sector of environment in Santorine and Therasia islands
  29. Engineering report of the Korinthos sewer system, Study of the Xerias creek, Introductory part
  30. Study of the water supply of the wider Rhodes from Gadouras dam: Aqueduct and water treatment plant
  31. Engineering study of the hydraulic project of old and new river bed of Peneios in Larisa
  32. General outline of the Acheloos River diversion project
  33. Water resources management of the Evinos river basin and hydrogeological study of the Evinos karstic system
  34. Assessment of the influence of forest fire of 1995 in the increase of sediment yield of the Megalo Rema in Raphena
  35. Integrated study of the environmental impacts from Acheloos diversion
  36. Study of environmental impacts from the small hydroelectric work in Metsovitikos river
  37. Arachthos River, Aghios Nicolaos hydroelectric project, Engineering Report
  38. Engineering study for improving the water supply of Athens with the construction of a dam at the Evinos River
  39. Master plan of the land reclamation works of the Arta plain
  40. Engineering study of the regulation of the Kallithea Stream in Mytilene
  41. Study of the Faneromeni dam in Mesara, Crete - Engineering report
  42. Study of the Plakiotissa dam in Mesara, Crete - Engineering report
  43. Study of the wastewater treatment plant of Aghios Nicolaos, Crete
  44. Engineering study of the flood protection works in the Boeoticos Kephisos river basin
  45. Engineering study of the flood protection and drainage works and the dam in the Artzan-Amatovo region
  46. Arachthos River, Steno - Kalaritikos hydroelectric project, Engineering Report
  47. Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Engineering report
  48. Preliminary study of the water supply of Karystos and Kallianos municipalities from the Demosari springs
  49. Master plan of Dereio dam
  50. Engineering study of sewer system and the wastewater treatment plant of Farsala
  51. Preliminary study of the reconstruction of the state-run saltern of Mesi, Komotene
  52. Arachthos River, Middle Course hydroelectric projects, Master Plan
  53. Study for the restoration, fixing, protection and prominence of the archaeological monument of Knossos
  54. Study of the sewer system of Neapolis, Lasithi, Engineering report
  55. Alternative studies for the irrigation of the Lasithi plateau
  56. Master plan of the foul sewer system of Kanallaki, Preveza
  57. Preliminary study of the sewer system of Kanallaki, Preveza
  58. Arachthos River, Middle Course hydroelectric projects, Alternative studies
  59. Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Preliminary study
  60. Study of the sewer system of Neapolis, Lasithi, Master plan
  61. Study of the sewer system of Neapolis, Lasithi, Alternative studies
  62. Engineering study of restoration of the water supply of Karpenesi
  63. Engineering study of the sewer system of the Karpenesi municipality
  64. Engineering study of the sewer system of the Karpenesi municipality

Published work

Publications in scientific journals

  1. D. Koutsoyiannis, and G.-F. Sargentis, Entropy and wealth, Entropy, 23 (10), 1356, doi:10.3390/e23101356, 2021.
  2. N. Mamassis, K. Mazi, E. Dimitriou, D. Kalogeras, N. Malamos, S. Lykoudis, A. Koukouvinos, I. L. Tsirogiannis, I. Papageorgaki, A. Papadopoulos, Y. Panagopoulos, D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. Vitantzakis, N. Kappos, D. Katsanos, B. Psiloglou, E. Rozos, T. Kopania, I. Koletsis, and A. D. Koussis, OpenHi.net: A synergistically built, national-scale infrastructure for monitoring the surface waters of Greece, Water, 13 (19), 2779, doi:10.3390/w13192779, 2021.
  3. P. Dimitriadis, T. Iliopoulou, G.-F. Sargentis, and D. Koutsoyiannis, Spatial Hurst–Kolmogorov Clustering, Encyclopedia, 1 (4), 1010–1025, doi:10.3390/encyclopedia1040077, 2021.
  4. D. Koutsoyiannis, and P. Dimitriadis, Towards generic simulation for demanding stochastic processes, Sci, 3, 34, doi:10.3390/sci3030034, 2021.
  5. G.-F. Sargentis, P. Siamparina, G.-K. Sakki, A. Efstratiadis, M. Chiotinis, and D. Koutsoyiannis, Agricultural land or photovoltaic parks? The water–energy–food nexus and land development perspectives in the Thessaly plain, Greece, Sustainability, 13 (16), 8935, doi:10.3390/su13168935, 2021.
  6. A. N. Angelakis, M. Valipour, A.T. Ahmed, V. Tzanakakis, N.V. Paranychianakis, J. Krasilnikoff, R. Drusiani, L.W. Mays, F. El Gohary, D. Koutsoyiannis, S. Khan, and L.J. Del Giacco, Water conflicts: from ancient to modern times and in the future, Sustainability, 13 (8), 4237, doi:10.3390/su13084237, 2021.
  7. S. Vavoulogiannis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Multiscale temporal irreversibility of streamflow and its stochastic modelling, Hydrology, 8 (2), 63, doi:10.3390/hydrology8020063, 2021.
  8. L. Katikas, P. Dimitriadis, D. Koutsoyiannis, T. Kontos, and P. Kyriakidis, A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series, Applied Energy, 295, 116873, doi:10.1016/j.apenergy.2021.116873, 2021.
  9. P. Dimitriadis, D. Koutsoyiannis, T. Iliopoulou, and P. Papanicolaou, A global-scale investigation of stochastic similarities in marginal distribution and dependence structure of key hydrological-cycle processes, Hydrology, 8 (2), 59, doi:10.3390/hydrology8020059, 2021.
  10. G.-F. Sargentis, T. Iliopoulou, P. Dimitriadis, N. Mamassis, and D. Koutsoyiannis, Stratification: An entropic view of society's structure, World, 2, 153–174, doi:10.3390/world2020011, 2021.
  11. D. Koutsoyiannis, Rethinking climate, climate change, and their relationship with water, Water, 13 (6), 849, doi:10.3390/w13060849, 2021.
  12. D. Koutsoyiannis, Advances in stochastics of hydroclimatic extremes, L'Acqua, 2021 (1), 23–32, 2021.
  13. D. Koutsoyiannis, and N. Mamassis, From mythology to science: the development of scientific hydrological concepts in the Greek antiquity and its relevance to modern hydrology, Hydrology and Earth System Sciences, 25, 2419–2444, doi:10.5194/hess-25-2419-2021, 2021.
  14. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, A stochastic view of varying styles in art paintings, Heritage, 4, 21, doi:10.3390/heritage4010021, 2021.
  15. G.-F. Sargentis, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Landscape planning of infrastructure through focus points’ clustering analysis. Case study: Plastiras artificial lake (Greece), Infrastructures, 6 (1), 12, doi:10.3390/infrastructures6010012, 2021.
  16. A. Efstratiadis, I. Tsoukalas, and D. Koutsoyiannis, Generalized storage-reliability-yield framework for hydroelectric reservoirs, Hydrological Sciences Journal, 66 (4), 580–599, doi:10.1080/02626667.2021.1886299, 2021.
  17. K. Glynis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of daily air temperature extremes from a global ground station network, Stochastic Environmental Research & Risk Assessment, doi:10.1007/s00477-021-02002-3, 2021.
  18. G.-F. Sargentis, T. Iliopoulou, S. Sigourou, P. Dimitriadis, and D. Koutsoyiannis, Evolution of clustering quantified by a stochastic method — Case studies on natural and human social structures, Sustainability, 12 (19), 7972, doi:10.3390/su12197972, 2020.
  19. D. Koutsoyiannis, and Z. W. Kundzewicz, Atmospheric temperature and CO₂: Hen-or-egg causality?, Sci, 2 (4), 83, doi:10.3390/sci2040083, 2020.
  20. R. Ioannidis, and D. Koutsoyiannis, A review of land use, visibility and public perception of renewable energy in the context of landscape impact, Applied Energy, 276, 115367, doi:10.1016/j.apenergy.2020.115367, 2020.
  21. Z. W. Kundzewicz, I. Pińskwar, and D. Koutsoyiannis, Variability of global mean annual temperature is significantly influenced by the rhythm of ocean-atmosphere oscillations, Science of the Total Environment, 747, 141256, doi:10.1016/j.scitotenv.2020.141256, 2020.
  22. G.-F. Sargentis, P. Dimitriadis, R. Ioannidis, T. Iliopoulou, E. Frangedaki, and D. Koutsoyiannis, Optimal utilization of water resources for local communities in mainland Greece (case study of Karyes, Peloponnese), Procedia Manufacturing, 44, 253–260, doi:10.1016/j.promfg.2020.02.229, 2020.
  23. T. Iliopoulou, and D. Koutsoyiannis, Projecting the future of rainfall extremes: better classic than trendy, Journal of Hydrology, 588, doi:10.1016/j.jhydrol.2020.125005, 2020.
  24. G.-F. Sargentis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues of Leonardo Da Vinci’s and Pablo Picasso’s paintings with stochastic evaluation, Heritage, 3 (2), 283–305, doi:10.3390/heritage3020017, 2020.
  25. D. Koutsoyiannis, Revisiting the global hydrological cycle: is it intensifying?, Hydrology and Earth System Sciences, 24, 3899–3932, doi:10.5194/hess-24-3899-2020, 2020.
  26. G. Papacharalampous, H. Tyralis, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale, Advances in Water Resources, 136, 103470, doi:10.1016/j.advwatres.2019.103470, 2020.
  27. G. Papacharalampous, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models, Advances in Water Resources, 136, 103471, doi:10.1016/j.advwatres.2019.103471, 2020.
  28. D. Koutsoyiannis, Simple stochastic simulation of time irreversible and reversible processes, Hydrological Sciences Journal, 65 (4), 536–551, doi:10.1080/02626667.2019.1705302, 2020.
  29. R. Ioannidis, T. Iliopoulou, C. Iliopoulou, L. Katikas, A. Petsou, M.-E. Merakou, M.-E. Asimomiti, N. Pelekanos, G. Koudouris, P. Dimitriadis, C. Plati, E. Vlahogianni, K. Kepaptsoglou, N. Mamassis, and D. Koutsoyiannis, Solar-powered bus route: introducing renewable energy into a university campus transport system, Advances in Geosciences, 49, doi:10.5194/adgeo-49-215-2019, 2019.
  30. G. Papacharalampous, H. Tyralis, A. Langousis, A. W. Jayawardena, B. Sivakumar, N. Mamassis, A. Montanari, and D. Koutsoyiannis, Probabilistic hydrological post-processing at scale: Why and how to apply machine-learning quantile regression algorithms, Water, doi:10.3390/w11102126, 2019.
  31. F. Lombardo, F. Napolitano, F. Russo, and D. Koutsoyiannis, On the exact distribution of correlated extremes in hydrology, Water Resources Research, 55 (12), 10405–10423, doi:10.1029/2019WR025547, 2019.
  32. P. Dimitriadis, and D. Koutsoyiannis, The mode of the climacogram estimator for a Gaussian Hurst-Kolmogorov process, Journal of Hydroinformatics, doi:10.2166/hydro.2019.038, 2019.
  33. T. Iliopoulou, and D. Koutsoyiannis, Revealing hidden persistence in maximum rainfall records, Hydrological Sciences Journal, 64 (14), 1673–1689, doi:10.1080/02626667.2019.1657578, 2019.
  34. G.-F. Sargentis, P. Dimitriadis, R. Ioannidis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic evaluation of landscapes transformed by renewable energy installations and civil works, Energies, 12 (4), 2817, doi:10.3390/en12142817, 2019.
  35. G.-F. Sargentis, R. Ioannidis, G. Karakatsanis, S. Sigourou, N. D. Lagaros, and D. Koutsoyiannis, The development of the Athens water supply system and inferences for optimizing the scale of water infrastructures, Sustainability, 11 (9), 2657, doi:10.3390/su11092657, 2019.
  36. D. Koutsoyiannis, Time’s arrow in stochastic characterization and simulation of atmospheric and hydrological processes, Hydrological Sciences Journal, 64 (9), 1013–1037, doi:10.1080/02626667.2019.1600700, 2019.
  37. E. Volpi, A. Fiori, S. Grimaldi, F. Lombardo, and D. Koutsoyiannis, Save hydrological observations! Return period estimation without data decimation, Journal of Hydrology, doi:10.1016/j.jhydrol.2019.02.017, 2019.
  38. D. Koutsoyiannis, Knowable moments for high-order stochastic characterization and modelling of hydrological processes, Hydrological Sciences Journal, 64 (1), 19–33, doi:10.1080/02626667.2018.1556794, 2019.
  39. T. Iliopoulou, C. Aguilar , B. Arheimer, M. Bermúdez, N. Bezak, A. Ficchi, D. Koutsoyiannis, J. Parajka, M. J. Polo, G. Thirel, and A. Montanari, A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers, Hydrology and Earth System Sciences, 23, 73–91, doi:10.5194/hess-23-73-2019, 2019.
  40. A. Koskinas, A. Tegos, P. Tsira, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and Τ. Williamson, Insights into the Oroville Dam 2017 spillway incident, Geosciences, 9 (37), doi:10.3390/geosciences9010037, 2019.
  41. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes, Stochastic Environmental Research & Risk Assessment, doi:10.1007/s00477-018-1638-6, 2019.
  42. P. Dimitriadis, K. Tzouka, D. Koutsoyiannis, H. Tyralis, A. Kalamioti, E. Lerias, and P. Voudouris, Stochastic investigation of long-term persistence in two-dimensional images of rocks, Spatial Statistics, 29, 177–191, doi:10.1016/j.spasta.2018.11.002, 2019.
  43. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Univariate time series forecasting of temperature and precipitation with a focus on machine learning algorithms: a multiple-case study from Greece, Water Resources Management, 32 (15), 5207–5239, doi:10.1007/s11269-018-2155-6, 2018.
  44. T. Iliopoulou, D. Koutsoyiannis, and A. Montanari, Characterizing and modeling seasonality in extreme rainfall, Water Resources Research, 54 (9), 6242–6258, doi:10.1029/2018WR023360, 2018.
  45. N. Malamos, and D. Koutsoyiannis, Field survey and modelling of irrigation water quality indices in a Mediterranean island catchment: A comparison between spatial interpolation methods, Hydrological Sciences Journal, 63 (10), 1447–1467, doi:10.1080/02626667.2018.1508874, 2018.
  46. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, A stochastic model for the hourly solar radiation process for application in renewable resources management, Advances in Geosciences, 45, 139–145, doi:10.5194/adgeo-45-139-2018, 2018.
  47. N. Quinn, G. Blöschl, A. Bardossy, A. Castellarin, M. Clark, C. Cudennec, D. Koutsoyiannis, U. Lall, L. Lichner, J. Parajka, C.D. Peters-Lidard, G. Sander, H. H. G. Savenije, K. Smettem, H. Vereecken, A. Viglione, P. Willems, A. Wood, R. Woods, C.-Y. Xu, and E. Zehe, Invigorating hydrological research through journal publications, Hydrological Sciences Journal, 63 (8), 1113–1117, doi:10.1080/02626667.2018.1496632, 2018.
  48. E. Klousakou, M. Chalakatevaki, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, G. Karakatsanis, A. Efstratiadis, N. Mamassis, R. Tomani, E. Chardavellas, and D. Koutsoyiannis, A preliminary stochastic analysis of the uncertainty of natural processes related to renewable energy resources, Advances in Geosciences, 45, 193–199, doi:10.5194/adgeo-45-193-2018, 2018.
  49. I. Tsoukalas, C. Makropoulos, and D. Koutsoyiannis, Simulation of stochastic processes exhibiting any-range dependence and arbitrary marginal distributions, Water Resources Research, 54 (11), 9484–9513, doi:10.1029/2017WR022462, 2018.
  50. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Predictability of monthly temperature and precipitation using automatic time series forecasting methods, Acta Geophysica, 66 (4), 807–831, doi:10.1007/s11600-018-0120-7, 2018.
  51. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, One-step ahead forecasting of geophysical processes within a purely statistical framework, Geoscience Letters, 5, 12, doi:10.1186/s40562-018-0111-1, 2018.
  52. H. Tyralis, P. Dimitriadis, D. Koutsoyiannis, P.E. O’Connell, K. Tzouka, and T. Iliopoulou, On the long-range dependence properties of annual precipitation using a global network of instrumental measurements, Advances in Water Resources, 111, 301–318, doi:10.1016/j.advwatres.2017.11.010, 2018.
  53. P. Dimitriadis, and D. Koutsoyiannis, Stochastic synthesis approximating any process dependence and distribution, Stochastic Environmental Research & Risk Assessment, 32 (6), 1493–1515, doi:10.1007/s00477-018-1540-2, 2018.
  54. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, 556, 980–992, doi:10.1016/j.jhydrol.2016.07.015, 2018.
  55. T. Iliopoulou, S.M. Papalexiou, Y. Markonis, and D. Koutsoyiannis, Revisiting long-range dependence in annual precipitation, Journal of Hydrology, 556, 891–900, doi:10.1016/j.jhydrol.2016.04.015, 2018.
  56. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, European Water, 59, 303–309, 2017.
  57. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Forecasting of geophysical processes using stochastic and machine learning algorithms, European Water, 59, 161–168, 2017.
  58. D. Koutsoyiannis, Entropy production in stochastics, Entropy, 19 (11), 581, doi:10.3390/e19110581, 2017.
  59. A. Tegos, N. Malamos, A. Efstratiadis, I. Tsoukalas, A. Karanasios, and D. Koutsoyiannis, Parametric modelling of potential evapotranspiration: a global survey, Water, 9 (10), 795, doi:10.3390/w9100795, 2017.
  60. E. Moschos, G. Manou, P. Dimitriadis, V. Afendoulis, D. Koutsoyiannis, and V. Tsoukala, Harnessing wind and wave resources for a Hybrid Renewable Energy System in remote islands: a combined stochastic and deterministic approach, Energy Procedia, 125, 415–424, doi:10.1016/j.egypro.2017.08.084, 2017.
  61. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, Investigation on the stochastic nature of the solar radiation process, Energy Procedia, 125, 398–404, 2017.
  62. K. Mavroyeoryos, I. Engonopoulos, H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system, Energy Procedia, 125, 435–442, doi:10.1016/j.egypro.2017.08.095, 2017.
  63. G. Karakatsanis, D. Roussis, Y. Moustakis, N. Gournari, I. Parara, P. Dimitriadis, and D. Koutsoyiannis, Energy, variability and weather finance engineering, Energy Procedia, 125, 389–397, doi:10.1016/j.egypro.2017.08.073, 2017.
  64. M. Chalakatevaki, P. Stamou, S. Karali, V. Daniil, P. Dimitriadis, K. Tzouka, T. Iliopoulou, D. Koutsoyiannis, P. Papanicolaou, and N. Mamassis, Creating the electric energy mix in a non-connected island, Energy Procedia, 125, 425–434, doi:10.1016/j.egypro.2017.08.089, 2017.
  65. K. Papoulakos, G. Pollakis, Y. Moustakis, A. Markopoulos, T. Iliopoulou, P. Dimitriadis, D. Koutsoyiannis, and A. Efstratiadis, Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability, Energy Procedia, 125, 405–414, doi:10.1016/j.egypro.2017.08.078, 2017.
  66. C. Pappas, M.D. Mahecha, D.C. Frank, F. Babst, and D. Koutsoyiannis, Ecosystem functioning is enveloped by hydrometeorological variability, Nature Ecology & Evolution, 1, 1263–1270, doi:10.1038/s41559-017-0277-5, 2017.
  67. H. Tyralis, and D. Koutsoyiannis, On the prediction of persistent processes using the output of deterministic models, Hydrological Sciences Journal, 62 (13), 2083–2102, doi:10.1080/02626667.2017.1361535, 2017.
  68. F. Lombardo, E. Volpi, D. Koutsoyiannis, and F. Serinaldi, A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall, Water Resources Research, 53 (6), 4586–4605, doi:10.1002/2017WR020529, 2017.
  69. A. Tegos, H. Tyralis, D. Koutsoyiannis, and K. H. Hamed, An R function for the estimation of trend signifcance under the scaling hypothesis- application in PET parametric annual time series, Open Water Journal, 4 (1), 66–71, 6, 2017.
  70. H. Tyralis, A. Tegos, A. Delichatsiou, N. Mamassis, and D. Koutsoyiannis, A perpetually interrupted interbasin water transfer as a modern Greek drama: Assessing the Acheloos to Pinios interbasin water transfer in the context of integrated water resources management, Open Water Journal, 4 (1), 113–128, 12, 2017.
  71. I. Deligiannis, P. Dimitriadis, Ο. Daskalou, Y. Dimakos, and D. Koutsoyiannis, Global investigation of double periodicity οf hourly wind speed for stochastic simulation; application in Greece, Energy Procedia, 97, 278–285, doi:10.1016/j.egypro.2016.10.001, 2016.
  72. Y. Markonis, S. C. Batelis, Y. Dimakos, E. C. Moschou, and D. Koutsoyiannis, Temporal and spatial variability of rainfall over Greece, Theoretical and Applied Climatology, doi:10.1007/s00704-016-1878-7, 2016.
  73. Y. Markonis, A. N. Angelakis, J. Christy, and D. Koutsoyiannis, Climatic variability and the evolution of water technologies in Crete, Hellas, Water History, 8 (2), 137–157, doi:10.1007/s12685-016-0159-9, 2016.
  74. S.M. Papalexiou, and D. Koutsoyiannis, A global survey on the seasonal variation of the marginal distribution of daily precipitation, Advances in Water Resources, 94, 131–145, doi:10.1016/j.advwatres.2016.05.005, 2016.
  75. D. Koutsoyiannis, G. Blöschl, A. Bardossy, C. Cudennec, D. Hughes, A. Montanari, I. Neuweiler, and H. H. G. Savenije, Joint Editorial: Fostering innovation and improving impact assessment for journal publications in hydrology, Hydrological Sciences Journal, 61 (7), 1170–1173, doi:10.1080/02626667.2016.1162953, 2016.
  76. D. Koutsoyiannis, M. Acreman, A. Castellarin, H. H. G. Savenije, C. Cudennec, G. Blöschl, G. Young, A. Montanari, and F. Watkins, Should auld acquaintance be forgot? Comment on “Farewell, HSJ!—address from the retiring editor” by Z.W. Kundzewicz, Hydrological Sciences Journal, doi:10.1080/02626667.2016.1150032, 2016.
  77. P. Dimitriadis, A. Tegos, A. Oikonomou, V. Pagana, A. Koukouvinos, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping, Journal of Hydrology, 534, 478–492, doi:10.1016/j.jhydrol.2016.01.020, 2016.
  78. Y. Markonis, and D. Koutsoyiannis, Scale-dependence of persistence in precipitation records, Nature Climate Change, 6, 399–401, doi:10.1038/nclimate2894, 2016.
  79. P.E. O’Connell, D. Koutsoyiannis, H. F. Lins, Y. Markonis, A. Montanari, and T.A. Cohn, The scientific legacy of Harold Edwin Hurst (1880 – 1978), Hydrological Sciences Journal, 61 (9), 1571–1590, doi:10.1080/02626667.2015.1125998, 2016.
  80. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of turbulence and hydrometeorological processes, Hydrological Sciences Journal, 61 (9), 1623–1640, doi:10.1080/02626667.2015.1085988, 2016.
  81. N. Malamos, and D. Koutsoyiannis, Bilinear surface smoothing for spatial interpolation with optional incorporation of an explanatory variable. Part 2: Application to synthesized and rainfall data, Hydrological Sciences Journal, 61 (3), 527–540, doi:10.1080/02626667.2015.1080826, 2016.
  82. N. Malamos, and D. Koutsoyiannis, Bilinear surface smoothing for spatial interpolation with optional incorporation of an explanatory variable. Part 1:Theory, Hydrological Sciences Journal, 61 (3), 519–526, doi:10.1080/02626667.2015.1051980, 2016.
  83. P. Dimitriadis, D. Koutsoyiannis, and K. Tzouka, Predictability in dice motion: how does it differ from hydrometeorological processes?, Hydrological Sciences Journal, 61 (9), 1611–1622, doi:10.1080/02626667.2015.1034128, 2016.
  84. D. Koutsoyiannis, Generic and parsimonious stochastic modelling for hydrology and beyond, Hydrological Sciences Journal, 61 (2), 225–244, doi:10.1080/02626667.2015.1016950, 2016.
  85. E. Volpi, A. Fiori, S. Grimaldi, F. Lombardo, and D. Koutsoyiannis, One hundred years of return period: Strengths and limitations, Water Resources Research, doi:10.1002/2015WR017820, 2015.
  86. P. Dimitriadis, and D. Koutsoyiannis, Application of stochastic methods to double cyclostationary processes for hourly wind speed simulation, Energy Procedia, 76, 406–411, doi:10.1016/j.egypro.2015.07.851, 2015.
  87. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, Agriculture and Agricultural Science Procedia, 4, 2–9, doi:10.1016/j.aaspro.2015.03.002, 2015.
  88. K. Kollyropoulos, G. Antoniou, I. Kalavrouziotis, J. Krasilnikoff, D. Koutsoyiannis, and A. N. Angelakis, Hydraulic characteristics of the drainage systems of ancient Hellenic theatres: Case study of the theatre of Dionysus and its implications, Journal of Irrigation and Drainage Engineering (ASCE), 141 (11), doi:10.1061/(ASCE)IR.1943-4774.0000906, 2015.
  89. A. Tegos, N. Malamos, and D. Koutsoyiannis, A parsimonious regional parametric evapotranspiration model based on a simplification of the Penman-Monteith formula, Journal of Hydrology, 524, 708–717, doi:10.1016/j.jhydrol.2015.03.024, 2015.
  90. P. Dimitriadis, and D. Koutsoyiannis, Climacogram versus autocovariance and power spectrum in stochastic modelling for Markovian and Hurst–Kolmogorov processes, Stochastic Environmental Research & Risk Assessment, 29 (6), 1649–1669, doi:10.1007/s00477-015-1023-7, 2015.
  91. A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Hydrological modelling of temporally-varying catchments: Facets of change and the value of information, Hydrological Sciences Journal, 60 (7-8), 1438–1461, doi:10.1080/02626667.2014.982123, 2015.
  92. D. Koutsoyiannis, and A. Montanari, Negligent killing of scientific concepts: the stationarity case, Hydrological Sciences Journal, 60 (7-8), 1174–1183, doi:10.1080/02626667.2014.959959, 2015.
  93. N. Malamos, and D. Koutsoyiannis, Broken line smoothing for data series interpolation by incorporating an explanatory variable with denser observations: Application to soil-water and rainfall data, Hydrological Sciences Journal, doi:10.1080/02626667.2014.899703, 2015.
  94. A. Sikorska, A. Montanari, and D. Koutsoyiannis, Estimating the uncertainty of hydrological predictions through data-driven resampling techniques, Journal of Hydrologic Engineering (ASCE), 20 (1), doi:10.1061/(ASCE)HE.1943-5584.0000926, 2015.
  95. A. Montanari, and D. Koutsoyiannis, Modeling and mitigating natural hazards: Stationarity is immortal!, Water Resources Research, 50 (12), 9748–9756, doi:10.1002/2014WR016092, 2014.
  96. A. Efstratiadis, Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence, Environmental Modelling and Software, 62, 139–152, doi:10.1016/j.envsoft.2014.08.017, 2014.
  97. S. Ceola, A. Montanari, and D. Koutsoyiannis, Toward a theoretical framework for integrated modeling of hydrological change, WIREs Water, 1 (5), 427–438, doi:10.1002/wat2.1038, 2014.
  98. C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, A quick gap-filling of missing hydrometeorological data, Journal of Geophysical Research-Atmospheres, 119 (15), 9290–9300, doi:10.1002/2014JD021633, 2014.
  99. D. Koutsoyiannis, Social vs. scientific perception of change in hydrology and climate — Reply to the Discussion by Arie Ben-Zvi on the Opinion Paper “Hydrology and Change”, Hydrological Sciences Journal, 59 (8), 1625–1626, doi:10.1080/02626667.2014.935382, 2014.
  100. A. Montanari, and D. Koutsoyiannis, Reply to comment by G. Nearing on ‘‘A blueprint for process-based modeling of uncertain hydrological systems’’, Water Resources Research, 50 (7), 6264–6268, doi:10.1002/2013WR014987, 2014.
  101. G. Blöschl, A. Bardossy, D. Koutsoyiannis, Z. W. Kundzewicz, I. G. Littlewood, A. Montanari, and H. H. G. Savenije, Joint Editorial—On the future of journal publications in hydrology, Hydrological Sciences Journal, 59 (5), 955–958, doi:10.1080/02626667.2014.908041, 2014.
  102. D. Koutsoyiannis, Entropy: from thermodynamics to hydrology, Entropy, 16 (3), 1287–1314, doi:10.3390/e16031287, 2014.
  103. A. Efstratiadis, A. D. Koussis, D. Koutsoyiannis, and N. Mamassis, Flood design recipes vs. reality: can predictions for ungauged basins be trusted?, Natural Hazards and Earth System Sciences, 14, 1417–1428, doi:10.5194/nhess-14-1417-2014, 2014.
  104. D. Koutsoyiannis, Reconciling hydrology with engineering, Hydrology Research, 45 (1), 2–22, doi:10.2166/nh.2013.092, 2014.
  105. G. Tsekouras, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy, Renewable Energy, 63, 624–633, doi:10.1016/j.renene.2013.10.018, 2014.
  106. H. Tyralis, and D. Koutsoyiannis, A Bayesian statistical model for deriving the predictive distribution of hydroclimatic variables, Climate Dynamics, 42 (11-12), 2867–2883, doi:10.1007/s00382-013-1804-y, 2014.
  107. A. Efstratiadis, A. Tegos, A. Varveris, and D. Koutsoyiannis, Assessment of environmental flows under limited data availability – Case study of the Acheloos River, Greece, Hydrological Sciences Journal, 59 (3-4), 731–750, doi:10.1080/02626667.2013.804625, 2014.
  108. F. Lombardo, E. Volpi, D. Koutsoyiannis, and S.M. Papalexiou, Just two moments! A cautionary note against use of high-order moments in multifractal models in hydrology, Hydrology and Earth System Sciences, 18, 243–255, doi:10.5194/hess-18-243-2014, 2014.
  109. M. Rianna, A. Efstratiadis, F. Russo, F. Napolitano, and D. Koutsoyiannis, A stochastic index method for calculating annual flow duration curves in intermittent rivers, Irrigation and Drainage, 62 (S2), 41–49, doi:10.1002/ird.1803, 2013.
  110. D. Koutsoyiannis, Physics of uncertainty, the Gibbs paradox and indistinguishable particles, Studies in History and Philosophy of Modern Physics, 44, 480–489, doi:10.1016/j.shpsb.2013.08.007, 2013.
  111. E. Kountouri, N. Petrochilos, N. Liaros, V. Oikonomou, D. Koutsoyiannis, N. Mamassis, N. Zarkadoulas, A. Vött, H. Hadler, P. Henning, and T. Willershäuser, The Mycenaean drainage works of north Kopais, Greece: a new project incorporating surface surveys, geophysical research and excavation, Water Science and Technology: Water Supply, 13 (3), 710–718, doi:10.2166/ws.2013.110, 2013.
  112. A. Montanari, G. Young, H. H. G. Savenije, D. Hughes, T. Wagener, L. L. Ren, D. Koutsoyiannis, C. Cudennec, E. Toth, S. Grimaldi, G. Blöschl, M. Sivapalan, K. Beven, H. Gupta, M. Hipsey, B. Schaefli, B. Arheimer, E. Boegh, S. J. Schymanski, G. Di Baldassarre, B. Yu, P. Hubert, Y. Huang, A. Schumann, D. Post, V. Srinivasan, C. Harman, S. Thompson, M. Rogger, A. Viglione, H. McMillan, G. Characklis, Z. Pang, and V. Belyaev, “Panta Rhei – Everything Flows”, Change in Hydrology and Society – The IAHS Scientific Decade 2013-2022, Hydrological Sciences Journal, 58 (6), 1256–1275, doi:10.1080/02626667.2013.809088, 2013.
  113. D. Koutsoyiannis, Hydrology and Change, Hydrological Sciences Journal, 58 (6), 1177–1197, doi:10.1080/02626667.2013.804626, 2013.
  114. S.M. Papalexiou, and D. Koutsoyiannis, Battle of extreme value distributions: A global survey on extreme daily rainfall, Water Resources Research, 49 (1), 187–201, doi:10.1029/2012WR012557, 2013.
  115. Y. Markonis, and D. Koutsoyiannis, Climatic variability over time scales spanning nine orders of magnitude: Connecting Milankovitch cycles with Hurst–Kolmogorov dynamics, Surveys in Geophysics, 34 (2), 181–207, doi:10.1007/s10712-012-9208-9, 2013.
  116. H. Tyralis, D. Koutsoyiannis, and S. Kozanis, An algorithm to construct Monte Carlo confidence intervals for an arbitrary function of probability distribution parameters, Computational Statistics, 28 (4), 1501–1527, doi:10.1007/s00180-012-0364-7, 2013.
  117. S.M. Papalexiou, D. Koutsoyiannis, and C. Makropoulos, How extreme is extreme? An assessment of daily rainfall distribution tails, Hydrology and Earth System Sciences, 17, 851–862, doi:10.5194/hess-17-851-2013, 2013.
  118. A. Montanari, and D. Koutsoyiannis, A blueprint for process-based modeling of uncertain hydrological systems, Water Resources Research, 48, W09555, doi:10.1029/2011WR011412, 2012.
  119. D. Koutsoyiannis, Reply to the Comment by T. López-Arias on “Clausius-Clapeyron equation and saturation vapour pressure: simple theory reconciled with practice”, European Journal of Physics, 33, L13–L14, 2012.
  120. F. Lombardo, E. Volpi, and D. Koutsoyiannis, Rainfall downscaling in time: Theoretical and empirical comparison between multifractal and Hurst-Kolmogorov discrete random cascades, Hydrological Sciences Journal, 57 (6), 1052–1066, 2012.
  121. D. Koutsoyiannis, Clausius-Clapeyron equation and saturation vapour pressure: simple theory reconciled with practice, European Journal of Physics, 33 (2), 295–305, doi:10.1088/0143-0807/33/2/295, 2012.
  122. S.M. Papalexiou, and D. Koutsoyiannis, Entropy based derivation of probability distributions: A case study to daily rainfall, Advances in Water Resources, 45, 51–57, doi:10.1016/j.advwatres.2011.11.007, 2012.
  123. S.M. Papalexiou, D. Koutsoyiannis, and A. Montanari, Can a simple stochastic model generate rich patterns of rainfall events?, Journal of Hydrology, 411 (3-4), 279–289, 2011.
  124. D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. G. Anagnostopoulos, and N. Mamassis, Scientific dialogue on climate: is it giving black eyes or opening closed eyes? Reply to “A black eye for the Hydrological Sciences Journal” by D. Huard, Hydrological Sciences Journal, 56 (7), 1334–1339, doi:10.1080/02626667.2011.610759, 2011.
  125. D. Koutsoyiannis, Scale of water resources development and sustainability: Small is beautiful, large is great, Hydrological Sciences Journal, 56 (4), 553–575, doi:10.1080/02626667.2011.579076, 2011.
  126. D. Koutsoyiannis, Hurst-Kolmogorov dynamics as a result of extremal entropy production, Physica A: Statistical Mechanics and its Applications, 390 (8), 1424–1432, doi:10.1016/j.physa.2010.12.035, 2011.
  127. D. Koutsoyiannis, A. Paschalis, and N. Theodoratos, Two-dimensional Hurst-Kolmogorov process and its application to rainfall fields, Journal of Hydrology, 398 (1-2), 91–100, doi:10.1016/j.jhydrol.2010.12.012, 2011.
  128. I. Nalbantis, A. Efstratiadis, E. Rozos, M. Kopsiafti, and D. Koutsoyiannis, Holistic versus monomeric strategies for hydrological modelling of human-modified hydrosystems, Hydrology and Earth System Sciences, 15, 743–758, doi:10.5194/hess-15-743-2011, 2011.
  129. D. Koutsoyiannis, Hurst-Kolmogorov dynamics and uncertainty, Journal of the American Water Resources Association, 47 (3), 481–495, doi:10.1111/j.1752-1688.2011.00543.x, 2011.
  130. H. Tyralis, and D. Koutsoyiannis, Simultaneous estimation of the parameters of the Hurst-Kolmogorov stochastic process, Stochastic Environmental Research & Risk Assessment, 25 (1), 21–33, 2011.
  131. G. Di Baldassarre, A. Montanari, H. F. Lins, D. Koutsoyiannis, L. Brandimarte, and G. Blöschl, Flood fatalities in Africa: from diagnosis to mitigation, Geophysical Research Letters, 37, L22402, doi:10.1029/2010GL045467, 2010.
  132. E. Rozos, and D. Koutsoyiannis, Error analysis of a multi-cell groundwater model, Journal of Hydrology, 392 (1-2), 22–30, 2010.
  133. G. G. Anagnostopoulos, D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, A comparison of local and aggregated climate model outputs with observed data, Hydrological Sciences Journal, 55 (7), 1094–1110, doi:10.1080/02626667.2010.513518, 2010.
  134. D. Koutsoyiannis, Z. W. Kundzewicz, F. Watkins, and C. Gardner, Something old, something new, something red, something blue, Hydrological Sciences Journal, 55 (1), 1–3, 2010.
  135. A. Efstratiadis, and D. Koutsoyiannis, One decade of multiobjective calibration approaches in hydrological modelling: a review, Hydrological Sciences Journal, 55 (1), 58–78, doi:10.1080/02626660903526292, 2010.
  136. D. Koutsoyiannis, A random walk on water, Hydrology and Earth System Sciences, 14, 585–601, doi:10.5194/hess-14-585-2010, 2010.
  137. S. Grimaldi, D. Koutsoyiannis, D. Piccolo, and A. Schumann, Guest Editorial—Recent developments of statistical tools for hydrological application, Physics and Chemistry of the Earth, 34 (10-12), 595, 2009.
  138. D. Koutsoyiannis, A. Montanari, H. F. Lins, and T.A. Cohn, Climate, hydrology and freshwater: towards an interactive incorporation of hydrological experience into climate research—DISCUSSION of “The implications of projected climate change for freshwater resources and their management”, Hydrological Sciences Journal, 54 (2), 394–405, doi:10.1623/hysj.54.2.394, 2009.
  139. D. Koutsoyiannis, and Z. W. Kundzewicz, Editorial—Recycling paper vs recycling papers, Hydrological Sciences Journal, 54 (1), 3–4, 2009.
  140. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.
  141. I. Zalachori, D. Koutsoyiannis, and A. Andreadakis, Infiltration and inflow in sewer systems: Identification and quantification in Greece, Technica Chronica, 28 (1), 43–51, 2008.
  142. D. Koutsoyiannis, A. Efstratiadis, N. Mamassis, and A. Christofides, On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671–684, doi:10.1623/hysj.53.4.671, 2008.
  143. A. Tsouni, C. Contoes, D. Koutsoyiannis, P. Elias, and N. Mamassis, Estimation of actual evapotranspiration by remote sensing: Application in Thessaly Plain, Greece, Sensors, 8 (6), 3586–3600, 2008.
  144. D. Koutsoyiannis, and Z. W. Kundzewicz, The choice of language and its relationship to the impact of hydrological studies. Reply to discussions of "Editorial-Quantifying the impact of hydrological studies", Hydrological Sciences Journal, 53 (2), 495–499, 2008.
  145. D. Koutsoyiannis, A power-law approximation of the turbulent flow friction factor useful for the design and simulation of urban water networks, Urban Water Journal, 5 (2), 117–115, 2008.
  146. D. Koutsoyiannis, H. Yao, and A. Georgakakos, Medium-range flow prediction for the Nile: a comparison of stochastic and deterministic methods, Hydrological Sciences Journal, 53 (1), 142–164, doi:10.1623/hysj.53.1.142, 2008.
  147. C. Makropoulos, D. Koutsoyiannis, M. Stanic, S. Djordevic, D. Prodanovic, T. Dasic, S. Prohaska, C. Maksimovic, and H. S. Wheater, A multi-model approach to the simulation of large scale karst flows, Journal of Hydrology, 348 (3-4), 412–424, 2008.
  148. A. Efstratiadis, I. Nalbantis, A. Koukouvinos, E. Rozos, and D. Koutsoyiannis, HYDROGEIOS: A semi-distributed GIS-based hydrological model for modified river basins, Hydrology and Earth System Sciences, 12, 989–1006, doi:10.5194/hess-12-989-2008, 2008.
  149. D. Koutsoyiannis, N. Zarkadoulas, A. N. Angelakis, and G. Tchobanoglous, Urban water management in Ancient Greece: Legacies and lessons, Journal of Water Resources Planning and Management - ASCE, 134 (1), 45–54, doi:10.1061/(ASCE)0733-9496(2008)134:1(45), 2008.
  150. C. Cudennec, C. Leduc, and D. Koutsoyiannis, Dryland hydrology in Mediterranean regions -- a review, Hydrological Sciences Journal, 52 (6), 1077–1087, doi:10.1623/hysj.52.6.1077, 2007.
  151. D. Koutsoyiannis, Discussion of "Generalized regression neural networks for evapotranspiration modelling", Hydrological Sciences Journal, 52 (4), 832–835, 2007.
  152. D. Koutsoyiannis, and A. Montanari, Statistical analysis of hydroclimatic time series: Uncertainty and insights, Water Resources Research, 43 (5), W05429, doi:10.1029/2006WR005592, 2007.
  153. L.W. Mays, D. Koutsoyiannis, and A. N. Angelakis, A brief history of urban water supply in antiquity, Water Science and Technology: Water Supply, 7 (1), 1–12, doi:10.2166/ws.2007.001, 2007.
  154. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Water Science and Technology: Water Supply, 7 (1), 13–22, 2007.
  155. A. N. Angelakis, and D. Koutsoyiannis, Water and wastewater technologies in ancient civilizations: Prolegomena, Water Science and Technology: Water Supply, 7 (1), vii–ix, 2007.
  156. D. Koutsoyiannis, and Z. W. Kundzewicz, Editorial - Quantifying the impact of hydrological studies, Hydrological Sciences Journal, 52 (1), 3–17, 2007.
  157. D. Koutsoyiannis, A. Efstratiadis, and K. Georgakakos, Uncertainty assessment of future hydroclimatic predictions: A comparison of probabilistic and scenario-based approaches, Journal of Hydrometeorology, 8 (3), 261–281, doi:10.1175/JHM576.1, 2007.
  158. S. Grimaldi, D. Koutsoyiannis, D. Piccolo, and F. Napolitano, Editorial - Time series analysis in hydrology, Physics and Chemistry of the Earth, 31 (18), 1097–1098, 2006.
  159. D. Koutsoyiannis, Editorial - Grateful and apprehensive, Hydrological Sciences Journal, 51 (6), 987–988, 2006.
  160. D. Koutsoyiannis, On the quest for chaotic attractors in hydrological processes, Hydrological Sciences Journal, 51 (6), 1065–1091, doi:10.1623/hysj.51.6.1065, 2006.
  161. Z. W. Kundzewicz, and D. Koutsoyiannis, Pathologies, improvements and optimism, Hydrological Sciences Journal, 51 (2), 357–363, 2006.
  162. S.M. Papalexiou, and D. Koutsoyiannis, A probabilistic approach to the concept of probable maximum precipitation, Advances in Geosciences, 7, 51-54, doi:10.5194/adgeo-7-51-2006, 2006.
  163. E. Rozos, and D. Koutsoyiannis, A multicell karstic aquifer model with alternative flow equations, Journal of Hydrology, 325 (1-4), 340–355, 2006.
  164. D. Koutsoyiannis, An entropic-stochastic representation of rainfall intermittency: The origin of clustering and persistence, Water Resources Research, 42 (1), W01401, doi:10.1029/2005WR004175, 2006.
  165. D. Koutsoyiannis, Nonstationarity versus scaling in hydrology, Journal of Hydrology, 324, 239–254, doi:10.1016/j.jhydrol.2005.09.022, 2006.
  166. D. Koutsoyiannis, A toy model of climatic variability with scaling behaviour, Journal of Hydrology, 322, 25–48, 2006.
  167. A. Langousis, and D. Koutsoyiannis, A stochastic methodology for generation of seasonal time series reproducing overyear scaling behaviour, Journal of Hydrology, 322, 138–154, 2006.
  168. D. Zarris, and D. Koutsoyiannis, Evaluating sediment yield estimations from large-scale hydrologic systems using the rating curve concept, RMZ - Materials and Geoenvironment, 52 (1), 157–159, 2005.
  169. K. Hadjibiros, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, A. Stamou, A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Multi-criteria reservoir water management, Global Network for Environmental Science and Technology, 7 (3), 386–394, doi:10.30955/gnj.000394, 2005.
  170. A. Christofides, A. Efstratiadis, D. Koutsoyiannis, G.-F. Sargentis, and K. Hadjibiros, Resolving conflicting objectives in the management of the Plastiras Lake: can we quantify beauty?, Hydrology and Earth System Sciences, 9 (5), 507–515, doi:10.5194/hess-9-507-2005, 2005.
  171. Z. W. Kundzewicz, and D. Koutsoyiannis, Editorial - The peer-review system: prospects and challenges, Hydrological Sciences Journal, 50 (4), 577–590, 2005.
  172. D. Koutsoyiannis, Uncertainty, entropy, scaling and hydrological stochastics, 2, Time dependence of hydrological processes and time scaling, Hydrological Sciences Journal, 50 (3), 405–426, doi:10.1623/hysj.50.3.405.65028, 2005.
  173. D. Koutsoyiannis, Uncertainty, entropy, scaling and hydrological stochastics, 1, Marginal distributional properties of hydrological processes and state scaling, Hydrological Sciences Journal, 50 (3), 381–404, doi:10.1623/hysj.50.3.381.65031, 2005.
  174. A. N. Angelakis, D. Koutsoyiannis, and G. Tchobanoglous, Urban wastewater and stormwater technologies in ancient Greece, Water Research, 39 (1), 210–220, doi:10.1016/j.watres.2004.08.033, 2005.
  175. E. Rozos, A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows, Hydrological Sciences Journal, 49 (5), 819–842, doi:10.1623/hysj.49.5.819.55130, 2004.
  176. D. Koutsoyiannis, Statistics of extremes and estimation of extreme rainfall, 2, Empirical investigation of long rainfall records, Hydrological Sciences Journal, 49 (4), 591–610, doi:10.1623/hysj.49.4.591.54424, 2004.
  177. D. Koutsoyiannis, Statistics of extremes and estimation of extreme rainfall, 1, Theoretical investigation, Hydrological Sciences Journal, 49 (4), 575–590, doi:10.1623/hysj.49.4.575.54430, 2004.
  178. K Mantoudi, N. Mamassis, and D. Koutsoyiannis, Water basin balance model using a geographical information system, Technica Chronica, 24 (1-3), 43–52, 2004.
  179. K. Mazi, A. D. Koussis, P. J. Restrepo, and D. Koutsoyiannis, A groundwater-based, objective-heuristic parameter optimisation method for a precipitation-runoff model and its application to a semi-arid basin, Journal of Hydrology, 290, 243–258, 2004.
  180. A. Efstratiadis, D. Koutsoyiannis, and D. Xenos, Minimizing water cost in the water resource management of Athens, Urban Water Journal, 1 (1), 3–15, doi:10.1080/15730620410001732099, 2004.
  181. D. Koutsoyiannis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, and A. Christofides, A decision support system for the management of the water resource system of Athens, Physics and Chemistry of the Earth, 28 (14-15), 599–609, doi:10.1016/S1474-7065(03)00106-2, 2003.
  182. D. Koutsoyiannis, and A. Economou, Evaluation of the parameterization-simulation-optimization approach for the control of reservoir systems, Water Resources Research, 39 (6), 1170, doi:10.1029/2003WR002148, 2003.
  183. D. Koutsoyiannis, C. Onof, and H. S. Wheater, Multivariate rainfall disaggregation at a fine timescale, Water Resources Research, 39 (7), 1173, doi:10.1029/2002WR001600, 2003.
  184. D. Koutsoyiannis, Climate change, the Hurst phenomenon, and hydrological statistics, Hydrological Sciences Journal, 48 (1), 3–24, doi:10.1623/hysj.48.1.3.43481, 2003.
  185. D. Koutsoyiannis, A. Efstratiadis, and G. Karavokiros, A decision support tool for the management of multi-reservoir systems, Journal of the American Water Resources Association, 38 (4), 945–958, doi:10.1111/j.1752-1688.2002.tb05536.x, 2002.
  186. D. Koutsoyiannis, The Hurst phenomenon and fractional Gaussian noise made easy, Hydrological Sciences Journal, 47 (4), 573–595, doi:10.1080/02626660209492961, 2002.
  187. D. Koutsoyiannis, and N. Mamassis, On the representation of hyetograph characteristics by stochastic rainfall models, Journal of Hydrology, 251, 65–87, 2001.
  188. D. Koutsoyiannis, and C. Onof, Rainfall disaggregation using adjusting procedures on a Poisson cluster model, Journal of Hydrology, 246, 109–122, 2001.
  189. D. Koutsoyiannis, Coupling stochastic models of different time scales, Water Resources Research, 37 (2), 379–391, doi:10.1029/2000WR900200, 2001.
  190. G. Baloutsos, D. Koutsoyiannis, A. Economou, and P. Kalliris, Investigation of the hydrologic response of the Xerias torrent basin to the rainstorm of January 1997 using the SCS method, Geotechnical Scientific Issues, 11 (1), 77–90, 2000.
  191. D. Koutsoyiannis, and G. Baloutsos, Analysis of a long record of annual maximum rainfall in Athens, Greece, and design rainfall inferences, Natural Hazards, 22 (1), 29–48, doi:10.1023/A:1008001312219, 2000.
  192. D. Koutsoyiannis, Broken line smoothing: A simple method for interpolating and smoothing data series, Environmental Modelling and Software, 15 (2), 139–149, 2000.
  193. D. Koutsoyiannis, A generalized mathematical framework for stochastic simulation and forecast of hydrologic time series, Water Resources Research, 36 (6), 1519–1533, doi:10.1029/2000WR900044, 2000.
  194. G. Tsakalias, and D. Koutsoyiannis, A comprehensive system for the exploration and analysis of hydrological data, Water Resources Management, 13, 269–302, 1999.
  195. D. Koutsoyiannis, A probabilistic view of Hershfield's method for estimating probable maximum precipitation, Water Resources Research, 35 (4), 1313–1322, doi:10.1029/1999WR900002, 1999.
  196. D. Koutsoyiannis, Optimal decomposition of covariance matrices for multivariate stochastic models in hydrology, Water Resources Research, 35 (4), 1219–1229, doi:10.1029/1998WR900093, 1999.
  197. D. Koutsoyiannis, D. Kozonis, and A. Manetas, A mathematical framework for studying rainfall intensity-duration-frequency relationships, Journal of Hydrology, 206 (1-2), 118–135, doi:10.1016/S0022-1694(98)00097-3, 1998.
  198. I. Nalbantis, and D. Koutsoyiannis, A parametric rule for planning and management of multiple reservoir systems, Water Resources Research, 33 (9), 2165–2177, doi:10.1029/97WR01034, 1997.
  199. D. Koutsoyiannis, and A. Manetas, Simple disaggregation by accurate adjusting procedures, Water Resources Research, 32 (7), 2105–2117, doi:10.1029/96WR00488, 1996.
  200. D. Koutsoyiannis, and D. Pachakis, Deterministic chaos versus stochasticity in analysis and modeling of point rainfall series, Journal of Geophysical Research-Atmospheres, 101 (D21), 26441–26451, doi:10.1029/96JD01389, 1996.
  201. N. Mamassis, and D. Koutsoyiannis, Influence of atmospheric circulation types in space-time distribution of intense rainfall, Journal of Geophysical Research-Atmospheres, 101 (D21), 26267–26276, 1996.
  202. D. Koutsoyiannis, A stochastic disaggregation method for design storm and flood synthesis, Journal of Hydrology, 156, 193–225, doi:10.1016/0022-1694(94)90078-7, 1994.
  203. D. Koutsoyiannis, and E. Foufoula-Georgiou, A scaling model of storm hyetograph, Water Resources Research, 29 (7), 2345–2361, doi:10.1029/93WR00395, 1993.
  204. I. Nalbantis, D. Koutsoyiannis, and Th. Xanthopoulos, Modelling the Athens water supply system, Water Resources Management, 6, 57–67, doi:10.1007/BF00872188, 1992.
  205. D. Koutsoyiannis, A nonlinear disaggregation method with a reduced parameter set for simulation of hydrologic series, Water Resources Research, 28 (12), 3175–3191, doi:10.1029/92WR01299, 1992.
  206. D. Koutsoyiannis, and Th. Xanthopoulos, A dynamic model for short-scale rainfall disaggregation, Hydrological Sciences Journal, 35 (3), 303–322, doi:10.1080/02626669009492431, 1990.
  207. D. Koutsoyiannis, and Th. Xanthopoulos, On the parametric approach to unit hydrograph identification, Water Resources Management, 3 (2), 107–128, doi:10.1007/BF00872467, 1989.
  208. D. Koutsoyiannis, and K. Tarla, Sediment Yield Estimations in Greece, Technica Chronica, A-7 (3), 127–154, 1987.

Book chapters and fully evaluated conference publications

  1. M. Pantazidou, D. Koutsoyiannis, H. Saroglou, V. Marinos, and T. Iliopoulou, Infuse teaching with research practices: a pilot project – welcome presentation for first-year students on time scales in civil engineering projects, 1st Joint Conference of EUCEET and AECEF: The role of education for Civil Engineers in the implementation of the SDGs, Thessaloniki, 2021.
  2. R.R.P. van Nooijen, D. Koutsoyiannis, and A.G. Kolechkina, Optimal and real-time control of water infrastructures, Oxford Research Encyclopedia of Oxford Research Encyclopedia of Environmental Science, doi:10.1093/acrefore/9780199389414.013.627, Oxford University Press, 2021.
  3. G.-F. Sargentis, R. Ioannidis, M. Chiotinis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues with stochastic evaluation, Data Analytics for Cultural Heritage, edited by A. Belhi, A. Bouras, A.K. Al-Ali, and A.H. Sadka, doi:10.1007/978-3-030-66777-1_8, Springer, 2021.
  4. N. Mamassis, A. Efstratiadis, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, and D. Koutsoyiannis, Water and Energy, Handbook of Water Resources Management: Discourses, Concepts and Examples, edited by J.J. Bogardi, T. Tingsanchali, K.D.W. Nandalal, J. Gupta, L. Salamé, R.R.P. van Nooijen, A.G. Kolechkina, N. Kumar, and A. Bhaduri, Chapter 20, 617–655, doi:10.1007/978-3-030-60147-8_20, Springer Nature, Switzerland, 2021.
  5. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Error evolution patterns in multi-step ahead streamflow forecasting, 13th International Conference on Hydroinformatics (HIC 2018), Palermo, Italy, doi:10.29007/84k6, 2018.
  6. D. Koutsoyiannis, Climate change impacts on hydrological science: How the climate change agenda has lowered the scientific level of hydrology (Plenary talk), 13th International Conference on Hydroinformatics (HIC 2018), Palermo, Italy, doi:10.13140/RG.2.2.12249.42084, 2018.
  7. D. Koutsoyiannis, and N. Mamassis, The water supply of Athens through the centuries, Schriften der Deutschen Wasserhistorischen Gesellschaft, edited by K. Wellbrock, 27 (1), Siegburg, 2018.
  8. D. Koutsoyiannis, P. Dimitriadis, F. Lombardo, and S. Stevens, From fractals to stochastics: Seeking theoretical consistency in analysis of geophysical data, Advances in Nonlinear Geosciences, edited by A.A. Tsonis, 237–278, doi:10.1007/978-3-319-58895-7_14, Springer, 2018.
  9. R. Ioannidis, and D. Koutsoyiannis, The architectural and landscape value of dams: from international examples to proposals for Greece, Proceedings of 3rd Hellenic Conference on Dams and Reservoirs, Zappeion, Hellenic Commission on Large Dams, Athens, 2017.
  10. P. Dimas, D. Bouziotas, D. Nikolopoulos, A. Efstratiadis, and D. Koutsoyiannis, Framework for optimal management of hydroelectric reservoirs through pumped storage: Investigation of Acheloos-Thessaly and Aliakmon hydrosystems, Proceedings of 3rd Hellenic Conference on Dams and Reservoirs, Zappeion, Hellenic Commission on Large Dams, Athens, 2017.
  11. D. Koutsoyiannis, and R. Ioannidis, The energetic, environmental and aesthetic superiority of large hydropower projects over other renewable energy projects, Proceedings of 3rd Hellenic Conference on Dams and Reservoirs, Zappeion, Hellenic Commission on Large Dams, Athens, 2017.
  12. P. Dimitriadis, A. Tegos, A. Petsiou, V. Pagana, I. Apostolopoulos, E. Vassilopoulos, M. Gini, A. D. Koussis, N. Mamassis, D. Koutsoyiannis, and P. Papanicolaou, Flood Directive implementation in Greece: Experiences and future improvements, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  13. D. Koutsoyiannis, ‘Panta Rhei’ and its relationship with uncertainty, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, doi:10.13140/RG.2.2.15701.73444, European Water Resources Association, 2017.
  14. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Forecasting of geophysical processes using stochastic and machine learning algorithms, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, EWRA2017_A_110904, doi:10.13140/RG.2.2.30581.27361, European Water Resources Association, Athens, 2017.
  15. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  16. D. Koutsoyiannis, and S.M. Papalexiou, Extreme rainfall: Global perspective, Handbook of Applied Hydrology, Second Edition, edited by V.P. Singh, 74.1–74.16, McGraw-Hill, New York, 2017.
  17. A. Tsouni, C. Contoes, E. Ieronymidi, A. Koukouvinos, and D. Koutsoyiannis, BEYOND Center of Excellence: flood mapping and modelling, 1st International Geomatics Applications “Geomapplica” Conference, Skiathos Island, Greece, doi:10.13140/RG.2.1.1129.7520, University of Thessaly, 2014.
  18. N. Mamassis, and D. Koutsoyiannis, Views on ancient Hellenic science and technology, IWA Regional Symposium on Water, Wastewater & Environment: Traditions & Culture, Patras, Greece, doi:10.13140/RG.2.1.2702.6163, International Water Association, 2014.
  19. D. Koutsoyiannis, Past and modern water problems: progress or regression? (Invited), IWA Regional Symposium on Water, Wastewater & Environment: Traditions & Culture, Patras, Greece, 3–13, doi:10.13140/RG.2.1.4144.4082, International Water Association, 2014.
  20. D. Koutsoyiannis, and A. Patrikiou, Water control in Ancient Greek cities, A History of Water: Water and Urbanization, edited by T. Tvedt and T. Oestigaard, 130–148, I.B. Tauris, London, 2014.
  21. E.N. Otay, A. Stamou, Y.C. Altan, G. Papadonikolaki, N. Copty, G. Christodoulou, F.T. Karakoc, V. Tsoukala, D. Koutsoyiannis, and A. Papadopoulos, Risk assessment of oil spill accidents, Part 2: application to Saronikos gulf and Izmir bay, Proceedings of the 13th International Conference on Environmental Science and Technology, Athens, 2013.
  22. N. Mamassis, and D. Koutsoyiannis, Information technologies in hydrometeorological data management in Greece, Honorary Edition for for Professor Emeritus D. Tolikas, edited by K. L. Katsifarakis and M. Vafiadis, 27–37, doi:10.13140/RG.2.1.1165.5928, Aristotle University of Thessaloniki, Thessaloniki, 2013.
  23. C. Ioannou, G. Tsekouras, A. Efstratiadis, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes for optimizing hybrid renewable energy systems, Proceedings of the 2nd Hellenic Concerence on Dams and Reservoirs, Athens, Zappeion, doi:10.13140/RG.2.1.3787.0327, Hellenic Commission on Large Dams, 2013.
  24. A. Efstratiadis, D. Bouziotas, and D. Koutsoyiannis, A decision support system for the management of hydropower systems – Application to the Acheloos-Thessaly hydrosystem, Proceedings of the 2nd Hellenic Concerence on Dams and Reservoirs, Athens, Zappeion, doi:10.13140/RG.2.1.1952.0244, Hellenic Commission on Large Dams, 2013.
  25. D. Koutsoyiannis, Water resources development and management for developing countries in the 21st century: revisiting older and newer ideas (keynote lecture), International Symposium on Answers to Asian Aquatic Problems 2013, Tokyo, Japan, 11–18, doi:10.13140/RG.2.1.3721.4965, Tokyo Metropolitan University, 2013.
  26. A. Efstratiadis, A. D. Koussis, S. Lykoudis, A. Koukouvinos, A. Christofides, G. Karavokiros, N. Kappos, N. Mamassis, and D. Koutsoyiannis, Hydrometeorological network for flood monitoring and modeling, Proceedings of First International Conference on Remote Sensing and Geoinformation of Environment, Paphos, Cyprus, 8795, 10-1–10-10, doi:10.1117/12.2028621, Society of Photo-Optical Instrumentation Engineers (SPIE), 2013.
  27. A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, A parametric model for potential evapotranspiration estimation based on a simplified formulation of the Penman-Monteith equation, Evapotranspiration - An Overview, edited by S. Alexandris, 143–165, doi:10.5772/52927, InTech, 2013.
  28. D. Koutsoyiannis, Reconciling hydrology with engineering (Openning lecture), IDRA 2012 – XXXIII Conference of Hydraulics and Hydraulic Engineering, Brescia, Italy, doi:10.13140/RG.2.1.2279.7046, 2012.
  29. S. Kozanis, A. Christofides, N. Mamassis, and D. Koutsoyiannis, openmeteo.org: a web service for the dissemination of free meteorological data, Advances in Meteorology, Climatology and Atmospheric Physics, edited by C.G. Helmis and P. Nastos, Athens, 203–208, doi:10.1007/978-3-642-29172-2_29, Springer, Athens, 2012.
  30. D. Koutsoyiannis, N. Zarkadoulas, N. Mamassis, A. N. Angelakis, and L.W. Mays, The evolution of water supply throughout the millennia: A short overview, Evolution of Water Supply Through the Millennia, edited by A. N. Angelakis, L.W. Mays, D. Koutsoyiannis, and N. Mamassis, 21, 553–560, doi:10.13140/RG.2.1.2541.8485, IWA Publishing, London, 2012.
  31. N. Zarkadoulas, D. Koutsoyiannis, N. Mamassis, and A. N. Angelakis, A brief history of urban water management in ancient Greece, Evolution of Water Supply Through the Millennia, edited by A. N. Angelakis, L.W. Mays, D. Koutsoyiannis, and N. Mamassis, 10, 259–270, doi:10.13140/RG.2.1.4114.7127, IWA Publishing, London, 2012.
  32. A. N. Angelakis, L.W. Mays, D. Koutsoyiannis, and N. Mamassis, Prolegomena: The evolution of water supply through the millennia, Evolution of Water Supply Through the Millennia, edited by A. N. Angelakis, L.W. Mays, D. Koutsoyiannis, and N. Mamassis, xxi–xxii, doi:10.13140/RG.2.1.1542.4245, IWA Publishing, 2012.
  33. E. Kountouri, N. Petrochilos, D. Koutsoyiannis, N. Mamassis, N. Zarkadoulas, A. Vött, H. Hadler, P. Henning, and T. Willershäuser, A new project of surface survey, geophysical and excavation research of the mycenaean drainage works of the North Kopais: the first study season, 3rd IWA Specialized Conference on Water & Wastewater Technologies in Ancient Civilizations, Istanbul, Turkey, 467–476, doi:10.13140/RG.2.1.2328.8563, International Water Association, 2012.
  34. A. N. Angelakis, D. Koutsoyiannis, and P. Papanicolaou, On the geometry of the Minoan water conduits, 3rd IWA Specialized Conference on Water & Wastewater Technologies in Ancient Civilizations, Istanbul, Turkey, 172–177, doi:10.13140/RG.2.1.4426.0083, International Water Association, 2012.
  35. D. Koutsoyiannis, N. Mamassis, A. Efstratiadis, N. Zarkadoulas, and Y. Markonis, Floods in Greece, Changes of Flood Risk in Europe, edited by Z. W. Kundzewicz, Chapter 12, 238–256, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2012.
  36. D. Koutsoyiannis, Prolegomena, Common Sense and Other Heresies, Selected Papers on Hydrology and Water Resources Engineering by Vít Klemeš (Second edition), edited by C. D. Sellars, xi–xv, Canadian Water Resources Association, International Association of Hydrological Sciences, 2011.
  37. D. Koutsoyiannis, and A. Langousis, Precipitation, Treatise on Water Science, edited by P. Wilderer and S. Uhlenbrook, 2, 27–78, doi:10.1016/B978-0-444-53199-5.00027-0, Academic Press, Oxford, 2011.
  38. N. Mamassis, and D. Koutsoyiannis, A web based information system for the inspection of the hydraulic works in Ancient Greece, Ancient Water Technologies, edited by L.W. Mays, 103–114, doi:10.1007/978-90-481-8632-7_6, Springer, Dordrecht, 2010.
  39. N. Evelpidou, N. Mamassis, A. Vassilopoulos, C. Makropoulos, and D. Koutsoyiannis, Flooding in Athens: The Kephisos River flood event of 21-22/10/1994, International Conference on Urban Flood Management, Paris, doi:10.13140/RG.2.1.4065.5601, UNESCO, 2009.
  40. D. Koutsoyiannis, and N. Mamassis, New approaches to estimation of extreme rainfall, 1st Hellenic Conference on Large Dams, Larisa, 2, 433–440, doi:10.13140/RG.2.1.1116.4400, Hellenic Commission on Large Dams, Technical Chamber of Greece, 2008.
  41. D. Koutsoyiannis, Older and modern considerations in the design and management of reservoirs, dams and hydropower plants (Solicited), 1st Hellenic Conference on Large Dams, Larisa, doi:10.13140/RG.2.1.3213.5922, Hellenic Commission on Large Dams, Technical Chamber of Greece, 2008.
  42. A. Efstratiadis, and D. Koutsoyiannis, Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach, Practical hydroinformatics: Computational intelligence and technological developments in water applications, edited by R.J. Abrahart, L. M. See, and D. P. Solomatine, 259–273, doi:10.1007/978-3-540-79881-1_19, Springer, 2008.
  43. N. Mamassis, and D. Koutsoyiannis, Physical, social and technological aspects of drought - The Athens example, Natural and Technological Disasters in Europe and Greece, edited by K. Sapountzaki, 61–88, doi:10.13140/RG.2.1.1640.7289, Gutenberg, Athens, 2007.
  44. N. Mamassis, V. Kanellopoulos, and D. Koutsoyiannis, A web based information system for the inspection of the hydraulic works in Ancient Greece, 5th International Symposium on Environmental Hydraulics, Tempe, Arizona, doi:10.13140/RG.2.1.3475.7362, International Association of Hydraulic Research, 2007.
  45. D. Koutsoyiannis, A critical review of probability of extreme rainfall: principles and models, Advances in Urban Flood Management, edited by R. Ashley, S. Garvin, E. Pasche, A. Vassilopoulos, and C. Zevenbergen, 139–166, doi:10.1201/9780203945988.ch7, Taylor and Francis, London, 2007.
  46. D. Koutsoyiannis, and A. N. Angelakis, Agricultural hydraulic works in ancient Greece, Encyclopedia of Water Science, Second Edition, edited by S. W. Trimble, 24–27, doi:10.13140/RG.2.1.2582.8084, CRC Press, 2007.
  47. Z. Theocharis, C. Memos, and D. Koutsoyiannis, Wave height background errors simulation and forecasting via stochastic methods in deep and intermediate waters, Proceedings of the 30th International Conference on Coastal Engineering, San Diego, 1, 578–589, doi:10.1142/9789812709554_0050, 2006.
  48. Z. Theocharis, C. Memos, and D. Koutsoyiannis, Wave forecasting errors in time and space, 4th National Conference of Harbour Works, Athens, 51–60, doi:10.13140/RG.2.1.1468.6967, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 2006.
  49. G Cox, C. Smythe, and D. Koutsoyiannis, The Hurst phenomenon and Monte Carlo simulation to forecast reliability of an Australian reservoir, Proceedings of the 30th Hydrology and Water Resources Symposium, Launceston, Australia, doi:10.13140/RG.2.1.2517.2721, Engineers Australia, 2006.
  50. A. N. Angelakis, D. Koutsoyiannis, and L.W. Mays, Water and wastewater technologies in ancient Civilizations: Conclusions, Proceedings of the 1st IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations, edited by A. N. Angelakis and D. Koutsoyiannis, Iraklio, doi:10.13140/RG.2.1.5138.7120, International Water Association, 2006.
  51. A. N. Angelakis, and D. Koutsoyiannis, Water and wastewater technologies in ancient Civilizations: Prolegomena, Proceedings of the 1st IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations, edited by A. N. Angelakis and D. Koutsoyiannis, Iraklio, i–iii, doi:10.13140/RG.2.1.2091.2887, International Water Association, 2006.
  52. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Logical and illogical exegeses of hydrometeorological phenomena in ancient Greece, Proceedings of the 1st IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations, edited by A. N. Angelakis and D. Koutsoyiannis, Iraklio, 135–143, doi:10.13140/RG.2.1.4188.4408, International Water Association, 2006.
  53. K. Hadjibiros, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, A. Stamou, A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Multi-criteria reservoir water management, Proceedings of the 9th International Conference on Environmental Science and Technology (9CEST), Rhodes, A, 535–543, Department of Environmental Studies, University of the Aegean, 2005.
  54. A. N. Angelakis, and D. Koutsoyiannis, Wastewater management in the Minoan civilization, Proceedings of the 2nd International Conference on Ancient Greek Technology, 551–556, doi:10.13140/RG.2.1.3270.9367, Technical Chamber of Greece, Athens, 2005.
  55. D. Koutsoyiannis, Hydrologic persistence and the Hurst phenomenon, Water Encyclopedia, Vol. 4, Surface and Agricultural Water, edited by J. H. Lehr and J. Keeley, 210–221, doi:10.1002/047147844X.sw434, Wiley, New York, 2005.
  56. D. Koutsoyiannis, Stochastic simulation of hydrosystems, Water Encyclopedia, Vol. 4, Surface and Agricultural Water, edited by J. H. Lehr and J. Keeley, 421–430, doi:10.1002/047147844X.sw913, Wiley, New York, 2005.
  57. D. Koutsoyiannis, Reliability concepts in reservoir design, Water Encyclopedia, Vol. 4, Surface and Agricultural Water, edited by J. H. Lehr and J. Keeley, 259–265, doi:10.1002/047147844X.sw776, Wiley, New York, 2005.
  58. N. Mamassis, A. Christofides, and D. Koutsoyiannis, Hydrometeorological data acquisition, management and analysis for the Athens water supply system, BALWOIS Conference on Water Observation and Information System for Decision Support, Ochrid, FYROM, doi:10.13140/RG.2.1.1845.5284, Ministry of Environment and Physical Planning FYROM, Skopie, 2004.
  59. D. Koutsoyiannis, Exploration of long records of extreme rainfall and design rainfall inferences, Hydrology: Science and Practice for the 21st Century, edited by B. Webb, N. Arnell, C. Onof, N. MacIntire, R. Gurney, and C. Kirby, London, I, 148–157, doi:10.13140/RG.2.1.1190.1681, British Hydrological Society, 2004.
  60. D. Koutsoyiannis, On the appropriateness of the Gumbel distribution for modelling extreme rainfall (solicited), Hydrological Risk: recent advances in peak river flow modelling, prediction and real-time forecasting. Assessment of the impacts of land-use and climate changes, edited by A. Brath, A. Montanari, and E. Toth, Bologna, 303–319, doi:10.13140/RG.2.1.3811.6080, Editoriale Bios, Castrolibero, Italy, 2004.
  61. A. Tsouni, D. Koutsoyiannis, C. Contoes, N. Mamassis, and P. Elias, Estimation of actual evapotranspiration by remote sensing: Application in Thessalia plain, Greece, Proceedings of the International Conference "Geographical Information Systems and Remote Sensing: Environmental Applications", Volos, doi:10.13140/RG.2.1.3025.1763, 2003.
  62. D. Koutsoyiannis, and A. Efstratiadis, Experience from the development of decision support systems for the management of large-scale hydrosystems of Greece, Proceedings of the Workshop "Water Resources Studies in Cyprus", edited by E. Sidiropoulos and I. Iakovidis, Nikosia, 159–180, Water Development Department of Cyprus, Aristotle University of Thessaloniki, Thessaloniki, 2003.
  63. D. Koutsoyiannis, Rainfall disaggregation methods: Theory and applications (invited), Proceedings, Workshop on Statistical and Mathematical Methods for Hydrological Analysis, edited by D. Piccolo and L. Ubertini, Rome, 1–23, doi:10.13140/RG.2.1.2840.8564, Università di Roma "La Sapienza", 2003.
  64. D. Koutsoyiannis, and A. N. Angelakis, Hydrologic and hydraulic science and technology in ancient Greece, The Encyclopedia of Water Science, edited by B. A. Stewart and T. Howell, 415–417, doi:10.13140/RG.2.1.1333.5282, Dekker, New York, 2003.
  65. A. N. Angelakis, and D. Koutsoyiannis, Urban water engineering and management in ancient Greece, The Encyclopedia of Water Science, edited by B. A. Stewart and T. Howell, 999–1007, doi:10.13140/RG.2.1.2644.2487, Dekker, New York, 2003.
  66. D. Zarris, E. Lykoudi, and D. Koutsoyiannis, Sediment yield estimation of a hydrological basin using measurements of reservoir deposits: A case study for the Kremasta reservoir, Western Greece, Proceedings of the 5th International Conference of European Water Resources Association: "Water Resources Management in the Era of Transition", edited by G. Tsakiris, Athens, 338–345, doi:10.13140/RG.2.1.2382.1047, European Water Resources Association, 2002.
  67. N. Mamassis, and D. Koutsoyiannis, A hydrometeorological telemetric network for the water resources monitoring of the Athens water resource system, Proceedings of the 5th International Conference of European Water Resources Association: "Water Resources Management in the Era of Transition", edited by G. Tsakiris, Athens, 157–163, doi:10.13140/RG.2.1.3954.9683, European Water Resources Association, 2002.
  68. I. Nalbantis, E. Rozos, G. M. T. Tentes, A. Efstratiadis, and D. Koutsoyiannis, Integrating groundwater models within a decision support system, Proceedings of the 5th International Conference of European Water Resources Association: "Water Resources Management in the Era of Transition", edited by G. Tsakiris, Athens, 279–286, European Water Resources Association, 2002.
  69. D. Zarris, E. Lykoudi, and D. Koutsoyiannis, The evolution of river sediment deposits in reservoirs as a dynamic phenomenon - Application to the Kremasta reservoir, Proceedings of the 6th Panhellenic Conference of the Greek Geographical Society, Thessaloniki, 2, 363–370, doi:10.13140/RG.2.1.1726.7446, Aristotle University of Thessaloniki, Greek Geographical Society, 2002.
  70. K. Hadjibiros, D. Koutsoyiannis, A. Katsiri, A. Stamou, A. Andreadakis, G.-F. Sargentis, A. Christofides, A. Efstratiadis, and A. Valassopoulos, Management of water quality of the Plastiras reservoir, 4th International Conference on Reservoir Limnology and Water Quality, Ceske Budejovice, Czech Republic, doi:10.13140/RG.2.1.4872.4723, 2002.
  71. D. Koutsoyiannis, and I. Tselentis, Comment on the perspectives of water resources development in Greece with regard to the Water Framework Directive, Water Framework Directive - Harmonization with the Greek reality, Proceedings, 87–92, doi:10.13140/RG.2.1.1988.8887, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 2002.
  72. A. Efstratiadis, and D. Koutsoyiannis, An evolutionary annealing-simplex algorithm for global optimisation of water resource systems, Proceedings of the Fifth International Conference on Hydroinformatics, Cardiff, UK, 1423–1428, doi:10.13140/RG.2.1.1038.6162, International Water Association, 2002.
  73. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, Determining management scenarios for the water resource system of Athens, Proceedings, Hydrorama 2002, 3rd International Forum on Integrated Water Management, 175–181, doi:10.13140/RG.2.1.3135.7684, Water Supply and Sewerage Company of Athens, Athens, 2002.
  74. D. Xenos, I. Passios, S. Georgiades, E. Parlis, and D. Koutsoyiannis, Water demand management and the Athens water supply, Proceedings of the 7th BNAWQ Scientific and Practical Conference "Water Quality Technologies and Management in Bulgaria", Sofia, 44–50, doi:10.13140/RG.2.1.3660.0561, Bulgarian National Association on Water Quality, 2002.
  75. R. E. Chandler, H. S. Wheater, V. S. Isham, C. Onof, S. M. Bate, P. J. Northrop, D. R. Cox, and D. Koutsoyiannis, Generation of spatially consistent rainfall data, Continuous river flow simulation: methods, applications and uncertainties, BHS Occasional Paper No. 13, 59–65, doi:10.13140/RG.2.1.2218.2642, British Hydrological Society, London, 2002.
  76. D. Koutsoyiannis, A. Efstratiadis, and G. Karavokiros, A decision support tool for the management of multi-reservoir systems, Proceedings of the Integrated Decision-Making for Watershed Management Symposium, Chevy Chase, Maryland, doi:10.13140/RG.2.1.3528.9848, US Environmental Protection Agency, Duke Power, Virginia Tech, 2001.
  77. D. Koutsoyiannis, N. Mamassis, and A. Christofides, Experience from the operation of the automatic telemetric meteorological station in the National Technical University, Proceedings of the 8th National Congress of the Greek Hydrotechnical Association, edited by G. Christodoulou, A. Stamou, and A. Nanou, Athens, 301–308, doi:10.13140/RG.2.1.4577.5603, Greek Hydrotechnical Association, 2000.
  78. A. Efstratiadis, N. Zervos, G. Karavokiros, and D. Koutsoyiannis, The Hydronomeas computational system and its application to the simulation of reservoir systems, Water resources management in sensitive regions of Greece, Proceedings of the 4th Conference, edited by G. Tsakiris, A. Stamou, and J. Mylopoulos, Volos, 36–43, doi:10.13140/RG.2.1.4053.2724, Greek Committee for the Water Resources Management, 1999.
  79. D. Zarris, D. Koutsoyiannis, and G. Karavokiros, A simple stochastic rainfall disaggregation scheme for urban drainage modelling, Proceedings of the 4th International Conference on Developments in Urban Drainage Modelling, edited by D. Butler and C. Maksimovic, London, 85–92, doi:10.13140/RG.2.1.3004.6969, International Association of Water Quality, International Association of Hydraulic Research, UNESCO, Imperial College, London, 1998.
  80. D. Koutsoyiannis, From the single hydraulic work to hydrosystem: The case of the hydrologic design of the Evinos works, Proceedings of the Hellenic Conference of the Civil Engineering Departments, Thessaloniki, 235–244, doi:10.13140/RG.2.1.2152.7280, Aristotle University of Thessaloniki, 1997.
  81. G. C. Koukis, and D. Koutsoyiannis, Greece, Geomorphological hazards in Europe, edited by C.&C. Embleton, 215–241, doi:10.1016/S0928-2025(97)80010-7, Elsevier, 1997.
  82. L. Lazaridis, G. Kalaouzis, D. Koutsoyiannis, and P. Marinos, Basic engineering and economic characteristics regarding water resources management of Thessaly, Proceedings of the International Conference on Water Resources Management, Larissa, doi:10.13140/RG.2.1.4512.0249, Technical Chamber of Greece, 1996.
  83. G. Tsakalias, and D. Koutsoyiannis, Hydrologic data management using RDBMS with Differential-Linear Data Storage, Hydraulic Engineering Software V: Proceedings of the 5th International Conference HYDROSOFT '94, edited by W. R. Blain and K. L. Katsifarakis, Sithonia, 2, 317–326, doi:10.13140/RG.2.1.2021.6565, Computational Mechanics Publications, Southampton, 1994.
  84. A. Sakellariou, D. Koutsoyiannis, and D. Tolikas, HYDROSCOPE: Experience from a distributed database system for hydrometeorological data, Hydraulic Engineering Software V: Proceedings of the 5th International Conference HYDROSOFT '94, edited by W. R. Blain and K. L. Katsifarakis, Sithonia, 2, 309–316, doi:10.13140/RG.2.1.1022.2325, Computational Mechanics Publications, Southampton, 1994.
  85. G. Tsakalias, and D. Koutsoyiannis, OPSIS: An intelligent tool for hydrologic data processing and visualisation, Proceedings of the 2nd European Conference on Advances in Water Resources Technology and Management, edited by G. Tsakiris and M. A. Santos, Lisbon, 45–50, doi:10.13140/RG.2.1.3070.2320, Balkema, Rotterdam, 1994.
  86. N. Papakostas, I. Nalbantis, and D. Koutsoyiannis, Modern computer technologies in hydrologic data management, Proceedings of the 2nd European Conference on Advances in Water Resources Technology and Management, edited by G. Tsakiris and M. A. Santos, Lisbon, 285–293, doi:10.13140/RG.2.1.4167.9604, Balkema, Rotterdam, 1994.
  87. N. Mamassis, et D. Koutsoyiannis, Structure stochastique de pluies intenses par type de temps, Publications de l'Association Internationale de Climatologie, 6eme Colloque International de Climatologie, edité par P. Maheras, Thessaloniki, 6, 301–313, doi:10.13140/RG.2.1.3643.6726, Association Internationale de Climatologie, Aix-en-Provence Cedex, France, 1993.
  88. I. Nalbantis, N. Mamassis, et D. Koutsoyiannis, Le phénomène recent de sécheresse persistante et l' alimentation en eau de la cité d' Athènes, Publications de l'Association Internationale de Climatologie, 6eme Colloque International de Climatologie, edité par P. Maheras, Thessaloniki, 6, 123–132, doi:10.13140/RG.2.1.4430.1041, Association Internationale de Climatologie, Aix-en-Provence Cedex, France, 1993.
  89. D. Tolikas, D. Koutsoyiannis, et Th. Xanthopoulos, HYDROSCOPE: Un systeme d'informations pour l'etude des phenomenes hydroclimatiques en Grece, Publications de l'Association Internationale de Climatologie, 6eme Colloque International de Climatologie, edité par P. Maheras, Thessaloniki, 6, 673–682, doi:10.13140/RG.2.1.2857.2409, Association Internationale de Climatologie, Aix-en-Provence Cedex, France, 1993.
  90. D. Koutsoyiannis, C. Tsolakidis, and N. Mamassis, HYDRA-PC, A data base system for regional hydrological data management, Proceedings of the 1st European Conference on Advances in Water Resources Technology, Athens, 551–557, doi:10.13140/RG.2.1.4954.3921, Balkema, Rotterdam, 1991.

Conference publications and presentations with evaluation of abstract

  1. G. Papacharalampous, H. Tyralis, A. Montanari, and D. Koutsoyiannis, Large-scale calibration of conceptual rainfall-runoff models for two-stage probabilistic hydrological post-processing, EGU General Assembly 2021, online, doi:10.5194/egusphere-egu21-18, European Geosciences Union, 2021.
  2. A. Lagos, S. Sigourou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Land Cover Change: Does it affect temperature variability?, EGU General Assembly 2021, online, EGU21-9000, doi:10.5194/egusphere-egu21-9000, European Geosciences Union, 2021.
  3. T. Iliopoulou, and D. Koutsoyiannis, PythOm: A python toolbox implementing recent advances in rainfall intensity (ombrian) curves, EGU General Assembly 2021, online, EGU21-389, doi:10.5194/egusphere-egu21-389, European Geosciences Union, 2021.
  4. G. Vagenas, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic analysis of time-series related to ocean acidification, EGU General Assembly 2021, online, EGU21-2637, doi:10.5194/egusphere-egu21-2637, European Geosciences Union, 2021.
  5. Ο. Akoumianaki, T. Iliopoulou, P. Dimitriadis, E. Varouchakis, and D. Koutsoyiannis, Stochastic analysis of the spatial stochastic structure of precipitation in the island of Crete, Greece, EGU General Assembly 2021, online, EGU21-4640, doi:10.5194/egusphere-egu21-4640, European Geosciences Union, 2021.
  6. A. Efstratiadis, I. Tsoukalas, and D. Koutsoyiannis, Revisiting the storage-reliability-yield concept in hydroelectricity, EGU General Assembly 2021, online, EGU21-10528, doi:10.5194/egusphere-egu21-10528, European Geosciences Union, 2021.
  7. K. Papoulakos, T. Iliopoulou, P. Dimitriadis, D. Tsaknias, and D. Koutsoyiannis, Investigating the impacts of clustering of floods on insurance practices; a spatiotemporal analysis in the USA, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-8667, doi:10.5194/egusphere-egu2020-8667, 2020.
  8. G.T. Manolis, K. Papoulakos, T. Iliopoulou, P. Dimitriadis, D. Tsaknias, and D. Koutsoyiannis, Clustering mechanisms of flood occurrence; modelling and relevance to insurance practices, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-9357, doi:10.5194/egusphere-egu2020-9357, 2020.
  9. D. Koutsoyiannis, and A. Montanari, A brisk local uncertainty estimator for hydrologic simulations and predictions (Blue Cat), European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, doi:10.5194/egusphere-egu2020-10125, 2020.
  10. A. Efstratiadis, N. Mamassis, A. Koukouvinos, D. Koutsoyiannis, K. Mazi, A. D. Koussis, S. Lykoudis, E. Demetriou, N. Malamos, A. Christofides, and D. Kalogeras, Open Hydrosystem Information Network: Greece’s new research infrastructure for water, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-4164, doi:10.5194/egusphere-egu2020-4164, 2020.
  11. G. Karavokiros, D. Nikolopoulos, S. Manouri, A. Efstratiadis, C. Makropoulos, N. Mamassis, and D. Koutsoyiannis, Hydronomeas 2020: Open-source decision support system for water resources management, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-20022, doi:10.5194/egusphere-egu2020-20022, 2020.
  12. D. Koutsoyiannis, Knowable moments for high-order characterization and modelling of hydrological processes for sustainable management of water resources, Invited Lecture, Bologna, Italy, doi:10.13140/RG.2.2.35109.86248, University of Bologna, 2019.
  13. C. Farmakis, P. Dimitriadis, V. Bellos, P. Papanicolaou, and D. Koutsoyiannis, Investigation of the uncertainty of spatial flood inundation among widely used 1D/2D hydrodynamic models, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15629, European Geosciences Union, 2019.
  14. D. Koutsoyiannis, Stochastic simulation of time irreversible processes and its use in hydrosystem control problems (Keynote talk), First Workshop on Control Methods for Water Resource Systems, Delft, The Netherlands, doi:10.13140/RG.2.2.10484.30088, International Federation of Automatic Control, 2019.
  15. K. Kardakaris, M. Kalli, T. Agoris, P. Dimitriadis, N. Mamassis, and D. Koutsoyiannis, Investigation of the stochastic structure of wind waves for energy production, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-13188, European Geosciences Union, 2019.
  16. S. Vavoulogiannis, N. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of rainfall and runoff series from a large hydrometeorological dataset, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, European Geosciences Union, 2019.
  17. T. Iliopoulou, and D. Koutsoyiannis, Comparing estimators for inferring dependence from records of hydrological extremes, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-9621, European Geosciences Union, 2019.
  18. T. Goulianou, K. Papoulakos, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic characteristics of flood impacts for agricultural insurance practices, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-5891, European Geosciences Union, 2019.
  19. D. Galanis, T. Andrikopoulou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Investigation and stochastic simulation of the music of wind and precipitation, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-13332, European Geosciences Union, 2019.
  20. M. Karataraki, A. Thanasko, K. Printziou, G. Koudouris, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, C. Plati, and D. Koutsoyiannis, Campus solar roads: a feasibility analysis, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15648-2, European Geosciences Union, 2019.
  21. M.-E. Asimomiti, N. Pelekanos, P. Dimitriadis, T. Iliopoulou, E. Vlahogianni, and D. Koutsoyiannis, Campus solar roads: Stochastic modeling of passenger demand, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10585, European Geosciences Union, 2019.
  22. A. Petsou, M.-E. Merakou, T. Iliopoulou, C. Iliopoulou, P. Dimitriadis, R. Ioannidis, K. Kepaptsoglou, and D. Koutsoyiannis, Campus solar roads: Optimization of solar panel and electric charging station location for university bus route, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10832, European Geosciences Union, 2019.
  23. G.-F. Sargentis, E. Frangedaki, P. Dimitriadis, and D. Koutsoyiannis, Development of a web platform of knowledge exchange for optimal selection of building materials based on ecological criteria, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10395, European Geosciences Union, 2019.
  24. Μ. Sako, E. Tsoli, R. Ioannidis, E. Frangedaki, G.-F. Sargentis, and D. Koutsoyiannis, Optimizing the size of Hilarion dam with technical, economical and environmental parameters, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15297, European Geosciences Union, 2019.
  25. R. Ioannidis, P. Dimitriadis, G.-F. Sargentis, E. Frangedaki, T. Iliopoulou, and D. Koutsoyiannis, Stochastic similarities between hydrometeorogical and art processes for optimizing architecture and landscape aesthetic parameters, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-11403, European Geosciences Union, 2019.
  26. D. Koutsoyiannis, Should we place a value on unmeasurable values?, Contribution to EGU 2019 Great Debate "Rewards and recognition in science: what value should we place on contributions that cannot be easily measured", European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, doi:10.13140/RG.2.2.36000.84483/1, European Geosciences Union, 2019.
  27. G. Papacharalampous, H. Tyralis, A. Langousis, A. W. Jayawardena, B. Sivakumar, N. Mamassis, A. Montanari, and D. Koutsoyiannis, Large-scale comparison of machine learning regression algorithms for probabilistic hydrological modelling via post-processing of point predictions, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-3576, European Geosciences Union, 2019.
  28. D. Koutsoyiannis, Extreme-oriented selection and fitting of probability distributions (solicited), European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10398, doi:10.13140/RG.2.2.15737.11362, European Geosciences Union, 2019.
  29. E. Zacharopoulou, I. Tsoukalas, A. Efstratiadis, and D. Koutsoyiannis, Impact of sample uncertainty of inflows to stochastic simulation of reservoirs, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-17233, European Geosciences Union, 2019.
  30. A. Efstratiadis, N. Mamassis, A. Koukouvinos, K. Mazi, E. Dimitriou, and D. Koutsoyiannis, Strategic plan for establishing a national-scale hydrometric network in Greece: challenges and perspectives, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-16714, European Geosciences Union, 2019.
  31. D. Koutsoyiannis, Unknowable and knowable moments: are they relevant to hydrofractals? (Plenary talk), Hydrofractals ’18, Constanta, Romania, doi:10.13140/RG.2.2.13446.27207, 2018.
  32. D. Koutsoyiannis, and N. Mamassis, Reconstructing the water supply conditions of the Ancient Piraeus, Biennial of Architectural and Urban Restoration (BRAU4), Pireaus, doi:10.13140/RG.2.2.18049.51044, 2018.
  33. A. Zoukos, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Global investigation of the multi-scale probabilistic behaviour of dry spells from rainfall records, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17966-1, doi:10.13140/RG.2.2.13555.78886, European Geosciences Union, 2018.
  34. V. Skoura, P. Dimitriadis, T. Iliopoulou, M. Crok, and D. Koutsoyiannis, A trendy analysis for the identification of extremal changes and trends in hydroclimatic processes; application to global precipitation, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17889-1, European Geosciences Union, 2018.
  35. E. Chardavellas, P. Dimitriadis, I. Papakonstantis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of vertical thermal jet and macroscale hydrometeorological processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17803-1, European Geosciences Union, 2018.
  36. P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Simulating precipitation at a fine time scale using a single continuous-state distribution, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18614, European Geosciences Union, 2018.
  37. P. Dimitriadis, and D. Koutsoyiannis, An innovative stochastic process and simulation algorithm for approximating any dependence structure and marginal distribution, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18710, European Geosciences Union, 2018.
  38. K. Sakellari, P. Dimitriadis, and D. Koutsoyiannis, A global stochastic analysis for the temperature and dew-point processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17941-1, European Geosciences Union, 2018.
  39. M. Chalakatevaki, E. Klousakou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of the uncertainty of hydrometeorological processes by means of the climacogram, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17714-1, European Geosciences Union, 2018.
  40. G. Karakatsanis, E. Kontarakis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Hydroclimate and agricultural output in developing countries, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-13059-1, European Geosciences Union, 2018.
  41. T. Iliopoulou, and D. Koutsoyiannis, A probabilistic index based on a two-state process to quantify clustering of rainfall extremes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-9777, European Geosciences Union, 2018.
  42. A. Tegos, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure and probability distribution of the global potential evapotranspiration, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17849-3, European Geosciences Union, 2018.
  43. E. Volpi, A. Fiori, S. Grimaldi, F. Lombardo, and D. Koutsoyiannis, Complete time-series frequency analysis: return period estimation for time-dependent processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-10439, European Geosciences Union, 2018.
  44. G. Papacharalampous, D. Koutsoyiannis, and A. Montanari, Toy models for increasing the understanding on stochastic process-based modelling, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-1900-1, European Geosciences Union, 2018.
  45. G.-F. Sargentis, R. Ioannidis, G. Karakatsanis, and D. Koutsoyiannis, The scale of infrastructures as a social decision. Case study: dams in Greece, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17082, European Geosciences Union, 2018.
  46. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, and D. Koutsoyiannis, Stochastic investigation of the Hurst-Kolmogorov behaviour in arts, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17740-1, European Geosciences Union, 2018.
  47. S. Sigourou, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, A. Skopeliti, K. Sakellari, G. Karakatsanis, L. Tsoulos, and D. Koutsoyiannis, Comparison of climate change vs. urbanization, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18598-2, European Geosciences Union, 2018.
  48. S. Sigourou, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, A. Skopeliti, K. Sakellari, G. Karakatsanis, L. Tsoulos, and D. Koutsoyiannis, Statistical and stochastic comparison of climate change vs. urbanization, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18608-2, European Geosciences Union, 2018.
  49. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, A step further from model-fitting for the assessment of the predictability of monthly temperature and precipitation, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-864, doi:10.6084/m9.figshare.7325783.v1, European Geosciences Union, 2018.
  50. D. Koutsoyiannis, and N. Mamassis, From mythology to science: the development of scientific hydrological concepts in the Greek antiquity (solicited), European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-10143-1, European Geosciences Union, 2018.
  51. P. Dimitriadis, H. Tyralis, T. Iliopoulou, K. Tzouka, Y. Markonis, N. Mamassis, and D. Koutsoyiannis, A climacogram estimator adjusted for timeseries length; application to key hydrometeorological processes by the Köppen-Geiger classification, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17832, European Geosciences Union, 2018.
  52. T. Iliopoulou, A. Montanari, and D. Koutsoyiannis, Estimating seasonality in river flows, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-12772, European Geosciences Union, 2018.
  53. A. Pizarro, P. Dimitriadis, C. Samela, D. Koutsoyiannis, O. Link, and S. Manfreda, Discharge uncertainty on bridge scour process, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-8045, European Geosciences Union, 2018.
  54. A. Pizarro, P. Dimitriadis, M. Chalakatevaki, C. Samela, S. Manfreda, and D. Koutsoyiannis, An integrated stochastic model of the river discharge process with emphasis on floods and bridge scour, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-8271, European Geosciences Union, 2018.
  55. A. Gkolemis, P. Dimitriadis, G. Karakatsanis, T. Iliopoulou, and D. Koutsoyiannis, A stochastic investigation of the intermittent behaviour of wind; application to renewable energy resources management, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-15979-3, European Geosciences Union, 2018.
  56. Y. Kalogeris, P. Dimitriadis, T. Iliopoulou, V. Papadopoulos, and D. Koutsoyiannis, Investigation of the correlation structure behaviour through intermediate storage retention, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17247-1, European Geosciences Union, 2018.
  57. K. Tzouka, P. Dimitriadis, E. Varouchakis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure of two-dimensional images of rocks from small to large scales, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17306-1, European Geosciences Union, 2018.
  58. P. Dimitriadis, E. Varouchakis, T. Iliopoulou, G. Karatzas, and D. Koutsoyiannis, Stochastic investigation of the spatial variability of precipitation over Crete, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17155-1, European Geosciences Union, 2018.
  59. M. Nezi, P. Dimitriadis, A. Pizarro, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of the streamflow process adjusted for human impact, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17473-1, European Geosciences Union, 2018.
  60. G. Koudouris, P. Dimitriadis, T. Iliopoulou, G. Karakatsanis, and D. Koutsoyiannis, A stochastic model for hourly solar radiation process applied in renewable resources management, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-16275-2, European Geosciences Union, 2018.
  61. E. Klousakou, M. Chalakatevaki, R. Tomani, P. Dimitriadis, A. Efstratiadis, T. Iliopoulou, R. Ioannidis, N. Mamassis, and D. Koutsoyiannis, Stochastic investigation of the uncertainty of atmospheric processes related to renewable energy resources, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-16982-2, European Geosciences Union, 2018.
  62. P. Dimitriadis, T. Iliopoulou, A. Efstratiadis, P. Papanicolaou, and D. Koutsoyiannis, Stochastic investigation of the uncertainty in common rating-curve relationships, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18947-2, European Geosciences Union, 2018.
  63. G. Markopoulos-Sarikas, C. Ntigkakis, P. Dimitriadis, G. Papadonikolaki, A. Efstratiadis, A. Stamou, and D. Koutsoyiannis, How probable was the flood inundation in Mandra? A preliminary urban flood inundation analysis, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17527-1, European Geosciences Union, 2018.
  64. C. Ntigkakis, G. Markopoulos-Sarikas, P. Dimitriadis, T. Iliopoulou, A. Efstratiadis, A. Koukouvinos, A. D. Koussis, K. Mazi, D. Katsanos, and D. Koutsoyiannis, Hydrological investigation of the catastrophic flood event in Mandra, Western Attica, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17591-1, European Geosciences Union, 2018.
  65. I. Anyfanti, P. Dimitriadis, D. Koutsoyiannis, N. Mamassis, and A. Efstratiadis, Handling the computation effort of time-demanding water-energy simulation models through surrogate approaches, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-12110, European Geosciences Union, 2018.
  66. A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Effective combination of stochastic and deterministic hydrological models in a changing environment, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-11989, European Geosciences Union, 2018.
  67. P. Dimitriadis, K. Tzouka, H. Tyralis, and D. Koutsoyiannis, Stochastic investigation of rock anisotropy based on the climacogram, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10632-1, European Geosciences Union, 2017.
  68. T. Iliopoulou, C. Aguilar , B. Arheimer, M. Bermúdez, N. Bezak, A. Ficchi, D. Koutsoyiannis, J. Parajka, M. J. Polo, G. Thirel, and A. Montanari, Investigating the physical basis of river memory and application to flood frequency prediction, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, European Geosciences Union, 2017.
  69. P. Dimitriadis, T. Iliopoulou, H. Tyralis, and D. Koutsoyiannis, Identifying the dependence structure of a process through pooled timeseries analysis, IAHS Scientific Assembly 2017, Port Elizabeth, South Africa, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2017.
  70. H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, An extensive review and comparison of R Packages on the long-range dependence estimators, Asia Oceania Geosciences Society (AOGS) 14th Annual Meeting, Singapore, HS06-A003, doi:10.13140/RG.2.2.18837.22249, Asia Oceania Geosciences Society, 2017.
  71. H. Tyralis, and D. Koutsoyiannis, The Bayesian Processor of Forecasts on the probabilistic forecasting of long-range dependent variables using General Circulation Models, Asia Oceania Geosciences Society (AOGS) 14th Annual Meeting, Singapore, HS20-A002, doi:10.13140/RG.2.2.15481.77922, Asia Oceania Geosciences Society, 2017.
  72. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Large scale simulation experiments for the assessment of one-step ahead forecasting properties of stochastic and machine learning point estimation methods, Asia Oceania Geosciences Society (AOGS) 14th Annual Meeting, Singapore, HS06-A002, doi:10.13140/RG.2.2.33273.77923, Asia Oceania Geosciences Society, 2017.
  73. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, A set of metrics for the effective evaluation of point forecasting methods used for hydrological tasks, Asia Oceania Geosciences Society (AOGS) 14th Annual Meeting, Singapore, HS01-A001, doi:10.13140/RG.2.2.19852.00641, Asia Oceania Geosciences Society, 2017.
  74. T. Iliopoulou, and D. Koutsoyiannis, Investigating links between Long-Range Dependence in mean rainfall and clustering of extreme rainfall, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-9890-1, doi:10.13140/RG.2.2.25992.21763, European Geosciences Union, 2017.
  75. H. Tyralis, P. Dimitriadis, T. Iliopoulou, K. Tzouka, and D. Koutsoyiannis, Dependence of long-term persistence properties of precipitation on spatial and regional characteristics, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-3711, doi:10.13140/RG.2.2.13252.83840/1, European Geosciences Union, 2017.
  76. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Investigation of the effect of the hyperparameter optimization and the time lag selection in time series forecasting using machine learning algorithms, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-3072-1, doi:10.13140/RG.2.2.20560.92165/1, European Geosciences Union, 2017.
  77. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Multi-step ahead streamflow forecasting for the operation of hydropower reservoirs, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-3069, doi:10.13140/RG.2.2.27271.80801, European Geosciences Union, 2017.
  78. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Comparison between stochastic and machine learning methods for hydrological multi-step ahead forecasting: All forecasts are wrong!, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-3068-2, doi:10.13140/RG.2.2.17205.47848, European Geosciences Union, 2017.
  79. V. Daniil, G. Pouliasis, E. Zacharopoulou, E. Demetriou, G. Manou, M. Chalakatevaki, I. Parara, C. Georganta, P. Stamou, S. Karali, E. Hadjimitsis, G. Koudouris, E. Moschos, D. Roussis, K. Papoulakos, A. Koskinas, G. Pollakis, N. Gournari, K. Sakellari, Y. Moustakis, N. Mamassis, A. Efstratiadis, H. Tyralis, P. Dimitriadis, T. Iliopoulou, G. Karakatsanis, K. Tzouka, I. Deligiannis, V. Tsoukala, P. Papanicolaou, and D. Koutsoyiannis, The uncertainty of atmospheric processes in planning a hybrid renewable energy system for a non-connected island, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-16781-4, doi:10.13140/RG.2.2.29610.62406, European Geosciences Union, 2017.
  80. P. Stamou, S. Karali, M. Chalakatevaki, V. Daniil, K. Tzouka, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and N. Mamassis, Creating the electric energy mix of a non-connected Aegean island, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10130-10, doi:10.13140/RG.2.2.36537.77927, European Geosciences Union, 2017.
  81. E. Hadjimitsis, E. Demetriou, K. Sakellari, H. Tyralis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Investigation of the stochastic nature of temperature and humidity for energy management, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10164-5, European Geosciences Union, 2017.
  82. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, Investigation of the stochastic nature of solar radiation for renewable resources management, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10189-4, doi:10.13140/RG.2.2.16215.06564, European Geosciences Union, 2017.
  83. E. Moschos, G. Manou, C. Georganta, P. Dimitriadis, T. Iliopoulou, H. Tyralis, D. Koutsoyiannis, and V. Tsoukala, Investigation of the stochastic nature of wave processes for renewable resources management: a pilot application in a remote island in the Aegean sea, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10225-3, doi:10.13140/RG.2.2.30226.66245, European Geosciences Union, 2017.
  84. A. Koskinas, E. Zacharopoulou, G. Pouliasis, I. Engonopoulos, K. Mavroyeoryos, I. Deligiannis, G. Karakatsanis, P. Dimitriadis, T. Iliopoulou, D. Koutsoyiannis, and H. Tyralis, Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10495-4, doi:10.13140/RG.2.2.10529.81767, European Geosciences Union, 2017.
  85. D. Roussis, I. Parara, N. Gournari, Y. Moustakis, P. Dimitriadis, T. Iliopoulou, D. Koutsoyiannis, and G. Karakatsanis, Energy, variability and weather finance engineering, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-16919, European Geosciences Union, 2017.
  86. K. Papoulakos, G. Pollakis, Y. Moustakis, A. Markopoulos, T. Iliopoulou, P. Dimitriadis, D. Koutsoyiannis, and A. Efstratiadis, Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10334-4, European Geosciences Union, 2017.
  87. P. Dimitriadis, Y. Markonis, T. Iliopoulou, E. Feloni, N. Gournari, I. Deligiannis, P. Kastis, C. Nasika, E. Lerias, Y. Moustakis, A. Petsiou, A. Sotiriadou, A. Markopoulos, V. Tyrogiannis, and D. Koutsoyiannis, Stochastic similarities between hydroclimatic processes for variability characterization, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, European Geosciences Union, 2016.
  88. I. Deligiannis, P. Dimitriadis, and D. Koutsoyiannis, Hourly temporal distribution of wind, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, 18, EGU2016-13138-4, doi:10.13140/RG.2.2.25967.53928, European Geosciences Union, 2016.
  89. E. Lerias, A. Kalamioti, P. Dimitriadis, Y. Markonis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of temperature process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14828-3, European Geosciences Union, 2016.
  90. I. Deligiannis, V. Tyrogiannis, Ο. Daskalou, P. Dimitriadis, Y. Markonis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of wind process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14946-6, doi:10.13140/RG.2.2.26681.36969, European Geosciences Union, 2016.
  91. A. Sotiriadou, A. Petsiou, E. Feloni, P. Kastis, T. Iliopoulou, Y. Markonis, H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of precipitation process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-15137-5, doi:10.13140/RG.2.2.28955.46881, European Geosciences Union, 2016.
  92. P. Dimitriadis, N. Gournari, and D. Koutsoyiannis, Markov vs. Hurst-Kolmogorov behaviour identification in hydroclimatic processes, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14577-4, doi:10.13140/RG.2.2.21019.05927, European Geosciences Union, 2016.
  93. Y. Markonis, C. Nasika, Y. Moustakis, A. Markopoulos, P. Dimitriadis, and D. Koutsoyiannis, Global investigation of Hurst-Kolmogorov behaviour in river runoff, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-17491, doi:10.13140/RG.2.2.16331.59684, European Geosciences Union, 2016.
  94. D. Koutsoyiannis, F. Lombardo, P. Dimitriadis, Y. Markonis, and S. Stevens, From fractals to stochastics: seeking theoretical consistency in analysis of geophysical data, 30 Years of Nonlinear Dynamics in Geosciences, Rhodes, Greece, doi:10.13140/RG.2.2.34215.55209, 2016.
  95. D. Koutsoyiannis, and P. Dimitriadis, From time series to stochastics: A theoretical framework with applications on time scales spanning from microseconds to megayears, Orlob Second International Symposium on Theoretical Hydrology, Davis, California, USA, doi:10.13140/RG.2.2.14082.89284, University California Davis, 2016.
  96. D. Koutsoyiannis, The unavoidable uncertainty of renewable energy and its management, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016–18430, doi:10.13140/RG.2.2.36312.70400, European Geosciences Union, 2016.
  97. Ο. Daskalou, M. Karanastasi, Y. Markonis, P. Dimitriadis, A. Koukouvinos, A. Efstratiadis, and D. Koutsoyiannis, GIS-based approach for optimal siting and sizing of renewables considering techno-environmental constraints and the stochastic nature of meteorological inputs, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-12044-1, doi:10.13140/RG.2.2.19535.48803, European Geosciences Union, 2016.
  98. C. Pappas, M.D. Mahecha, D.C. Frank, and D. Koutsoyiannis, New insights on the variability of ecosystem functioning across time scales, AGU 2015 Fall Meeting, San Francisco, USA, doi:10.13140/RG.2.2.24568.65280, American Geophysical Union, 2015.
  99. E. Volpi, A. Fiori, S. Grimaldi, F. Lombardo, and D. Koutsoyiannis, Return period for time-dependent processes, STAHY’15 Workshop, doi:10.13140/RG.2.2.22052.07044, International Association of Hydrological Sciences, Addis Ababa, Ethiopia, 2015.
  100. N. Malamos, A. Tegos, I. L. Tsirogiannis, A. Christofides, and D. Koutsoyiannis, Implementation of a regional parametric model for potential evapotranspiration assessment, IrriMed 2015 – Modern technologies, strategies and tools for sustainable irrigation management and governance in Mediterranean agriculture, Bari, doi:10.13140/RG.2.1.3992.0725, 2015.
  101. D. Koutsoyiannis, and N. Mamassis, The water supply of Athens through the centuries, 16th conference Cura Aquarum, Athens, doi:10.13140/RG.2.2.24516.22400/1, German Water History Association, German Archaeological Institute in Athens, 2015.
  102. P. Dimitriadis, L. Lappas, Ο. Daskalou, A. M. Filippidou, M. Giannakou, Ε. Gkova, R. Ioannidis, Α. Polydera, Ε. Polymerou, Ε. Psarrou, A. Vyrini, S.M. Papalexiou, and D. Koutsoyiannis, Application of stochastic methods for wind speed forecasting and wind turbines design at the area of Thessaly, Greece, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-13810, doi:10.13140/RG.2.2.25355.08486, European Geosciences Union, 2015.
  103. Y. Markonis, T. Dimoulas, A. Atalioti, C. Konstantinou, A. Kontini, Μ.-Ι. Pipini, E. Skarlatou, V. Sarantopoulos, K. Tzouka, S.M. Papalexiou, and D. Koutsoyiannis, Comparison between satellite and instrumental solar irradiance data at the city of Athens, Greece, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5719, doi:10.13140/RG.2.2.12274.09920, European Geosciences Union, 2015.
  104. D. Koutsoyiannis, Parsimonious entropy-based stochastic modelling for changing hydroclimatic processes, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4461, doi:10.13140/RG.2.2.13951.82089, European Geosciences Union, 2015.
  105. D. Koutsoyiannis, and A. Montanari, Climate is changing, everything is flowing, stationarity is immortal, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4411-2, doi:10.13140/RG.2.2.10596.37762, European Geosciences Union, 2015.
  106. E. Rozos, A. D. Koussis, and D. Koutsoyiannis, Efficient discretization in finite difference method, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-9608, doi:10.13140/RG.2.1.3140.1044, European Geosciences Union, 2015.
  107. P. Kossieris, A. Efstratiadis, I. Tsoukalas, and D. Koutsoyiannis, Assessing the performance of Bartlett-Lewis model on the simulation of Athens rainfall, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-8983, doi:10.13140/RG.2.2.14371.25120, European Geosciences Union, 2015.
  108. A. Koukouvinos, D. Nikolopoulos, A. Efstratiadis, A. Tegos, E. Rozos, S.M. Papalexiou, P. Dimitriadis, Y. Markonis, P. Kossieris, H. Tyralis, G. Karakatsanis, K. Tzouka, A. Christofides, G. Karavokiros, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Integrated water and renewable energy management: the Acheloos-Peneios region case study, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-4912, doi:10.13140/RG.2.2.17726.69440, European Geosciences Union, 2015.
  109. A. Efstratiadis, I. Tsoukalas, P. Kossieris, G. Karavokiros, A. Christofides, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Computational issues in complex water-energy optimization problems: Time scales, parameterizations, objectives and algorithms, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5121, doi:10.13140/RG.2.2.11015.80802, European Geosciences Union, 2015.
  110. A. Zarkadoulas, K. Mantesi, A. Efstratiadis, A. D. Koussis, K. Mazi, D. Katsanos, A. Koukouvinos, and D. Koutsoyiannis, A hydrometeorological forecasting approach for basins with complex flow regime, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-3904, doi:10.13140/RG.2.2.21920.99842, European Geosciences Union, 2015.
  111. P. Dimitriadis, and D. Koutsoyiannis, Using multiple stochastic tools in identification of scaling in hydrometeorology, AGU 2014 Fall Meeting, San Francisco, USA, American Geophysical Union, 2014.
  112. G. Karakatsanis, N. Mamassis, and D. Koutsoyiannis, Entropy, recycling and macroeconomics of water resources, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, European Geosciences Union, 2014.
  113. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, IRLA2014 – The Effects of Irrigation and Drainage on Rural and Urban Landscapes, Patras, doi:10.13140/RG.2.2.14004.24966, 2014.
  114. D. Koutsoyiannis, Random musings on stochastics (Lorenz Lecture), AGU 2014 Fall Meeting, San Francisco, USA, doi:10.13140/RG.2.1.2852.8804, American Geophysical Union, 2014.
  115. D. Koutsoyiannis, and A. Montanari, Risks from dismissing stationarity, AGU 2014 Fall Meeting, San Francisco, USA, doi:10.13140/RG.2.2.36234.06084, American Geophysical Union, 2014.
  116. F. Lombardo, E. Volpi, and D. Koutsoyiannis, Temporal disaggregation of rainfall, IDRA 2014 – XXXIV Conference of Hydraulics and Hydraulic Engineering, Bari, Italy, doi:10.13140/RG.2.2.32878.61768, 2014.
  117. I. Koukas, V. Koukoravas, K. Mantesi, K. Sakellari, T.-D. Xanthopoulou, A. Zarkadoulas, Y. Markonis, S.M. Papalexiou, and D. Koutsoyiannis, Statistical properties and Hurst-Kolmogorov dynamics in climatic proxy data and temperature reconstructions, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-9290-2, doi:10.13140/RG.2.2.21134.56644, European Geosciences Union, 2014.
  118. Y. Dimakos, E. C. Moschou, S. C. Batelis, Y. Markonis, and D. Koutsoyiannis, Monthly rainfall trends in Greece (1950 - 2012), European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-8289, doi:10.13140/RG.2.2.14594.07367, European Geosciences Union, 2014.
  119. I. Pappa, Y. Dimakos, P. Dimas, P. Kossieris, P. Dimitriadis, and D. Koutsoyiannis, Spatial and temporal variability of wind speed and energy over Greece, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-13591, doi:10.13140/RG.2.2.11238.63048, European Geosciences Union, 2014.
  120. G. Karakatsanis, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Entropy, pricing and macroeconomics of pumped-storage systems, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-15858-6, European Geosciences Union, 2014.
  121. P. Dimas, D. Bouziotas, A. Efstratiadis, and D. Koutsoyiannis, A holistic approach towards optimal planning of hybrid renewable energy systems: Combining hydroelectric and wind energy, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-5851, doi:10.13140/RG.2.2.28854.70723, European Geosciences Union, 2014.
  122. D. Koutsoyiannis, Hydrology, society, change and uncertainty (invited talk), European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-4243, doi:10.13140/RG.2.2.15432.93441, European Geosciences Union, 2014.
  123. A. M. Filippidou, A. Andrianopoulos, C. Argyrakis, L. E. Chomata, V. Dagalaki, X. Grigoris, T. S. Kokkoris, M. Nasioka, K. A. Papazoglou, S.M. Papalexiou, H. Tyralis, and D. Koutsoyiannis, Comparison of climate time series produced by General Circulation Models and by observed data on a global scale, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-8529, doi:10.13140/RG.2.2.33887.87200, European Geosciences Union, 2014.
  124. D. Koutsoyiannis, Glimpsing God playing dice over water and climate, Lectio Inauguralis, Bogotá, Colombia, doi:10.13140/RG.2.2.13755.21282, Pontificia Universidad Javeriana, 2014.
  125. T.A. Cohn, D. Koutsoyiannis, H. F. Lins, and A. Montanari, If I had not believed it, I would not have seen it (Contribution to the Round Table for Harold Edwin Hurst), Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.17110.65609, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  126. F. Lombardo, E. Volpi, and D. Koutsoyiannis, How to parsimoniously disaggregate rainfall in time, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.11448.34560, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  127. P. Dimitriadis, D. Koutsoyiannis, and C. Onof, N-Dimensional generalized Hurst-Kolmogorov process and its application to wind fields, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.15642.64963, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  128. H. Tyralis, and D. Koutsoyiannis, Simultaneous use of observations and deterministic model outputs to forecast persistent stochastic processes, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.1.3230.4889, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  129. E. Rozos, and D. Koutsoyiannis, Assessing the error of geometry-based discretizations in groundwater modelling, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.17320.37120, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  130. V.K. Vasilaki, S. Curceac, S.M. Papalexiou, and D. Koutsoyiannis, Geophysical time series vs. financial time series of agricultural products: Similarities and differences, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.36194.73922, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  131. C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, A quick gap-filling of missing hydrometeorological data, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.22772.96641, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  132. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Climacogram-based modelling of isotropic turbulence, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  133. P. Dimitriadis, K. Tzouka, and D. Koutsoyiannis, Windows of predictability in dice motion, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.19417.52322, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  134. T. Tsitseli, D. Koutsoyiannis, A. Koukouvinos, and N. Mamassis, Construction of ombrian curves using the Hydrognomon software system, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.34517.01762, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  135. E. C. Moschou, S. C. Batelis, Y. Dimakos, I. Fountoulakis, Y. Markonis, S.M. Papalexiou, N. Mamassis, and D. Koutsoyiannis, Spatial and temporal rainfall variability over Greece, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.19102.95045, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  136. N. Bountas, N. Boboti, E. Feloni, L. Zeikos, Y. Markonis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Temperature variability over Greece: Links between space and time, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.17739.80164, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  137. Y. Markonis, A. Efstratiadis, A. Koukouvinos, N. Mamassis, and D. Koutsoyiannis, Investigation of drought characteristics in different temporal and spatial scales: A case study in the Mediterranean region , Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  138. G. Karakatsanis, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Entropy and reliability of water use via a statistical approach of scarcity, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.24450.68809, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  139. P. Kossieris, A. Efstratiadis, and D. Koutsoyiannis, Coupling the strengths of optimization and simulation for calibrating Poisson cluster models, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.15223.21929, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  140. P. Kossieris, A. Efstratiadis, and D. Koutsoyiannis, The use of stochastic objective functions in water resource optimization problems, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.18578.66249, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  141. P. Dimas, D. Bouziotas, A. Efstratiadis, and D. Koutsoyiannis, A stochastic simulation framework for planning and management of combined hydropower and wind energy systems, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.27491.55841, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  142. E. Michailidi, T. Mastrotheodoros, A. Efstratiadis, A. Koukouvinos, and D. Koutsoyiannis, Flood modelling in river basins with highly variable runoff, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.30847.00167, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  143. A. Efstratiadis, A. Koukouvinos, P. Dimitriadis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, A stochastic simulation framework for flood engineering, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.16848.51201, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  144. F. Lombardo, E. Volpi, and D. Koutsoyiannis, Effect of time discretization and finite record length on continuous-time stochastic properties, IAHS - IAPSO - IASPEI Joint Assembly, Gothenburg, Sweden, doi:10.13140/RG.2.2.29955.71206, International Association of Hydrological Sciences, International Association for the Physical Sciences of the Oceans, International Association of Seismology and Physics of the Earth's Interior, 2013.
  145. A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Hydrological modelling in presence of non-stationarity induced by urbanisation: an assessment of the value of information, “Knowledge for the future”, IAHS - IAPSO – IASPEI Joint Assembly 2013, Gothenburg, doi:10.13140/RG.2.2.13178.49607, International Association of Hydrological Sciences, 2013.
  146. D. Koutsoyiannis, Entropy: from thermodynamics to hydrology (invited talk), Orlob First International Symposium on Theoretical Hydrology, Davis, California, USA, doi:10.13140/RG.2.2.28277.99048, University California Davis, 2013.
  147. D. Koutsoyiannis, In defence of stationarity (invited talk), IAHS - IAPSO - IASPEI Joint Assembly, Gothenburg, Sweden, doi:10.13140/RG.2.2.18211.66083, International Association of Hydrological Sciences, International Association for the Physical Sciences of the Oceans, International Association of Seismology and Physics of the Earth's Interior, 2013.
  148. A. Oikonomou, P. Dimitriadis, A. Koukouvinos, A. Tegos, V. Pagana, P. Panagopoulos, N. Mamassis, and D. Koutsoyiannis, Floodplain mapping via 1D and quasi-2D numerical models in the valley of Thessaly, Greece, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10366, doi:10.13140/RG.2.2.25165.03040, European Geosciences Union, 2013.
  149. T. Iliopoulou, S.M. Papalexiou, and D. Koutsoyiannis, Assessment of the dependence structure of the annual rainfall using a large data set, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-5276, doi:10.13140/RG.2.2.13080.19202, European Geosciences Union, 2013.
  150. S. Nerantzaki, S.M. Papalexiou, and D. Koutsoyiannis, Extreme rainfall distribution tails: Exponential, subexponential or hyperexponential?, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-5149, doi:10.13140/RG.2.2.29857.40803, European Geosciences Union, 2013.
  151. A. Mystegniotis, V. Vasilaki, I. Pappa, S. Curceac, D. Saltouridou, N. Efthimiou, I. Papatsoutsos, S.M. Papalexiou, and D. Koutsoyiannis, Clustering of extreme events in typical stochastic models, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-4599, doi:10.13140/RG.2.2.10353.89449, European Geosciences Union, 2013.
  152. E. Anagnostopoulou, A. Galani, P. Dimas, A. Karanasios, T. Mastrotheodoros, E. Michailidi, D. Nikolopoulos, S. Pontikos, F. Sourla, A. Chazapi, S.M. Papalexiou, and D. Koutsoyiannis, Record breaking properties for typical autocorrelation structures, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-4520, doi:10.13140/RG.2.2.20420.22400, European Geosciences Union, 2013.
  153. D. Koutsoyiannis, Climacogram-based pseudospectrum: a simple tool to assess scaling properties, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-4209, doi:10.13140/RG.2.2.18506.57284, European Geosciences Union, 2013.
  154. G. Tsekouras, C. Ioannou, A. Efstratiadis, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes for optimizing hybrid renewable energy systems, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-11660, doi:10.13140/RG.2.2.30250.62404, European Geosciences Union, 2013.
  155. A. Venediki, S. Giannoulis, C. Ioannou, L. Malatesta, G. Theodoropoulos, G. Tsekouras, Y. Dialynas, S.M. Papalexiou, A. Efstratiadis, and D. Koutsoyiannis, The Castalia stochastic generator and its applications to multivariate disaggregation of hydro-meteorological processes, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-11542, doi:10.13140/RG.2.2.15675.41764, European Geosciences Union, 2013.
  156. Y. Markonis, S.M. Papalexiou, and D. Koutsoyiannis, The role of teleconnections in extreme (high and low) precipitation events: The case of the Mediterranean region, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-5368, doi:10.13140/RG.2.2.10642.25286, European Geosciences Union, 2013.
  157. E. Rozos, and D. Koutsoyiannis, Studying solute transport using parsimonious groundwater modelling, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-2225, doi:10.13140/RG.2.2.29516.62087, European Geosciences Union, Vienna, Austria, 2013.
  158. F. Lombardo, E. Volpi, S.M. Papalexiou, and D. Koutsoyiannis, Multifractal downscaling models: a crash test, 3rd STAHY International Workshop on Statistical Methods for Hydrology and Water Resources Management, Tunis, Tunisia, doi:10.13140/RG.2.2.32872.06404, International Association of Hydrological Sciences, 2012.
  159. P. Dimitriadis, D. Koutsoyiannis, and Y. Markonis, Spectrum vs Climacogram, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-993, doi:10.13140/RG.2.2.27838.89920, European Geosciences Union, 2012.
  160. D. Koutsoyiannis, and A. Efstratiadis, The necessity for large-scale hybrid renewable energy systems, Hydrology and Society, EGU Leonardo Topical Conference Series on the hydrological cycle 2012, Torino, doi:10.13140/RG.2.2.30355.48161, European Geosciences Union, 2012.
  161. A. Efstratiadis, D. Bouziotas, and D. Koutsoyiannis, The parameterization-simulation-optimization framework for the management of hydroelectric reservoir systems, Hydrology and Society, EGU Leonardo Topical Conference Series on the hydrological cycle 2012, Torino, doi:10.13140/RG.2.2.36437.22243, European Geosciences Union, 2012.
  162. A. Efstratiadis, A. D. Koussis, D. Koutsoyiannis, N. Mamassis, and S. Lykoudis, Flood design recipes vs. reality: Can predictions for ungauged basins be trusted? – A perspective from Greece, Advanced methods for flood estimation in a variable and changing environment, Volos, doi:10.13140/RG.2.2.19660.00644, University of Thessaly, 2012.
  163. D. Koutsoyiannis, From deterministic heterogeneity to stochastic homogeneity, IAHS 90th Anniversary – PUB Symposium 2012, Delft, The Netherlands, doi:10.13140/RG.2.2.34759.50085, International Association of Hydrological Sciences, 2012.
  164. D. Koutsoyiannis, Vít Klemeš: Lessons of vitality, 3rd STAHY International Workshop on Statistical Methods for Hydrology and Water Resources Management, Tunis, Tunisia, doi:10.13140/RG.2.2.25532.03204, International Association of Hydrological Sciences, 2012.
  165. Y. Markonis, P. Kossieris, A. Lykou, and D. Koutsoyiannis, Effects of Medieval Warm Period and Little Ice Age on the hydrology of Mediterranean region, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 12181, doi:10.13140/RG.2.2.30565.19683, European Geosciences Union, 2012.
  166. E. Steirou, and D. Koutsoyiannis, Investigation of methods for hydroclimatic data homogenization, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 956-1, doi:10.13140/RG.2.2.23854.31046, European Geosciences Union, 2012.
  167. S. Giannoulis, C. Ioannou, E. Karantinos, L. Malatesta, G. Theodoropoulos, G. Tsekouras, A. Venediki, P. Dimitriadis, S.M. Papalexiou, and D. Koutsoyiannis, Long term properties of monthly atmospheric pressure fields, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 4680, doi:10.13140/RG.2.2.36017.79201, European Geosciences Union, 2012.
  168. S.M. Papalexiou, and D. Koutsoyiannis, A global survey on the distribution of annual maxima of daily rainfall: Gumbel or Fréchet?, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 10563, doi:10.13140/RG.2.2.29306.90566, European Geosciences Union, 2012.
  169. E. Houdalaki, M. Basta, N. Boboti, N. Bountas, E. Dodoula, T. Iliopoulou, S. Ioannidou, K. Kassas, S. Nerantzaki, E. Papatriantafyllou, K. Tettas, D. Tsirantonaki, S.M. Papalexiou, and D. Koutsoyiannis, On statistical biases and their common neglect, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 4388, doi:10.13140/RG.2.2.25951.46248, European Geosciences Union, 2012.
  170. H. Tyralis, and D. Koutsoyiannis, A Bayesian approach to hydroclimatic prognosis using the Hurst-Kolmogorov stochastic process, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, doi:10.13140/RG.2.2.24273.74089, European Geosciences Union, 2012.
  171. S. Kozanis, A. Christofides, A. Efstratiadis, A. Koukouvinos, G. Karavokiros, N. Mamassis, D. Koutsoyiannis, and D. Nikolopoulos, Using open source software for the supervision and management of the water resources system of Athens, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 7158, doi:10.13140/RG.2.2.28468.04482, European Geosciences Union, 2012.
  172. P. Kossieris, D. Koutsoyiannis, C. Onof, H. Tyralis, and A. Efstratiadis, HyetosR: An R package for temporal stochastic simulation of rainfall at fine time scales, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 11718, European Geosciences Union, 2012.
  173. D. Koutsoyiannis, A Monte Carlo approach to water management (solicited), European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 3509, doi:10.13140/RG.2.2.20079.43687, European Geosciences Union, 2012.
  174. P. Dimitriadis, P. Papanicolaou, and D. Koutsoyiannis, Hurst-Kolmogorov dynamics applied to temperature fields for small turbulence scales, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-772, doi:10.13140/RG.2.2.22137.26724, European Geosciences Union, 2011.
  175. P. Dimitriadis, D. Koutsoyiannis, C. Onof, and K. Tzouka, Multidimensional Hurst-Kolmogorov process for modelling temperature and rainfall fields, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-739, doi:10.13140/RG.2.2.12070.93761, European Geosciences Union, 2011.
  176. Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A computer system for the stochastic disaggregation of monthly into daily hydrological time series as part of a three–level multivariate scheme, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-290, doi:10.13140/RG.2.2.23814.98885, European Geosciences Union, 2011.
  177. D. Koutsoyiannis, A hymn to entropy (Invited talk), IUGG 2011, Melbourne, doi:10.13140/RG.2.2.36607.61601, International Union of Geodesy and Geophysics, 2011.
  178. D. Koutsoyiannis, Hydrology and Change (Plenary lecture), IUGG 2011, Melbourne, doi:10.13140/RG.2.1.3685.6568, International Union of Geodesy and Geophysics, 2011.
  179. G. Di Baldassarre, A. Montanari, H. F. Lins, D. Koutsoyiannis, L. Brandimarte, and G. Blöschl, Increasing flood risk in Africa: a climate signal?, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-5634-1, doi:10.13140/RG.2.2.26541.28648, European Geosciences Union, 2011.
  180. F. Lombardo, E. Volpi, and D. Koutsoyiannis, Theoretical and empirical comparison of stochastic disaggregation and downscaling approaches for rainfall time series, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-854-1, doi:10.13140/RG.2.2.31574.45124, European Geosciences Union, 2011.
  181. D. Tsaknias, D. Bouziotas, A. Christofides, A. Efstratiadis, and D. Koutsoyiannis, Statistical comparison of observed temperature and rainfall extremes with climate model outputs, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-3454, doi:10.13140/RG.2.2.15321.52322, European Geosciences Union, 2011.
  182. A. Christofides, and D. Koutsoyiannis, Causality in climate and hydrology, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-7440, doi:10.13140/RG.2.2.33776.46082, European Geosciences Union, 2011.
  183. S.M. Papalexiou, and D. Koutsoyiannis, A worldwide probabilistic analysis of rainfall at multiple timescales based on entropy maximization, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-11557, doi:10.13140/RG.2.2.20354.68800, European Geosciences Union, 2011.
  184. D. Bouziotas, G. Deskos, N. Mastrantonas, D. Tsaknias, G. Vangelidis, S.M. Papalexiou, and D. Koutsoyiannis, Long-term properties of annual maximum daily river discharge worldwide, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-1439, doi:10.13140/RG.2.2.13643.80164, European Geosciences Union, 2011.
  185. S.M. Papalexiou, and D. Koutsoyiannis, Entropy maximization, p-moments and power-type distributions in nature, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-6884, doi:10.13140/RG.2.2.16999.24484, European Geosciences Union, 2011.
  186. Y. Markonis, and D. Koutsoyiannis, Hurst-Kolmogorov dynamics in long climatic proxy records, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-13700, doi:10.13140/RG.2.2.23080.98565, European Geosciences Union, 2011.
  187. D. Koutsoyiannis, S. Kozanis, and H. Tyralis, A general Monte Carlo method for the construction of confidence intervals for a function of probability distribution parameters, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-1489, doi:10.13140/RG.2.2.33147.31527, European Geosciences Union, 2011.
  188. S.M. Papalexiou, E. Kallitsi, E. Steirou, M. Xirouchakis, A. Drosou, V. Mathios, H. Adraktas-Rentis, I. Kyprianou, M.-A. Vasilaki, and D. Koutsoyiannis, Long-term properties of annual maximum daily rainfall worldwide, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-1444, doi:10.13140/RG.2.2.13014.65600, European Geosciences Union, 2011.
  189. E. Rozos, and D. Koutsoyiannis, Benefits from using Kalman filter in forward and inverse groundwater modelling, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-2212, doi:10.13140/RG.2.2.28114.15040, European Geosciences Union, 2011.
  190. A. Montanari, and D. Koutsoyiannis, Stochastic physically-based modelling in hydrology: towards a synthesis of different approaches for a new target, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-11775, doi:10.13140/RG.2.2.35663.89763, European Geosciences Union, 2011.
  191. D. Koutsoyiannis, and S.M. Papalexiou, Scaling as enhanced uncertainty, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-1305, doi:10.13140/RG.2.2.15531.23844, European Geosciences Union, 2011.
  192. A. Montanari, and D. Koutsoyiannis, Is deterministic physically-based hydrological modeling a feasible target? Incorporating physical knowledge in stochastic modeling of uncertain systems, American Geophysical Union, Fall Meeting 2010, San Francisco, USA, doi:10.13140/RG.2.2.18886.68164, American Geophysical Union, 2010.
  193. D. Koutsoyiannis, Scale of water resources development and sustainability: Small is beautiful, large is great (Invited), LATSIS Symposium 2010: Ecohydrology, Lausanne, doi:10.13140/RG.2.2.20564.40320, Ecole Polytechnique Federale de Lausanne, 2010.
  194. S.M. Papalexiou, and D. Koutsoyiannis, A world-wide investigation of the probability distribution of daily rainfall, International Precipitation Conference (IPC10), Coimbra, Portugal, doi:10.13140/RG.2.2.15950.66888, 2010.
  195. D. Koutsoyiannis, A note of caution for consistency checking and correcting methods of point precipitation records, International Precipitation Conference (IPC10), Coimbra, Portugal, doi:10.13140/RG.2.2.34667.75044, 2010.
  196. Y. Markonis, D. Koutsoyiannis, and N. Mamassis, Orbital climate theory and Hurst-Kolmogorov dynamics, 11th International Meeting on Statistical Climatology, Edinburgh, doi:10.13140/RG.2.2.31312.30724, International Meetings on Statistical Climatology, University of Edinburgh, 2010.
  197. D. Koutsoyiannis, Memory in climate and things not to be forgotten (Invited talk), 11th International Meeting on Statistical Climatology, Edinburgh, doi:10.13140/RG.2.2.17890.53445, International Meetings on Statistical Climatology, University of Edinburgh, 2010.
  198. D. Koutsoyiannis, Some methodological issues in water resources management in the light of contemporary knowledge and needs, Rational Management of Water Basins: Towards Sustainable Development of Westen Greece, Patra, doi:10.13140/RG.2.2.35506.61127, University of Patra, Technical Chamber of Greece, 2010.
  199. S.M. Papalexiou, D. Koutsoyiannis, and A. Montanari, Mind the bias!, STAHY Official Workshop: Advances in statistical hydrology, Taormina, Italy, doi:10.13140/RG.2.2.12018.50883, International Association of Hydrological Sciences, 2010.
  200. H. Tyralis, and D. Koutsoyiannis, Performance evaluation and interdependence of parameter estimators of the Hurst-Kolmogorov stochastic process, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-10476, doi:10.13140/RG.2.2.27118.00322, European Geosciences Union, 2010.
  201. Y. Dialynas, P. Kossieris, K. Kyriakidis, A. Lykou, Y. Markonis, C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, Optimal infilling of missing values in hydrometeorological time series, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-9702, doi:10.13140/RG.2.2.23762.56005, European Geosciences Union, 2010.
  202. Y. Markonis, and D. Koutsoyiannis, Hurst-Kolmogorov dynamics in paleoclimate reconstructions, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-14816, doi:10.13140/RG.2.2.36555.18724, European Geosciences Union, 2010.
  203. P. Dimitriadis, D. Koutsoyiannis, and A. Paschalis, Three dimensional Hurst-Kolmogorov process for modelling rainfall fields, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-979-1, doi:10.13140/RG.2.2.29844.30088, European Geosciences Union, 2010.
  204. S.M. Papalexiou, and D. Koutsoyiannis, On the tail of the daily rainfall probability distribution: Exponential-type, power-type or something else?, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-11769-1, doi:10.13140/RG.2.2.36660.04489, European Geosciences Union, 2010.
  205. E. Rozos, and D. Koutsoyiannis, Use of Modflow as an interpolation method, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12, 10184, doi:10.13140/RG.2.2.29949.15845, European Geosciences Union, 2010.
  206. D. Koutsoyiannis, Why (and how) to write and publish a scientific paper in hydrology? (Invited lecture), European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, European Geosciences Union, 2010.
  207. D. Koutsoyiannis, Some problems in inference from time series of geophysical processes (solicited), European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-14229, doi:10.13140/RG.2.2.13171.94244, European Geosciences Union, 2010.
  208. A. Varveris, P. Panagopoulos, K. Triantafillou, A. Tegos, A. Efstratiadis, N. Mamassis, and D. Koutsoyiannis, Assessment of environmental flows of Acheloos Delta, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12046, doi:10.13140/RG.2.2.14849.66404, European Geosciences Union, 2010.
  209. S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon – open source software for the analysis of hydrological data, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12419, doi:10.13140/RG.2.2.21350.83527, European Geosciences Union, 2010.
  210. A. Efstratiadis, I. Nalbantis, E. Rozos, and D. Koutsoyiannis, Accounting for water management issues within hydrological simulation: Alternative modelling options and a network optimization approach, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 10085, doi:10.13140/RG.2.2.22189.69603, European Geosciences Union, 2010.
  211. S.M. Papalexiou, and D. Koutsoyiannis, Ombrian curves: from theoretical consistency to engineering practice, 8th IAHS Scientific Assembly / 37th IAH Congress, Hyderabad, India, doi:10.13140/RG.2.2.12123.36648, 2009.
  212. D. Koutsoyiannis, Seeking parsimony in hydrology and water resources technology (solicited), European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 11469, doi:10.13140/RG.2.2.20511.97443, European Geosciences Union, 2009.
  213. A. Tegos, N. Mamassis, and D. Koutsoyiannis, Estimation of potential evapotranspiration with minimal data dependence, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 1937, doi:10.13140/RG.2.2.27222.86089, European Geosciences Union, 2009.
  214. A. Efstratiadis, K. Mazi, A. D. Koussis, and D. Koutsoyiannis, Flood modelling in complex hydrologic systems with sparsely resolved data, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 4157, doi:10.13140/RG.2.2.13801.08807, European Geosciences Union, 2009.
  215. V. Montesarchio, F. Napolitano, and D. Koutsoyiannis, Preliminary data analysis for a multisite rainfall stochastic model implementation, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 8689, European Geosciences Union, 2009.
  216. S.M. Papalexiou, and D. Koutsoyiannis, An all-timescales rainfall probability distribution, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 13469, doi:10.13140/RG.2.2.23867.41762, European Geosciences Union, 2009.
  217. A. Efstratiadis, and D. Koutsoyiannis, On the practical use of multiobjective optimisation in hydrological model calibration, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 2326, doi:10.13140/RG.2.2.10445.64480, European Geosciences Union, 2009.
  218. G. G. Anagnostopoulos, D. Koutsoyiannis, A. Efstratiadis, A. Christofides, and N. Mamassis, Credibility of climate predictions revisited, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 611, doi:10.13140/RG.2.2.15898.24009, European Geosciences Union, 2009.
  219. A. Katerinopoulou, K. Kagia, M. Karapiperi, A. Kassela, A. Paschalis, G.-M. Tsarouchi, Y. Markonis, S.M. Papalexiou, and D. Koutsoyiannis, Reservoir yield-reliability relationship and frequency of multi-year droughts for scaling and non-scaling reservoir inflows, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 8063, doi:10.13140/RG.2.2.12542.79682, European Geosciences Union, 2009.
  220. D. Koutsoyiannis, A random walk on water (Henry Darcy Medal Lecture), European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 14033, doi:10.13140/RG.2.1.2139.4800, European Geosciences Union, 2009.
  221. S.M. Papalexiou, and D. Koutsoyiannis, Probabilistic description of rainfall intensity at multiple time scales, IHP 2008 Capri Symposium: “The Role of Hydrology in Water Resources Management”, Capri, Italy, doi:10.13140/RG.2.2.17575.96169, UNESCO, International Association of Hydrological Sciences, 2008.
  222. D. Koutsoyiannis, From climate certainties to climate stochastics (Opening Lecture), IHP 2008 Capri Symposium: “The Role of Hydrology in Water Resources Management”, Capri, Italy, doi:10.13140/RG.2.2.28481.15205/1, UNESCO, International Association of Hydrological Sciences, 2008.
  223. D. Koutsoyiannis, Long tails of marginal distribution and autocorrelation function of rainfall produced by the maximum entropy principle, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 10751, doi:10.13140/RG.2.2.13381.65766, European Geosciences Union, 2008.
  224. S.M. Papalexiou, and D. Koutsoyiannis, Ombrian curves in a maximum entropy framework, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 00702, doi:10.13140/RG.2.2.23447.98720, European Geosciences Union, 2008.
  225. D. Koutsoyiannis, N. Mamassis, A. Christofides, A. Efstratiadis, and S.M. Papalexiou, Assessment of the reliability of climate predictions based on comparisons with historical time series, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 09074, doi:10.13140/RG.2.2.16658.45768, European Geosciences Union, 2008.
  226. D. Koutsoyiannis, and T.A. Cohn, The Hurst phenomenon and climate (solicited), European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 11804, doi:10.13140/RG.2.2.13303.01447, European Geosciences Union, 2008.
  227. N. Zarkadoulas, D. Koutsoyiannis, N. Mamassis, and S.M. Papalexiou, Climate, water and health in ancient Greece, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 12006, doi:10.13140/RG.2.2.31757.95207, European Geosciences Union, 2008.
  228. D. Koutsoyiannis, On detectability of nonstationarity from data using statistical tools, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 05634, doi:10.13140/RG.2.2.32596.81282, European Geosciences Union, 2008.
  229. D. Koutsoyiannis, Emergence of antipersistence and persistence from a deterministic toy model, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 05615, doi:10.13140/RG.2.2.30919.09122, European Geosciences Union, 2008.
  230. D. Koutsoyiannis, S.M. Papalexiou, and A. Montanari, Can a simple stochastic model generate a plethora of rainfall patterns? (invited), The Ultimate Rainmap: Rainmap Achievements and the Future in Broad-Scale Rain Modelling, Oxford, doi:10.13140/RG.2.2.36371.68642, Engineering and Physical Sciences Research Council, 2007.
  231. A. Montanari, D. Koutsoyiannis, and S.M. Papalexiou, The omnipresence of scaling behaviour in hydrometeorological time series and its implications in climatic change assessments, XXIV General Assembly of the International Union of Geodesy and Geophysics, Perugia, doi:10.13140/RG.2.2.26305.35688, International Union of Geodesy and Geophysics, International Association of Hydrological Sciences, 2007.
  232. E. Rozos, and D. Koutsoyiannis, Simulation error in groundwater models with rectangular and non rectangular discretization, XXIV General Assembly of the International Union of Geodesy and Geophysics, Perugia, doi:10.13140/RG.2.2.27983.07848, International Union of Geodesy and Geophysics, International Association of Hydrological Sciences, 2007.
  233. D. Koutsoyiannis, and A. Montanari, Long term persistence and uncertainty on the long term, European Geosciences Union General Assembly 2007, Geophysical Research Abstracts, Vol. 9, Vienna, 05619, doi:10.13140/RG.2.2.35532.82567, European Geosciences Union, 2007.
  234. D. Koutsoyiannis, A. Efstratiadis, and K. Georgakakos, A stochastic methodological framework for uncertainty assessment of hydroclimatic predictions, European Geosciences Union General Assembly 2007, Geophysical Research Abstracts, Vol. 9, Vienna, 06026, doi:10.13140/RG.2.2.16029.31202, European Geosciences Union, 2007.
  235. S.M. Papalexiou, A. Montanari, and D. Koutsoyiannis, Scaling properties of fine resolution point rainfall and inferences for its stochastic modelling, European Geosciences Union General Assembly 2007, Geophysical Research Abstracts, Vol. 9, Vienna, 11253, doi:10.13140/RG.2.2.26095.64167, European Geosciences Union, 2007.
  236. I. Nalbantis, A. Efstratiadis, and D. Koutsoyiannis, On the use and misuse of semi-distributed rainfall-runoff models, XXIV General Assembly of the International Union of Geodesy and Geophysics, Perugia, doi:10.13140/RG.2.2.14351.59044, International Union of Geodesy and Geophysics, International Association of Hydrological Sciences, 2007.
  237. D. Koutsoyiannis, and A. Georgakakos, Lessons from the long flow records of the Nile: determinism vs indeterminism and maximum entropy, 20 Years of Nonlinear Dynamics in Geosciences, Rhodes, Greece, doi:10.13140/RG.2.2.10996.14727, 2006.
  238. Z. Theocharis, C. Memos, and D. Koutsoyiannis, Improvement of wave height forecast in deep and intermediate waters with the use of stochastic methods, 13th WISE Annual Meeting, Venice, doi:10.13140/RG.2.2.18545.89448, Waves In Shallow Environments (WISE) group, 2006.
  239. D. Koutsoyiannis, H. Yao, and A. Georgakakos, Multiyear behaviour and monthly simulation and forecasting of the Nile River flow, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 05046, doi:10.13140/RG.2.2.33645.38888, European Geosciences Union, 2006.
  240. E. Rozos, and D. Koutsoyiannis, Modelling a karstic aquifer with a mixed flow equation, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 03970, doi:10.13140/RG.2.2.13512.72960, European Geosciences Union, 2006.
  241. E. Rozos, and D. Koutsoyiannis, Subsurface flow simulation with model coupling, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 02551, doi:10.13140/RG.2.2.23579.05924, European Geosciences Union, 2006.
  242. K. Georgakakos, D. Koutsoyiannis, and A. Efstratiadis, Uncertainty assessment of future hydroclimatic predictions: Methodological framework and a case study in Greece, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 08065, doi:10.13140/RG.2.2.29975.37284, European Geosciences Union, 2006.
  243. A. Efstratiadis, D. Koutsoyiannis, and G. Karavokiros, Linking hydroinformatics tools towards integrated water resource systems analysis, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 02096, doi:10.13140/RG.2.2.26619.92966, European Geosciences Union, 2006.
  244. A. Efstratiadis, A. Koukouvinos, E. Rozos, I. Nalbantis, and D. Koutsoyiannis, Control of uncertainty in complex hydrological models via appropriate schematization, parameterization and calibration, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 02181, doi:10.13140/RG.2.2.28297.65124, European Geosciences Union, 2006.
  245. A. Efstratiadis, G. Karavokiros, S. Kozanis, A. Christofides, A. Koukouvinos, E. Rozos, N. Mamassis, I. Nalbantis, K. Noutsopoulos, E. Romas, L. Kaliakatsos, A. Andreadakis, and D. Koutsoyiannis, The ODYSSEUS project: Developing an advanced software system for the analysis and management of water resource systems, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 03910, doi:10.13140/RG.2.2.24942.20805, European Geosciences Union, 2006.
  246. D. Zarris, and D. Koutsoyiannis, Estimating suspended sediment yield based on reservoir hydrographic survey, rating relationships and distributed hydrological modelling, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, European Geosciences Union, 2005.
  247. S.M. Papalexiou, and D. Koutsoyiannis, A probabilistic approach to the concept of Probable Maximum Precipitation, 7th Plinius Conference on Mediterranean Storms, Rethymnon, Crete, doi:10.13140/RG.2.2.15714.73927, European Geosciences Union, 2005.
  248. A. Efstratiadis, A. Tegos, I. Nalbantis, E. Rozos, A. Koukouvinos, N. Mamassis, S.M. Papalexiou, and D. Koutsoyiannis, Hydrogeios, an integrated model for simulating complex hydrographic networks - A case study to West Thessaly region, 7th Plinius Conference on Mediterranean Storms, Rethymnon, Crete, doi:10.13140/RG.2.2.25781.06881, European Geosciences Union, 2005.
  249. E. Rozos, and D. Koutsoyiannis, Application of the Integrated Finite Difference Method in groundwater flow, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 00579, doi:10.13140/RG.2.2.30185.08803, European Geosciences Union, 2005.
  250. D. Koutsoyiannis, Similarities and scaling of extreme rainfall worldwide (solicited), European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 03775, doi:10.13140/RG.2.2.14928.30720, European Geosciences Union, 2005.
  251. D. Koutsoyiannis, The long-range dependence of hydrological processes as a result of the maximum entropy principle, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 03779, doi:10.13140/RG.2.2.11572.86402, European Geosciences Union, 2005.
  252. C. Derzekos, D. Koutsoyiannis, and C. Onof, A new randomised Poisson cluster model for rainfall in time, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 07236, doi:10.13140/RG.2.2.32544.38403, European Geosciences Union, 2005.
  253. D. Koutsoyiannis, The scaling properties in the distribution of hydrological variables as a result of the maximum entropy principle (solicited), European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 03781, doi:10.13140/RG.2.2.25833.49769, European Geosciences Union, 2005.
  254. S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon - A hydrological data management and processing software tool, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04644, doi:10.13140/RG.2.2.34222.10561, European Geosciences Union, 2005.
  255. A. Efstratiadis, G. Karavokiros, and D. Koutsoyiannis, Hydronomeas: A water resources planning and management software system, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04675, doi:10.13140/RG.2.2.29608.37128, European Geosciences Union, 2005.
  256. A. Efstratiadis, and D. Koutsoyiannis, The multiobjective evolutionary annealing-simplex method and its application in calibrating hydrological models, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04593, doi:10.13140/RG.2.2.32963.81446, European Geosciences Union, 2005.
  257. A. Efstratiadis, E. Rozos, A. Koukouvinos, I. Nalbantis, G. Karavokiros, and D. Koutsoyiannis, An integrated model for conjunctive simulation of hydrological processes and water resources management in river basins, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 03560, doi:10.13140/RG.2.2.27930.64960, European Geosciences Union, 2005.
  258. D. Koutsoyiannis, The water resource management of Athens in the perspective of the Olympic Games, The Olympic Games Athens 2004 and the National Technical University of Athens, edited by K. Moutzouris, Athens, 17–27, doi:10.13140/RG.2.2.35480.39680, National Technical University of Athens, 2004.
  259. D. Koutsoyiannis, Alternative wastewater collection systems, Management of Urban Wastewater, edited by A. N. Angelakis, 21–25, doi:10.13140/RG.2.2.32124.95361, National Centre of Environment and Sustainable Development, Larisa, Greece, 2004.
  260. D. Koutsoyiannis, Simple methods to generate time series with scaling behaviour (solicited), European Geosciences Union General Assembly 2004, Geophysical Research Abstracts, Vol. 6, Nice, doi:10.13140/RG.2.2.29503.51362, European Geosciences Union, 2004.
  261. D. Koutsoyiannis, and A. Efstratiadis, Climate change certainty versus climate uncertainty and inferences in hydrological studies and water resources management (solicited), European Geosciences Union General Assembly 2004, Geophysical Research Abstracts, Vol. 6, Nice, doi:10.13140/RG.2.2.12726.29764, European Geosciences Union, 2004.
  262. Z. Theocharis, D. Koutsoyiannis, C. Memos, and T. Soukissian, Improvement of the wave height real-time forecast in the Aegean Sea using stochastic methods, European Geosciences Union General Assembly 2004, Geophysical Research Abstracts, Vol. 6, Nice, doi:10.13140/RG.2.2.31181.23520, European Geosciences Union, 2004.
  263. P. Fytilas, D. Koutsoyiannis, and F. Napolitano, A case study of spatial-temporal rainfall disaggregation at the Tiber river basin, Italy, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.11048.57604, European Geophysical Society, 2003.
  264. D. Zarris, E. Lykoudi, D. Koutsoyiannis, and S. E. Poulos, Channel change and sediment movement after a major level drawdown at Kremasta reservoir, Western Greece, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.21953.76643, European Geophysical Society, 2003.
  265. A. Tsouni, D. Koutsoyiannis, C. Contoes, N. Mamassis, and P. Elias, Application of satellite-based methods for estimating evapotranspiration in Thessalia plain, Greece, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.1.3221.7840, European Geophysical Society, 2003.
  266. A. Langousis, and D. Koutsoyiannis, A stochastic methodology for generation of seasonal time series reproducing overyear scaling, Hydrofractals '03, An international conference on fractals in hydrosciences, Monte Verita, Ascona, Switzerland, doi:10.13140/RG.2.2.15242.88006, ETH Zurich, MIT, Université Pierre et Marie Curie, 2003.
  267. D. Koutsoyiannis, A toy model of climatic variability with scaling behaviour, Hydrofractals '03, An international conference on fractals in hydrosciences, Monte Verita, Ascona, Switzerland, doi:10.13140/RG.2.2.13565.15848, ETH Zurich, MIT, Université Pierre et Marie Curie, 2003.
  268. D. Koutsoyiannis, On embedding dimensions and their use to detect deterministic chaos in hydrological processes, Hydrofractals '03, An international conference on fractals in hydrosciences, Monte Verita, Ascona, Switzerland, doi:10.13140/RG.2.2.16920.60165, ETH Zurich, MIT, Université Pierre et Marie Curie, 2003.
  269. A. Efstratiadis, D. Koutsoyiannis, K. Hadjibiros, A. Andreadakis, A. Stamou, A. Katsiri, G.-F. Sargentis, and A. Christofides, A multicriteria approach for the sustainable management of the Plastiras reservoir, Greece, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.23631.48801, European Geophysical Society, 2003.
  270. A. Efstratiadis, D. Koutsoyiannis, E. Rozos, and I. Nalbantis, Calibration of a conjunctive surface-groundwater simulation model using multiple responses, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.23002.34246, European Geophysical Society, 2003.
  271. D. Koutsoyiannis, Hydrological statistics for engineering design in a varying climate, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.16291.45602, European Geophysical Society, 2003.
  272. K Mantoudi, N. Mamassis, and D. Koutsoyiannis, A simple water balance model using a geographical information system, 26th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 3, Nice, doi:10.13140/RG.2.2.26357.78567, European Geophysical Society, 2001.
  273. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, A decision support system for the management of the water resource system of Athens, 26th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 3, Nice, doi:10.13140/RG.2.2.28035.50724, European Geophysical Society, 2001.
  274. D. Koutsoyiannis, and A. Efstratiadis, A stochastic hydrology framework for the management of multiple reservoir systems, 26th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 3, Nice, doi:10.13140/RG.2.2.11258.29125, European Geophysical Society, 2001.
  275. D. Koutsoyiannis, C. Onof, and H. S. Wheater, Stochastic disaggregation of spatial-temporal rainfall with limited data, 26th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 3, Nice, doi:10.13140/RG.2.2.28874.36800, European Geophysical Society, 2001.
  276. A. Efstratiadis, and D. Koutsoyiannis, Global optimisation techniques in water resources management, 26th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 3, Nice, doi:10.13140/RG.2.2.13774.87360, European Geophysical Society, 2001.
  277. D. Koutsoyiannis, and C. Onof, A computer program for temporal rainfall disaggregation using adjusting procedures (HYETOS), 25th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 2, Nice, doi:10.13140/RG.2.2.33488.10243, European Geophysical Society, 2000.
  278. H. S. Wheater, V. S. Isham, C. Onof, R. E. Chandler, P. J. Northrop, P. Guiblin, S. M. Bate, D. R. Cox, and D. Koutsoyiannis, Generation of spatially-consistent rainfall fields for rainfall-runoff modelling, 7th National Hydrology Symposium of the British Hydrological Society, Newcastle, doi:10.13140/RG.2.1.4315.4163, British Hydrological Society, University of Newcastle, 2000.
  279. D. Koutsoyiannis, and N. Mamassis, The scaling model of storm hyetograph versus typical stochastic rainfall event models, 24th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 1, The Hague, 769, doi:10.13140/RG.2.1.1192.2165, European Geophysical Society, 1999.
  280. D. Koutsoyiannis, and D. Zarris, Simulation of rainfall events for design purposes with inadequate data, 24th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 1, The Hague, 296, doi:10.13140/RG.2.1.2797.8482, European Geophysical Society, 1999.
  281. D. Koutsoyiannis, An advanced method for preserving skewness in single-variate, multivariate and disaggregation models in stochastic hydrology, 24th General Assembly of the European Geophysical Society, Geophysical Research Abstracts, Vol. 1, The Hague, 346, doi:10.13140/RG.2.1.1749.2725, European Geophysical Society, 1999.
  282. D. Koutsoyiannis, and N. Mamassis, Metsovo: The hydrological heart of Greece, Proceedings of the 1st Inter-university Conference for Metsovo, edited by D. Rokos, Metsovo, 209–229, doi:10.13140/RG.2.1.2928.9205, National Technical University of Athens Press – National Technical University of Athens, Athens, 1998.
  283. D. Koutsoyiannis, and M. Mimikou, Country Paper for Greece, Management and Prevention of Crisis Situations: Floods, Droughts and Institutional Aspects, 3rd EURAQUA Technical Review, Rome, 63–77, doi:10.13140/RG.2.1.2142.4888, EURAQUA, 1996.
  284. M. Mimikou, and D. Koutsoyiannis, Extreme floods in Greece: The case of 1994, U.S. - ITALY Research Workshop on the Hydrometeorology, Impacts, and Management of Extreme Floods, Perugia, Italy, doi:10.13140/RG.2.1.1945.8802, 1995.
  285. D. Zarris, and D. Koutsoyiannis, Occurrence and general characteristics of deposits in the Athens storm sewers, International Conference on Sewer Solids: Characteristics, Movement, Effects and Control, Dundee, U.K., doi:10.13140/RG.2.1.3780.8885, 1995.
  286. N. Mamassis, and D. Koutsoyiannis, Weather types and geographical distribution of intense rainfall, Abstracts of the 5th International Conference on Precipitation, Elounda, Greece, 1.13, doi:10.13140/RG.2.1.1290.5208, 1995.
  287. D. Koutsoyiannis, and D. Pachakis, Deterministic chaos versus stochasticity in analysis and modelling of rainfall structure, Abstracts of the 5th International Conference on Precipitation, Elounda, Greece, 4.6, doi:10.13140/RG.2.1.1552.6648, 1995.
  288. N. Mamassis, D. Koutsoyiannis, and I. Nalbantis, Intense rainfall and flood event classification by weather type, 19th General Assembly of the European Geophysical Society, Annales Geophysicae, Vol. 12, Supplement II, Part II, Grenoble, 440, doi:10.13140/RG.2.1.4124.9520, European Geophysical Society, 1994.
  289. N. Mamassis, D. Koutsoyiannis, and E. Foufoula-Georgiou, Stochastic rainfall forecasting by conditional simulation using a scaling storm model, 19th General Assembly of the European Geophysical Society, Annales Geophysicae, Vol. 12, Supplement II, Part II, Grenoble, 324, 408, doi:10.13140/RG.2.1.1241.3682, European Geophysical Society, 1994.
  290. M. Vafiadis, D. Tolikas, and D. Koutsoyiannis, HYDROSCOPE: The new Greek national database system for meteorological, hydrological and hydrogeological information, 2nd International Conference on Flow Regimes from International Experimental and Network Data, Braunschweig, doi:10.13140/RG.2.1.3182.8726, UNESCO, 1993.
  291. D. Koutsoyiannis, and E. Foufoula-Georgiou, On the concept of similar storms and their parameterization via scaling, 1992 Western Pacific Geophysical Meeting, American Geophysical Union, EOS Transactions, Hong Kong, 73/25, 34, American Geophysical Union, 1992.
  292. I. Nalbantis, D. Koutsoyiannis, and Th. Xanthopoulos, Modelling the Athens water supply system, 1st European Conference on Advances in Water Resources Technology, Athens, European Water Resources Association, 1991.
  293. I. Nalbantis, D. Koutsoyiannis, C. Tsolakidis, and Th. Xanthopoulos, Planning and operating of the hydrosystem of Athens, Workshop for the perspectives of resolving the water supply problem of Athens, edited by D. Koutsoyiannis, 101–108, doi:10.13140/RG.2.1.3952.9207, G. Fountas, 1990.
  294. N. Mamassis, S. Roti, D. Koutsoyiannis, and Th. Xanthopoulos, Hydrological characteristics of the Mornos, Evinos and Yliki basins, Workshop for the perspectives of resolving the water supply problem of Athens, edited by D. Koutsoyiannis, 55–64, doi:10.13140/RG.2.1.2177.3043, G. Fountas, 1990.
  295. D. Koutsoyiannis, and Th. Xanthopoulos, Reliability and safety of the water resource system of Athens, Workshop for the perspectives of resolving the water supply problem of Athens, edited by D. Koutsoyiannis, 91–100, doi:10.13140/RG.2.1.1980.6968, G. Fountas, 1990.
  296. D. Koutsoyiannis, Hydrology and quantitative estimations of sediments, Seminar for the land reclamation works, 174–188, doi:10.13140/RG.2.1.1718.5528, Greek Union of the Rural and Surveying Engineers, 1986.
  297. A. Katsiri, A. Andreadakis, and D. Koutsoyiannis, Assimilative capacity of the Kalamas River and the Lake Pamvotis, Proceedings of the 2nd International Symposium on Environmental Technology for Developing Countries, Istanbul, Turkey, doi:10.13140/RG.2.1.4995.3520, 1984.

Presentations and publications in workshops

  1. D. Koutsoyiannis, The perpetual change in climate and the technology-augmented human ability of adaptation (Invited), Water 3rd Webinar | Climate Change and Water Resources: Evidence, Impacts, Adaptation, doi:10.13140/RG.2.2.22354.27849, 2021.
  2. D. Koutsoyiannis, Contribution to the Panel Session: Advancing New Methods for the Treatment of Climate Change and Extreme Events (Invited), 2021 World Environmental & Water Resources Congress, Virtual Online, doi:10.13140/RG.2.2.31716.71046, American Society of Civil Engineers, 2021.
  3. D. Koutsoyiannis, Ancient climate and the modern myth of climate crisis, From the Myths of Hercules to the reality of climate change, doi:10.13140/RG.2.2.35277.87520, UNESCO, International Association for Hydro-Environment Engineering and Research (IAHR), Thessaloniki, 2020.
  4. D. Koutsoyiannis, Climate of the past and present, and its hydrological relevance, School for Young Scientists “Modelling and forecasting of river flows and managing hydrological risks: Towards a new generation of methods” (2020), doi:10.13140/RG.2.2.20826.77761, Russian Academy of Sciences, Moscow, 2020.
  5. D. Koutsoyiannis, Advances in stochastics of hydroclimatic extremes, Giornata di studio in memoria di Baldassare Bacchi, Brescia, Italy, doi:10.13140/RG.2.2.30655.05282/1, Universita Degli Studi di Brescia, 2019.
  6. D. Koutsoyiannis, Stochastic simulation of time irreversible processes, Invited Lecture, Rome, Università di Roma "La Sapienza", 2019.
  7. A. Efstratiadis, N. Mamassis, A. Koukouvinos, T. Iliopoulou, S. Antoniadi, and D. Koutsoyiannis, Strategic plan for developing a National Hydrometric Network, Hellenic Integrated Marine and Inland water Observing, Forecasting and offshore Technology System (HIMIOFoTS) - Second meeting of project partners, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2019.
  8. N. Mamassis, A. Efstratiadis, A. Koukouvinos, and D. Koutsoyiannis, Open Hydrosystem Information Network (OpenHi.net): Evolution of works, challeneges and perspectives, Hellenic Integrated Marine and Inland water Observing, Forecasting and offshore Technology System (HIMIOFoTS) - Second meeting of project partners, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2019.
  9. D. Koutsoyiannis, N. Mamassis, and P. Defteraios, The evolution of water science and technology in ancient Athens, Hydrotechnologies in Ancient Greece, Chania, doi:10.13140/RG.2.2.31867.16167, Technical University of Crete, 2019.
  10. N. Mamassis, and D. Koutsoyiannis, The tragedy of hydropower in Greece of crisis, Workshop of the Association of Thessalian Studies, Athens, 2019.
  11. D. Koutsoyiannis, Climate change impacts on hydrological science: How the climate change agenda has lowered the scientific level of hydrology, School for Young Scientists “Modelling and forecasting of river flows and managing hydrological risks: Towards a new generation of methods” (2018), doi:10.13140/RG.2.2.11110.06727, Russian Academy of Sciences, Lomonosov Moscow State University, 2018.
  12. D. Koutsoyiannis, Modelling extreme rainfall in the era of climate change concerns: Towards a consistent stochastic methodology, School for Young Scientists “Modelling and forecasting of river flows and managing hydrological risks: Towards a new generation of methods” (2018), doi:10.13140/RG.2.2.22015.25766, Russian Academy of Sciences, Lomonosov Moscow State University, Moscow, 2018.
  13. N. Mamassis, A. Efstratiadis, D. Koutsoyiannis, and A. Koukouvinos, Open Hydrosystem Information Network (OpenHi.net), Hellenic Integrated Marine and Inland water Observing, Forecasting and offshore Technology System (HIMIOFoTS) - First meeting of project partners, Anavyssos, Hellenic Centre for Marine Research, 2018.
  14. D. Koutsoyiannis, On the book "Requiem with Crescendo" by T. Xanthopoulos, Presentation of the book "Requiem with Crescendo" , Athens, doi:10.13140/RG.2.2.12794.41927, National Technical University of Athens, 2018.
  15. N. Mamassis, and D. Koutsoyiannis, Book presentation: Evolution of Water Supply Through the Millennia, Temporal evolution of water management technologies for antiquity to present, Patra, Patras, 2017.
  16. D. Koutsoyiannis, Saving the world from climate threats vs. dispelling climate myths and fears, Invited Seminar, Lunz am See, Austria, doi:10.13140/RG.2.2.34278.42565, WasserCluster Lunz – Biologische Station GmbH, 2017.
  17. D. Koutsoyiannis, Environment, Water, Energy and search of Orthos Logos, Workshop for the World Day of Environment, Larisa, doi:10.13140/RG.2.2.36732.13443, DEYA of Larisa, 2016.
  18. Ο. Daskalou, A. Koukouvinos, A. Efstratiadis, and D. Koutsoyiannis, Methodology for optimal allocation and sizing of renewable energy sources using ArcGIS 10.3: Case study of Thessaly Perfecture, 24th Hellenic Meeting of ArcGIS Users, Crowne Plaza, Athens, Marathon Data Systems, 2016.
  19. A. Efstratiadis, A. Koukouvinos, N. Mamassis, and D. Koutsoyiannis, The quantitative dimension of WFD 2000/60, Water Framework Directive 2000/60 and Inland Water Protection: Research and Perspectives, Athens, Hellenic Centre for Marine Research, Specific Secreteriat of Water – Ministry of Environment, Energy and Climate Change, 2015.
  20. A. D. Koussis, and D. Koutsoyiannis, Challenges and perpectives of research project DEUCALION, Workshop - Deucalion research project, Goulandris National Histroy Museum, 2014.
  21. D. Koutsoyiannis, The research project DEUCALION: Hellenic and international framework, Workshop - Deucalion research project, Goulandris National Histroy Museum, doi:10.13140/RG.2.2.34539.95521, 2014.
  22. A. Tegos, A. Efstratiadis, A. Varveris, N. Mamassis, A. Koukouvinos, and D. Koutsoyiannis, Assesment and implementation of ecological flow constraints in large hydroelectric works: The case of Acheloos, Ecological flow of rivers and the importance of their true assesment, 2014.
  23. N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Perspectives of combined management of water and energy in Thessaly region, , Larissa, 21 pages, doi:10.13140/RG.2.2.15760.61442, Technical Chamber of Greece / Department of CW Thessaly, 2014.
  24. N. Mamassis, and D. Koutsoyiannis, Exploration of ancient Greek hydraulic tecnhology using web-based data, Hydrotechnologies in Ancient Greece, edited by E. G. Kolokytha, Thessaloniki, 21 pages, Aristotle University of Thessaloniki, Thessaloniki, 2013.
  25. A. D. Koussis, S. Lykoudis, A. Efstratiadis, A. Koukouvinos, N. Mamassis, D. Koutsoyiannis, A. Peppas, and A. Maheras, Estimating flood flows in ungauged Greek basins under hydroclimatic variability (Deukalion project) - Development of physically-established conceptual-probabilistic framework and computational tools, Climate and Environmental Change in the Mediterranean Region, Pylos, Navarino Environmental Observatory, 2012.
  26. D. Koutsoyiannis, Re-establishing the link of hydrology with engineering, Invited lecture at the National Institute of Agronomy of Tunis (INAT), Tunis, Tunisia, doi:10.13140/RG.2.2.32862.23361, 2012.
  27. D. Koutsoyiannis, Water control in the Greek cities (solicited), Water systems and urbanization in Africa and beyond, Uppsala, Sweden, doi:10.13140/RG.2.2.36217.67680, 2012.
  28. D. Koutsoyiannis, Climate is changing ... since 4.5 billion years ago, Climate change: natural or human-induced, Athens, doi:10.13140/RG.2.2.24054.19524, Massachusetts Institute of Technology Alumni, University of Michigan Alumni, Athens, 2011.
  29. A. Montanari, and D. Koutsoyiannis, Uncertainty estimation in hydrology: Incorporating physical knowledge in stochastic modeling of uncertain systems, Invited Seminar at the University of Uppsala, Uppsala, doi:10.13140/RG.2.2.25731.91684, 2011.
  30. N. Mamassis, and D. Koutsoyiannis, Climatic uncertainty and water resources management - from science to divination, 23th general assembly EDEYA, Larisa, Larisa, 2011.
  31. A. Christofides, and D. Koutsoyiannis, God and the arrogant species: Contrasting nature's intrinsic uncertainty with our climate simulating supercomputers, 104th Annual Conference & Exhibition, Orlando, Florida, Air & Waste Management Association, 2011.
  32. D. Koutsoyiannis, and N. Mamassis, Strategy for flood prevention: Modern technological framework, Integrated planning of flood protection: A challenge for the future, Athens, doi:10.13140/RG.2.2.27671.78242, Association of Civil Engineers of Greece, Athens, 2010.
  33. D. Koutsoyiannis, Hydroscope: From yesterday to tomorrow, Towards a rational handling of current water resource problems: Utilizing Data and Informatics for Information, Hilton Hotel, Athens, doi:10.13140/RG.2.2.19283.17447, Athens, 2010.
  34. N. Mamassis, E. Tiligadas, D. Koutsoyiannis, M. Salahoris, G. Karavokiros, S. Mihas, K. Noutsopoulos, A. Christofides, S. Kozanis, A. Efstratiadis, E. Rozos, and L. Bensasson, HYDROSCOPE: National Databank for Hydrological, Meteorological and Geographical Information, Towards a rational handling of current water resource problems: Utilizing Data and Informatics for Information, Hilton Hotel, Athens, 2010.
  35. D. Koutsoyiannis, Hurst-Kolmogorov dynamics and uncertainty, Workshop on Nonstationarity, Hydrologic Frequency Analysis, and Water Management, Boulder, Colorado, USA, doi:10.13140/RG.2.2.36060.39045, International Center for Integrated Water Resources Management, US Army Corps of Engineers, United States Geological Survey, US Department of the Interior - Bureau of Reclamation, National Oceanic and Atmospheric Administration, US Environmental Protection Agency, Colorado State University, 2010.
  36. D. Koutsoyiannis, Kephisos as a river, 2nd Scientific Workshop for the Kephisos River, Athens, doi:10.13140/RG.2.2.17186.02245, Organization for the Management and Restoration of the Kephisos River and its Tributaries, National Technical University of Athens, 2009.
  37. D. Koutsoyiannis, N. Mamassis, and A. Tegos, Hydrometeorological issues in ancient Greek science and philosophy, The Eco-nomy of Water, edited by E Efthymiopoulos and M. Modinos, Hydra island, doi:10.13140/RG.2.2.25574.63040, Hellenica Grammata, 2009.
  38. C. Makropoulos, D. Koutsoyiannis, and A. Efstratiadis, Challenges and perspectives in urban water management, Local Govenance Conference: The Green Technology in the Cities, Athens, Ecocity, Central Association of Greek Municipalities, 2009.
  39. D. Koutsoyiannis, Entropy as an explanatory concept and modelling tool in hydrology, Invited lecture, Rome, doi:10.13140/RG.2.2.31902.13124, Università di Roma "La Sapienza", 2008.
  40. D. Koutsoyiannis, Climate change as a scapegoat in water science, technology and management, EUREAU Workshop on Climate Changes Impact on Water Resources with Emphasis on Potable Water, Chania, doi:10.13140/RG.2.2.35519.71843, European Association of Water and Wastewater Services, Hellenic Union of Water and Wastewater Enterprises, 2008.
  41. D. Koutsoyiannis, Flood protection planning in Greece - Utilization of scientific knowledge, The role of science in reconstitution of the burned areas, Kalamata, doi:10.13140/RG.2.2.12991.71844, Technical Chamber of Greece, 2008.
  42. D. Koutsoyiannis, and A. Efstratiadis, Energy, water and agriculture: Prospects of integrated management in the Prefecture of Karditsa, Water Resources Management in the Prefecture of Karditsa, Workshop of The Local Union of Municipalities and Communities, Karditsa, doi:10.13140/RG.2.2.33124.37760, 2008.
  43. A. Efstratiadis, D. Koutsoyiannis, and N. Mamassis, Optimization of the water supply network of Athens, Second International Congress: "Environment - Sustainable Water Resource Management", Athens, Association of Civil Engineers of Greece, European Council of Civil Engineers, 2007.
  44. D. Koutsoyiannis, Towards a national programme for water resources management and preservation, Consultative Committee of Water, Athens, doi:10.13140/RG.2.2.36479.82089, 2007.
  45. D. Koutsoyiannis, A. Andreadakis, R. Mavrodimou, A. Koukouvinos, and N. Mamassis, The Master Plan for the water resource management of Greece (invited talk), International Conference: Integrated Management of Coastal Areas, Faliro, doi:10.13140/RG.2.2.30398.08005, CoPraNet, Mediterranean SOS, 2006.
  46. G. Karavokiros, and D. Koutsoyiannis, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System, Research and Technology Days 2006, Athens, 2006.
  47. D. Koutsoyiannis, The underestimation of probability of extreme rainfall and flood by prevailing statistical methodologies and how to avoid it, EU COST Action C22: Urban Flood Management, 2nd meeting, Athens, doi:10.13140/RG.2.2.25469.77286, University of Athens, 2006.
  48. E. Rozos, and D. Koutsoyiannis, Managing water supply resources in karstic environment (temperate climate), UNESCO Workshop - Integrated Urban Water Management in Temperate Climates, Belgrade, doi:10.13140/RG.2.2.28756.40329/1, 2006.
  49. D. Koutsoyiannis, A new stochastic hydrological framework inspired by the Athens water resource system, Invited lecture, Bologna, doi:10.13140/RG.2.2.28546.68809, University of Bologna, 2006.
  50. Z. W. Kundzewicz, and D. Koutsoyiannis, The peer review system revisited, Hydrology Journal Editors Meeting, Vienna, doi:10.13140/RG.2.2.32180.65920, Advances in Water Resources, Hydrological Processes, Hydrological Sciences Journal, Hydrology and Earth System Sciences, Journal of Hydrology, Journal of River Basin Management, Nordic Hydrology, Water Resources Research, 2006.
  51. D. Koutsoyiannis, The management of the Plastiras reservoir: From study to application, The water supply of Karditsa - Problems and perspectives, Karditsa, doi:10.13140/RG.2.2.28825.21602, Municipality of Karditsa, Municipal Company of Water Supply and Sewerage of Karditsa, 2006.
  52. D. Koutsoyiannis, A new stochastic hydrologic framework inspired by the Athens water resource system, Invited lecture, Durham, N. Carolina, doi:10.13140/RG.2.2.28546.68809, School of Engineering, Duke University, 2006.
  53. D. Koutsoyiannis, A new stochastic hydrologic framework inspired by the Athens water resource system, Invited lecture, Atlanta, doi:10.13140/RG.2.2.28546.68809, School of Civil and Environmental Engineering, Georgia Institute of Technology, 2006.
  54. D. Koutsoyiannis, The management of the Athens water resource system: Methodology and implementation, Invited lecture, Atlanta, doi:10.13140/RG.2.2.11209.13928, Georgia Water Resources Institute, 2006.
  55. E. Vassilopoulos, and D. Koutsoyiannis, New forms of wastewater collection and drainage, Wastewater management by decentralized processing systems, Neochori Karditsas, doi:10.13140/RG.2.2.31341.79846, Central Association of Greek Municipalities, Hellenic Union of Water and Wastewater Enterprises, Municipality of Karditsa, Technical Chamber of Greece, 2005.
  56. D. Koutsoyiannis, The management of the Athens water resource system: Methodological issues, Invited lecture, San Diego, doi:10.13140/RG.2.2.12886.86089, Hydrologic Research Center, 2005.
  57. D. Koutsoyiannis, A. Andreadakis, and N. Mamassis, ODYSSEUS: Information system for the simulation and management of hydrosystems, 15th meeting of the Greek users of Geographical Information Systems (G.I.S.) ArcInfo - ArcView - ArcIMS, Athens, doi:10.13140/RG.2.2.14145.15203, Marathon Data Systems, 2005.
  58. D. Koutsoyiannis, Climatic uncertainty, the Joseph effect and the water resource management, Man and environment in the 21st century - The crucial problems - Atmosphere and climate, Athens, doi:10.13140/RG.2.2.22533.76008, Goulandris Natural History Museum, 2005.
  59. D. Koutsoyiannis, I. Zalachori, and A. Andreadakis, Infiltration and inflows to foul sewers, Symposium for water resources management, Theba, doi:10.13140/RG.2.2.18339.45607, 2005.
  60. D. Koutsoyiannis, and A. Efstratiadis, Climatic change certainty and climatic uncertainty from a hydrological and water resources management viewpoint, Invited seminar, University of Thessaly, Volos, doi:10.13140/RG.2.2.31761.22888, University of Thessaly, 2004.
  61. D. Koutsoyiannis, A methodological approach for the rainfall intensity-duration-frequency relationship in Athens, Flood protection of Attica, Athens, doi:10.13140/RG.2.2.21694.89926, Technical Chamber of Greece, 2004.
  62. D. Koutsoyiannis, and A. Efstratiadis, The Hydronomeas computational system and its application to the study of the Acheloos river diversion, Water resource management with emphasis in Epiros, Ioannina, doi:10.13140/RG.2.2.35116.67205, Municipal Company of Water Supply and Sewerage of Ioannina, 2003.
  63. D. Koutsoyiannis, Mathematical tools in water resource management, Workshop of the Hellenic Mathematical Society (Branch of Arta), Arta, doi:10.13140/RG.2.2.16320.94722, 2003.
  64. I. Paspallis, and D. Koutsoyiannis, Geomorphometric characteristics of hydrologic basins of Greece, 12th meeting of the Greek users of ArcInfo, Marathon Data Systems, Athens, 2002.
  65. D. Zarris, E. Lykoudi, and D. Koutsoyiannis, Appraisal of river sediment deposits in reservoirs of hydropower dams, Workshop for the presentation of research projects of PPC/DAYE, Athens, doi:10.13140/RG.2.2.10239.20649, Department for the Development of Hydroelectric Works – Public Power Corporation, 2002.
  66. D. Koutsoyiannis, A. Efstratiadis, and A. Koukouvinos, Hydrological investigation of the Plastiras lake management, Workshop for the presentation of the research project "Investigation of scenarios for the management and protection of the quality of the Plastiras Lake", doi:10.13140/RG.2.2.16950.09286, Municipality of Karditsa, Karditsa, 2002.
  67. D. Koutsoyiannis, Decision support systems for water resource management: The case of the water supply system of Athens, Water and Environment 2, doi:10.13140/RG.2.2.27016.42248, Water Supply and Sewerage Company of Athens, 2001.
  68. D. Koutsoyiannis, Hydrological aspects of the operation of the Plastiras hydroelectric project, Workshop for the water resources management in Plastiras lake, doi:10.13140/RG.2.2.28694.14408, Municipal Water Supply and Sewerage Company of Karditsa, 2001.
  69. D. Koutsoyiannis, Urban water systems management: Remarks - questions - opinions, Water and Environment, doi:10.13140/RG.2.2.24499.84006, Water Supply and Sewerage Company of Athens, 2000.
  70. A. Xanthakis, and D. Koutsoyiannis, The management plan of the water resource system of Athens for the next five years, Water for the city: Strategic planning, demand management and network losses control, doi:10.13140/RG.2.2.19886.10562, National Technical University of Athens, University of the Aegean, Water Supply and Sewerage Company of Athens, 2000.
  71. H. Coccossis, and D. Koutsoyiannis, Water for the city: Strategic planning, demand management and network losses control, Water for the city: Strategic planning, demand management and network losses control, doi:10.13140/RG.2.2.33307.87843, National Technical University of Athens, University of the Aegean, Water Supply and Sewerage Company of Athens, 2000.
  72. K Mantoudi, N. Mamassis, and D. Koutsoyiannis, Water balance model of a catchment using geographical information system, 10th meeting of the Greek users of ArcInfo - ArcView, Marathon Data Systems, 2000.
  73. D. Koutsoyiannis, N. Mamassis, and E. Arapaki, Water shortage in Ethiopia: A first approach, Solidarity for Ethiopia, doi:10.13140/RG.2.2.23556.12165, Hellas-Ethiopia, General Consulate of Ethiopia in Greece, 2000.
  74. D. Koutsoyiannis, The Athens water resource system: A modern management perspective, Invited lecture, London, doi:10.13140/RG.2.2.29008.71685, Imperial College, London, 1999.
  75. D. Koutsoyiannis, Summary of the research project: Evaluation of Management of the Water Resources of Sterea Hellas, Workshop for the presentation of the research project Evaluation and Management of the Water Resources of Sterea Hellas, National Technical University of Athens, Ministry of Environment, Planning and Public Works, 1998.
  76. D. Koutsoyiannis, Experience from the elaboration of the masterplan of the water resources management of Greece, Workshop for the Masterplan of the water resources management in Greece, Ministry of Development, National Technical University of Athens, Institute of Geological and Mining Research, Centre for Research and Planning, 1997.
  77. E. Rozos, D. Koutsoyiannis, and A. Koukouvinos, Supervision and investigation of the boreholes of the Yliki area using geographical information system, 7th meeting of the Greek users of ArcInfo, Marathon Data Systems, 1997.
  78. G. Tsakalias, and D. Koutsoyiannis, Hydrological characteristics of the Sperchios basin, Sperchios 2000+, 89–98, doi:10.13140/RG.2.2.15334.63047, Sterea Hellas District, National Technical University of Athens, 1995.
  79. N. Mamassis, and D. Koutsoyiannis, Study of the geographical distribution of hydrometeorological variables using geographical information system, 5th meeting of the Greek users of ArcInfo, Marathon Data Systems, 1995.
  80. D. Hadjichristos, D. Koutsoyiannis, and A. Koukouvinos, Investigation of the design of storm sewer networks using geographical information system, 5th meeting of the Greek users of ArcInfo, Marathon Data Systems, 1995.
  81. Th. Xanthopoulos, D. Christoulas, M. Mimikou, M. Aftias, and D. Koutsoyiannis, A strategy for the problem of floods in Athens, Flood protection of the Athens basin, doi:10.13140/RG.2.2.35719.60320, Technical Chamber of Greece, 1995.
  82. D. Koutsoyiannis, G. Tsakalias, A. Christofides, A. Manetas, A. Sakellariou, R. Mavrodimou, N. Papakostas, N. Mamassis, I. Nalbantis, and Th. Xanthopoulos, HYDROSCOPE: Creation of a national data bank of hydrological and meteorological information, Research and Technology Days '95, National Technical University of Athens, 1995.
  83. D. Koutsoyiannis, N. Mamassis, and E. Foufoula-Georgiou, Rainfall modelling, Workshop for the presentation of the research project A comprehensive forecasting system for flood risk mitigation and control, Bologna, Italy, University of Bologna, 1994.
  84. D. Koutsoyiannis, HYDROSCOPE : Creation of a national data bank of hydrological and meteorological information, Workshop for the STRIDE HELLAS programme, General Secretariat of Research and Technology, 1994.
  85. I. Nalbantis, N. Mamassis, D. Koutsoyiannis, E. Baltas, M. Aftias, M. Mimikou, and Th. Xanthopoulos, Hydrologic characteristics of the water shortage, The water supply problem of Athens, 13–28, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 1994.
  86. D. Koutsoyiannis, HYDROSCOPE: Organization and technical characteristics, Workshop for the presentation of the Hydroscope research project, National Technical University of Athens, 1994.
  87. D. Tolikas, D. Koutsoyiannis, and Th. Xanthopoulos, HYDROSCOPE : An information system for the study of hydroclimatic phenomena in Greece, 8th Seminar for the protection of the environment, 36–44, Aristotle University of Thessaloniki, Municipality of Thessaloniki, Goethe German Institute of Thessaloniki, 1993.
  88. N. Mamassis, and D. Koutsoyiannis, Some results on rainfall modelling - Univariate versus multivariate stochastic modelling of rainfall, 5th Meeting of AFORISM, Cork, Ireland, University College Cork, 1993.
  89. N. Mamassis, and D. Koutsoyiannis, An attempt for stochastic forecasting of rainfall, 4th Meeting of AFORISM, Grenoble, Institut National Polytechnique de Grenoble, 1993.
  90. I. Nalbantis, and D. Koutsoyiannis, Assessment of the risk for inadequacy of the water supply system of Athens, Water Supply of Athens, Association of Civil Engineers of Greece, Greek Union of Chemical Engineers, Association of the Greek Consulting Companies, 1992.
  91. N. Mamassis, I. Nalbantis, and D. Koutsoyiannis, Investigation of hydrological characteristics of Mornos, Boeoticos Kephisos and Yliki basins, Water Supply of Athens, Association of Civil Engineers of Greece, Greek Union of Chemical Engineers, Association of the Greek Consulting Companies, 1992.
  92. I. Spyrakos, I. Stamataki, and D. Koutsoyiannis, Analysis of a geographical information system for hydrological data , 2nd meeting of the Greek users of ArcInfo, Marathon Data Systems, 1992.
  93. D. Koutsoyiannis, I. Nalbantis, and N. Mamassis, Assessment of the risk for inadequacy of the water supply system of Athens in case of persistent drought, Likelihood of persistent drought and water supply of Athens, doi:10.13140/RG.2.2.13244.03207, Water Supply and Sewerage Company of Athens, 1992.
  94. D. Koutsoyiannis, and G. Tsakalias, A disaggregation model for storm hyetographs, 3rd Meeting of AFORISM, Athens, doi:10.13140/RG.2.2.28343.52649, National Technical University of Athens, 1992.
  95. D. Koutsoyiannis, and E. Foufoula-Georgiou, A scaling model of storm hyetograph, 2nd Meeting of AFORISM, Lausanne, Ecole Polytechnique Federale de Lausanne, 1992.
  96. I. Spyrakos, N. Mamassis, and D. Koutsoyiannis, Development of a geographical information system for hydrological data, 1st meeting of the Greek users of ArcInfo, Marathon Data Systems, 1991.
  97. Th. Xanthopoulos, D. Koutsoyiannis, and I. Nalbantis, Pilot study for the management of Louros and Arachthos basins. Appraisal of methodology and results, Computer aided water resources management, doi:10.13140/RG.2.2.35893.27360, Ministry of the Industry, 1991.

Various publications

  1. D. Koutsoyiannis, Slides for G. Sachinis' show in Crete TV – 2021-10-08, 2021.
  2. D. Koutsoyiannis, V. Marinos, M. Pantazidou, and H. Saroglou, Earth, water, time and us, School of Civil Engineering – National Technical University of Athens, Athens, 2020.
  3. D. Koutsoyiannis, A voyage in climate, hydrology and life on a 4.5-billion-years old planet, Self-organized lecture, doi:10.13140/RG.2.2.27000.26883, School of Civil Engineering – National Technical University of Athens, Athens, 20 July 2020.
  4. D. Koutsoyiannis, The political origin of the climate change agenda, Self-organized lecture, doi:10.13140/RG.2.2.10223.05283, School of Civil Engineering – National Technical University of Athens, Athens, 14 April 2020.
  5. D. Koutsoyiannis, Personal knowable moments (DK-moments) for high-order characterization of coincidence in totalitarianism, Self-organized lecture, doi:10.13140/RG.2.2.23117.38885/1, Bologna, Italy, 17 December 2019.
  6. D. Koutsoyiannis, Proceedings of the School of Civil Engineering NTUA and report of the outgoing Dean - 2014-2018, doi:10.13140/RG.2.2.36800.99849, School of Civil Engineering – National Technical University of Athens, 2018.
  7. D. Koutsoyiannis, Climate change impacts on hydrological science: A comment on the relationship of the climacogram with Allan variance and variogram, ResearchGate, doi:10.13140/RG.2.2.11886.66884, 2018.
  8. D. Koutsoyiannis, Edo Polytechneio… — 44 years after, doi:10.13140/RG.2.2.25488.30727, Athens, 2017.
  9. D. Koutsoyiannis, The 1821 revolution for freedom and the 180 years of struggles in NTUA for education, Official celebration of the national holiday of 25 March 1821, Athens, 24 March 2017.
  10. D. Koutsoyiannis, Antonis Koussis, the epistemon – polites, National Observatory of Athens, doi:10.13140/RG.2.2.16757.58089, Athens, 2016.
  11. D. Tsaknias, D. Bouziotas, and D. Koutsoyiannis, Statistical comparison of observed temperature and rainfall extremes with climate model outputs in the Mediterranean region, ResearchGate, doi:10.13140/RG.2.2.11993.93281, 2016.
  12. N. Mamassis, P. Defteraios, N. Zarkadoulas, and D. Koutsoyiannis, Research on water supply of ancient Piraeus-Representation of ancient cisterns operation, 16 pages, doi:10.13140/RG.2.2.11392.64000, 15 May 2015.
  13. D. Koutsoyiannis, On the collapse of the historical bridge of Plaka, Kathimerini, 8 February 2015.
  14. D. Koutsoyiannis, Book Review: "Meteorological Wandering - The Story of a Butterfly" by Theodore Kolydas, doi:10.13140/RG.2.2.24814.41282, Athens, 16 June 2014.
  15. D. Koutsoyiannis, Citation for the 2014 Tison Award, Dublin, 24 April 2014.
  16. D. Koutsoyiannis, International Hydrology Prize – Dooge Medal 2014: Response, doi:10.13140/RG.2.2.18103.52646, Dublin, 24 April 2014.
  17. D. Koutsoyiannis, The Department of Water Resources and Environmental Engineering, Presentation in the framework of the evaluation of the School of Civil Engineering of NTUA, Athens, November 2013.
  18. D. Koutsoyiannis, LTP: Looking Trendy—Persistently, Climate Dialogue, doi:10.13140/RG.2.2.13070.36169, 2013.
  19. D. Koutsoyiannis, Citation for the 2012 Tison Award, IAHS 90th Anniversary, Delft, The Netherlands, 23 October 2012.
  20. D. Koutsoyiannis, Invitation to Kos 2013: Facets of Uncertainty, Hydrology and Society, 2012 EGU Leonardo Conference, Turin, 15 November 2012.
  21. D. Koutsoyiannis, Review report of 'Socio-hydrology: A new science of people and water', 6 November 2011.
  22. D. Koutsoyiannis, Research funding as the enemy of innovation, Bishop Hill Blog, doi:10.13140/RG.2.2.31525.29928 , 2011.
  23. D. Koutsoyiannis, We don't mind, we do not have, Eleftherotypia, 28 May 2011.
  24. D. Koutsoyiannis, Vít Klemeš (1932-2010), The Reference Frame (by Luboš Motl), 5 pages, doi:10.13140/RG.2.2.10344.06404, 2011.
  25. M. Karlaftis, and D. Koutsoyiannis, [No English title available], Newspaper "To Vima", Α6, Athens, 26 November 2010.
  26. D. Koutsoyiannis, Three remarks for the rector election in NTUA in 2010, 5 pages, Athens, 1 July 2010.
  27. D. Koutsoyiannis, A brief tribute to Vit Klemeš, IAHS/STAHY Workshop--Advances in Statistical Hydrology, Taormina, Sicily, Italy, 24 May 2010.
  28. D. Koutsoyiannis, Will propaganda and lies save the Earth?, 2 pages, Athens, 1 April 2010.
  29. D. Koutsoyiannis, Beware saviors!, Climate Science (by Roger Pielke Sr.), 2 pages, doi:10.13140/RG.2.2.23765.83688, 2009.
  30. D. Koutsoyiannis, Rainfall shortage as an opportunity for fertile thinking, Kathimerini, 16 March 2008.
  31. D. Koutsoyiannis, Energy and water resources management, Energy Point, 3, Athens, August 2007.
  32. D. Koutsoyiannis, On the problem of erosion and sediment deposition in the area upstream of the Lavrio Cultural Park, 5 pages, National Technical University of Athens, Athens, 2007.
  33. D. Koutsoyiannis, Kephisos is an X-ray image of the society, Newspaper "Kathimerini", 36, Athens, 11 March 2007.
  34. D. Koutsoyiannis, A. Andreadakis, and C. Memos, On the revision of the curriculum of the School of Civil Engineering, Athens, 2006.
  35. D. Koutsoyiannis, What are the conditions for valid extrapolation of statistical predictions?, Niche Modeling, 2 pages, August 2006.
  36. D. Koutsoyiannis, Hurst, Joseph, colours and noises: The importance of names in an important natural behaviour, Niche Modeling, 10 pages, doi:10.13140/RG.2.2.23513.52320, 2006.
  37. D. Koutsoyiannis, Two comments on "How Red are my Proxies?" by David Ritson, Real Climate, 6 pages, doi:10.13140/RG.2.2.36778.00960, 2006.
  38. D. Koutsoyiannis, Energy aspects of the Acheloos diversion project, Ergotaxiaka Themata, 125, 35–37, Athens, November 2006.
  39. D. Koutsoyiannis, Commercialized education and entrance examination: difficult problems and easy solutions, Athens, 11 July 2006.
  40. D. Koutsoyiannis, Diversions and aberrations, Newspaper "To Vima", A55, Athens, 30 August 2006.
  41. D. Koutsoyiannis, Two comments on "Naturally trendy?" by Rasmus E. Benestad, Real Climate, 5 pages, May 2005.
  42. H. Perlman, C. Makropoulos, and D. Koutsoyiannis, The water cycle, http://ga.water.usgs.gov/edu/watercyclegreek.html, 19 pages, doi:10.13140/RG.2.2.11182.92480, United States Geological Survey, 2005.
  43. D. Koutsoyiannis, Terror scenarios about a dam, Newspaper "To Vima", A8, 12 February 2005.
  44. D. Koutsoyiannis, A masterplan for rational management of water resources, Economist-Kathimerini, 26 September 2004.
  45. D. Koutsoyiannis, The complicated water supply system of Athens, Economist-Kathimerini, 26 September 2004.
  46. C. Gardner, D. Koutsoyiannis, Z. W. Kundzewicz, and F. Watkins, IAHS and Electronic Publishing of HSJ, 5 pages, International Association of Hydrological Sciences, London, 2003.
  47. D. Koutsoyiannis, Atmosphere and climate, Man and Environment in the 21st Century, The crucial problems, 1, 6 pages, doi:10.13140/RG.2.2.31315.58406, Goulandris Natural History Museum, Athens, 2003.
  48. D. Koutsoyiannis, On the covering of Kephisos River, Daemon of Ecology, 6 October 2002.
  49. Th. Xanthopoulos, and D. Koutsoyiannis, Climate worsening: Inherent weaknesses in reliable prediction, and unjustified doomsaying, Bulletin of the National Chamber of Greece, 144–146, 8 July 2002.
  50. D. Koutsoyiannis, and I. Tselentis, Comment on the perspectives of water resources development in Greece with regard to the Water Framework Directive, Hydroeconomy, 2, 82–87, July 2002.
  51. D. Koutsoyiannis, On the covering of Kephisos River, Newspaper 'Machetiki of Moschato", 8 June 2002.
  52. Th. Xanthopoulos, and D. Koutsoyiannis, Climate worsening: Inherent weaknesses in reliable prediction, and unjustified doomsaying, Newspaper "To Vima", A38–A39, 2 June 2002.
  53. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, The management of resources for the water supply of Athens, Hellenic Association of Consulting Firms Newsletter, 65, 4–5, Athens, October 2001.
  54. Th. Xanthopoulos, and D. Koutsoyiannis, Prediction of climate: Scientific evidence, historical experience and the truth, Newspaper "To Vima", A10–A11, 17 September 2000.
  55. D. Koutsoyiannis, 1 measurement = 1000 calculations, Newspaper "To Vima", Special extra supplement on water, 18–20, 12 November 2000.
  56. Greek Committee for Desertification, Greek provisional action plan for combating desertification, 142 pages, Ministry of Agriculture, 2000.
  57. D. Koutsoyiannis, Climate change: Myths and reality, New Ecology, 151, 27–28, May 1997.
  58. Th. Xanthopoulos, and D. Koutsoyiannis, Water resources, Technology and Informatics, Educational Greek Encyclopedia, 19, 403–404, Ekdotiki Athinon, 1997.
  59. Th. Xanthopoulos, D. Christoulas, M. Mimikou, M. Aftias, and D. Koutsoyiannis, Flood protection of the Athens basin, Monthly Technical Review, 48, 50–53, 1996.
  60. D. Koutsoyiannis, Comments on the reform and modernization of undergraduate Civil Engineering courses, Athens, 1995.
  61. D. Koutsoyiannis, P. Marinos, and M. Mimikou, Hydrological approach of the Acheloos diversion, Pyrphoros, 21, 29–32, November 1995.
  62. Th. Xanthopoulos, D. Christoulas, M. Mimikou, M. Aftias, and D. Koutsoyiannis, The problem of flood protection of Athens: Strategy to deal with, Newspaper "Pontiki", 14–15, 24 November 1994.
  63. P. Burlando, and D. Koutsoyiannis, Precipitation measurement, modelling and forecasting - Stochastic modelling of rainfall in space and time (Conference session report), EGS Newsletter, 51, 17, 1994.
  64. Th. Xanthopoulos, M. Mimikou, M. Aftias, D. Koutsoyiannis, and I. Nalbantis, Assessment of the water supply problem of Athens under the prevailing drought, Report to the Minister of Environment, Planning & Public Works, 8 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 1993.
  65. D. Koutsoyiannis, The nature of drought, Pyrphoros, 7, 6–7, May 1993.
  66. Th. Xanthopoulos, and D. Koutsoyiannis, Special supplement on the problems of the water supply of Athens, Bulletin of the National Chamber of Greece, 1646, 15–52, 14 January 1991.
  67. D. Koutsoyiannis, The degradation of the role of Mathematics in education, Newspaper "Kathimerini", 10 December 1991.
  68. D. Koutsoyiannis, Comments on the draft curriculum of core courses (School of Civil Engineering NTUA, 1990), Athens, 1990.
  69. Th. Xanthopoulos, and D. Koutsoyiannis, Reliability and safety of the water resource system of Athens, Economicos Tachydromos, 47(1907), 44–48, 22 November 1990.

Books

  1. D. Koutsoyiannis, Stochastics of Hydroclimatic Extremes - A Cool Look at Risk, ISBN: 978-618-85370-0-2, 333 pages, Kallipos, Athens, 2021.
  2. D. Koutsoyiannis, and A. Efstratiadis, Lecture Notes on Urban Hydraulic Works - Water Supply, 83 pages, doi:10.13140/RG.2.1.3559.7044, National Technical University of Athens, February 2015.
  3. A. N. Angelakis, L.W. Mays, D. Koutsoyiannis, and N. Mamassis, Evolution of Water Supply Through the Millennia, 560 pages, IWA Publishing, London, 2012.
  4. D. Koutsoyiannis, Design of Urban Sewer Networks, Edition 4, 180 pages, doi:10.13140/RG.2.1.2169.1125, National Technical University of Athens, Athens, 2011.
  5. D. Koutsoyiannis, Probability and statistics for geophysical processes, doi:10.13140/RG.2.1.2300.1849/1, National Technical University of Athens, Athens, 2008.
  6. A. N. Angelakis, and D. Koutsoyiannis, Proceedings of the 1st IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations, 792 pages, doi:10.13140/RG.2.1.2511.1287, Heracleion, Crete, Greece, 2006.
  7. D. Koutsoyiannis, and Th. Xanthopoulos, Engineering Hydrology, Edition 3, 418 pages, doi:10.13140/RG.2.1.4856.0888, National Technical University of Athens, Athens, 1999.
  8. D. Koutsoyiannis, Statistical Hydrology, Edition 4, 312 pages, doi:10.13140/RG.2.1.5118.2325, National Technical University of Athens, Athens, 1997.

Educational notes

  1. D. Koutsoyiannis, Clausius-Clapeyron equation and saturation vapour pressure: Typical hydrometeorological calculations, 5 pages, doi:10.13140/RG.2.2.13548.08322/2, National Technical University of Athens, Athens, 2021.
  2. A. Efstratiadis, N. Mamassis, and D. Koutsoyiannis, Lecture notes on Renewable Energy and Hydroelectric Works, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2020.
  3. D. Koutsoyiannis, M. Pantazidou, N. Mamassis, G.-F. Sargentis, P. Thanopoulos, S. Lampropoulos, D Vamvatsikos, and K. Hadjibiros, Lecture Notes for the Laboratory on Humanities, School of Civil Engineering – National Technical University of Athens, Athens, 2020.
  4. D. Koutsoyiannis, Historical and Philosophical Introduction to the Scientific Method, Lecture Notes for the Laboratory on Humanities, doi:10.13140/RG.2.2.19594.00963/1, School of Civil Engineering – National Technical University of Athens, 2020.
  5. A. Efstratiadis, and D. Koutsoyiannis, Lecture notes on Hydraulics and Hydraulic Works: Sewage works, 72 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, December 2018.
  6. N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Lecture notes on renewable Energy and Hydroelectric Works, 327 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2018.
  7. D. Koutsoyiannis, Lecture notes on stochastics, Università degli Studi Roma Tre, Roma, doi:10.13140/RG.2.2.30801.84327, 2018.
  8. D. Koutsoyiannis, and A. Efstratiadis, Lecture notes on Hydraulics and Hydraulic Works: Aqueducts, 68 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2017.
  9. D. Koutsoyiannis, Lecture notes on Hydraulics and Hydraulic Works: Review of fluid mechanics and hydraulics, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2017.
  10. D. Koutsoyiannis, Lecture notes on Stochastic Methods, School of Civil Engineering – National Technical University of Athens, Athens, 2017.
  11. A. Efstratiadis, and D. Koutsoyiannis, Lecture notes on Water Resources Management, 97 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2015.
  12. A. Efstratiadis, and D. Koutsoyiannis, Lecture notes: Urban stormwater drainage networks, 23 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2014.
  13. D. Koutsoyiannis, A brief introduction to probability, doi:10.13140/RG.2.2.12634.54722, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2014.
  14. D. Koutsoyiannis, Encolpion of stochastics: Fundamentals of stochastic processes, doi:10.13140/RG.2.2.10956.82564, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2013.
  15. D. Koutsoyiannis, Lecture notes on Stochastic Methods in Water Resources, Edition 4, 100 pages, National Technical University of Athens, Athens, 2013.
  16. D. Koutsoyiannis, Lecture Notes on Hydrometeorology: A probability-based introduction to atmospheric thermodynamics, 45 pages, doi:10.13140/RG.2.2.22700.87686, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2011.
  17. D. Koutsoyiannis, Lecture Notes on Hydrometeorology: Simple physical principles for complex systems, 19 pages, doi:10.13140/RG.2.2.36122.64967, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2011.
  18. A. Efstratiadis, N. Mamassis, and D. Koutsoyiannis, Lecture notes on Water Resources Management - Part 2, 97 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 2011.
  19. D. Koutsoyiannis, Water technology and management in Ancient Greece: Legacies and lessons, 28 pages, doi:10.13140/RG.2.2.27314.61129, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, May 2007.
  20. D. Koutsoyiannis, and A. Efstratiadis, Lecture notes on Urban Hydraulic Works - Part 1: Water Supply, 146 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2007.
  21. D. Koutsoyiannis, Lecture notes on Water Resources Management - Part 1, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 2007.
  22. A. Efstratiadis, and D. Koutsoyiannis, Lecture notes on Typical Hydraulic Works - Part 2: Water Distribution Networks, 90 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 2006.
  23. A. Katsiri, and D. Koutsoyiannis, Reservoirs: necessity, impacts and their management - Case study: the Tavropos reservoir, 67 pages, doi:10.13140/RG.2.2.15570.56007, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 2005.
  24. A. Efstratiadis, and D. Koutsoyiannis, Lecture notes on Water Resource System Optimisation - Part 2, 140 pages, National Technical University of Athens, Athens, 2004.
  25. D. Koutsoyiannis, The modern Athens water resource system and its management, doi:10.13140/RG.2.2.22281.44643, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 2002.
  26. D. Koutsoyiannis, Water resources technologies in ancient Greece, 24 pages, doi:10.13140/RG.2.2.25846.60483, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 2002.
  27. D. Koutsoyiannis, Lecture notes on Urban Hydraulic Works - Part 2: Sewerage, 35 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 2000.
  28. D. Koutsoyiannis, Lecture notes on Water Resource System Optimisation - Part 1, Edition 2, 91 pages, National Technical University of Athens, Athens, 2000.
  29. N. Mamassis, and D. Koutsoyiannis, Lecture notes on Hydrometeorology - Part 2, Edition 2, 176 pages, National Technical University of Athens, Athens, 2000.
  30. D. Koutsoyiannis, Lecture notes on Hydrometeorology - Part 1, Edition 2, 157 pages, National Technical University of Athens, Athens, 2000.
  31. N. Mamassis, and D. Koutsoyiannis, Lecture notes on Advanced Hydrology - Part 2, 65 pages, National Technical University of Athens, Athens, 1999.
  32. D. Koutsoyiannis, Lecture notes on Advanced Hydrology - Part 1, 52 pages, National Technical University of Athens, Athens, 1999.
  33. D. Koutsoyiannis, Probabilistic and statistical methods in engineering hydrology, 24 pages, National Technical University of Athens, Athens, 1994.
  34. D. Koutsoyiannis, Topics of surface hydrology - Notes on training courses, Edition 2, 36 pages, National Technical University of Athens, 1994.
  35. D. Koutsoyiannis, Instructions for solving water supply networks, Edition 2, 25 pages, National Technical University of Athens, Athens, 1990.
  36. D. Koutsoyiannis, Quantitative assessment of water resources - Estimation of mean, maximum and minimum flows, 31 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 1989.
  37. D. Koutsoyiannis, Hydrological methods of flood routing, 16 pages, National Technical University of Athens, Athens, 1988.
  38. D. Koutsoyiannis, Lecture notes on river hydraulics and sedimentation engineering, 84 pages, National Technical University of Athens, Athens, 1982.

Academic works

  1. D. Koutsoyiannis, A disaggregation model of point rainfall, PhD thesis, 310 pages, doi:10.12681/eadd/0910, National Technical University of Athens, Athens, 1988.
  2. E. Karakosti, and D. Koutsoyiannis, Penetration of a jet into a counterflow, Diploma thesis, 192 pages, National Technical University of Athens, 1978.

Research reports

  1. N. Mamassis, A. Efstratiadis, A. Koukouvinos, and D. Koutsoyiannis, Technical report: Development of a national monitoring system for surface water resources, Open Hydrosystem Information Network (OpenHi.net), Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, Τεύχος 2.1, June 2019.
  2. N. Mamassis, D. Koutsoyiannis, A. Efstratiadis, and A. Koukouvinos, Technical report: Specification analysis of OpenHi.net system, Open Hydrosystem Information Network (OpenHi.net), Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 29 pages, Τεύχος 3.1, September 2018.
  3. A. Koukouvinos, A. Efstratiadis, D. Nikolopoulos, H. Tyralis, A. Tegos, N. Mamassis, and D. Koutsoyiannis, Case study in the Acheloos-Thessaly system, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 98 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2015.
  4. D. Koutsoyiannis, S.M. Papalexiou, Y. Markonis, P. Dimitriadis, and P. Kossieris, Stochastic framework for uncertainty assessment of hydrometeorological procesess, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 231 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, January 2015.
  5. A. Efstratiadis, A. Koukouvinos, E. Michailidi, E. Galiouna, K. Tzouka, A. D. Koussis, N. Mamassis, and D. Koutsoyiannis, Description of regional approaches for the estimation of characteristic hydrological quantities, DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools, Contractors: ETME: Peppas & Collaborators, Grafeio Mahera, Department of Water Resources and Environmental Engineering – National Technical University of Athens, National Observatory of Athens, 146 pages, September 2014.
  6. N. Mamassis, K. Pipili, and D. Koutsoyiannis, [No English title available], , Contractor: Hellenic Centre for Marine Research, Athens, 2013.
  7. A. Efstratiadis, D. Koutsoyiannis, and S.M. Papalexiou, Description of methodology for intense rainfall analysis , DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools, Contractors: ETME: Peppas & Collaborators, Grafeio Mahera, Department of Water Resources and Environmental Engineering – National Technical University of Athens, National Observatory of Athens, 55 pages, November 2012.
  8. A. Efstratiadis, D. Koutsoyiannis, N. Mamassis, P. Dimitriadis, and A. Maheras, Litterature review of flood hydrology and related tools, DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools, Contractors: ETME: Peppas & Collaborators, Grafeio Mahera, Department of Water Resources and Environmental Engineering – National Technical University of Athens, National Observatory of Athens, 115 pages, October 2012.
  9. D. Koutsoyiannis, Alternative Robust Energy Technologies for Environmental Sustainability (ARETES), Athens, 2011.
  10. D. Koutsoyiannis, WATer pathways towards the non-deterministic future of renewable enERGY (WATERGY), Athens, 2011.
  11. I. Papakonstantis, P. Papanicolaou, V. Kotsioni, M. Hondros, C. Memos, and D. Koutsoyiannis, Final report, Integrated study for the investigation of the quantity, quality and recovery of the underwater springs of the Stoupa region in Municipality of Lefktros, Messinia, Contractors: Hellenic Centre for Marine Research, Agricultural University of Athens, National Technical University of Athens, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2010.
  12. D. Koutsoyiannis, N. Mamassis, A. Koukouvinos, and A. Efstratiadis, Summary report, Athens, Investigation of management scenarios for the Smokovo reservoir, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 37 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, August 2008.
  13. D. Koutsoyiannis, N. Mamassis, A. Koukouvinos, and A. Efstratiadis, Final report, Investigation of management scenarios for the Smokovo reservoir, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 4, 66 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, July 2008.
  14. A. Efstratiadis, A. Koukouvinos, N. Mamassis, and D. Koutsoyiannis, Alternative scenarios for the management and optimal operation of the Smokovo reservoir and the related works, Investigation of management scenarios for the Smokovo reservoir, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 3, 104 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2008.
  15. D. Koutsoyiannis, A. Andreadakis, R. Mavrodimou, A. Christofides, N. Mamassis, A. Efstratiadis, A. Koukouvinos, G. Karavokiros, S. Kozanis, D. Mamais, and K. Noutsopoulos, National Programme for the Management and Protection of Water Resources, Support on the compilation of the national programme for water resources management and preservation, 748 pages, doi:10.13140/RG.2.2.25384.62727, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, February 2008.
  16. A. Efstratiadis, G. Karavokiros, and D. Koutsoyiannis, Theoretical documentation of model for simulating and optimising the management of water resources "Hydronomeas", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 9, 91 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2007.
  17. N. Mamassis, R. Mavrodimou, A. Efstratiadis, M. Heidarlis, A. Tegos, A. Koukouvinos, P. Lazaridou, M. Magaliou, and D. Koutsoyiannis, Investigation of alternative organisations and operations of a Water Management Body for the Smokovo projects, Investigation of management scenarios for the Smokovo reservoir, Report 2, 73 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2007.
  18. A. Efstratiadis, D. Koutsoyiannis, and S. Kozanis, Theoretical documentation of stochastic simulation of hydrological variables model "Castalia", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 3, 61 pages, doi:10.13140/RG.2.2.30224.40966, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2005.
  19. D. Koutsoyiannis, and S. Kozanis, A simple Monte Carlo methodology to calculate generalized approximate confidence intervals, Research report, Contractor: [Not funded], doi:10.13140/RG.2.2.33579.85286, Hydrologic Research Center, 2005.
  20. D. Koutsoyiannis, Hydrological flood study, Investigation and remedy of the stability problems of the banks and bed of the Philothei Creek using mathematical models and modern environmental methods, 22 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2004.
  21. I. Nalbantis, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Final report, Modernisation of the supervision and management of the water resource system of Athens, Report 25, 135 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2004.
  22. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, Hydronomeas (version 3.2) - A system to support the management of water resources, Modernisation of the supervision and management of the water resource system of Athens, Report 24, 142 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  23. A. Efstratiadis, and D. Koutsoyiannis, Castalia (version 2.0) - A system for stochastic simulation of hydrological variables, Modernisation of the supervision and management of the water resource system of Athens, Report 23, 103 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  24. D. Koutsoyiannis, I. Nalbantis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, A. Christofides, E. Rozos, A. Economou, and G. M. T. Tentes, Methodology and theoretical background, Modernisation of the supervision and management of the water resource system of Athens, Report 15, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  25. Ministry of Development, NTUA, Institute of Geological and Mining Research, and Centre for Research and Planning, Master plan for water resource management of the country, Completion of the classification of quantitative and qualitative parameters of water resources in water districts of Greece, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 549 pages, Ministry of Development, Athens, January 2003.
  26. D. Koutsoyiannis, A. Efstratiadis, G. Karavokiros, A. Koukouvinos, N. Mamassis, I. Nalbantis, E. Rozos, Ch. Karopoulos, A. Nassikas, E. Nestoridou, and D. Nikolopoulos, Master plan of the Athens water resource system — Year 2002–2003, Modernisation of the supervision and management of the water resource system of Athens, Report 14, 215 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2002.
  27. A. Efstratiadis, G. Karavokiros, and D. Koutsoyiannis, Second updating of simulations of the Athens water resource system for hydrologic year 2001-02, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 13b, 25 pages, Athens, April 2002.
  28. A. Efstratiadis, G. Karavokiros, and D. Koutsoyiannis, First updating of simulations of the Athens water resource system for hydrologic year 2001-02, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 13a, 21 pages, Athens, February 2002.
  29. A. Efstratiadis, A. Koukouvinos, D. Koutsoyiannis, and N. Mamassis, Hydrological Study, Investigation of scenarios for the management and protection of the quality of the Plastiras Lake, Report 2, 70 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2002.
  30. K. Hadjibiros, D. Koutsoyiannis, A. Andreadakis, A. Katsiri, A. Stamou, A. Valassopoulos, A. Efstratiadis, I. Katsiris, M. Kapetanaki, A. Koukouvinos, N. Mamassis, K. Noutsopoulos, G.-F. Sargentis, and A. Christofides, Overview report, Investigation of scenarios for the management and protection of the quality of the Plastiras Lake, Report 1, 23 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2002.
  31. D. Koutsoyiannis, and N. Mamassis, Hydrological investigation of intense rainfall and sediment yield in Thriasio, Assessment of sediment generation in Thriasio, 21 pages, School of Civil Engineering – National Technical University of Athens, Athens, 2001.
  32. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, Second updating of simulations of the Athens water resource system for hydrologic year 2000-01, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 17 pages, Athens, June 2001.
  33. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, First updating of simulations of the Athens water resource system for hydrologic year 2000-01, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 14 pages, Athens, February 2001.
  34. D. Zarris, E. Lykoudi, and D. Koutsoyiannis, Final Report, Appraisal of river sediment deposits in reservoirs of hydropower dams, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 243 pages, October 2001.
  35. D. Koutsoyiannis, A. Efstratiadis, G. Karavokiros, A. Koukouvinos, N. Mamassis, I. Nalbantis, D. Grintzia, N. Damianoglou, Ch. Karopoulos, S. Nalpantidou, A. Nassikas, D. Nikolopoulos, A. Xanthakis, and K. Ripis, Master plan of the Athens water resource system — Year 2001–2002, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 13, Athens, December 2001.
  36. D. Koutsoyiannis, and N. Mamassis, Final Report of Phase A, Modernisation of the supervision and management of the water resource system of Athens, Report 12, 63 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2000.
  37. D. Koutsoyiannis, A. Efstratiadis, G. Karavokiros, A. Koukouvinos, N. Mamassis, I. Nalbantis, D. Grintzia, N. Damianoglou, A. Xanthakis, S Politaki, and V. Tsoukala, Master plan of the Athens water resource system - Year 2000-2001, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 5, 165 pages, Athens, December 2000.
  38. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, Hydronomeas (version 2): A system for the support of the water resources management, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 11, 84 pages, Athens, December 2000.
  39. A. Efstratiadis, and D. Koutsoyiannis, Castalia: A system for the stochastic simulation of hydrological variables, Modernisation of the supervision and management of the water resource system of Athens, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Report 9, 70 pages, Athens, December 2000.
  40. H. S. Wheater, V. S. Isham, C. Onof, R. E. Chandler, P. J. Northrop, P. Guiblin, S. M. Bate, D. R. Cox, and D. Koutsoyiannis, Generation of spatially consistent rainfall data, Technical Report 204, Generation of spatially consistent rainfall data, Contractor: Imperial College, London, 170 pages, doi:10.13140/RG.2.1.3791.1286, University College London, London, 2000.
  41. D. Koutsoyiannis, The water supply system of Athens, Development of legislation framework for the drinking water of Athens, 11 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, 1999.
  42. D. Zarris, and D. Koutsoyiannis, Final Report of Phase A, Appraisal of river sediment deposits in reservoirs of hydropower dams, 97 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 1999.
  43. I. Nalbantis, and D. Koutsoyiannis, Final Report of Phase C, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3, Report 41, 100 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 1999.
  44. G. Karavokiros, D. Koutsoyiannis, and N. Mandellos, Model development for simulation and optimisation of the Eastern Sterea Hellas hydrosystem, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3, Report 40, 161 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 1999.
  45. D. Koutsoyiannis, and M. Mimikou, Terms and specifications for hydrological data entry, National databank for hydrological and meteorological information - Hydroscope 2000, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 176 pages, May 1997.
  46. I. Nalbantis, and D. Koutsoyiannis, Final Report, Upgrading and updating of hydrological information of Thessalia, Report 4, 78 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 1997.
  47. Team of the YBET96 project, Master plan for the country's water resource management, Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 339 pages, Ministry of Development, Athens, November 1996.
  48. AFORISM final report authoring team, Final report, AFORISM: A comprehensive forecasting system for flood risk mitigation and control, Contractor: University of Bologna, 568 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Bologna, April 1996.
  49. N. Mamassis, and D. Koutsoyiannis, Hydroscope II - A preliminary application to the Thessaly water district - Final Report, Hydroscope II - Creation of a National Databank for Hydrological and Meteorological Information, 41 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 1996.
  50. D. Koutsoyiannis, G. Tsakalias, N. Mamassis, and A. Koukouvinos, Surface water resources, Integrated management of the riparian ecosystem of the Sperhios river, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 16 pages, 1995.
  51. D. Koutsoyiannis, and P. Marinos, Final Report of Phase B, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 32, 95 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 1995.
  52. G. Tsakalias, and D. Koutsoyiannis, Stage-discharge curves and derivation of discharges, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 19, 125 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 1995.
  53. G. Tsakalias, and D. Koutsoyiannis, A pilot model for the management of the reservoir system for the water supply of Athens, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 14, 52 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, November 1995.
  54. D. Koutsoyiannis, and A. Manetas, Computer software for the construction of IDF curves - User's manual, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 13, 41 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, November 1995.
  55. D. Koutsoyiannis, and A. Manetas, A model of stochastic simulation of hydrological time series using a simple disaggregation technique - User's manual, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 12, 57 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, November 1995.
  56. A. Manetas, and D. Koutsoyiannis, Upgrade of the computational environment for the hydrological data processing, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 11, 23 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, November 1995.
  57. NTUA Hydroscope Team, HYDROSCOPE, User manual for the database and applications for hydrology and meteorology, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 180 pages, National Technical University of Athens, Athens, December 1994.
  58. Th. Xanthopoulos, D. Koutsoyiannis, and I. Nalbantis, Third Annual Report (1993-1994), Contribution of the National Technical University of Athens research team, AFORISM: A comprehensive forecasting system for flood risk mitigation and control, Contractor: University of Bologna, 13 pages, Bologna, 1994.
  59. NTUA Committee for the Selection of Hydroscope Infrastructure, and Workteam for the Selection of Hydroscope Infrastructure, Selection of network routers, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Report 1/9, 73 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 1993.
  60. NTUA Committee for the Selection of Hydroscope Infrastructure, and Workteam for the Selection of Hydroscope Infrastructure, Selection of modems, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Report 1/10, 51 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 1993.
  61. Th. Xanthopoulos, and D. Koutsoyiannis, Second Annual Report (1992-1993), Contribution of the National Technical University of Athens research team, AFORISM: A comprehensive forecasting system for flood risk mitigation and control, Contractor: University of Bologna, 11 pages, Bologna, September 1993.
  62. NTUA Committee for the Selection of Hydroscope Infrastructure, and Workteam for the Selection of Hydroscope Infrastructure, Selection of data base management system (DBMS), Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Report 1/2, 53 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, July 1992.
  63. NTUA Committee for the Selection of Hydroscope Infrastructure, and Workteam for the Selection of Hydroscope Infrastructure, Selection of basic computer equipment, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Report 1/1, 102 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1992.
  64. P. Papanicolaou, and D. Koutsoyiannis, Guidelines for the layout of deliverable reports, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Report 0/1, 16 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, July 1992.
  65. Th. Xanthopoulos, D. Koutsoyiannis, and I. Nalbantis, First Annual Report (1991-1992), Contribution of the National Technical University of Athens research team, AFORISM: A comprehensive forecasting system for flood risk mitigation and control, Contractor: University of Bologna, 74 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Bologna, June 1992.
  66. D. Koutsoyiannis, and I. Nalbantis, Final Report of Phase A, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 1, Report 10, 71 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 1992.
  67. D. Koutsoyiannis, Computer programmes for stochastic simulation of hydrologic time series, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 1, Report 7, 87 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 1992.
  68. I. Nalbantis, D. Koutsoyiannis, and Th. Xanthopoulos, Final report, Assessment of methodology and results, A pilot study for the management of the Louros and Arachthos watersheds, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, April 1991.
  69. D. Koutsoyiannis, and Th. Xanthopoulos, Conclusions Summary, Appraisal of existing potential for improving the water supply of greater Athens - Phase 2, Report 19, 48 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1990.
  70. D. Koutsoyiannis, Th. Xanthopoulos, and M. Aftias, Final Report, Appraisal of existing potential for improving the water supply of greater Athens - Phase 2, Report 18, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1990.
  71. N. Stavridis, S. Roti, and D. Koutsoyiannis, Study of upgrading the hydrometeorological network of the Mornos and Evinos basins, Appraisal of existing potential for improving the water supply of greater Athens - Phase 2, Report 17, 79 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 1990.
  72. D. Koutsoyiannis, I. Nalbantis, and C. Tsolakidis, Operation scheduling of the existing water supply system, Appraisal of existing potential for improving the water supply of greater Athens - Phase 2, Report 16, 75 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1990.
  73. D. Koutsoyiannis, N. Mamassis, and I. Nalbantis, Stochastic simulation of hydrological variables, Appraisal of existing potential for improving the water supply of greater Athens - Phase 2, Report 13, 313 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 1990.
  74. D. Koutsoyiannis, and I. Nalbantis, Capacity assessment of the present Mornos-Yliki supply system, Appraisal of existing potential for improving the water supply of greater Athens - Phase 2, Report 8, 87 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 1989.
  75. D. Koutsoyiannis, and Th. Xanthopoulos, Final report of the first phase, Appraisal of existing potential for improving the water supply of greater Athens - Phase 1, Report 7, 114 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 1989.
  76. S. Roti, N. Mamassis, and D. Koutsoyiannis, Study of monthly hydrometeorological data, Appraisal of existing potential for improving the water supply of greater Athens - Phase 1, Report 6, 288 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 1989.
  77. G. Tsakiris, and D. Koutsoyiannis, Final report, Investigation of use of stormwater for irrigation - Application to the area of Archanes municipality, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 150 pages, 1988.
  78. D. Koutsoyiannis, S. Roti, and J. Tzeranis, Drawings-Maps, Hydrological investigation of the Thessalia water basin, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1988.
  79. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Stage and discharge data, Hydrological investigation of the Thessalia water basin, Appendix Δ2, 589 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 1988.
  80. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Stage and discharge data, Hydrological investigation of the Thessalia water basin, Appendix Δ, 559 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 1988.
  81. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Final Report, Hydrological investigation of the Thessalia water basin, Report 7, 105 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1988.
  82. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Monthly data processing, Hydrological investigation of the Thessalia water basin, Report 6, 354 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1988.
  83. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Hydrological study for minimum flows of Pinios river, Hydrological investigation of the Thessalia water basin, Report 5, 35 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 1988.
  84. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Design Floods, Hydrological investigation of the Thessalia water basin, Report 4, 107 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1988.
  85. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Rainfall depth-duration-frequency curves, Hydrological investigation of the Thessalia water basin, Report 3, 501 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1988.
  86. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Hydrometeorological measurement stations, Hydrological investigation of the Thessalia water basin, Report 2, 124 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 1988.
  87. D. Koutsoyiannis, and J. Tzeranis, 2nd preliminary report: Approximate water budget of the Mornos watershed, Appraisal of existing potential for improving the water supply of greater Athens - Phase 1, 32 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, April 1988.
  88. D. Koutsoyiannis, Computer programmes for hydrological data archiving end processing, Appraisal of existing potential for improving the water supply of greater Athens - Phase 1, Report 5, 71 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 1988.
  89. S. Tsimpidis, and D. Koutsoyiannis, Hydrological investigation, Environmental impacts of the irrigation project in the lake Mikri Prespa, Florina, Phase A, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 1987.
  90. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Discharge measurements, Stage-discharge curves, Hydrological investigation of the Thessalia water basin, Appendix E, 197 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 1987.
  91. D. Koutsoyiannis, S. Roti, and J. Tzeranis, Rainfall data, Hydrological investigation of the Thessalia water basin, Appendix 3, 814 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 1987.
  92. D. Koutsoyiannis, S. Roti, and J. Tzeranis, Rainfall data, Hydrological investigation of the Thessalia water basin, Appendix 2, 69 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 1987.
  93. D. Koutsoyiannis, Review of hydrologic data and analyses of earlier studies, Hydrological investigation of the Thessalia water basin, Appendix 1, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 1987.
  94. D. Koutsoyiannis, S. Roti, J. Tzeranis, and Th. Xanthopoulos, Computer programs for hydrological data archiving and processing, Hydrological investigation of the Thessalia water basin, Report 1, 74 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 1987.
  95. Th. Xanthopoulos, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, and L. Vamvakeridou-Lyroudia, Final report, Water quality and assimilative capacity investigations of Kalamas river and lake Pamvotis (Ioannina), 341 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 1984.

Miscellaneous works

  1. N. Mamassis, and D. Koutsoyiannis, Water and energy in 21th century. Views on hydroelectric production, Conference of EYDAP employees union for the world water day, Athens, 21 March 2016.
  2. D. Koutsoyiannis, and H. H. G. Savenije, Guidelines for the use of units, symbols and equations in hydrology, doi:10.13140/RG.2.2.10775.21922, 2013.
  3. P. Papanicolaou, D. Koutsoyiannis, and A. Stamou, Guidelines for the presentation of academic works in the Department of Water Resources & Environmental Engineering, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, 2012.
  4. G. Karavokiros, A. Efstratiadis, and D. Koutsoyiannis, Hydronomeas: A system for supporting water resources management, 8 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 2002.
  5. A. Christofides, and D. Koutsoyiannis, Hydrognomon: A database for hydrological and meteorological time series and a processing system of time series, 16 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 2002.
  6. D. Koutsoyiannis, and A. Efstratiadis, Castalia: A system for stochastic simulation of hydrologic variables, 6 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 2002.
  7. D. Koutsoyiannis, Memories.

Engineering reports

  1. D. Koutsoyiannis, A. Efstratiadis, and A. Koukouvinos, Technical report: Investigation of flood flows in the river basin of Almopaios, Pleriminary study of Almopaios dam, Commissioner: Roikos Consulting Engeineers S.A., Contractors: , 43 pages, July 2014.
  2. A. Efstratiadis, A. Koukouvinos, N. Mamassis, S. Baki, Y. Markonis, and D. Koutsoyiannis, [No English title available], , Commissioner: Ministry of Environment, Energy and Climate Change, Contractor: Exarhou Nikolopoulos Bensasson, 205 pages, February 2013.
  3. A. Koukouvinos, A. Efstratiadis, N. Mamassis, Y. Markonis, S. Baki, and D. Koutsoyiannis, [No English title available], , Commissioner: Ministry of Environment, Energy and Climate Change, Contractor: Exarhou Nikolopoulos Bensasson, 144 pages, February 2013.
  4. A. Stamou, D. Koutsoyiannis, and N. Mamassis, Technical Report, Investigation of the hydrographic network development in Mavro Vouno, Grammatiko, Attica, Greece, Commissioner: Perifereiako Tameio Anaptyxis Attikis, Contractors: A. Stamou, D. Koutsoyiannis, N. Mamassis, 40 pages, Athens, 2012.
  5. D. Koutsoyiannis, Y. Markonis, A. Koukouvinos, S.M. Papalexiou, N. Mamassis, and P. Dimitriadis, Hydrological study of severe rainfall in the Kephisos basin, Greece, Study of the management of Kephisos , Commissioner: General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: Exarhou Nikolopoulos Bensasson, Denco, G. Karavokiris, et al., 154 pages, Athens, 2010.
  6. D. Koutsoyiannis, and Y. Markonis, Hydrological study of the Xerias Basina, Magnesia, Greece, Study of urgent flood protection works of the Xerias, Seskouliotis and Kakaviotis streams, Commissioner: Prefectural Government of Magnesia, Contractor: Grafeio Mahera, Athens, 2010.
  7. D. Koutsoyiannis, Y. Markonis, A. Koukouvinos, and N. Mamassis, Hydrological study of Arachthos floods, Delineation of the Arachthos River bed in the town of Arta, Commissioner: Municipality of Arta, Contractors: ADK - Aronis Drettas Karlaftis Consulting Engineers, YDROTEK, V. Mouzos, 272 pages, 2010.
  8. D. Koutsoyiannis, N. Mamassis, and A. Efstratiadis, Essential works to ensure the established ecological flow, Specific Technical Study for the Ecological Flow from the Dam of Stratos, Commissioner: Public Power Corporation, Contractor: ECOS Consultants S.A., 22 pages, Athens, May 2009.
  9. D. Koutsoyiannis, N. Mamassis, and A. Efstratiadis, Investigation of ecological flow, Specific Technical Study for the Ecological Flow from the Dam of Stratos, Commissioner: Public Power Corporation, Contractor: ECOS Consultants S.A., 88 pages, Athens, May 2009.
  10. D. Koutsoyiannis, and N. Mamassis, Consultative report for the flood of the 12/2005-2/2006 in the region of Lower Acheloos in Aetoloacarnania, Technical consulting for the floods of Lower Acheloos and Edesseos, Commissioner: Public Power Corporation, Contractors: D. Koutsoyiannis, N. Mamassis, 29 pages, June 2008.
  11. D. Koutsoyiannis, On the method selection for areal integration of point rainfall in the Aegean islands - Technical memo, Development of tools for the water resource management of the hydrological district of Aegean islands, Commissioner: Ministry of Development, Contractors: TEM, LDK, Ydroexigiantiki, TERRAMENTOR, 4 pages, Athens, 2005.
  12. D. Koutsoyiannis, and N. Mamassis, Consultative report for the flood of December 1996 in the region of Lower Acheloos in Aetoloacarnania, Technical consulting for the floods of Lower Acheloos and Edesseos, Commissioner: Public Power Corporation, Contractors: D. Koutsoyiannis, N. Mamassis, 18 pages, Athens, June 2005.
  13. D. Koutsoyiannis, and N. Mamassis, Consultative report for the flood of December 2002 in the region of Limne Nesiou, Technical consulting for the floods of Lower Acheloos and Edesseos, Commissioner: Public Power Corporation, Contractors: D. Koutsoyiannis, N. Mamassis, 13 pages, Athens, February 2005.
  14. D. Koutsoyiannis, and N. Mamassis, Consultative report for the flood of March 1999 in the region of Limne Nesiou, Technical consulting for the floods of Lower Acheloos and Edesseos, Commissioner: Public Power Corporation, Contractors: D. Koutsoyiannis, N. Mamassis, 12 pages, Athens, May 2005.
  15. D. Koutsoyiannis, Infiltration and inflows in the foul sewer network of the Municipality of Ellomeno in Leukas, Study of sewerage and wastewater treatment of the Municipality of Ellomeno in Leukas, Contractors: , 11 pages, Athens, 2004.
  16. D. Koutsoyiannis, Rainfall idf curves for the Kanavari-Dombrena-Prodromos road, Hydraulic study for drainage of the Kanavari-Dombrena-Prodromos road, Commissioner: Prefectural Government of Boeotia, Contractor: D. Argyropoulos, 9 pages, Athens, 2004.
  17. D. Koutsoyiannis, Technical report, Characterization of the size of Zaravina lake in Delvinaki area of the prefecture of Ioannina, Commissioner: P. Mentzos, Contractor: D. Koutsoyiannis, 35 pages, Athens, 2004.
  18. A. Andreadakis, D. Koutsoyiannis, and M. Aftias, Technical report , Expertise for the quality control of engineering studies for the project "Water supply of Patra from Peiros and Parapeiros rivers", Commissioner: Ministry of Environment, Planning and Public Works, Contractors: A. Andreadakis, D. Koutsoyiannis, M. Aftias, 20 pages, Athens, 2004.
  19. D. Koutsoyiannis, and N. Mamassis, Hydrological investigation, Diversion of the Soulou Stream for the Development of Lignite Exploitations of the Public Power Corporation in the Mine of Southern Field of Region Kozani-Ptolemais, Commissioner: Public Power Corporation, Contractors: D. Koutsoyiannis, N. Mamassis, 18 pages, Public Power Corporation, Athens, 2004.
  20. C. Maksimovic, H. S. Wheater, D. Koutsoyiannis, S. Prohaska, D. Peach, S. Djordevic, D. Prodanovic, C. Makropoulos, P. Docx, T. Dasic, M. Stanic, D. Spasova, and D. Brnjos, Final Report, Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina, Commissioner: Energy Financing Team, Switzerland, Contractors: CUW-UK, ICCI Limited, London, 2004.
  21. D. Koutsoyiannis, Drainage study of the football courts of Rouf and Kypsele in the Municipality of Athens, Construction of artificial lawn in the football courts of Rouf and Kypsele, Contractors: , 11 pages, Athens, 2003.
  22. N. Mamassis, A. Efstratiadis, M. Lasithiotakis, and D. Koutsoyiannis, First monitoring programme for the estimation of water resources in the Pylos-Romanos area for the water supply of the ITDA , Water resource management of the Integrated Tourist Development Area in Messenia, Commissioner: TEMES - Tourist Enterprises of Messinia, Contractor: D. Argyropoulos, 17 pages, Athens, 2003.
  23. D. Koutsoyiannis, N. Mamassis, and A. Efstratiadis, Hydrological study of the Sperheios basin, Hydrological and hydraulic study for the flood protection of the new railway in the region of Sperhios river, Commissioner: ERGA OSE, Contractor: D. Soteropoulos, Collaborators: D. Koutsoyiannis, 197 pages, Athens, January 2003.
  24. P. Marinos, M. Kavvadas, and D. Koutsoyiannis, Experts reports, Flood Protection Works of Diakoniaris Stream, Preliminary Study, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: Ydroexigiantiki, Grafeio Mahera, Ydroereyna, Collaborators: P. Marinos, M. Kavvadas, D. Koutsoyiannis, 44 pages, Athens, July 2002.
  25. A. Efstratiadis, G. M. T. Tentes, D. Koutsoyiannis, and D. Argyropoulos, Technical report, Preliminary Water Supply Study of the Thermoelectric Livadia Power Plant, Contractor: Ypologistiki Michaniki, 63 pages, Athens, 2001.
  26. D. Koutsoyiannis, Hydrological study, Engineering study for the licence of positioning of the Valorema Small Hydroelectric Project, Commissioner: YDROSAR, Contractor: D. Argyropoulos, 9 pages, Athens, 2001.
  27. D. Koutsoyiannis, Flood study, Study of the Potamos River, Corfu, Commissioner: Anaptyxiaki Demou Kerkyreon, Contractor: M. Papakosta, 46 pages, Athens, 2001.
  28. D. Koutsoyiannis, Hydrological study of the Western Road Axis, segment Antirrio-Kefalovriso, Study of the Segment Antirrio-Kefalovriso of the Western Road Axis, Commissioner: General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: NAMA, Kastor, 38 pages, Athens, 2001.
  29. D. Koutsoyiannis, I. Nalbantis, N. Mamassis, A. Efstratiadis, L. Lazaridis, and A. Daniil, Flood study, Engineering consultant for the project "Water supply of Heracleio and Agios Nicolaos from the Aposelemis dam", Commissioner: Ministry of Environment, Planning and Public Works, Contractor: Aposelemis Joint Venture, Athens, October 2001.
  30. D. Koutsoyiannis, A. Efstratiadis, N. Mamassis, I. Nalbantis, and L. Lazaridis, Hydrological study of reservoir operation, Engineering consultant for the project "Water supply of Heracleio and Agios Nicolaos from the Aposelemis dam", Commissioner: Ministry of Environment, Planning and Public Works, Contractor: Aposelemis Joint Venture, Athens, October 2001.
  31. D. Koutsoyiannis, A. Efstratiadis, and N. Mamassis, Appraisal of the surface water potential and its exploitation in the Acheloos river basin and in Thessaly, Ch. 5 of Study of Hydrosystems, Complementary study of environmental impacts from the diversion of Acheloos to Thessaly, Commissioner: Ministry of Environment, Planning and Public Works, Contractor: Ydroexigiantiki, Collaborators: D. Koutsoyiannis, 2001.
  32. D. Koutsoyiannis, N. Mamassis, D. Zarris, J. Gavriilidis, T. Papathanasiadis, and I. Nalbantis, Flow measurements and estimation of losses from DXX irrigation canal of Lower Acheloos, Estimation of losses from DXX canal in the irrigation network of Lower Acheloos, Commissioner: Division of Land Reclamation Works – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractor: NAMA, 20 pages, Division of Land Reclamation Works – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, 1999.
  33. D. Koutsoyiannis, Flood studies (Ch. 1-4 and App. 1), Study of the water supply of the wider Rhodes from Gadouras dam: Aqueduct and water treatment plant, Commissioner: Ministry of Environment, Planning and Public Works, Contractors: Grafeio Mahera, G. Kafetzopoulos - D. Benakis - I. Printatko, Ydroexigiantiki, P. Kerhoulas, 62 pages, 1998.
  34. D. Koutsoyiannis, Simulation of the operation of Gadouras reservoir, Ch. 4 of the Hydrological Study of Water Balance, Study of the water supply of the wider Rhodes from Gadouras dam: Aqueduct and water treatment plant, Commissioner: Ministry of Environment, Planning and Public Works, Contractors: Grafeio Mahera, G. Kafetzopoulos - D. Benakis - I. Printatko, Ydroexigiantiki, P. Kerhoulas, 18 pages, 1998.
  35. D. Koutsoyiannis, and L. Lazaridis, Flood study, Engineering report of the Korinthos sewer system, Study of the Xerias creek, Introductory part, Commissioner: Ministry of Environment, Planning and Public Works, Contractor: Ydroexigiantiki, 122 pages, 1998.
  36. I. Nalbantis, N. Mamassis, and D. Koutsoyiannis, Hydrological investigations of the Santorine watersheds, Concerted actions for the sector of environment in Santorine and Therasia islands, Commissioner: Cohesion Fund EU, Contractors: NAMA, SPEED, VLAR, 1998.
  37. I. Nalbantis, N. Mamassis, and D. Koutsoyiannis, Hydrological investigation - Part B: Investigation of flow duration characteristics, Engineering study of the hydraulic project of old and new river bed of Peneios in Larisa, Commissioner: Ministry of Environment, Planning and Public Works, Contractors: Th. Gofas and Partners, Petra Synergatiki, D. Koutsoudakis, Helliniki Meletitiki, G. Kafetzopoulos - D. Benakis - I. Printatko, 100 pages, 1997.
  38. I. Nalbantis, N. Mamassis, and D. Koutsoyiannis, Hydrological investigation - Part A, Engineering study of the hydraulic project of old and new river bed of Peneios in Larisa, Commissioner: Ministry of Environment, Planning and Public Works, Contractors: Th. Gofas and Partners, Petra Synergatiki, D. Koutsoudakis, Helliniki Meletitiki, G. Kafetzopoulos - D. Benakis - I. Printatko, 148 pages, 1997.
  39. P. Panagopoulos, A. Dakanalis, K. Triantafillou, D. Mertziotis, I. Nalbantis, N. Mamassis, G. Tsakalias, and D. Koutsoyiannis, Final Report, Water resources management of the Evinos river basin and hydrogeological study of the Evinos karstic system, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: P. Panagopoulos, General Studies, Istria, Ecosystems Analysis, 1996.
  40. A. Kotronarou, S. Kaimaki, G. Baloutsos, and D. Koutsoyiannis, Technical report, Assessment of the influence of forest fire of 1995 in the increase of sediment yield of the Megalo Rema in Raphena, Commissioner: Prefectural Government of Eastern Attica, Contractors: , November 1996.
  41. D. Koutsoyiannis, Study of the operation of reservoirs , General outline of the Acheloos River diversion project, Contractor: Directorate for Acheloos Diversion Works – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Collaborators: G. Kalaouzis, ELECTROWATT, P. Marinos, D. Koutsoyiannis, 420 pages, 1996.
  42. D. Koutsoyiannis, Hydrological investigation, General outline of the Acheloos River diversion project, Contractor: Directorate for Acheloos Diversion Works – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Collaborators: G. Kalaouzis, ELECTROWATT, P. Marinos, D. Koutsoyiannis, 44 pages, 1996.
  43. I. Nalbantis, N. Mamassis, and D. Koutsoyiannis, Hydrological study, Water resources management of the Evinos river basin and hydrogeological study of the Evinos karstic system, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: P. Panagopoulos, General Studies, Istria, Ecosystems Analysis, Report number II, Athens, 1996.
  44. D. Koutsoyiannis, N. Mamassis, and I. Nalbantis, Appraisal of the surface water potential and its exploitation in the Acheloos river basin and in Thessaly, Ch. 5 of Study of Hydrosystems, Integrated study of the environmental impacts from Acheloos diversion, Contractor: Directorate for Acheloos Diversion Works – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Collaborators: Ydroexigiantiki, 150 pages, 1995.
  45. D. Koutsoyiannis, I. Nalbantis, and N. Mamassis, Hydrological investigation - Annex, Engineering study for improving the water supply of Athens with the construction of a dam at the Evinos River, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: OTME, Ydroilektriki, YDROTEK, D. Constantinidis, G. Karavokiris, Th. Gofas and Partners, 82 pages, 1991.
  46. D. Koutsoyiannis, I. Nalbantis, and N. Mamassis, Hydrological investigation - Appendices E-F, Engineering study for improving the water supply of Athens with the construction of a dam at the Evinos River, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: OTME, Ydroilektriki, YDROTEK, D. Constantinidis, G. Karavokiris, Th. Gofas and Partners, 204 pages, 1991.
  47. D. Koutsoyiannis, I. Nalbantis, and N. Mamassis, Hydrological investigation - Appendices A-D, Engineering study for improving the water supply of Athens with the construction of a dam at the Evinos River, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: OTME, Ydroilektriki, YDROTEK, D. Constantinidis, G. Karavokiris, Th. Gofas and Partners, 233 pages, 1991.
  48. D. Koutsoyiannis, I. Nalbantis, and N. Mamassis, Hydrological investigation - Report, Engineering study for improving the water supply of Athens with the construction of a dam at the Evinos River, Commissioner: Directorate of Water Supply and Sewage – General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: OTME, Ydroilektriki, YDROTEK, D. Constantinidis, G. Karavokiris, Th. Gofas and Partners, 192 pages, 1991.
  49. D. Constantinidis, and D. Koutsoyiannis, Hydrological study, Master plan of the land reclamation works of the Arta plain, Commissioner: Ministry of Agriculture, Contractors: Ydrodomiki, D. Constantinidis, Ydroexigiantiki, Abramopoulos, Report number II, 86 pages, 1990.
  50. D. Koutsoyiannis, and R. Matisen, Hydrological study, Ch. 9 of the Engineering Report, Engineering study of the regulation of the Kallithea Stream in Mytilene, Commissioner: Ministry of National Education, Contractor: TENET, 19 pages, November 1988.
  51. D. Constantinidis, and D. Koutsoyiannis, Hydrological study, Study of the Faneromeni dam in Mesara, Crete - Engineering report, Commissioner: Ministry of Agriculture, Contractors: D. Constantinidis, Grafeio Doxiadi, Report number 3, 100 pages, November 1988.
  52. D. Constantinidis, and D. Koutsoyiannis, Hydrological study - Tables, Study of the Plakiotissa dam in Mesara, Crete - Engineering report, Commissioner: Ministry of Agriculture, Contractors: D. Constantinidis, Grafeio Doxiadi, Report number 4, 200 pages, May 1986.
  53. D. Constantinidis, and D. Koutsoyiannis, Hydrological study, Study of the Plakiotissa dam in Mesara, Crete - Engineering report, Commissioner: Ministry of Agriculture, Contractors: D. Constantinidis, Grafeio Doxiadi, Report number 3, 119 pages, May 1986.
  54. D. Constantinidis, and D. Koutsoyiannis, Hydrological study - Tables, Engineering study of the flood protection works in the Boeoticos Kephisos river basin, Commissioner: Ministry of Public Works, Contractor: D. Constantinidis, 216 pages, November 1985.
  55. D. Constantinidis, and D. Koutsoyiannis, Hydrological study - Report, Engineering study of the flood protection works in the Boeoticos Kephisos river basin, Commissioner: Ministry of Public Works, Contractor: D. Constantinidis, Report number 12, 81 pages, November 1985.
  56. D. Koutsoyiannis, Heliolousto Dam, Updated hydrological study III, Engineering study of the flood protection and drainage works and the dam in the Artzan-Amatovo region, Commissioner: Ministry of Public Works, Contractors: OTME, D. Constantinidis, METER, Report number 11, 180 pages, April 1985.
  57. R. Ruoss, and D. Koutsoyiannis, Hydraulic analyses, Appendix C in Appendices to Engineering Studies I, Arachthos River, Steno - Kalaritikos hydroelectric project, Engineering Report, Commissioner: Public Power Corporation, Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG), Report number 4, 140 pages, Athens, August 1984.
  58. R. Ruoss, and D. Koutsoyiannis, Hydrology, Ch. 4 in Engineering Studies I, Arachthos River, Steno - Kalaritikos hydroelectric project, Engineering Report, Commissioner: Public Power Corporation, Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG), Report number 2, 17 pages, Athens, August 1984.
  59. D. Koutsoyiannis, and P. van der Riet, Hydrology, Ch. 5, Arachthos River, Aghios Nicolaos hydroelectric project, Engineering Report, Commissioner: Public Power Corporation, Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG), Report number 2, 38 pages, Athens, August 1984.
  60. E. Vassilopoulos, E. Karalis, and D. Koutsoyiannis, Technical report, Preliminary study of the water supply of Karystos and Kallianos municipalities from the Demosari springs, Commissioner: Prefectural Fund of Euboea, Contractor: E. Vassilopoulos, Report number 1, 82 pages, April 1983.
  61. E. Vassilopoulos, and D. Koutsoyiannis, Hydraulic analyses, Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Engineering report, Commissioner: Prefectural Fund of Peiraias, Contractor: E. Vassilopoulos, Report number 7, 24 pages, May 1983.
  62. E. Vassilopoulos, D. Koutsoyiannis, and E. Liosis, Economical analyses, Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Engineering report, Commissioner: Prefectural Fund of Peiraias, Contractor: E. Vassilopoulos, Report number 5-6, 74 pages, May 1983.
  63. E. Vassilopoulos, and D. Koutsoyiannis, Technical specifications, Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Engineering report, Commissioner: Prefectural Fund of Peiraias, Contractor: E. Vassilopoulos, Report number 4, 66 pages, May 1983.
  64. E. Vassilopoulos, and D. Koutsoyiannis, Technical report, Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Engineering report, Commissioner: Prefectural Fund of Peiraias, Contractor: E. Vassilopoulos, Report number 2, 30 pages, May 1983.
  65. D. Koutsoyiannis, Summary report, Study of the sewer system of Neapolis, Lasithi, Engineering report, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 12, 7 pages, January 1983.
  66. D. Koutsoyiannis, and E. Karakosti, General and special indenture, Study of the sewer system of Neapolis, Lasithi, Engineering report, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 10, 24 pages, January 1983.
  67. D. Koutsoyiannis, and M. Goudelis, Cost analyses, Study of the sewer system of Neapolis, Lasithi, Engineering report, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 6, 59 pages, January 1983.
  68. D. Koutsoyiannis, Estimation of quantities , Study of the sewer system of Neapolis, Lasithi, Engineering report, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 5, 148 pages, January 1983.
  69. D. Koutsoyiannis, and E. Karakosti, Structural analyses of sewer works, Study of the sewer system of Neapolis, Lasithi, Engineering report, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 3, 62 pages, January 1983.
  70. D. Koutsoyiannis, Technical report, Study of the sewer system of Neapolis, Lasithi, Engineering report, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, January 1983.
  71. D. Koutsoyiannis, Hydrology report and study of erosion and flood protection, Study for the restoration, fixing, protection and prominence of the archaeological monument of Knossos , Commissioner: Ministry of Culture and Sciences, Contractor: I. Skandalis, Collaborators: P. Melissaris, D. Koutsoyiannis, Report number 5, 53 pages, November 1983.
  72. D. Koutsoyiannis, Study of hydrology, Engineering study of sewer system and the wastewater treatment plant of Farsala, Commissioner: Ministry of Public Works, Contractor: METER, 24 pages, June 1983.
  73. D. Constantinidis, and D. Koutsoyiannis, Hydrological study - Tables, Master plan of Dereio dam, Commissioner: Ministry of Public Works, Contractors: Grafeio Doxiadi, D. Constantinidis, Report number 3, 218 pages, August 1983.
  74. D. Constantinidis, and D. Koutsoyiannis, Hydrological study - Report and diagrams, Master plan of Dereio dam, Commissioner: Ministry of Public Works, Contractors: Grafeio Doxiadi, D. Constantinidis, Report number 2, 129 pages, August 1983.
  75. D. Koutsoyiannis, and P. van der Riet, Hydrology, Ch. 5 in Engineering Studies, Arachthos River, Middle Course hydroelectric projects, Master Plan, Commissioner: Public Power Corporation, Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG), Report number 2, 38 pages, Athens, October 1983.
  76. E. Vassilopoulos, and D. Koutsoyiannis, Economical data, Master plan of the foul sewer system of Kanallaki, Preveza, Commissioner: Prefectural Fund of Preveza, Contractor: E. Vassilopoulos, Report number 3, 5 pages, December 1982.
  77. E. Vassilopoulos, and D. Koutsoyiannis, Hydraulic analyses, Master plan of the foul sewer system of Kanallaki, Preveza, Commissioner: Prefectural Fund of Preveza, Contractor: E. Vassilopoulos, Report number 2, 13 pages, December 1982.
  78. D. Koutsoyiannis, Technical report, Alternative studies for the irrigation of the Lasithi plateau, Commissioner: Prefectural Fund of Lasithi, Contractors: METER, Exarxou and Nikolopoulos, Kalatzopoulos, 90 pages, Athens, October 1982.
  79. D. Koutsoyiannis, Summary report, Alternative studies for the irrigation of the Lasithi plateau, Commissioner: Prefectural Fund of Lasithi, Contractors: METER, Exarxou and Nikolopoulos, Kalatzopoulos, 27 pages, October 1982.
  80. P. van der Riet, and D. Koutsoyiannis, Chapter 6: Hydrology, in Report of alternative studies, Arachthos River, Middle Course hydroelectric projects, Alternative studies, Commissioner: Public Power Corporation, Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG), 11 pages, Athens, March 1982.
  81. D. Koutsoyiannis, Study of surface hydrology, Alternative studies for the irrigation of the Lasithi plateau, Commissioner: Prefectural Fund of Lasithi, Contractors: METER, Exarxou and Nikolopoulos, Kalatzopoulos, Report number 1, 59 pages, October 1982.
  82. D. Koutsoyiannis, E. Vassilopoulos, and E. Karalis, Hydrological study - Tables and diagrams, Engineering study of the flood protection and drainage works and the dam in the Artzan-Amatovo region, Commissioner: Ministry of Public Works, Contractors: OTME, D. Constantinidis, METER, Report number 2, 154 pages, March 1982.
  83. D. Koutsoyiannis, E. Vassilopoulos, and E. Karalis, Hydrological study - Report , Engineering study of the flood protection and drainage works and the dam in the Artzan-Amatovo region, Commissioner: Ministry of Public Works, Contractors: OTME, D. Constantinidis, METER, Report number 1, 70 pages, March 1982.
  84. E. Vassilopoulos, and D. Koutsoyiannis, Technical report, Preliminary study of the sewer system of Kanallaki, Preveza, Commissioner: Prefectural Fund of Preveza, Contractor: E. Vassilopoulos, 55 pages, October 1981.
  85. E. Vassilopoulos, and D. Koutsoyiannis, Report on foul sewer system, Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Preliminary study, Commissioner: Prefectural Fund of Peiraias, Contractor: E. Vassilopoulos, Report number 1, 43 pages, December 1981.
  86. D. Koutsoyiannis, and E. Karakosti, Wastewater treatment plant - Contract data, Study of the sewer system of Neapolis, Lasithi, Master plan, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 7, 54 pages, July 1981.
  87. D. Koutsoyiannis, Foul and storm sewer networks - Technical report, Study of the sewer system of Neapolis, Lasithi, Master plan, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 1, 49 pages, July 1981.
  88. D. Koutsoyiannis, Foul and storm sewer networks - Economical data, Study of the sewer system of Neapolis, Lasithi, Master plan, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 2, 13 pages, July 1981.
  89. D. Koutsoyiannis, Hydrological study, Study of the sewer system of Neapolis, Lasithi, Master plan, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, Report number 4, 20 pages, July 1981.
  90. D. Koutsoyiannis, Technical report, Study of the sewer system of Neapolis, Lasithi, Alternative studies, Commissioner: Prefectural Fund of Lasithi, Contractor: G. Koukourakis and Colleagues, April 1980.
  91. D. Koutsoyiannis, and A. Psilopoulos, Hydraulic analyses, Engineering study of the sewer system of the Karpenesi municipality, Commissioner: Prefectural Fund of Evritania, Contractor: A. Psilopoulos, 1979.
  92. A. Psilopoulos, and D. Koutsoyiannis, Hydraulic analyses, Engineering study of the sewer system of the Karpenesi municipality, Commissioner: Prefectural Fund of Eleia, Contractor: A. Psilopoulos, 1978.

Details on research projects

Participation as Project Director

  1. Upgrade of the hydraulics laboratory for the modeling of water supply networks & design and operation optimization study

    Duration: September 2012–August 2015

    Budget: €34 422

    Commissioned by: Research Promotion Foundation of Cyprys

    Contractors:

    1. Cyprus University of Technology
    2. Water Development Department of Cyprus
    3. Department of Water Resources and Environmental Engineering
    4. ISOTHERM Ltd.
    5. Paphos Municipality

    Project director: D. Koutsoyiannis

    Principal investigator: P. Papanicolaou

    The main components of the project are: (a) Upgrading of the existing technological equipment of the Cyprus University of Technology, for supporting the research needs; (b) Development of a digital imprint of a selected water supply network (Paphos Municipality), with combined use of state-of-the-art technologies, such as GPS, GIS and SRS; (c) Development of a generalized modelling framework and related computational/mathematical tools (in terms of hydraulic simulation models and multiobjective evolutionary algorithms), which will be tested in the optimization of the design and operation of the pilot water supply network; (d) Development of an experimental representation aimed at improving the design and operation of the network and its systems, (e) Experimental verification of the computational results and development of know-how in matters relating to systems of supervision and self-regulation of pumps and valves. NTUA mainly contributes in water supply network modelling issues, focusing on the development of the optimization framework and their integration within a computational system. Moreover, NTUA provides support in the formulation of the specifications for the upgrading of the laboratory equipment and the implementation of the experiments.

  1. Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO)

    Duration: February 2014–July 2015

    Budget: €315 000

    Commissioned by: General Secretariat of Research and Technology

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: N. Mamassis

    Programme: Αριστεία ΙΙ

    The project's objective is to develop a holistic framework for optimal planning and management of large-scale hybrid renewable energy systems, in which hydropower plays the dominant role. The scale refers to both the size of energy units and their spatial extent, and is of major importance, as efficiency increases with scale, while uncertainty decreases. Outcomes of the research include a coherent stochastic-entropic theory for uncertainty assessment of the processes that are related to energy production (wind velocity, solar radiation, streamflow), and a parameterization-simulation-optimization scheme inspired from established system-based approaches for supporting optimal decision-making in complex water management problems. The whole framework is integrated within a decision support system (DSS), in which several software tools are integrated . The methodology and the DSS are tested at a large region that covers 12% of Greece, characterized by substantial hydropower potential. The study area is viewed as a closed and energy-autonomous system, in order to investigate the perspectives of sustainable development at a regional scale, using exclusively renewable energy sources. Following the principle of openness, we provide free accessibility to data, methods and tools, through a broad range of dissemination activities.

  1. DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools

    Duration: March 2011–March 2014

    Budget: €145 000

    Commissioned by: General Secretariat of Research and Technology

    Contractors:

    1. ETME: Peppas & Collaborators
    2. Grafeio Mahera
    3. Department of Water Resources and Environmental Engineering
    4. National Observatory of Athens

    Project director: D. Koutsoyiannis

    Principal investigator: N. Mamassis

    Programme: ΕΣΠΑ "Συνεργασία"

    The project aims to develop a set of physically-based methodologies associated with modelling and forecasting of extreme rainfall events and the subsequent flood events, and adapted to the peculiarities of the hydroclimatic and geomorphological conditions of Greece. It includes the implementation of a set of research river basins that comprises a number of gauged basins in Greece and Cyprus with reliable measurements of adequate length, as well as three new experimental basins (with their sub-basins), which will be equipped with the necessary infrastructure. From the field data analysis (hydrological, meteorological, geographical) physically-established regional models will be devoloped for the estimation of characteristic hydrological design quantities, along with hydrological-hydraulic models, which will be integrated within an operational system for hydrometeorological forecasting. A framework of design criteria and methodologies (in a draft form for discussion) will be prepared for the elaboration of hydrological studies for flood-prevention works.

    Project web-page: http://deucalionproject.gr/

  1. Integrated study for the investigation of the quantity, quality and recovery of the underwater springs of the Stoupa region in Municipality of Lefktros, Messinia

    Duration: January 2009–December 2010

    Budget: €220 000

    Commissioned by:

    1. Municipality of Lefktros
    2. Prefectural Government of Messinia

    Contractors:

    1. Hellenic Centre for Marine Research
    2. Agricultural University of Athens
    3. National Technical University of Athens

    Project director: D. Koutsoyiannis

    Principal investigator: P. Papanicolaou

    The main objective of the project is to investigate the possibility of exploitation of the underwater springs of Stoupa, in the Municipality of Lefktra. The contribution of NTUA is the evaluation of the possible freshwater capture works from the underwater spring. The project comprises two stages: (a) the investigation of the problem and the development of a methodology for the capture, transport and temporary storage of the freshwater, which includes field work in a pilot study, and the construction and testing of the temporary pilot facility, and (b) the outline of the works required for the transport and storage of potable water.

  1. Flood risk estimation and forecast using hydrological models and probabilistic methods

    Duration: February 2007–August 2008

    Budget: €15 000

    Commissioned by: National Technical University of Athens

    Contractor: Department of Water Resources and Environmental Engineering

    Collaborators: Hydrologic Research Center

    Project director: D. Koutsoyiannis

    Principal investigator: S.M. Papalexiou

    Programme: Πρόγραμμα Βασικής Έρευνας ΕΜΠ "Κωνσταντίνος Καραθεοδωρή"

    The objective of this project is the development of an integrated framework for the estimation and forecast of flood risk using stochastic, hydrological and hydraulics methods. The study area is the Boeticos Kephisos river basin. The project includes analysis of severe storm episodes in the basin, the understanding of mechanisms of flood generation in this karstic basin and the estimation of flood risk in characteristic sites of the hydrosystem.

  1. Nonlinear methods in multicriteria water resource optimization problems

    Duration: November 2002–December 2007

    Budget: €33 274

    Commissioned by: Ministry of National Education

    Contractor: National Technical University of Athens

    Project director: D. Koutsoyiannis

    Principal investigator: A. Efstratiadis

    Programme: Ηράκλειτος

  1. Support on the compilation of the national programme for water resources management and preservation

    Duration: February 2007–May 2007

    Budget: €45 000

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: A. Andreadakis

    This project updates and expands a previous research project (Classification of quantitative and qualitative parameters of water resources in water districts of Greece), which has been commissioned by the Ministry of Development and conducted by the same team of NTUA in co-operation with the Ministry of Development, IGME, and KEPE.

    The project includes defining the methodology, analyzing the water resources in the 14 water districts, quantity and quality and the relations between them, describing the existing administrative and development frameworks for water resources management and protection presenting the national, peripheral and sectoral water-related policies, and proposing an approach to a water resource management and protection programme (conclusions, problems, solutions, and proposals for projects and measures).

  1. Investigation of management scenarios for the Smokovo reservoir

    Duration: November 2005–December 2006

    Budget: €60 000

    Commissioned by: Special Directorate for the Management of Corporate Programs of Thessaly

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: N. Mamassis

    Programme: Επιχειρησιακά Σχέδια Διαχείρισης Δικτύων Σμοκόβου

  1. Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)

    Duration: July 2003–June 2006

    Budget: €779 656

    Commissioned by: General Secretariat of Research and Technology

    Contractor: NAMA

    Collaborators:

    1. Department of Water Resources, Hydraulic and Maritime Engineering
    2. Municipal Company of Water Supply and Sewerage of Karditsa
    3. Aeiforiki Dodekanisou
    4. Marathon Data Systems

    Project director: D. Koutsoyiannis

    Principal investigator: A. Andreadakis

    Programme: ΕΠΑΝ, Φυσικό Περιβάλλον και Βιώσιμη Ανάπτυξη

    The project aims at providing support to decision-making processes within the direction of integrated management of water resource systems at a variety of scales. Several methodologies and computing tools are developed, which are incorporated into an integrated information system. The main deliverable is an operational software package of general use, which is evaluated and tested on two pilot case studies, concerning hydrosystems in Greece with varying characteristics (Karditsa, Dodecanesus). The end-product of the project is a software system for simulation and optimisation of hydrosystem operation, as well as a series of separate software applications for solving specific problems, aiming at producing input data to the central system or post-processing of the results. The project includes eleven work packages, eight for basic research, two for industrial research and one for the pilot applications.

  1. Testing of the new measuring system of the aqueduct of Mornos

    Duration: January 2001–December 2003

    Commissioned by: Water Supply and Sewerage Company of Athens

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: J. Gavriilidis

    In an earlier research project, the development of an automatic measuring system of water level meters and flow meters was proposed for the aqueduct network of the water supply of Athens. After the realisation of the measuring system, its devices should be checked for proper operation. The current project aims at scheduling and implementing a flow measurement programme at the sites where discharge meters are installed by the Water Supply and Sewerage Company of Athens (EYDAP) in the Mornos aqueduct, in order to check their accuracy based on the methodology proposed in the earlier project. Specifically, measurements are done using flow meter according to the ISO standard ISO 748 (1979, 1997; Measurement of liquid flow in open channels - Velocity-area methods). At each site 5 flow measurements (one daily measurement per month on the average) for different values of the discharge are done in steady state flow conditions. The measurements are processed appropriately, whereas for any problems of instrument inaccuracies that emerge, the appropriate solutions are studied and suggested.
  1. Modernisation of the supervision and management of the water resource system of Athens

    Duration: March 1999–December 2003

    Commissioned by: Water Supply and Sewerage Company of Athens

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: D. Koutsoyiannis

    Due to the dry climate of the surrounding region, Athens has suffered from frequent water shortages during its long history but now has acquired a reliable system for water supply. This extensive and complex water resource system extends over an area of around 4000 km2 and includes surface water and groundwater resources. It incorporates four reservoirs, 350 km of main aqueducts, 15 pumping stations and more than 100 boreholes. The water resource system also supplies secondary uses such as irrigation and water supply of nearby towns. The Athens Water Supply and Sewerage Company (EYDAP) that runs the system commissioned this project, which comprises: (a) development of a geographical information system for the representation and supervision of the external water supply system; (b) development of a measurement system for the water resources of Athens; (c) development of a system for the estimation and prediction of the water resource system of Athens utilising stochastic models; (d) development of a decision support system for the integrated management of water resource system of Athens using simulation-optimisation methodologies; and (e) cooperation and transfer of knowledge between NTUA and EYDAP.

    Products: 17 reports; 14 publications

  1. Completion of the classification of quantitative and qualitative parameters of water resources in water districts of Greece

    Duration: November 2001–April 2003

    Commissioned by: Directorate of Water and Natural Resources

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators: Directorate of Water and Natural Resources

    Project director: D. Koutsoyiannis

    Principal investigator: D. Mamais

    The project continues an earlier study elaborated by the Ministry of Development, the Department of Water Resources of the National Technical University of Athens, the Institute of Geology & Mineral Exploration, and the Centre of Planning and Research.The project objective is the classification of the existing information related to water quantity and quality in characteristic areas (water districts) of Greece, using geographical information systems. The specific objective of this phase is the analysis of water supply and demand balance, and the qualitative characterisation of water resources in four water districts of Greece.

  1. Appraisal of river sediment deposits in reservoirs of hydropower dams

    Duration: February 1998–October 2001

    Commissioned by:

    1. General Secretariat of Research and Technology
    2. Public Power Corporation

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: D. Koutsoyiannis

    The objective of this research project is the estimation of the sediment deposits in reservoirs of hydropower dams. Specifically, an estimation of the volume of deposits in one of the reservoirs of the Public Power Corporation (the Kremasta Reservoir) is done using hydrographic methods. The estimation is used as a basis to calibrate a mathematical model of sediment discharge, which accounts for the processes involved such as soil erosion, sediment transport and deposition.

  1. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3

    Duration: November 1996–December 2000

    Commissioned by: Directorate of Water Supply and Sewage

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: D. Koutsoyiannis

    The main objectives of the research project are the evaluation and management of the water resources, both surface and subsurface, of the Sterea Hellas region, and the systematic study of all parameters related to the rational development and management of the water resources of this region. Another objective of the project, considered as an infrastructure work, is the development of software for the hydrological, hydrogeological and operational simulation of the combined catchments of the study area. The development of the software and, at the same time, the development of methodologies suitable for the Greek conditions will assist in decision-making concerning the water resources management of Sterea Hellas and of other Greek regions. The project also aims at the improving of the cooperation between the National Technical University of Athens and the Ministry of Environment, Planning and Public Works. This is considered as a necessary condition for the continuous updating of the project results as well as for the rational analysis of the water resource problems of the Sterea Hellas region. The specific themes of Phase 3 are: (a) the completion of the information systems of the previous phases, which concerned hydrological and hydrogeological information, by including two additional levels of information related to the water uses and the water resources development works; (b) the development of methodologies for optimising the hydrosystems operation and the construction of integrated simulation and optimisation models for the two major hydrosystems of the study area (Western and Eastern Sterea Hellas); and (c) the integration of all computer systems (databases, geographical information systems, application models) into a unified system with collaborating components.

  1. Systematisation of the raw data archive of surface and subsurface waters of the Ministry of Agriculture in Thessalia

    Duration: February 1997–January 1999

    Commissioned by: Department of Hydrogeology, Boreholes and Mathematical Models

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: I. Nalbantis

    The project aims at the modernisation of the archive of surface and subsurface water related data of the Ministry of Agriculture in the Thessalia region (mainly data on quantities of the drafts from both surface waters and groundwater pumped from public or private boreholes). It also includes the data organisation into a geographical information system and the data evaluation and processing, from which the evapotranspiration of the area is estimated using semi-empirical methods.

  1. Upgrading and updating of hydrological information of Thessalia

    Duration: May 1996–March 1997

    Commissioned by: Directorate for Acheloos Diversion Works

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: I. Nalbantis

    The project includes the updating of existing archives of hydrometeorological data with the new measurements, and the upgrading of the databases using the new computational environment of the Hydroscope project. It also includes data processing and analysis in order to obtain a reliable and consistent hydrometeorological data set. The databases are linked to a geographical information system that is used for the processing and the visualisation of information. Based on this processing, the basic parameters of the water potential of the area are estimated and their geographical distribution is studied with emphasis on the recent persistent drought.

  1. Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems

    Duration: February 1996–September 1996

    Commissioned by: Directorate of Water and Natural Resources

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

    1. Directorate of Water and Natural Resources
    2. Institute of Geological and Mining Research
    3. Centre for Research and Planning

    Project director: D. Koutsoyiannis

    Principal investigator: A. Andreadakis

    The project part related to water quantity aims at the development of a methodology for establishing a water balance between supply and demand and extracting the most important summary characteristics that are then entered into a geographical information system. The methodology is applied to characteristic areas (water districts) of Greece with adequacy of information (based on existing studies). The project part related to water quality aims at the characterisation of the rivers, lakes and aquifers based on the water quality characteristics, and the water uses and requirements. The characterisation is based on the classification of critical quantity parameters that have been measured and includes the use of a geographical information system.

  1. Hydroscope II - Creation of a National Databank for Hydrological and Meteorological Information

    Duration: April 1993–September 1995

    Commissioned by:

    1. Ministry of Agriculture
    2. Ministry of the Industry
    3. Ministry of Environment, Planning and Public Works
    4. Water Supply and Sewerage Company of Athens
    5. Public Power Corporation

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: D. Koutsoyiannis

    This project is complementary to the major Hydroscope project. Its objectives are the purchase of computational infrastructure and the pilot data entry into the databank that is developed in the framework of the major project. The data entered provides a means for testing of the operation of the distributed database and the wide area network, and the operational use of the related infrastructure.

  1. Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information

    Duration: January 1992–December 1993

    Budget: 394 238 400 DRS (about €1 600 000)

    Commissioned by:

    1. General Secretariat of Research and Technology
    2. Ministry of the Industry
    3. Hellenic National Meteorological Service
    4. Ministry of Agriculture
    5. Ministry of Environment, Planning and Public Works
    6. National Observatory of Athens
    7. Water Supply and Sewerage Company of Athens
    8. National Centre for Scientific Research "Democritos"
    9. Ministry of National Education

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

    1. Division of Hydraulics and Environmental Engineering
    2. Division of Applications Physics
    3. Energy Division
    4. Hellenic National Meteorological Service
    5. Department for the Development of Hydroelectric Works
    6. Directorate of Water and Natural Resources
    7. General Secretariat of Land Reclamation Works and Agricultural Structures
    8. General Secretariat of Public Works
    9. Institute of Meteorology and Physics of the Atmospheric Environment
    10. Centre for Renewable Energy Sources
    11. Water Supply and Sewerage Company of Athens
    12. National Centre for Scientific Research "Democritos"
    13. Greek Corporation of Regional Governent and Development

    Project director: D. Koutsoyiannis

    Principal investigators: M. Aftias, D. Koutsoyiannis

    Programme: STRIDE

    The main objective of HYDROSCOPE is the creation of a modern information infrastructure for the hydrological cycle in Greece. Specifically, it aims at organising and systematising the hydrological, hydrogeological and meteorological information using the capacities that are provided by the modern methods and techniques of computer science and telecommunications. The database, which will be built, will contribute to the reliable programming, planning and management of the water resources of the country, the mitigation of phenomena like flood and drought, the evaluation of hydroclimatic parameters and their effects to the natural and biological environment, the diagnosis of climatic changes as well as the prediction and the control of the air pollution and the groundwater and surface water pollution. The development of a unified synergistic network, the information exchange and the co-ordination of the activities of the participating organisations, which are involved with the components of the hydrological cycle (Universities, Research Centres, Ministries and Services) as well as the reorganisation and standardisation of the hydrometeorological networks' function are considered as indirect but essential benefits. The programme includes: (a) hardware equipment, to install a network with 13 major nodes (RISC Workstations with Unix operation system) in Athens and Thessaloniki, local networks of PCs in each node, private high speed wide area network using routers and leased telephone lines, (b) infrastructure software, and specifically, distributed relational data base and graphic environment for applications' development, and (c) application software, and specifically, a distributed database system and applications concerning the input, the supervision and the processing of data in a graphic environment. This distributed database system provides firstly, the autonomy of each participant in managing data and secondly, a transparent, relatively to the data position, access. In addition, the project includes the locating of the available hydrological, hydrogeological and meteorological data that is maintained by the participants and the determination of the volume, the form and the reliability of measurements. Finally, a significant part of HYDROSCOPE deals with the development and the standardisation of methodologies regarding the processing as well as the pilot data entry of a part of the hydrological, hydrogeological and meteorological information aiming at the testing of the methodologies and systems.

Participation as Principal Investigator

  1. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system

    Duration: October 2008–November 2011

    Budget: €72 000

    Project director: N. Mamassis

    Principal investigator: D. Koutsoyiannis

    This research project includes the maintenance, upgrading and extension of the Decision Support System that developed by NTUA for EYDAP in the framework of the research project “Updating of the supervision and management of the water resources’ system for the water supply of the Athens’ metropolitan area”. The project is consisted of the following parts: (a) Upgrading of the Data Base, (b)Upgrading and extension of hydrometeorological network, (c) upgrading of the hydrometeorological data process software, (d) upgrading and extension of the Hydronomeas software, (e) hydrological data analysis and (f) support to the preparation of the annual master plans

  1. Building the Future of Transnational Cooperation in Water Resources in South East Europe (EDUCATE!)

    Duration: May 2006–August 2008

    Budget: €200 000

    Commissioned by: European Union

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

    1. School of Chemical Engineering
    2. University of Ljubljana
    3. Technical University of Bucharest
    4. University of Belgrade
    5. IRTCUD

    Project director: A. Katsiri

    Principal investigator: D. Koutsoyiannis

    Programme: Interreg IIIB CADSES (Neighborhood Programme)

    Educate! assists in shaping current and future policy and practice in Water Resources Management in SE Europe, through professional capacity building and provision of a common understanding of IWRM for young graduates within a cooperative, transnational environment. Specifically, Educate! is: 1. Setting up and operate a network of Higher Education Organisations in SE Europe with an expertise in Environmental Protection and Water Resources Management; 2. Developping a transnational postgraduate course on Integrated Water Resources Management; 3. Developping a flexible structure for delivering the course across geographic areas and across different audiences (from students to professionals) through e-learning and a modular format and 4. Running a pilot transnational postgraduate course and professional educational and training courses for governmental officials and industry.

  1. Investigation of scenarios for the management and protection of the quality of the Plastiras Lake

    Duration: May 2001–January 2002

    Commissioned by:

    1. Prefectural Government of Karditsa
    2. Municipality of Karditsa

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: K. Hadjibiros

    Principal investigator: D. Koutsoyiannis

    To protect the Plastiras Lake, a high quality of the natural landscape and a satisfactory water quality must be ensured, the conflicting water uses and demands must be arranged and effective water management practices must be established. To this aim, the hydrology of the catchment is investigated, the geographical, meteorological and water power data are collected and processed, the water balance is studied and a stochastic model is constructed to support the study of alternative management scenarios. In addition, an analysis of the natural landscape is performed and the negative influences (e.g. dead tries) are determined and quantified using GIS. Furthermore, the water quality parameters are evaluated, the water quality state is assessed, the quantitative targets are determined, the pollution sources are identified and measures for the reduction of pollution are studied using a hydrodynamic model with emphasis on the nutrient status. Based on the results of these analyses, scenarios of safe water release are suggested.

  1. National databank for hydrological and meteorological information - Hydroscope 2000

    Duration: January 1997–December 2000

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: M. Mimikou

    Principal investigators: D. Koutsoyiannis, M. Mimikou

  1. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2

    Duration: November 1993–October 1995

    Commissioned by: Directorate of Water Supply and Sewage

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigators: D. Koutsoyiannis, P. Marinos

    The main objectives of the research project are the evaluation and management of the water resources, both surface and subsurface, of the Sterea Hellas region, and the systematic study of all parameters related to the rational development and management of the water resources of this region. Another objective of the project, considered as an infrastructure work, is the development of software for the hydrological, hydrogeological and operational simulation of the combined catchments of the study area. The development of the software and, at the same time, the development of methodologies suitable for the Greek conditions will assist in decision-making concerning the water resources management of Sterea Hellas and of other Greek regions. The project also aims at the improving of the cooperation between the National Technical University of Athens and the Ministry of Environment, Planning and Public Works. This is considered as a necessary condition for the continuous updating of the project results as well as for the rational analysis of the water resource problems of the Sterea Hellas region. The specific themes of Phase 2 are: (a) the conversion of the databases of the previous phase into the new computer environment based on Unix and Windows workstations; (b) the conversion of the computer programs for statistical processing of hydrologic data into the new computer environment; (c) the development of software for hydrologic data processing and the processing of the Sterea Hellas data; (d) the development of a geographical information system for hydrological and hydrogeological information; (e) the review of existing studies regarding water uses; (f) the collection, evaluation and organising of hydrogeological data; and (g) the hydrogeological study of selected watersheds.

  1. AFORISM: A comprehensive forecasting system for flood risk mitigation and control

    Duration: June 1991–May 1994

    Budget: 17 300 000 DRS (about €83 900)

    Commissioned by: DGXII / FP6-SUSTDEV-2005-3.II.1.2

    Contractor: University of Bologna

    Collaborators:

    1. National Technical University of Athens
    2. Ente Regionale di Sciluppo Agricolo
    3. University College Cork
    4. University of Newcastle
    5. Ecole Polytechnique Federale de Lausanne
    6. Instituto Superior de Agronomia, Lisbon
    7. Institut National Polytechnique de Grenoble

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    Programme: EPOCH

    The aim of this project is the development of a comprehensive flood forecasting system and the study of alternative management policies intending to flood risk mitigation. The Greek research team contributes to AFORISM in the following tasks: (a) the analysis of intense rainfall events and their classification by weather type as well as the modelling of intense rainfall and the production of alternative hyetographs of temporal evolution of rainfall; (b) the comparison of the alternative rainfall-runoff models, using multiple time steps in modelling rainfall-runoff and applying it to Greek hydrological basins. The contribution of the other research teams deal with: (a) the forecasting of spatial-temporal evolution of rainfall using limited area models; (b) the development of optimisation models in order to mitigate flood risks; (c) the development of an expert system for flood management; (d) the development of a geographical information system for visualisation of the evaluation of flood and its consequences; and (e) the integration of the forecast and control system in the Reno basin (Italy).

  1. Development of a relational data base for management and processing of hydrometric information

    Duration: September 1991–May 1993

    Commissioned by: General Secretariat of Research and Technology

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    Programme: ΠΕΝΕΔ/1989

    This project aims in utilising modern computer techniques, namely relational databases, for the management of hydrological data, and, to some extent, river flow data. It also aims in the development of software for data entry, testing, presentation, and processing of the data. Specifically, it includes: (1) development of specifications, and selection, purchase and installation of a relational database system; (2) database design on conceptual and physical level; (3) development of software for data entry and preliminary testing of data, and for conversion of data already available in other systems; (4) development of software for data processing (e.g. generation of hourly discharge time series from stage recorder tapes and discharge measurements); and (5) development of software for viewing and printing the raw hydrological data and their statistical characteristics, as well as standardisation of the most important database queries (e.g. mean discharge, maximum discharge, discharge correlation between different positions or basins, etc.)

  1. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 1

    Duration: December 1990–November 1992

    Commissioned by: Directorate of Water Supply and Sewage

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    The main objectives of the research project are the evaluation and management of the water resources, both surface and subsurface, of the Sterea Hellas region, and the systematic study of all parameters related to the rational development and management of the water resources of this region. Another objective of the project, considered as an infrastructure work, is the development of software for the hydrological, hydrogeological and operational simulation of the combined catchments of the study area. The development of the software and, at the same time, the development of methodologies suitable for the Greek conditions will assist in decision-making concerning the water resources management of Sterea Hellas and of other Greek regions. The project also aims at the improving of the cooperation between the National Technical University of Athens and the Ministry of Environment, Planning and Public Works. This is considered as a necessary condition for the continuous updating of the project results as well as for the rational analysis of the water resource problems of the Sterea Hellas region. The specific objective of Phase 1 is the collection and the organising of the surface water data and the development of hydrological simulation programs.

  1. A pilot study for the management of the Louros and Arachthos watersheds

    Duration: June 1989–April 1991

    Commissioned by: Directorate of Water and Natural Resources

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

    1. Directorate of Water and Natural Resources
    2. Delft Hydraulics

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    The objective of the pilot study is the combined management of the surface and subsurface water resources of the Louros and Arachthos watersheds. The main target is to obtain an insight of the interrelation of the relevant quantities, to draw conclusions regarding the management of water resources of the two catchments, and to locate the issues that will require further research. An additional objective is the development of a methodology for water resources planning and management, which can be applied to other watersheds or water districts in Greece.

  1. Appraisal of existing potential for improving the water supply of greater Athens - Phase 2

    Duration: May 1989–June 1990

    Commissioned by: Directorate of Water Supply and Sewage

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    The project includes the following main components: (1) Processing and analysis of the available hydrometeorological data and estimation of the water potential of the Mornos, Evinos and Yliki watersheds. (2) Hydrologic design study of alternative reservoirs in the Evinos River basin combined with the operation of the Mornos reservoir. (3) Study for improving of the hydrometeorological measuring system at Mornos and Evinos watersheds. (4) Evaluation of the exploitable water potential of the Yliki Lake and the alternative rational ways of its management, both under the current conditions and future conditions, without or with the Evinos reservoir. (5) Development of methodologies and computer programs for the support of the rational scheduling of the water release from Yliki.

  1. Appraisal of existing potential for improving the water supply of greater Athens - Phase 1

    Duration: November 1987–February 1989

    Commissioned by: Directorate of Water Supply and Sewage

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    This project aims at organising the hydrological information in the Mornos and Evinos watersheds, and more specifically, the collection, the evaluation, the archiving and the processing of hydrometeorological data of these basins. The project also deals with the estimation of the actual release capacity of the Mornos reservoir and the appraisal of the alternatives for improving it by diverting water from the Evinos River.

  1. Hydrological investigation of the Thessalia water basin

    Duration: July 1986–October 1988

    Commissioned by: Division of Acheloos Diversion Works

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigator: D. Koutsoyiannis

    The project aims at organising the hydrological information in the Thessalia water district, and more specifically, the collection, the evaluation, the archiving and the processing of hydrometeorological data of the district. The project also deals with the development of an appropriate hydrological infrastructure (criteria and hydrologic design parameters) to support the studies of the works for the development of the Thessalia Plain (irrigation projects, flood protection works and dams) also considering the planned diversion of the Acheloos River.

Participation as Researcher

  1. Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information"

    Duration: December 2009–May 2011

    Budget: €140 000

    Commissioned by: Hydroscope Systems Consortium

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: N. Mamassis

    Principal investigator: N. Mamassis

    The Ministry of Environment, Physical Planning & Public Works assigned to a consortium of consultancy companies the Project "Development of a new software platform for the management and operation of the National Databank for Hydrologic and Meteorological Information - 3rd Phase within a GIS environment and relevant dissemination actions". In the framework of the specific project a research team of NTUA undertakes a part as subcontractor. NTUA delivers methodologies for further development of the databases and applications of the Databank and their migration into a web platform (including the experimental node openmeteo.org for free data storage for the public). Specifically, using the knowhow that has been developed in the past by Research Teams from the Department of Water Resources of the School of Civil Engineering a database system and software applications (included hydrological models) are created fully adapted for operation over the Internet. NTUA's contribution is primarily on the design of the new system and the hydrological and geographical database the development of distibuted hydological models, the adaptation of the system to the WFD 2000/60/EC and on supporting dissemination activities. Finally NTUA will participate in the technical support and pilot operation of the project after its delivery from the consortium to the Ministry.

    More information is available at http://www.hydroscope.gr/.

  1. Observations, Analysis and Modeling of Lightning Activity in Thunderstorms, for Use in Short Term Forecasting of Flash Floods

    Duration: October 2006–September 2009

    Commissioned by: DGXII / FP6-SUSTDEV-2005-3.II.1.2

    Contractor: National Observatory of Athens

    Project director: K. Lagouvardos

  1. Development of a Geographical Information System and an Internet application for the supervision of Kephisos protected areas

    Duration: April 2008–March 2009

    Budget: €30 000

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: N. Mamassis

    Principal investigator: N. Mamassis

    The main purpose of the system is the supervision of the protected areas in Kephisos river basin. Using the applications that will be developed, the staff of Kephisos Institution will achieve the real time recording of various activities that are built up inside the limits of protection belts. Specifically, three main applications will be developed: (a) A Geographical Information System (GIS) (b) An General Positioning System Application (GPS) (c) An Internet application

  1. EU COST Action C22: Urban Flood Management

    Duration: June 2005–December 2007

    Project director: C. Zevenbergen

    The primary objective is to increase knowledge required for prevention and mitigation of potential flood impacts to urban areas by exchanging experiences, developing integrated approaches, and by promoting the diffusion of best practices in Urban Flood Management. Secondary objectives are to develop holistic approaches in Urban Flood Management, to initiate R&D projects for the EU 7th Framework programme, to stimulate national R&D activities and to increase awareness of the importance of flood management. The action includes three phases: (1) inventory (state-of-the-art relevant aspects of UFM), (2) analysis and integration (best practices and knowledge gaps), and (3) dissimination and consolidation. The action involves four working groups: (1) models and tools to assess flood probability and measures to reduce probability, (2) models and tools to assess impact of flooding to decrease vulnerability, (3) flood recovery methods and methods of damage compensation, and (4) non-technical measures and techniques to decrease vulnerability.

  1. Investigation and remedy of the stability problems of the banks and bed of the Philothei Creek using mathematical models and modern environmental methods

    Duration: March 2004–September 2004

    Budget: €74 500

    Commissioned by: Municipality of Philothei

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: A. Stamou

    The effect of a series of alternative environmental-friendly works in the Philothei Creek, aiming at the ensuring of bed and banks stability, is investigated. The project includes (1) identification of the geometrical characteristics of the creek, (2) assessment of a series of alternative environmental-friendly works at specific sites, (3) examination of these works from the hydraulic point of view (hydrological and hydraulic modelling) and (4) formulation of final scheme of works and estimation of their cost.

  1. Study and research network with applications in Greece and Cyprus

    Duration: November 2000–November 2002

    Commissioned by: General Secretariat of Research and Technology

    Contractor: Aristotle University of Thessaloniki

    Collaborators:

    1. Depatment of Water Development of Cyprus
    2. Demokritos University of Thrace
    3. University of Thessaly
    4. University of Athens
    5. National Technical University of Athens

    Project director: E. Sidiropoulos

    Programme: ΕΠΑΝ

    A Network for the Research of the Water Resources of Greece and Cyprus is created, whose objective is the theoretical and practical study of water resource problems that are met mostly in Cyprus, but also are relevant with Greek areas with similar hydroclimatic conditions.

  1. Generation of spatially consistent rainfall data - Refinement and testing of simplified models

    Duration: January 2001–December 2001

    Commissioned by: UK Ministry of Agriculture, Fisheries and Food

    Contractor: Imperial College, London

    Collaborators: University College London

    Project directors: V. S. Isham, H. S. Wheater

  1. Assessment of sediment generation in Thriasio

    Duration: January 2001–December 2001

    Contractor: School of Civil Engineering

    Project director: P. Marinos

  1. Development of legislation framework for the drinking water of Athens

    Duration: June 1999–May 2000

    Commissioned by: Water Supply and Sewerage Company of Athens

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: M. Bonazountas

  1. Generation of spatially consistent rainfall data

    Duration: January 1999–January 2000

    Commissioned by: UK Ministry of Agriculture, Fisheries and Food

    Contractor: Imperial College, London

    Collaborators: University College London

    Project directors: V. S. Isham, H. S. Wheater

  1. Integrated management of the riparian ecosystem of the Sperhios river

    Duration: January 1995–May 1995

    Commissioned by: European Union

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: M. Bonazountas

    Programme: LIFE

  1. A pilot study for the water resources management of the Epirus water district

    Duration: September 1991–September 1993

    Commissioned by: Directorate of Water and Natural Resources

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

    1. Directorate of Water and Natural Resources
    2. Delft Hydraulics
    3. Ecosystems Analysis

    Project director: Th. Xanthopoulos

    Principal investigator: I. Nalbantis

    The main objective is to obtain an insight of the interrelation of the water balance components of the Epirus water district. The methodology is based on an earlier project regarding the water resources of the Louros and Arachthos watersheds. The role of the research team of the National Technical University of Athens is to supervise the project and evaluate its results at each stage of the project.

  1. Study of the measuring system of the aqueduct network of Athens - Phase 1

    Duration: June 1990–December 1990

    Commissioned by: Water Supply and Sewerage Company of Athens

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: Th. Xanthopoulos

    Principal investigator: J. Gavriilidis

    The objective of Phase 1 of the project is the testing of the reliability of the existing measuring system of the aqueduct network of Athens and the initial approximate estimation of the discharge capacities of the aqueducts.

  1. Investigation of use of stormwater for irrigation - Application to the area of Archanes municipality

    Duration: January 1988–December 1988

    Commissioned by: Municipality of Archanes

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: G. Tsakiris

  1. Environmental impacts of the irrigation project in the lake Mikri Prespa, Florina, Phase A

    Duration: January 1987–December 1987

    Commissioned by: Ministry of the National Economy

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: M. Bonazountas

  1. Estimation and integrated management of the water resources and environment of the Aliakmon watershed

    Duration: January 1982–January 1986

    Commissioned by: General Secretariat of Research and Technology

    Project director: Th. Xanthopoulos

  1. Water quality and assimilative capacity investigations of Kalamas river and lake Pamvotis (Ioannina)

    Duration: February 1984–December 1984

    Commissioned by: Ministry of Planning, Housing and Environment

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators: Laboratory of Analytical Chemistry

    Project director: Th. Xanthopoulos

    The project components are the following: (1) Hydrological and hydraulic characteristics of the Kalamas River and the Lapsista ditch. (2) Water budget of the Pambotis Lake. (3) Sampling and water quality analyses. (4) Inventory of pollution sources. (5) Assessment of the potential of the development of the Ioannina area. (6) Inventory of water uses. (7) Formulation of pollution scenarios. (8) Fitting of a mathematical model for the pollution of the Kalamas River. (9) Conclusions regarding the water uses and the acceptable pollution loads.

Details on engineering studies

  1. Pleriminary study of Almopaios dam

    Duration: July 2014–July 2014

    Commissioned by: Roikos Consulting Engeineers S.A.

  1. Investigation of the hydrographic network development in Mavro Vouno, Grammatiko, Attica, Greece

    Duration: May 2012–June 2012

    Budget: €15 000

    Commissioned by: Perifereiako Tameio Anaptyxis Attikis

    Contractors:

    1. A. Stamou
    2. D. Koutsoyiannis
    3. N. Mamassis

  1. Study of the management of Kephisos

    Duration: June 2009–April 2010

    Commissioned by: General Secretariat of Public Works

    Contractors:

    1. Exarhou Nikolopoulos Bensasson
    2. Denco
    3. G. Karavokiris
    4. et al.

  1. Delineation of the Arachthos River bed in the town of Arta

    Duration: January 2009–February 2010

    Commissioned by: Municipality of Arta

    Contractors:

    1. ADK - Aronis Drettas Karlaftis Consulting Engineers
    2. YDROTEK
    3. V. Mouzos

  1. Specific Technical Study for the Ecological Flow from the Dam of Stratos

    Duration: January 2009–June 2009

    Commissioned by: Public Power Corporation

    Contractor: ECOS Consultants S.A.

  1. Development of tools for the water resource management of the hydrological district of Aegean islands

    Duration: January 2003–December 2008

    Commissioned by: Ministry of Development

    Contractors:

    1. TEM
    2. LDK
    3. Ydroexigiantiki
    4. TERRAMENTOR

  1. Water resource management of the Integrated Tourist Development Area in Messenia

    Duration: January 2003–December 2005

    Commissioned by: TEMES - Tourist Enterprises of Messinia

    Contractor: D. Argyropoulos

  1. Technical consulting for the floods of Lower Acheloos and Edesseos

    Duration: September 2004–June 2005

    Budget: €21 000

    Commissioned by: Public Power Corporation

    Contractors:

    1. D. Koutsoyiannis
    2. N. Mamassis

  1. Expertise for the quality control of engineering studies for the project "Water supply of Patra from Peiros and Parapeiros rivers"

    Duration: October 2004–December 2004

    Budget: €13 800

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractors:

    1. A. Andreadakis
    2. D. Koutsoyiannis
    3. M. Aftias

  1. Characterization of the size of Zaravina lake in Delvinaki area of the prefecture of Ioannina

    Duration: September 2003–December 2004

    Commissioned by: P. Mentzos

    Contractor: D. Koutsoyiannis

  1. Diversion of the Soulou Stream for the Development of Lignite Exploitations of the Public Power Corporation in the Mine of Southern Field of Region Kozani-Ptolemais

    Duration: September 2004–October 2004

    Budget: €3 000

    Commissioned by: Public Power Corporation

    Contractors:

    1. D. Koutsoyiannis
    2. N. Mamassis

  1. Analysis of the effects of the water transfer through the tunnel Fatnicko Polje - Bileca reservoir on the hydrologic regime of Bregava River in Bosnia and Herzegovina

    Duration: April 2004–June 2004

    Commissioned by: Energy Financing Team, Switzerland

    Contractors:

    1. CUW-UK
    2. ICCI Limited

  1. Study of sewerage and wastewater treatment of the Municipality of Ellomeno in Leukas

    Duration: January 2004–February 2004

  1. Hydraulic study for drainage of the Kanavari-Dombrena-Prodromos road

    Duration: January 2004–January 2004

    Commissioned by: Prefectural Government of Boeotia

    Contractor: D. Argyropoulos

  1. Hydrological and hydraulic study for the flood protection of the new railway in the region of Sperhios river

    Duration: October 2002–January 2003

    Budget: €90 000

    Commissioned by: ERGA OSE

    Contractor: D. Soteropoulos

    Collaborators: D. Koutsoyiannis

  1. Study of the enhancement of water flow in Lethaeos and Ayiaminiotis rivers

    Duration: May 2002–December 2002

    Commissioned by: Municipality of Trikala

    Contractor: I. Tzeranis

  1. Engineering consultant for the project "Water supply of Heracleio and Agios Nicolaos from the Aposelemis dam"

    Duration: October 2000–December 2002

    Budget: €1 782 000

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Aposelemis Joint Venture

  1. Flood Protection Works of Diakoniaris Stream, Preliminary Study

    Duration: June 2002–July 2002

    Budget: €5 000

    Commissioned by: Directorate of Water Supply and Sewage

    Contractors:

    1. Ydroexigiantiki
    2. Grafeio Mahera
    3. Ydroereyna

    Collaborators:

    1. P. Marinos
    2. M. Kavvadas
    3. D. Koutsoyiannis

  1. Study of the Segment Antirrio-Kefalovriso of the Western Road Axis

    Duration: January 2001–December 2001

    Commissioned by: General Secretariat of Public Works

    Contractors:

    1. NAMA
    2. Kastor

  1. Preliminary Water Supply Study of the Thermoelectric Livadia Power Plant

    Duration: January 2001–December 2001

    Contractor: Ypologistiki Michaniki

  1. Consultative service for the spring "Kephalovriso" in Kaloskope

    Duration: May 2000–December 2001

    Commissioned by: Association of Kaloskopi Parnassidas

  1. Engineering study for the licence of positioning of the Valorema Small Hydroelectric Project

    Duration: September 2001–September 2001

    Commissioned by: YDROSAR

    Contractor: D. Argyropoulos

  1. Study of the Potamos River, Corfu

    Duration: January 2001–June 2001

    Commissioned by: Anaptyxiaki Demou Kerkyreon

    Contractor: M. Papakosta

  1. Complementary study of environmental impacts from the diversion of Acheloos to Thessaly

    Duration: December 2000–February 2001

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Ydroexigiantiki

    Collaborators: D. Koutsoyiannis

  1. Management study of the river Boeoticos Kephisos and the lakes Hylike and Paralimne

    Duration: January 1998–December 2000

    Commissioned by: Division of Land Reclamation Works

    Contractor: ETME- Antoniou Peppas and Co.

  1. Compilation of specifications and requirements for the elaboration of environmental impact studies for various works

    Duration: November 1999–December 1999

    Contractor: ECOS Meletitiki

  1. Estimation of losses from DXX canal in the irrigation network of Lower Acheloos

    Duration: January 1999–December 1999

    Commissioned by: Division of Land Reclamation Works

    Contractor: NAMA

  1. Concerted actions for the sector of environment in Santorine and Therasia islands

    Duration: November 1998–December 1998

    Commissioned by: Cohesion Fund EU

    Contractors:

    1. NAMA
    2. SPEED
    3. VLAR

  1. Engineering report of the Korinthos sewer system, Study of the Xerias creek, Introductory part

    Duration: January 1998–December 1998

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Ydroexigiantiki

  1. Study of the water supply of the wider Rhodes from Gadouras dam: Aqueduct and water treatment plant

    Duration: January 1998–December 1998

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractors:

    1. Grafeio Mahera
    2. G. Kafetzopoulos - D. Benakis - I. Printatko
    3. Ydroexigiantiki
    4. P. Kerhoulas

  1. Engineering study of the hydraulic project of old and new river bed of Peneios in Larisa

    Duration: January 1997–December 1997

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractors:

    1. Th. Gofas and Partners
    2. Petra Synergatiki
    3. D. Koutsoudakis
    4. Helliniki Meletitiki
    5. G. Kafetzopoulos - D. Benakis - I. Printatko

  1. General outline of the Acheloos River diversion project

    Duration: January 1996–December 1996

    Contractor: Directorate for Acheloos Diversion Works

    Collaborators:

    1. G. Kalaouzis
    2. ELECTROWATT
    3. P. Marinos
    4. D. Koutsoyiannis

  1. Water resources management of the Evinos river basin and hydrogeological study of the Evinos karstic system

    Duration: January 1996–December 1996

    Commissioned by: Directorate of Water Supply and Sewage

    Contractors:

    1. P. Panagopoulos
    2. General Studies
    3. Istria
    4. Ecosystems Analysis

  1. Assessment of the influence of forest fire of 1995 in the increase of sediment yield of the Megalo Rema in Raphena

    Duration: June 1996–November 1996

    Commissioned by: Prefectural Government of Eastern Attica

  1. Integrated study of the environmental impacts from Acheloos diversion

    Duration: September 1995–December 1995

    Contractor: Directorate for Acheloos Diversion Works

    Collaborators: Ydroexigiantiki

  1. Study of environmental impacts from the small hydroelectric work in Metsovitikos river

    Duration: January 1995–December 1995

    Contractor: Epsilon

  1. Arachthos River, Aghios Nicolaos hydroelectric project, Engineering Report

    Duration: November 1983–August 1994

    Commissioned by: Public Power Corporation

    Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG)

  1. Engineering study for improving the water supply of Athens with the construction of a dam at the Evinos River

    Duration: January 1991–December 1991

    Commissioned by: Directorate of Water Supply and Sewage

    Contractors:

    1. OTME
    2. Ydroilektriki
    3. YDROTEK
    4. D. Constantinidis
    5. G. Karavokiris
    6. Th. Gofas and Partners

  1. Master plan of the land reclamation works of the Arta plain

    Duration: January 1990–December 1990

    Commissioned by: Ministry of Agriculture

    Contractors:

    1. Ydrodomiki
    2. D. Constantinidis
    3. Ydroexigiantiki
    4. Abramopoulos

  1. Engineering study of the regulation of the Kallithea Stream in Mytilene

    Duration: January 1988–December 1988

    Commissioned by: Ministry of National Education

    Contractor: TENET

  1. Study of the Faneromeni dam in Mesara, Crete - Engineering report

    Duration: January 1988–December 1988

    Commissioned by: Ministry of Agriculture

    Contractors:

    1. D. Constantinidis
    2. Grafeio Doxiadi

  1. Study of the Plakiotissa dam in Mesara, Crete - Engineering report

    Duration: January 1986–December 1986

    Commissioned by: Ministry of Agriculture

    Contractors:

    1. D. Constantinidis
    2. Grafeio Doxiadi

  1. Study of the wastewater treatment plant of Aghios Nicolaos, Crete

    Duration: January 1984–December 1986

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Joint Venture Akvantan-Tapeions-Talios

  1. Engineering study of the flood protection works in the Boeoticos Kephisos river basin

    Duration: January 1985–December 1985

    Commissioned by: Ministry of Public Works

    Contractor: D. Constantinidis

  1. Engineering study of the flood protection and drainage works and the dam in the Artzan-Amatovo region

    Duration: January 1982–December 1985

    Commissioned by: Ministry of Public Works

    Contractors:

    1. OTME
    2. D. Constantinidis
    3. METER

  1. Arachthos River, Steno - Kalaritikos hydroelectric project, Engineering Report

    Duration: January 1984–August 1984

    Commissioned by: Public Power Corporation

    Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG)

  1. Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Engineering report

    Duration: January 1982–June 1984

    Commissioned by: Prefectural Fund of Peiraias

    Contractor: E. Vassilopoulos

  1. Preliminary study of the water supply of Karystos and Kallianos municipalities from the Demosari springs

    Duration: October 1982–May 1984

    Commissioned by: Prefectural Fund of Euboea

    Contractor: E. Vassilopoulos

  1. Master plan of Dereio dam

    Duration: January 1983–December 1983

    Commissioned by: Ministry of Public Works

    Contractors:

    1. Grafeio Doxiadi
    2. D. Constantinidis

  1. Engineering study of sewer system and the wastewater treatment plant of Farsala

    Duration: January 1983–December 1983

    Commissioned by: Ministry of Public Works

    Contractor: METER

  1. Preliminary study of the reconstruction of the state-run saltern of Mesi, Komotene

    Duration: January 1983–December 1983

    Commissioned by: Ministry of the Industry

    Contractors:

    1. METER
    2. E. Vassilopoulos
    3. C. Fourniotis-Pavlatos

  1. Arachthos River, Middle Course hydroelectric projects, Master Plan

    Duration: January 1983–October 1983

    Commissioned by: Public Power Corporation

    Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG)

  1. Study for the restoration, fixing, protection and prominence of the archaeological monument of Knossos

    Duration: January 1983–January 1983

    Commissioned by: Ministry of Culture and Sciences

    Contractor: I. Skandalis

    Collaborators:

    1. P. Melissaris
    2. D. Koutsoyiannis

  1. Study of the sewer system of Neapolis, Lasithi, Engineering report

    Duration: April 1982–January 1983

    Commissioned by: Prefectural Fund of Lasithi

    Contractor: G. Koukourakis and Colleagues

  1. Alternative studies for the irrigation of the Lasithi plateau

    Duration: January 1982–December 1982

    Commissioned by: Prefectural Fund of Lasithi

    Contractors:

    1. METER
    2. Exarxou and Nikolopoulos
    3. Kalatzopoulos

  1. Master plan of the foul sewer system of Kanallaki, Preveza

    Duration: June 1982–December 1982

    Commissioned by: Prefectural Fund of Preveza

    Contractor: E. Vassilopoulos

  1. Preliminary study of the sewer system of Kanallaki, Preveza

    Duration: April 1981–June 1982

    Commissioned by: Prefectural Fund of Preveza

    Contractor: E. Vassilopoulos

  1. Arachthos River, Middle Course hydroelectric projects, Alternative studies

    Duration: October 1981–March 1982

    Commissioned by: Public Power Corporation

    Contractor: Arachthos Swiss-Anglo-German Consulting Group (ASAG)

  1. Study of the sewer system of Aghia Marina in Mesagros municipality, Aegina, Preliminary study

    Duration: September 1981–December 1981

    Commissioned by: Prefectural Fund of Peiraias

    Contractor: E. Vassilopoulos

  1. Study of the sewer system of Neapolis, Lasithi, Master plan

    Duration: August 1980–July 1981

    Commissioned by: Prefectural Fund of Lasithi

    Contractor: G. Koukourakis and Colleagues

  1. Study of the sewer system of Neapolis, Lasithi, Alternative studies

    Duration: January 1980–April 1980

    Commissioned by: Prefectural Fund of Lasithi

    Contractor: G. Koukourakis and Colleagues

  1. Engineering study of restoration of the water supply of Karpenesi

    Duration: January 1979–December 1979

    Commissioned by: Prefectural Fund of Evritania

    Contractor: A. Psilopoulos

  1. Engineering study of the sewer system of the Karpenesi municipality

    Duration: January 1979–December 1979

    Commissioned by: Prefectural Fund of Evritania

    Contractor: A. Psilopoulos

  1. Engineering study of the sewer system of the Karpenesi municipality

    Duration: January 1978–December 1978

    Commissioned by: Prefectural Fund of Eleia

    Contractor: A. Psilopoulos

Published work in detail

Publications in scientific journals

  1. D. Koutsoyiannis, and G.-F. Sargentis, Entropy and wealth, Entropy, 23 (10), 1356, doi:10.3390/e23101356, 2021.

    While entropy was introduced in the second half of the 19th century in the international vocabulary as a scientific term, in the 20th century it became common in colloquial use. Popular imagination has loaded “entropy” with almost every negative quality in the universe, in life and in society, with a dominant meaning of disorder and disorganization. Exploring the history of the term and many different approaches to it, we show that entropy has a universal stochastic definition, which is not disorder. Hence, we contend that entropy should be used as a mathematical (stochastic) concept as rigorously as possible, free of metaphoric meanings. The accompanying principle of maximum entropy, which lies behind the Second Law, gives explanatory and inferential power to the concept, and promotes entropy as the mother of creativity and evolution. As the social sciences are often contaminated by subjectivity and ideological influences, we try to explore whether maximum entropy, applied to the distribution of a wealth-related variable, namely annual income, can give an objective description. Using publicly available income data, we show that income distribution is consistent with the principle of maximum entropy. The increase in entropy is associated to increases in society’s wealth, yet a standardized form of entropy can be used to quantify inequality. Historically, technology has played a major role in the development of and increase in the entropy of income. Such findings are contrary to the theory of ecological economics and other theories that use the term entropy in a Malthusian perspective.

    Full text: http://www.itia.ntua.gr/en/getfile/2150/1/documents/entropy-23-01356-v2_corrections.pdf (7388 KB)

  1. N. Mamassis, K. Mazi, E. Dimitriou, D. Kalogeras, N. Malamos, S. Lykoudis, A. Koukouvinos, I. L. Tsirogiannis, I. Papageorgaki, A. Papadopoulos, Y. Panagopoulos, D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. Vitantzakis, N. Kappos, D. Katsanos, B. Psiloglou, E. Rozos, T. Kopania, I. Koletsis, and A. D. Koussis, OpenHi.net: A synergistically built, national-scale infrastructure for monitoring the surface waters of Greece, Water, 13 (19), 2779, doi:10.3390/w13192779, 2021.

    The large-scale surface-water monitoring infrastructure for Greece Open Hydrosystem Information Network (Openhi.net) is presented in this paper. Openhi.net provides free access to water data, incorporating existing networks that manage their own databases. In its pilot phase, Openhi.net operates three telemetric networks for monitoring the quantity and the quality of surface waters, as well as meteorological and soil variables. Aspiring members must also offer their data for public access. A web-platform was developed for on-line visualization, processing and managing telemetric data. A notification system was also designed and implemented for inspecting the current values of variables. The platform is built upon the web 2.0 technology that exploits the ever-increasing capabilities of browsers to handle dynamic data as a time series. A GIS component offers web-services relevant to geo-information for water bodies. Accessing, querying and downloading geographical data for watercourses (segment length, slope, name, stream order) and for water basins (area, mean elevation, mean slope, basin order, slope, mean CN-curve number) are provided by Web Map Services and Web Feature Services. A new method for estimating the streamflow from measurements of the surface velocity has been advanced as well to reduce hardware expenditures, a low-cost ‘prototype’ hydro-telemetry system (at about half the cost of a comparable commercial system) was designed, constructed and installed at six monitoring stations of Openhi.net.

    Full text: http://www.itia.ntua.gr/en/getfile/2147/1/documents/water-13-02779-v2.pdf (3567 KB)

    See also: https://www.mdpi.com/2073-4441/13/19/2779

  1. P. Dimitriadis, T. Iliopoulou, G.-F. Sargentis, and D. Koutsoyiannis, Spatial Hurst–Kolmogorov Clustering, Encyclopedia, 1 (4), 1010–1025, doi:10.3390/encyclopedia1040077, 2021.

    The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is introduced as a robust means to identify, model and simulate the Hurst–Kolmogorov (HK) dynamics, ranging from small (fractal) to large scales exhibiting the clustering behavior (else known as the Hurst phenomenon or long-range dependence). The HK clustering is an attribute of a multidimensional (1D, 2D, etc.) spatio-temporal stationary stochastic process with an arbitrary marginal distribution function, and a fractal behavior on small spatio-temporal scales of the dependence structure and a power-type on large scales, yielding a high probability of low- or high-magnitude events to group together in space and time. This behavior is preferably analyzed through the second-order statistics, and in the scale domain, by the stochastic metric of the climacogram, i.e., the variance of the averaged spatio-temporal process vs. spatio-temporal scale.

  1. D. Koutsoyiannis, and P. Dimitriadis, Towards generic simulation for demanding stochastic processes, Sci, 3, 34, doi:10.3390/sci3030034, 2021.

    We outline and test a new methodology for genuine simulation of stochastic processes with any dependence structure and any marginal distribution. We reproduce time dependence with a generalized, time symmetric or asymmetric, moving-average scheme. This implements linear filtering of non-Gaussian white noise, with the weights of the filter determined by analytical equations, in terms of the autocovariance of the process. We approximate the marginal distribu-tion of the process, irrespective of its type, using a number of its cumulants, which in turn deter-mine the cumulants of white noise, in a manner that can readily support the generation of random numbers from that approximation, so that it be applicable for stochastic simulation. The simulation method is genuine as it uses the process of interest directly, without any transformation (e.g., normalization). We illustrate the method in a number of synthetic and real-world applications, with either persistence or antipersistence, and with non-Gaussian marginal distributions that are bounded, thus making the problem more demanding. These include distributions bounded from both sides, such as uniform, and bounded from below, such as exponential and Pareto, possibly having a discontinuity at the origin (intermittence). All examples studied show the satisfactory performance of the method.

    Full text: http://www.itia.ntua.gr/en/getfile/2137/1/documents/sci-03-00034-v3.pdf (3002 KB)

  1. G.-F. Sargentis, P. Siamparina, G.-K. Sakki, A. Efstratiadis, M. Chiotinis, and D. Koutsoyiannis, Agricultural land or photovoltaic parks? The water–energy–food nexus and land development perspectives in the Thessaly plain, Greece, Sustainability, 13 (16), 8935, doi:10.3390/su13168935, 2021.

    Water, energy, land, and food are vital elements with multiple interactions. In this context, the concept of a water–energy–food (WEF) nexus was manifested as a natural resource management approach, aiming at promoting sustainable development at the international, national, or local level and eliminating the negative effects that result from the use of each of the four resources against the other three. At the same time, the transition to green energy through the application of renewable energy technologies is changing and perplexing the relationships between the constituent elements of the nexus, introducing new conflicts, particularly related to land use for energy production vs. food. Specifically, one of the most widespread “green” technologies is photovoltaic (PV) solar energy, now being the third foremost renewable energy source in terms of global installed capacity. However, the growing development of PV systems results in ever expanding occupation of agricultural lands, which are most advantageous for siting PV parks. Using as study area the Thessaly Plain, the largest agricultural area in Greece, we investigate the relationship between photovoltaic power plant development and food production in an attempt to reveal both their conflicts and their synergies.

    Full text: http://www.itia.ntua.gr/en/getfile/2136/1/documents/sustainability-13-08935.pdf (2709 KB)

    See also: https://www.mdpi.com/2071-1050/13/16/8935

  1. A. N. Angelakis, M. Valipour, A.T. Ahmed, V. Tzanakakis, N.V. Paranychianakis, J. Krasilnikoff, R. Drusiani, L.W. Mays, F. El Gohary, D. Koutsoyiannis, S. Khan, and L.J. Del Giacco, Water conflicts: from ancient to modern times and in the future, Sustainability, 13 (8), 4237, doi:10.3390/su13084237, 2021.

    Since prehistoric times, water conflicts have occurred as a result of a wide range of tensions and/or violence, which have rarely taken the form of traditional warfare waged over water resources alone. Instead, water has historically been a (re)source of tension and a factor in conflicts that start for other reasons. In some cases, water was used directly as a weapon through its ability to cause damage through deprivation or erosion or water resources of enemy populations and their armies. However, water conflicts, both past and present, arise for several reasons; including territorial disputes, fight for resources, and strategic advantage. The main reasons of water conflicts are usually delimitation of boundaries, waterlogging (e.g., dams and lakes), diversion of rivers flow, running water, food, and political distresses. In recent decades, the number of human casualties caused by water conflicts is more than that of natural disasters, indicating the importance of emerging trends on water wars in the world. This paper presents arguments, fights, discourses, and conflicts around water from ancient times to the present. This diachronic survey attempts to provide water governance alternatives for the current and future.

    Full text: http://www.itia.ntua.gr/en/getfile/2119/1/documents/sustainability-13-04237-v2.pdf (3322 KB)

  1. S. Vavoulogiannis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Multiscale temporal irreversibility of streamflow and its stochastic modelling, Hydrology, 8 (2), 63, doi:10.3390/hydrology8020063, 2021.

    We investigate the impact of time's arrow on the hourly streamflow process. Although time asymmetry, i.e., temporal irreversibility, has been previously implemented in stochastics, it has only recently attracted attention in the hydrological literature. Relevant studies have shown that the time asymmetry of the streamflow process is manifested at scales up to several days and vanishes at larger scales. The latter highlights the need to reproduce it in flood simulations of fine-scale resolution. To this aim, we develop an enhancement of a recently proposed simulation algorithm for irreversible processes, based on an asymmetric moving average (AMA) scheme that allows for the explicit preservation of time asymmetry at two or more timescales. The method is successfully applied to a large hourly streamflow time series from the United States Geological Survey (USGS) database, with time asymmetry prominent at time scales up to four days.

    Full text: http://www.itia.ntua.gr/en/getfile/2116/1/documents/hydrology-08-00063-v2.pdf (2541 KB)

  1. L. Katikas, P. Dimitriadis, D. Koutsoyiannis, T. Kontos, and P. Kyriakidis, A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series, Applied Energy, 295, 116873, doi:10.1016/j.apenergy.2021.116873, 2021.

    Lacking coastal and offshore wind speed time series of sufficient length, reanalysis data and wind speed models serve as the primary sources of valuable information for wind power management. In this study, long-length observational records and modelled data from Uncertainties in Ensembles of Regional Re-Analyses system are collected, analyzed and modelled. The first stage refers to the statistical analysis of the time series marginal structure in terms of the fitting accuracy, the distributions’ tails behavior, extremes response and the power output errors, using Weibull distribution and three parameter Weibull-related distributions (Burr Type III and XII, Generalized Gamma). In the second stage, the co-located samples in time and space are compared in order to investigate the reanalysis data performance. In the last stage, the stochastic generation mathematical framework is applied based on a Generalized Hurst-Kolmogorov process embedded in a Symmetric-Moving-Average scheme, which is used for the simulation of a wind process while preserving explicitly the marginal moments, wind’s intermittency and long-term persistence. Results indicate that Burr and Generalized Gamma distribution could be successfully used for wind resource assessment, although, the latter emerged enhanced performance in most of the statistical tests. Moreover, the credibility of the reanalysis data is questionable due to increased bias and root mean squared errors, however, high-order statistics along with the long-term persistence are thoroughly preserved. Eventually, the simplicity and the flexibility of the stochastic generation scheme to reproduce the seasonal and diurnal wind characteristics by preserving the long-term dependence structure are highlighted.

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, D. Koutsoyiannis, T. Iliopoulou, and P. Papanicolaou, A global-scale investigation of stochastic similarities in marginal distribution and dependence structure of key hydrological-cycle processes, Hydrology, 8 (2), 59, doi:10.3390/hydrology8020059, 2021.

    To seek stochastic analogies in key processes related to the hydrological cycle, an extended collection of several billions of data values from hundred thousands of worldwide stations is used in this work. The examined processes are the near-surface hourly temperature, dew point, relative humidity, sea level pressure, and atmospheric wind speed, as well as the hourly/daily streamflow and precipitation. Through the use of robust stochastic metrics such as the K-moments and a secondorder climacogram (i.e., variance of the averaged process vs. scale), it is found that several stochastic similarities exist in both the marginal structure, in terms of the first four moments, and in the secondorder dependence structure. Stochastic similarities are also detected among the examined processes, forming a specific hierarchy among their marginal and dependence structures, similar to the one in the hydrological cycle. Finally, similarities are also traced to the isotropic and nearly Gaussian turbulence, as analyzed through extensive lab recordings of grid turbulence and of turbulent buoyant jet along the axis, which resembles the turbulent shear and buoyant regime that dominates and drives the hydrological-cycle processes in the boundary layer. The results are found to be consistent with other studies in literature such as solar radiation, ocean waves, and evaporation, and they can be also justified by the principle of maximum entropy. Therefore, they allow for the development of a universal stochastic view of the hydrological-cycle under the Hurst–Kolmogorov dynamics, with marginal structures extending from nearly Gaussian to Pareto-type tail behavior, and with dependence structures exhibiting roughness (fractal) behavior at small scales, long-term persistence at large scales, and a transient behavior at intermediate scales.

    Full text: http://www.itia.ntua.gr/en/getfile/2114/1/documents/hydrology-08-00059-v5.pdf (7374 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G.-F. Sargentis, T. Iliopoulou, P. Dimitriadis, N. Mamassis, and D. Koutsoyiannis, Stratification: An entropic view of society's structure, World, 2, 153–174, doi:10.3390/world2020011, 2021.

    In human societies, we observe a wide range of types of stratification, i.e., in terms of financial class, political power, level of education, sanctity, and military force. In financial, political, and social sciences, stratification is one of the most important issues and tools as the Lorenz Curve and the Gini Coefficient have been developed to describe some of its aspects. Stratification is greatly dependent on the access of people to wealth. By “wealth”, we mean the quantified prosperity which increases the life expectancy of people. Prosperity is also connected to the water‐food‐energy nexus which is necessary for human survival. Analyzing proxies of the water‐food‐energy nexus, we suggest that the best proxy for prosperity is energy, which is closely related to Gross Domestic Product (GDP) per capita and life expectancy. In order to describe the dynamics of social stratification, we formulate an entropic view of wealth in human societies. An entropic approach to income distribution, approximated as available energy in prehistoric societies, till present‐day economies, shows that stratification can be viewed as a stochastic process subject to the principle of maximum entropy and occurring when limits to the wealth of society are set, either by the political and economic system and/or by the limits of available technology.

    Full text: http://www.itia.ntua.gr/en/getfile/2107/1/documents/world-02-00011-v3.pdf (10384 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Rethinking climate, climate change, and their relationship with water, Water, 13 (6), 849, doi:10.3390/w13060849, 2021.

    We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate was established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acts upon it. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this varia-bility, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleo-nasm as climate, like weather, has been ever-changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing true roles and cau-sality directions. For this reason, we provide arguments that water is the main element that drives climate, and not the opposite.

    Remarks:

    Blog discussions about this article

    1. Rethinking Climate, Climate Change, and Their Relationship with Water by Charles Rotter, 2020-10-05 (Watts Up With That?)

    Full text: http://www.itia.ntua.gr/en/getfile/2098/1/documents/water-13-00849-v4.pdf (5096 KB)

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Advances in stochastics of hydroclimatic extremes, L'Acqua, 2021 (1), 23–32, 2021.

    The 21st century has been marked by a substantial progress in hydroclimatic data collection and access to them, accompanied by regression in methodologies to study and interpret the behaviour of natural processes and in particular of extremes thereof. The developing culture of prophesising the future, guided by deterministic climate modelling approaches, has seriously affected hydrology. Therefore, aspired advances are related to abandoning the certainties of deterministic approaches and returning to stochastic descriptions, seeking in the latter theoretical consistency and optimal use of available data.

    Full text: http://www.itia.ntua.gr/en/getfile/2092/1/documents/2021_LACQUA_DK.pdf (8789 KB)

  1. D. Koutsoyiannis, and N. Mamassis, From mythology to science: the development of scientific hydrological concepts in the Greek antiquity and its relevance to modern hydrology, Hydrology and Earth System Sciences, 25, 2419–2444, doi:10.5194/hess-25-2419-2021, 2021.

    Whilst hydrology is a Greek term, it has not been in use in the Classical literature but much later, during the Renaissance, in its Latin version, hydrologia. On the other hand, Greek natural philosophers created robust knowledge in related scientific areas, to which they gave names such as meteorology, climate and hydraulics. These terms are now in common use internationally. Within these areas, Greek natural philosophers laid the foundation of hydrological concepts and the hydrological cycle in its entirety. Knowledge development was brought about by search for technological solutions to practical problems, as well as by scientific curiosity to explain natural phenomena. While initial explanations belong to the sphere of mythology, the rise of philosophy was accompanied by attempts to provide scientific descriptions of the phenomena. It appears that the first geophysical problem formulated in scientific terms was the explanation of the flood regime of the Nile, then regarded as a paradox because of the spectacular difference from the river flow regime in Greece and other Mediterranean regions, i.e., the fact that the Nile flooding occurs in summer when in most of the Mediterranean the rainfall is very low. While some of the early attempts to explain it were influenced by Homer’s mythical view (archaic period), eventually, Aristotle was able to formulate a correct hypothesis, which he tested through what it appears to be the first in history scientific expedition, in the turn from the Classical to Hellenistic period. This confirms the fact that the hydrological cycle was well understood during the Classical period yet it poses the question why Aristotle’s correct explanation had not been accepted and, instead, ancient and modern mythical views had been preferred up to the 18th century.

    Full text: http://www.itia.ntua.gr/en/getfile/2087/1/documents/hess-25-2419-2021.pdf (30835 KB)

    Additional material:

  1. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, A stochastic view of varying styles in art paintings, Heritage, 4, 21, doi:10.3390/heritage4010021, 2021.

    A physical process is characterized as complex when it is difficult to analyze and explain in a simple way, and even more difficult to predict. The complexity within an art painting is expected to be high, possibly comparable to that of nature. Herein, we apply a 2D stochastic methodology to images of both portrait photography and artistic portraits, the latter belonging to different genres of art, with the aim to better understand their variability in quantitative terms. To quantify the dependence structure and variability, we estimate the Hurst parameter, which is a common dependence metric for hydrometeorological processes. We also seek connections between the identified stochastic patterns and the desideratum that each art movement aimed to express. Results show remarkable stochastic similarities between portrait paintings, linked to philosophical, cultural and theological characteristics of each period.

    Full text: http://www.itia.ntua.gr/en/getfile/2086/1/documents/heritage-04-00021.pdf (3242 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G.-F. Sargentis, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Landscape planning of infrastructure through focus points’ clustering analysis. Case study: Plastiras artificial lake (Greece), Infrastructures, 6 (1), 12, doi:10.3390/infrastructures6010012, 2021.

    Even though landscape quality is largely a subjective issue, the integration of infrastructure into landscapes has been identified as a key element of sustainability. In a spatial planning context, the landscape impacts that are generated by infrastructures are commonly quantified through visibility analysis. In this study, we develop a new method of visibility analysis and apply it in a case study of a reservoir (Plastiras dam in Greece). The methodology combines common visibility analysis with a stochastic tool for visual-impacts evaluation; points that generate high visual contrasts in landscapes are considered Focus Points (FPs) and their clustering in landscapes is analyzed trying to answer two questions: (1) How does the clustering of Focus Points (FPs) impact the aesthetic value of the landscape? (2) How can the visual impacts of these FPs be evaluated? Visual clustering is calculated utilizing a stochastic analysis of generated Zones of Theoretical Visibility. Based on the results, we argue that if the visual effect of groups of FPs is positive, then the optimal sitting of FPs should be in the direction of faint clustering, whereas if the effect is negative, the optimal sitting of FPs should be directed to intense clustering. In order to optimize the landscape integration of infrastructure, this method could be a useful analytical tool for environmental impact assessment or a monitoring tool for a project’s managing authorities. This is demonstrated through the case study of Plastiras’ reservoir, where the clustering of positively perceived FPs is found to be an overlooked attribute of its perception as a highly sustainable infrastructure project.

    Full text: http://www.itia.ntua.gr/en/getfile/2083/1/documents/infrastructures-06-00012-v2.pdf (5634 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Efstratiadis, I. Tsoukalas, and D. Koutsoyiannis, Generalized storage-reliability-yield framework for hydroelectric reservoirs, Hydrological Sciences Journal, 66 (4), 580–599, doi:10.1080/02626667.2021.1886299, 2021.

    Although storage-reliability-yield (SRY) relationships have been widely used in the design and planning of water supply reservoirs, their application in hydroelectricity is practically nil. Here, we revisit the SRY analysis and seek its generic configuration for hydroelectric reservoirs, following a stochastic simulation approach. After defining key concepts and tools of conventional SRY studies, we adapt them for hydropower systems, which are subject to several peculiarities. We illustrate that under some reasonable assumptions, the problem can be substantially simplified. Major innovations are the storage-head-energy conversion via the use of a sole parameter, representing the reservoir geometry, and the development of an empirical statistical metric expressing the reservoir performance on the basis of the simulated energy-probability curve. The proposed framework is applied to numerous hypothetical reservoirs at three river sites in Greece, using monthly synthetic inflow data, to provide empirical expressions of reliable energy as a function of reservoir storage and geometry.

    Additional material:

  1. K. Glynis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of daily air temperature extremes from a global ground station network, Stochastic Environmental Research & Risk Assessment, doi:10.1007/s00477-021-02002-3, 2021.

    Near-surface air temperature is one of the most widely studied hydroclimatic variables, as both its regular and extremal behaviors are of paramount importance to human life. Following the global warming observed in the past decades and the advent of the anthropogenic climate change debate, interest in temperature’s variability and extremes has been rising. It has since become clear that it is imperative not only to identify the exact shape of the temperature’s distribution tails, but also to understand their temporal evolution. Here, we investigate the stochastic behavior of near-surface air temperature using the newly developed estimation tool of Knowable (K-)moments. K-moments, because of their property to substitute higher-order deviations from the mean with the distribution function, enable reliable estimation and an effective alternative to order statistics and, particularly for the outliers-prone distribution tails. We compile a large set of daily timeseries (30–200 years) of average, maximum and minimum air temperature, which we standardize with respect to the monthly variability of each record. Our focus is placed on the maximum and minimum temperatures, because they are more reliably measured than the average, yet very rarely analyzed in the literature. We examine segments of each timeseries using consecutive rolling 30-year periods, from which we extract extreme values corresponding to specific return period levels. Results suggest that the average and minimum temperature tend to increase, while overall the maximum temperature is slightly decreasing. Furthermore, we model the temperature timeseries as a filtered Hurst-Kolmogorov process and use Monte Carlo simulation to produce synthetic records with similar stochastic properties through the explicit Symmetric Moving Average scheme. We subsequently evaluate how the patterns observed in the longest records can be reproduced by the synthetic series.

    Additional material:

  1. G.-F. Sargentis, T. Iliopoulou, S. Sigourou, P. Dimitriadis, and D. Koutsoyiannis, Evolution of clustering quantified by a stochastic method — Case studies on natural and human social structures, Sustainability, 12 (19), 7972, doi:10.3390/su12197972, 2020.

    Clustering structures appearing from small to large scales are ubiquitous in the physical world. Interestingly, clustering structures are omnipresent in human history too, ranging from the mere organization of life in societies (e.g., urbanization) to the development of large-scale infrastructure and policies for meeting organizational needs. Indeed, in its struggle for survival and progress, mankind has perpetually sought the benefits of unions. At the same time, it is acknowledged that as the scale of the projects grows, the cost of the delivered products is reduced while their quantities are maximized. Thus, large-scale infrastructures and policies are considered advantageous and are constantly being pursued at even great scales. This work develops a general method to quantify the temporal evolution of clustering, using a stochastic computational tool called 2D-C, which is applicable for the study of both natural and human social spatial structures. As case studies, the evolution of the structure of the universe, of ecosystems and of human clustering structures such as urbanization, are investigated using novel sources of spatial information. Results suggest the clear existence both of periods of clustering and declustering in the natural world and in the human social structures; yet clustering is the general trend. In view of the ongoing COVID-19 pandemic, societal challenges arising from large-scale clustering structures are discussed.

    Full text: http://www.itia.ntua.gr/en/getfile/2066/1/documents/sustainability-12-07972.pdf (8123 KB)

    See also: https://www.mdpi.com/2071-1050/12/19/7972/htm

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, and Z. W. Kundzewicz, Atmospheric temperature and CO₂: Hen-or-egg causality?, Sci, 2 (4), 83, doi:10.3390/sci2040083, 2020.

    It is common knowledge that increasing CO₂ concentration plays a major role in enhancement of the greenhouse effect and contributes to global warming. The purpose of this study is to complement the conventional and established theory that increased CO₂ concentration due to human emissions causes an increase of temperature, by considering the reverse causality. Since increased temperature causes an increase in CO₂ concentration, the relationship of atmospheric CO₂ and temperature may qualify as belonging to the category of “hen-or-egg” problems, where it is not always clear which of two interrelated events is the cause and which the effect. We examine the relationship of global temperature and atmospheric carbon dioxide concentration at the monthly time step, covering the time interval 1980–2019, in which reliable instrumental measurements are available. While both causality directions exist, the results of our study support the hypothesis that the dominant direction is T → CO₂. Changes in CO₂ follow changes in T by about six months on a monthly scale, or about one year on an annual scale. We attempt to interpret this mechanism by involving biochemical reactions, as at higher temperatures soil respiration, and hence CO₂ emission, are increasing.

    Remarks:

    Full text in html of version 2 on journal's site: https://www.mdpi.com/2413-4155/2/4/77/htm

    Full text in pdf of version 2 on journal's site: https://www.mdpi.com/2413-4155/2/4/77/pdf

    Review reports and replies of version 2 on journal's site: https://www.mdpi.com/2413-4155/2/4/77/review_report

    Full text in html of version 1 on journal's site: https://www.mdpi.com/2413-4155/2/3/81/htm

    Full text in pdf of version 1 on journal's site: https://www.mdpi.com/2413-4155/2/3/81/pdf

    Review reports and replies of version 1 on journal's site: https://www.mdpi.com/2413-4155/2/3/81/review_report

    Blog discussions about this article

    1. New Study Finds Robust Statistical Probability Temperature Drives CO2 Changes, Upending ‘Scientific Perception’ by Kenneth Richard, 2020-10-05 (NoTricksZone)
    2. New Study: Strong Likelihood That Temperature Drives CO2 Changes—Reproduced #1 as #2 with comments by Kenneth Richard, 2020-10-05 (Climate Dispatch)
    3. Reproduced #1 in newscats.org
    4. Reproduced #2 in altnews.org
    5. Atmosfæretemperatur og CO2 by Geir Aaslid, 2020-10-11 (Klimarealistene)
    6. IPCC har förväxlat orsak och verkan, temperaturen driver luftens halt av CO₂ , 2020-10-13 (Klimatsans)
    7. Shock Study: CO2 Climate Theory Exposed During COVID Lockdown, by John O'Sullivan, 2020-10-13 (Principia Scientific)
    8. E’ nato prima l’uovo o la gallina?, by Donato Barone, 2020-10-20 (Climatemonitor)
    9. Temperature and Carbon Dioxide: Defying Alarmists, by Jack Dini, 2020-10-22 (Canada Free Press)
    10. Prima l’uovo o la gallina? 2.a parte: Una visione un po’ diversa, by Franco Zavatti, 2020-10-24 (Climatemonitor)

    Full text: http://www.itia.ntua.gr/en/getfile/2064/1/documents/sci-02-00083-v2.pdf (5476 KB)

    Additional material:

    See also: https://www.mdpi.com/2413-4155/2/4/83

    Works that cite this document: View on Google Scholar or ResearchGate

  1. R. Ioannidis, and D. Koutsoyiannis, A review of land use, visibility and public perception of renewable energy in the context of landscape impact, Applied Energy, 276, 115367, doi:10.1016/j.apenergy.2020.115367, 2020.

    Landscape impacts associated with aesthetics have been a persistent cause of opposition against renewable energy projects. However, the current uncertainty over the spatial extents and the rationality of reported impacts impedes the development of optimal strategies for their mitigation. In this paper, a typology of landscape impacts is formed for hydroelectric, wind and solar energy through the review of three metrics that have been used extensively for impact-assessment: land use, visibility and public perception. Additionally, a generic landscape-impact ranking is formed, based on data from realized projects, demonstrating that hydroelectric energy has been the least impactful to landscapes per unit energy generation, followed by solar and wind energy, respectively. More importantly, the analysis highlights the strengths and weaknesses of each technology, in a landscape impact context, and demonstrates that, depending on landscape attributes, any technology can potentially be the least impactful. Finally, a holistic approach is proposed for future research and policy for the integration of renewable energy to landscapes, introducing the maximum utilization of the advantages of each technology as an additional strategy in an effort to expand beyond the mitigation of negative impacts.

    Remarks:

    Download site: https://authors.elsevier.com/c/1bbKL15eiezzux

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. Z. W. Kundzewicz, I. Pińskwar, and D. Koutsoyiannis, Variability of global mean annual temperature is significantly influenced by the rhythm of ocean-atmosphere oscillations, Science of the Total Environment, 747, 141256, doi:10.1016/j.scitotenv.2020.141256, 2020.

    While global warming has been evolving over several decades, in particular years there have been considerable deviations of global temperature from the underlying trend. These could be explained by climate variability patterns and, in particular, by the major interplays of atmospheric and oceanic processes that generate variations in the global climatic system. Here we show, in a simple and straightforward way, that a rhythm of the major ocean-atmosphere oscillations, such as the ENSO and IPO in the Pacific as well as the AMO in the Atlantic, is indeed meaningfully influencing the global mean annual temperature. We construct time series of residuals of the global temperature from the medium-term (5-year) running averages and show that these largely follow the rhythm of residuals of three basic ocean-atmosphere oscillation modes (ENSO, IPO and AMO) from the 5-year running averages. We find meaningful correlations between analyzed climate variability and deviations of global mean annual temperature residuals that are robust across various datasets and assumptions and explain over 70% of the annual temperature variability in terms of residuals from medium-term averages.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G.-F. Sargentis, P. Dimitriadis, R. Ioannidis, T. Iliopoulou, E. Frangedaki, and D. Koutsoyiannis, Optimal utilization of water resources for local communities in mainland Greece (case study of Karyes, Peloponnese), Procedia Manufacturing, 44, 253–260, doi:10.1016/j.promfg.2020.02.229, 2020.

    Water is the basis of our civilization and the development of society is intertwined with the exploitation of water resources in various scales, from a well dug to irrigate a garden, to a large dam providing water and energy for a large area. However, for remote mountainous areas, intermittent natural water resources and high seasonal demand the above tasks become challenging. Here we discuss various alternative management options and appropriate solutions on how to exploit water resources meeting the above restrictions under limited infrastructure budgets. As a case study we examine the area of Karyes in Peloponnese that meets the above criteria, exploring various solutions to satisfy the water demand.

    Full text: http://www.itia.ntua.gr/en/getfile/2047/1/documents/1-s2.0-S2351978920308167-main.pdf (1660 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. T. Iliopoulou, and D. Koutsoyiannis, Projecting the future of rainfall extremes: better classic than trendy, Journal of Hydrology, 588, doi:10.1016/j.jhydrol.2020.125005, 2020.

    Non-stationarity approaches have been increasingly popular in hydrology, reflecting scientific concerns regarding intensification of the water cycle due to global warming. A considerable share of relevant studies is dominated by the practice of identifying linear trends in data through in-sample analysis. In this work, we reframe the problem of trend identification using the out-of-sample predictive performance of trends as a reference point. We devise a systematic methodological framework in which linear trends are compared to simpler mean models, based on their performance in predicting climatic-scale (30-year) annual rainfall indices, i.e. maxima, totals, wet-day average and probability dry, from long-term daily records. The models are calibrated in two different schemes: block-moving, i.e. fitted on the recent 30 years of data, obtaining the local trend and local mean, and global-moving, i.e. fitted on the whole period known to an observer moving in time, thus obtaining the global trend and global mean. The investigation of empirical records spanning over 150 years suggests that a great degree of variability has been ever present in the rainfall process, leaving small potential for long-term predictability. The local mean model ranks first in terms of average predictive performance, followed by the global mean and the global trend, in decreasing order of performance, while the local trend model ranks last among the models, showing the worst performance overall. Parallel experiments from synthetic timeseries characterized by persistence corroborated this finding, suggesting that future long-term variability of persistent processes is better captured using parsimonious features of the past. In line with the empirical findings, it is shown that, prediction-wise, simple is preferable to trendy.

    Remarks:

    Official site for free access (temporary): https://authors.elsevier.com/c/1b41M52cuR14A

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G.-F. Sargentis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues of Leonardo Da Vinci’s and Pablo Picasso’s paintings with stochastic evaluation, Heritage, 3 (2), 283–305, doi:10.3390/heritage3020017, 2020.

    A physical process is characterized as complex when it is difficult to analyze or explain in a simple way. The complexity within an art painting is expected to be high, possibly comparable to that of nature. Therefore, constructions of artists (e.g., paintings, music, literature, etc.) are expected to be also of high complexity since they are produced by numerous human (e.g., logic, instinct, emotions, etc.) and non-human (e.g., quality of paints, paper, tools, etc.) processes interacting with each other in a complex manner. The result of the interaction among various processes is not a white-noise behavior, but one where clusters of high or low values of quantified attributes appear in a non-predictive manner, thus highly increasing the uncertainty and the variability. In this work, we analyze stochastic patterns in terms of the dependence structure of art paintings of Da Vinci and Picasso with a stochastic 2D tool and investigate the similarities or differences among the artworks.

    Full text: http://www.itia.ntua.gr/en/getfile/2043/1/documents/heritage-03-00017.pdf (9130 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Revisiting the global hydrological cycle: is it intensifying?, Hydrology and Earth System Sciences, 24, 3899–3932, doi:10.5194/hess-24-3899-2020, 2020.

    As a result of technological advances in monitoring atmosphere, hydrosphere, cryosphere and biosphere, as well as in data management and processing, several data bases have become freely available. These can be exploited in revisiting the global hydrological cycle with the aim, on the one hand, to better quantify it and, on the other hand, to test the established climatological hypotheses, according to which the hydrological cycle should be intensifying because of global warming. By processing the information from gridded ground observations, satellite data and reanalyses, it turns out that the established hypotheses are not confirmed. Instead of monotonic trends, there appear fluctuations from intensification to deintensification and vice versa, with deintensification prevailing in the 21st century. The water balance on land and sea appears to be lower than the standard figures of literature, but with greater variability on climatic time scales, which is in accordance with Hurst-Kolmogorov stochastic dynamics. The most obvious anthropogenic signal in the hydrological cycle appears to be the overexploitation of groundwater, which has a visible effect on sea level rise. Melting of glaciers has an equal effect, but in this case it is not known which part is anthropogenic, as studies on polar regions attribute mass loss mostly to ice dynamics.

    Remarks:

    Author's notes

    1. The paper was the most read paper of Hydrology and Earth System Sciences in 2020. (See also Altmetric.)
    1. The pdf files linked above are the original ones as reviewed and published in the journal. After publication, by initiative of the handling editor Erwin Zehe and after discussion of the Editors Alberto Guadagnini and Erwin Zehe, and the author Demetris Koutsoyiannis, a minor change in the Acknowledgements section was agreed. Specifically, it was agreed that the links to related presentations of the author that were given in the Acknowledgements section be replaced by a link to the author’s personal home page. This agreement was announced by the Editors in an Editorial Note and implemented. The modified files can be downloaded from the official journal's site at the doi of the paper given above.

    External reviews, comments and forum discussions about this article

    1. Bandwagon Of Doom Washed Away By Tidal Wave Of Data by Andrew Montford, 2020-04-02 (The Global Warming Policy Forum—GWPF)
    2. Bandwagon Of Doom Washed Away By Tidal Wave Of Data—Reproduced #1 as #2 with comments by Paul Homewood, 2020-04-02 (Not a Lot of People Know That)
    3. Bandwagon Of Doom Washed Away By Tidal Wave Of Data—Reproduced #1 as #3 with comments,, 2020-04-02 (Climate Change Dispatch)
    4. Bandwagon Of Doom Washed Away By Tidal Wave Of Data—Comments for #1, 2020-04-02 (Debate Politics)
    5. Bandwagon Of Doom Washed Away By Tidal Wave Of Data—Reproduced #1 as #5, 2020-04-02 (Before It's News)
    6. Bandwagon Of Doom Washed Away By Tidal Wave Of Data—Reproduced #1 as #6, 2020-04-02 (Roald J. Larsen)
    7. Bandwagon Of Doom Washed Away By Tidal Wave Of Data—Reproduced #1 as #7, 2020-04-02 (Iowa Climate Science Education)
    8. Week in review – climate science edition (with comments) by Judith Curry, 2020-04-03 (Climate Etc.)
    9. Weekly Climate and Energy News Roundup #405) by Ken Haapala, 2020-04-06 (Watts Up With That?)
    10. Eine Waggonladung Untergang von Daten-Flutwelle hinweg gespült—German translation of #1, 2020-04-17 (EIKE – Europäisches Institut für Klima & Energie)
    11. The 'Hydro-illogical cycle' by John Robson, 2020-04-15 (Climate Discussion Nexus)
    12. Weekly Climate and Energy News Roundup #406) by Ken Haapala, 2020-04-20 (Watts Up With That?)
    13. The Sound Of Settled Science (with comments) (Small Dead Animals)
    14. 観測データと気候モデルの結果が合わない / English translation: Observation data and climate model results do not match (International Environment and Economy Institute)
    15. Revisiting the global hydrological cycle: is it intensifying? by Charles Rotter with comments (Watts Up With That?).

    Full text: http://www.itia.ntua.gr/en/getfile/2042/1/documents/hess-24-3899-2020.pdf (16336 KB)

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Papacharalampous, H. Tyralis, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale, Advances in Water Resources, 136, 103470, doi:10.1016/j.advwatres.2019.103470, 2020.

    Predictive hydrological uncertainty can be quantified by using ensemble methods. If properly formulated, these methods can offer improved predictive performance by combining multiple predictions. In this work, we use 50-year-long monthly time series observed in 270 catchments in the United States to explore the performances provided by an ensemble learning post-processing methodology for issuing probabilistic hydrological predictions. This methodology allows the utilization of flexible quantile regression models for exploiting information about the hydrological model's error. Its key differences with respect to basic two-stage hydrological post-processing methodologies using the same type of regression models are that (a) instead of a single point hydrological prediction it generates a large number of “sister predictions” (yet using a single hydrological model), and that (b) it relies on the concept of combining probabilistic predictions via simple quantile averaging. A major hydrological modelling challenge is obtaining probabilistic predictions that are simultaneously reliable and associated to prediction bands that are as narrow as possible; therefore, we assess both these desired properties of the predictions by computing their coverage probabilities, average widths and average interval scores. The results confirm the usefulness of the proposed methodology and its larger robustness with respect to basic two-stage post-processing methodologies. Finally, this methodology is empirically proven to harness the “wisdom of the crowd” in terms of average interval score, i.e., the average of the individual predictions combined by this methodology scores no worse –usually better− than the average of the scores of the individual predictions.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Papacharalampous, D. Koutsoyiannis, and A. Montanari, Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models, Advances in Water Resources, 136, 103471, doi:10.1016/j.advwatres.2019.103471, 2020.

    We introduce an ensemble learning post-processing methodology for probabilistic hydrological modelling. This methodology generates numerous point predictions by applying a single hydrological model, yet with different parameter values drawn from the respective simulated posterior distribution. We call these predictions “sister predictions”. Each sister prediction extending in the period of interest is converted into a probabilistic prediction using information about the hydrological model's errors. This information is obtained from a preceding period for which observations are available, and is exploited using a flexible quantile regression model. All probabilistic predictions are finally combined via simple quantile averaging to produce the output probabilistic prediction. The idea is inspired by the ensemble learning methods originating from the machine learning literature. The proposed methodology offers larger robustness in performance than basic post-processing methodologies using a single hydrological point prediction. It is also empirically proven to “harness the wisdom of the crowd” in terms of average interval score, i.e., the obtained quantile predictions score no worse –usually better− than the average score of the combined individual predictions. This proof is provided within toy examples, which can be used for gaining insight on how the methodology works and under which conditions it can optimally convert point hydrological predictions to probabilistic ones. A large-scale hydrological application is made in a companion paper.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Simple stochastic simulation of time irreversible and reversible processes, Hydrological Sciences Journal, 65 (4), 536–551, doi:10.1080/02626667.2019.1705302, 2020.

    As time irreversibility of streamflow is marked for time scales up to several days, while common stochastic generation methods are good only for time symmetric processes, the need for new methods to handle irreversibility, particularly in flood simulations, has been recently highlighted. As a generic solution to this problem, an analytical exact method based on an asymmetric moving average (AMA) scheme is proposed. The method is studied theoretically in its general setting, as well as in its most interesting special cases, and is successfully applied to streamflow generation at hourly scale.

    Remarks:

    eprint: https://www.tandfonline.com/eprint/7B2PCSMKFDXRMS87PJ4X/full?target=10.1080/02626667.2019.1705302

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. R. Ioannidis, T. Iliopoulou, C. Iliopoulou, L. Katikas, A. Petsou, M.-E. Merakou, M.-E. Asimomiti, N. Pelekanos, G. Koudouris, P. Dimitriadis, C. Plati, E. Vlahogianni, K. Kepaptsoglou, N. Mamassis, and D. Koutsoyiannis, Solar-powered bus route: introducing renewable energy into a university campus transport system, Advances in Geosciences, 49, doi:10.5194/adgeo-49-215-2019, 2019.

    We investigate the application of a solar-powered bus route to a small-scale transportation system, as such of a university campus. In particular, we explore the prospect of replacing conventional fossil fuel buses by electric buses powered by solar energy and electricity provided by the central grid. To this end, we employ GIS mapping technology to estimate the solar radiation at the university campus and, accordingly, we investigate three different scenarios for harnessing the available solar power: (1) solar panels installed on the roof of bus stop shelters, (2) solar panels installed at an unused open space in the university, and (3) solar roads, i.e. roads constructed by photovoltaic (PV) materials. For each of the three scenarios, we investigate the optimal technical configuration, the resulting energy generation, as well as the capital cost for application in the case of NTUA campus in Athens (Greece). The preliminary feasibility analysis showcases that all three scenarios contribute to satisfying transportation demand, proportionately to their size, with scenario (2) presenting the lowest capital cost in relation to energy generation. Therefore, we further explore this scenario by simulating its daily operation including the actions of buying and selling energy to the central grid, when there is energy deficit or surplus, respectively. A sensitivity analysis is carried out in order to ascertain the optimal size of the solar panel installation in relation to profit and reliability. Overall, results indicate that, albeit the high capital costs, solar-powered transportation schemes present a viable alternative for replacing conventional buses at the studied location, especially considering conventional PV panels. We note that present results heavily depend on the choice of capacity factors of PV materials, which differ among technologies. Yet, as capacity factors of PV panels are currently increasing, the studied schemes might be more promising in the future.

    Full text: http://www.itia.ntua.gr/en/getfile/2016/1/documents/adgeo-49-215-2019.pdf (8167 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Papacharalampous, H. Tyralis, A. Langousis, A. W. Jayawardena, B. Sivakumar, N. Mamassis, A. Montanari, and D. Koutsoyiannis, Probabilistic hydrological post-processing at scale: Why and how to apply machine-learning quantile regression algorithms, Water, doi:10.3390/w11102126, 2019.

    We conduct a large-scale benchmark experiment aiming to advance the use of machine-learning quantile regression algorithms for probabilistic hydrological post-processing “at scale” within operational contexts. The experiment is set up using 34-year-long daily time series of precipitation, temperature, evapotranspiration and streamflow for 511 catchments over the contiguous United States. Point hydrological predictions are obtained using the Génie Rural à 4 paramètres Journalier (GR4J) hydrological model and exploited as predictor variables within quantile regression settings. Six machine-learning quantile regression algorithms and their equal-weight combiner are applied to predict conditional quantiles of the hydrological model errors. The individual algorithms are quantile regression, generalized random forests for quantile regression, generalized random forests for quantile regression emulating quantile regression forests, gradient boosting machine, model-based boosting with linear models as base learners and quantile regression neural networks. The conditional quantiles of the hydrological model errors are transformed to conditional quantiles of daily streamflow, which are finally assessed using proper performance scores and benchmarking. The assessment concerns various levels of predictive quantiles and central prediction intervals, while it is made both independently of the flow magnitude and conditional upon this magnitude. Key aspects of the developed methodological framework are highlighted, and practical recommendations are formulated. In technical hydro-meteorological applications, the algorithms should be applied preferably in a way that maximizes the benefits and reduces the risks from their use. This can be achieved by (i) combining algorithms (e.g., by averaging their predictions) and (ii) integrating algorithms within systematic frameworks (i.e., by using the algorithms according to their identified skills), as our large-scale results point out.

    Full text: http://www.itia.ntua.gr/en/getfile/2001/1/documents/water-11-02126.pdf (6451 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. F. Lombardo, F. Napolitano, F. Russo, and D. Koutsoyiannis, On the exact distribution of correlated extremes in hydrology, Water Resources Research, 55 (12), 10405–10423, doi:10.1029/2019WR025547, 2019.

    The analysis of hydrological hazards usually relies on asymptotic results of extreme value theory (EVT), which commonly deals with block maxima (BM) or peaks over threshold (POT) data series. However, data quality and quantity of BM and POT hydrological records do not usually fulfill the basic requirements of EVT, thus making its application questionable and results prone to high uncertainty and low reliability. An alternative approach to better exploit the available information of continuous time series and non-extreme records is to build the exact distribution of maxima (i.e., non-asymptotic extreme value distributions) from a sequence of low-threshold POT. Practical closed-form results for this approach do exist only for independent high-threshold POT series with Poisson occurrences. This study introduces new closed-form equations of the exact distribution of maxima taken from low-threshold POT with magnitudes characterized by an arbitrary marginal distribution and first-order Markovian dependence, and negative binomial occurrences. The proposed model encompasses and generalizes the independent-Poisson model and allows for analyses relying on significantly larger samples of low-threshold POT values exhibiting dependence, temporal clustering and overdispersion. To check the analytical results, we also introduce a new generator (called Gen2Mp) of proper first-order Markov chains with arbitrary marginal distributions. An illustrative application to long-term rainfall and streamflow data series shows that our model for the distribution of extreme maxima under dependence takes a step forward in developing more reliable data-rich-based analyses of extreme values.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, and D. Koutsoyiannis, The mode of the climacogram estimator for a Gaussian Hurst-Kolmogorov process, Journal of Hydroinformatics, doi:10.2166/hydro.2019.038, 2019.

    Geophysical processes are often characterized by long-term persistence. An important characteristic of such behaviour is the induced large statistical bias, i.e. the deviation of a statistical characteristic from its theoretical value. Here, we examine the most probable value (i.e. mode) of the estimator of variance to adjust the model for statistical bias. Particularly, we conduct an extensive Monte Carlo analysis based on the climacogram (i.e. variance of the average process vs. scale) of the simple scaling (Gaussian Hurst-Kolmogorov) process, and we show that its classical estimator is highly skewed especially in large scales. We observe that the mode of the climacogram estimator can be well approximated by its lower quartile (25% quantile). To derive an easy-to-fit empirical expression for the mode, we assume that the climacogram estimator follows a gamma distribution, an assumption strictly valid for Gaussian white noise processes. The results suggest that when a single timeseries is available, it is advantageous to estimate the Hurst parameter using the mode estimator rather than the expected one. Finally, it is discussed that while the proposed model for mode bias works well for Gaussian processes, for higher accuracy and non-Gaussian processes, one should perform a Monte Carlo simulation following an explicit generation algorithm.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. T. Iliopoulou, and D. Koutsoyiannis, Revealing hidden persistence in maximum rainfall records, Hydrological Sciences Journal, 64 (14), 1673–1689, doi:10.1080/02626667.2019.1657578, 2019.

    Clustering of extremes is critical for hydrological design and risk management and challenges the popular assumption of independence of extremes. We investigate the links between clustering of extremes and long-term persistence, else Hurst-Kolmogorov (HK) dynamics, in the parent process exploring the possibility of inferring the latter from the former. We find that (a) identifiability of persistence from maxima depends foremost on the choice of the threshold for extremes, the skewness and kurtosis of the parent process, and less on sample size; and (b) existing indices for inferring dependence from series of extremes are downward biased when applied to non-Gaussian processes. We devise a probabilistic index based on the probability of occurrence of peak-over-threshold events across multiple scales, which can reveal clustering, linking it to the persistence of the parent process. Its application shows that rainfall extremes may exhibit noteworthy departures from independence and consistency with an HK model.

    See also: https://www.tandfonline.com/doi/full/10.1080/02626667.2019.1657578

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G.-F. Sargentis, P. Dimitriadis, R. Ioannidis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic evaluation of landscapes transformed by renewable energy installations and civil works, Energies, 12 (4), 2817, doi:10.3390/en12142817, 2019.

    Renewable energy (RE) installations and civil works are beneficial in terms of sustainability, but a considerable amount of space in the landscape is required in order to harness this energy. In contemporary environmental theory the landscape is considered an environmental parameter and the transformation of the landscape by RE works has received increasing attention by the scientific community and affected societies. This research develops a novel computational stochastic tool the 2D Climacogram (2D-C) that allows the analysis and comparison of images of landscapes, both original and transformed by RE works. This is achieved by a variability characterization of the grayscale intensity of 2D images. A benchmark analysis is performed for art paintings in order to evaluate the properties of the 2D-C for image analysis, and the change in variability among images. Extensive applications are performed for landscapes transformed by RE works. Results show that the 2D-C is able to quantify the changes in variability of the image features, which may prove useful in the landscape impact assessment of large-scale engineering works.

    Full text: http://www.itia.ntua.gr/en/getfile/1984/1/documents/energies-12-02817.pdf (2772 KB)

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Ding, L., Q. Li, J. Tang, J. Wang, and X. Chen, Linking land use metrics measured in aquatic-terrestrial interfaces to water quality of reservoir-based water sources in Eastern China, Sustainability, 11(18), 4860, doi:10.3390/su11184860, 2019.

  1. G.-F. Sargentis, R. Ioannidis, G. Karakatsanis, S. Sigourou, N. D. Lagaros, and D. Koutsoyiannis, The development of the Athens water supply system and inferences for optimizing the scale of water infrastructures, Sustainability, 11 (9), 2657, doi:10.3390/su11092657, 2019.

    Modern organized societies require robust infrastructures, among which hydraulic projects, such as water supply and drainage systems, are most important, particularly in water-scarce areas. Athens is a unique example because it is a big city (population 3.7 million) located in a very dry area. In order to support the development of the city, large hydraulic projects had to be constructed during its history and, as a result, Athens currently has one of the largest water supply systems in the world. Could Athenians choose smaller scale infrastructures instead? Analyzing social, technical and economical historical data, we can see that large capital investments were required. In order to evaluate these investments this paper presents a technical summary of the development. An economic analysis displays historical values of these investments in present monetary values. The cost of existing infrastructure is compared to the cost of constructing smaller reservoirs and a model is created to correlate the price of water and the cost of water storage with the size of reservoirs. In particular, if more and smaller reservoirs were built instead of the large existing ones, the cost of the water would significantly increase, as illustrated by modelling the cost using local data.

    Full text: http://www.itia.ntua.gr/en/getfile/1970/1/documents/sustainability-11-02657-v3.pdf (6450 KB)

    See also: https://www.mdpi.com/2071-1050/11/9/2657

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Time’s arrow in stochastic characterization and simulation of atmospheric and hydrological processes, Hydrological Sciences Journal, 64 (9), 1013–1037, doi:10.1080/02626667.2019.1600700, 2019.

    Time’s arrow has important philosophical, scientific and technical connotations and is closely related to randomness as well as to causality. Stochastics offers a frame to explore, characterize and simulate irreversibility in natural processes. Indicators of irreversibility are different if we study a single process alone, or more processes simultaneously. In the former case, description of irreversibility requires at least third-order properties, while in the latter lagged second-order properties may suffice to reveal causal relations. Several examined data sets indicate that in atmospheric processes irreversibility is negligible at hydrologically relevant time scales, but may exist at the finest scales. However, the irreversibility of streamflow is marked for scales of several days and this highlights the need to reproduce it in flood simulations. For this reason, two methods of generating time series with irreversibility are developed, from which one, based on an asymmetric moving average scheme, proves to be satisfactory.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Brunner, M. I., A. Bárdossy, and R. Furrer, Technical note: Stochastic simulation of streamflow time series using phase randomization, Hydrology and Earth System Sciences, 23, 3175-3187, doi:10.5194/hess-23-3175-2019, 2019.

  1. E. Volpi, A. Fiori, S. Grimaldi, F. Lombardo, and D. Koutsoyiannis, Save hydrological observations! Return period estimation without data decimation, Journal of Hydrology, doi:10.1016/j.jhydrol.2019.02.017, 2019.

    The concept of return period and its estimation are pivotal in risk management for many geophysical applications. Return period is usually estimated by inferring a probability distribution from an observed series of the random process of interest and then applying the classical equation, i.e. the inverse of the exceedance probability. Traditionally, we form a statistical sample by selecting, from the ”complete” time series (e.g. at the daily scale), those values that can reasonably be considered as realizations of independent extremes, e.g. annual maxima or peaks over a certain high threshold. Such a selection procedure entails that a large number of observations are discarded; this wastage of information could have important consequences in practical problems, where the reduction of the already small size of common hydrological records significantly affects the reliability of the estimates. Under such circumstances, it is crucial to exploit all the available information. To this end, we investigate the advantages of estimating the return period without any data decimation, by using the full data-set. The proposed procedure, denoted as Complete Time-series Analysis (CTA), exploits the property that the average interarrival time (i.e. return period) of potentially damaging events is not affected by the dependence structure of the underlying process, even for cyclo-stationary (e.g. seasonal) processes. For the sake of illustration, the CTA is compared to that based on annual maxima selection, through a simple non-parametric approach, discussing advantages and limitations of the method. Results suggest that the proposed CTA approach provides a more conservative return period estimation in an holistic implementation framework within a broader range of return period values than that pertaining to other methods, which means not only the largest extremes that are the focus of extreme value theory.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Knowable moments for high-order stochastic characterization and modelling of hydrological processes, Hydrological Sciences Journal, 64 (1), 19–33, doi:10.1080/02626667.2018.1556794, 2019.

    Classical moments, raw or central, express important theoretical properties of probability distributions but can hardly be estimated from typical hydrological samples for orders beyond two. L-moments are better estimated, but they all are of first order in terms of the process of interest; while they are effective in inferring the marginal distribution of stochastic processes, they cannot characterize even secondorder dependence of processes (autocovariance, climacogram, power spectrum) and thus they cannot help in stochastic modelling. Picking from both categories, we introduce knowable (K-) moments, which combine advantages of both classical and L-moments, and enable reliable estimation from samples and effective description of high-order statistics, useful for marginal and joint distributions of stochastic processes. Further, we extend recent stochastic tools by introducing the K-climacogram and the K-climacospectrum, which enable characterization, in terms of univariate functions, of high-order properties of stochastic processes, as well as preservation thereof in simulations.

    Remarks:

    Free e-prints: https://www.tandfonline.com/eprint/vqPitmiKgeNpgbHXxHHR/full?target=10.1080/02626667.2018.1556794

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. T. Iliopoulou, C. Aguilar , B. Arheimer, M. Bermúdez, N. Bezak, A. Ficchi, D. Koutsoyiannis, J. Parajka, M. J. Polo, G. Thirel, and A. Montanari, A large sample analysis of European rivers on seasonal river flow correlation and its physical drivers, Hydrology and Earth System Sciences, 23, 73–91, doi:10.5194/hess-23-73-2019, 2019.

    The geophysical and hydrological processes governing river flow formation exhibit persistence at several timescales, which may manifest itself with the presence of positive seasonal correlation of streamflow at several different time lags. We investigate here how persistence propagates along subsequent seasons and affects low and high flows. We define the high-flow season (HFS) and the low-flow season (LFS) as the 3-month and the 1-month periods which usually exhibit the higher and lower river flows, respectively. A dataset of 224 rivers from six European countries spanning more than 50 years of daily flow data is exploited. We compute the lagged seasonal correlation between selected river flow signatures, in HFS and LFS, and the average river flow in the antecedent months. Signatures are peak and average river flow for HFS and LFS, respectively. We investigate the links between seasonal streamflow correlation and various physiographic catchment characteristics and hydro-climatic properties. We find persistence to be more intense for LFS signatures than HFS. To exploit the seasonal correlation in the frequency estimation of high and low flows, we fit a bi-variate meta-Gaussian probability distribution to the selected flow signatures and average flow in the antecedent months in order to condition the distribution of high and low flows in the HFS and LFS, respectively, upon river flow observations in the previous months. The benefit of the suggested methodology is demonstrated by updating the frequency distribution of high and low flows one season in advance in a real-world case. Our findings suggest that there is a traceable physical basis for river memory which, in turn, can be statistically assimilated into high- and low-flow frequency estimation to reduce uncertainty and improve predictions for technical purposes.

    Full text: http://www.itia.ntua.gr/en/getfile/1927/1/documents/hess-23-73-2019.pdf (6166 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Koskinas, A. Tegos, P. Tsira, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and Τ. Williamson, Insights into the Oroville Dam 2017 spillway incident, Geosciences, 9 (37), doi:10.3390/geosciences9010037, 2019.

    In February 2017, a failure occurring in Oroville Dam’s main spillway risked causing severe damages downstream. A unique aspect of this incident was the fact that it happened during a flood scenario well within its design and operational procedures, prompting research into its causes and determining methods to prevent similar events from reoccurring. In this study, a hydroclimatic analysis of Oroville Dam’s catchment is conducted, along with a review of related design and operational manuals. The data available allows for the comparison of older flood-frequency analyses to new alternative methods proposed in this paper and relevant literature. Based on summary characteristics of the 2017 floods, possible causes of the incident are outlined, in order to understand which factors contributed more significantly. It turns out that the event was most likely the result of a structural problem in the dam’s main spillway and detrimental geological conditions, but analysis of surface level data also reveals operational issues that were not present during previous larger floods, promoting a discussion about flood control design methods, specifications, and dam inspection procedures, and how these can be improved to prevent a similar event from occurring in the future.

    Full text: http://www.itia.ntua.gr/en/getfile/1926/1/documents/geosciences-09-00037-2.pdf (6834 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes, Stochastic Environmental Research & Risk Assessment, doi:10.1007/s00477-018-1638-6, 2019.

    Research within the field of hydrology often focuses on the statistical problem of comparing stochastic to machine learning (ML) forecasting methods. The performed comparisons are based on case studies, while a study providing large-scale results on the subject is missing. Herein, we compare 11 stochastic and 9 ML methods regarding their multi-step ahead forecasting properties by conducting 12 extensive computational experiments based on simulations. Each of these experiments uses 2000 time series generated by linear stationary stochastic processes. We conduct each simulation experiment twice; the first time using time series of 100 values and the second time using time series of 300 values. Additionally, we conduct a real-world experiment using 405 mean annual river discharge time series of 100 values. We quantify the forecasting performance of the methods using 18 metrics. The results indicate that stochastic and ML methods may produce equally useful forecasts.

    Remarks:

    Supplementary information: https://doi.org/10.6084/m9.figshare.7092824.v1

    Additional material:

  1. P. Dimitriadis, K. Tzouka, D. Koutsoyiannis, H. Tyralis, A. Kalamioti, E. Lerias, and P. Voudouris, Stochastic investigation of long-term persistence in two-dimensional images of rocks, Spatial Statistics, 29, 177–191, doi:10.1016/j.spasta.2018.11.002, 2019.

    Determining the geophysical properties of rocks and geological formations is of high importance in many fields such as geotechnical engineering. In this study, we investigate the second-order dependence structure of spatial (two-dimensional) processes through the statistical perspective of variance vs. scale (else known as the climacogram) instead of covariance vs. lag (e.g. autocovariance, variogram etc.) or power vs. frequency (e.g. power spectrum, scaleogram, wavelet transform etc.) which traditionally are applied. In particular, we implement a two-dimensional (visual) estimator, adjusted for bias and for unknown process mean, through the (plot of) variance of the space-averaged process vs. the spatial scale. Additionally, we attempt to link the climacogram to the type of rocks and provide evidence on stochastic similarities in certain of their characteristics, such as mineralogical composition and resolution. To this end, we investigate two-dimensional spatial images of rocks in terms of their stochastic microstructure as estimated by the climacogram. The analysis is based both on microscale and macroscale data extracted from grayscale images of rocks. Interestingly, a power-law drop of variance vs. scale (or else known as long-term persistence) is detected in all scales presenting a similar power-exponent. Furthermore, the strengths and limitations of the climacogram as a stochastic tool are discussed and compared with the traditional tool in spatial statistics, the variogram. We show that the former has considerable strengths for detecting the long-range dependence in spatial statistics.

    Remarks:

    Share Link: https://authors.elsevier.com/c/1YJjr7su79fMuR

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Univariate time series forecasting of temperature and precipitation with a focus on machine learning algorithms: a multiple-case study from Greece, Water Resources Management, 32 (15), 5207–5239, doi:10.1007/s11269-018-2155-6, 2018.

    We provide contingent empirical evidence on the solutions to three problems associated with univariate time series forecasting using machine learning (ML) algorithms by conducting an extensive multiple-case study. These problems are: (a) lagged variable selection, (b) hyperparameter handling, and (c) comparison between ML and classical algorithms. The multiple-case study is composed by 50 single-case studies, which use time series of mean monthly temperature and total monthly precipitation observed in Greece. We focus on two ML algorithms, i.e. neural networks and support vector machines, while we also include four classical algorithms and a naïve benchmark in the comparisons. We apply a fixed methodology to each individual case and, subsequently, we perform a cross-case synthesis to facilitate the detection of systematic patterns. We fit the models to the deseasonalized time series. We compare the one- and multi-step ahead forecasting performance of the algorithms. Regarding the one-step ahead forecasting performance, the assessment is based on the absolute error of the forecast of the last monthly observation. For the quantification of the multi-step ahead forecasting performance we compute five metrics on the test set (last year’s monthly observations), i.e. the root mean square error, the Nash-Sutcliffe efficiency, the ratio of standard deviations, the coefficient of correlation and the index of agreement. The evidence derived by the experiments can be summarized as follows: (a) the results mostly favour using less recent lagged variables, (b) hyperparameter optimization does not necessarily lead to better forecasts, (c) the ML and classical algorithms seem to be equally competitive.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. T. Iliopoulou, D. Koutsoyiannis, and A. Montanari, Characterizing and modeling seasonality in extreme rainfall, Water Resources Research, 54 (9), 6242–6258, doi:10.1029/2018WR023360, 2018.

    A comprehensive understanding of seasonality in extreme rainfall is essential for climate studies, flood prediction and various hydrological applications such as scheduling season‐specific engineering works, intra‐annual management of reservoirs, seasonal flood risk mitigation and stormwater management. To identify seasonality in extreme rainfall and quantify its impact in a theoretically consistent yet practically appealing manner, we investigate a dataset of 27 daily rainfall records spanning at least 150 years. We aim to objectively identify periods within the year with distinct seasonal properties of extreme rainfall by employing the Akaike Information Criterion (AIC). Optimal partitioning of seasons is identified by minimizing the within‐season variability of extremes. The statistics of annual and seasonal extremes are evaluated by fitting a generalized extreme value (GEV) distribution to the annual and seasonal block maxima series. The results indicate that seasonal properties of rainfall extremes mainly affect the average values of seasonal maxima and their variability, while the shape of their probability distribution and its tail do not substantially vary from season to season. Uncertainty in the estimation of the GEV parameters is quantified by employing three different estimation methods (Maximum Likelihood, Method of Moments and Least Squares) and the opportunity for joint parameter estimation of seasonal and annual probability distributions of extremes is discussed. The effectiveness of the proposed scheme for seasonal characterization and modeling is highlighted when contrasted to results obtained from the conventional approach of using fixed climatological seasons.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. N. Malamos, and D. Koutsoyiannis, Field survey and modelling of irrigation water quality indices in a Mediterranean island catchment: A comparison between spatial interpolation methods, Hydrological Sciences Journal, 63 (10), 1447–1467, doi:10.1080/02626667.2018.1508874, 2018.

    A biannual survey of physico-chemical quality indices of 104 irrigation-water wells located in a cultivated plain of a Mediterranean island catchment was conducted using a multi-parameter probe. The campaign was planned so as to differentiate between the dry and wet seasons. The acquired data constituted the test bed for evaluating the results and the features of four spatial interpolation methods, i.e. ordinary kriging, universal kriging, inverse distance weighted and nearest neighbours, against those of the recently introduced bilinear surface smoothing (BSS). In several cases, BSS outperformed the other interpolation methods, especially during the two-fold cross-validation procedure. The study emphasizes the fact that both in situ measurements and good mathematical techniques for studying the spatial distribution of water quality indices are pivotal to agricultural practice management. In the specific case studied, the spatio-temporal variability of water quality parameters and the need for monitoring were evident, as low irrigation water quality was encountered throughout the study area.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, A stochastic model for the hourly solar radiation process for application in renewable resources management, Advances in Geosciences, 45, 139–145, doi:10.5194/adgeo-45-139-2018, 2018.

    Since the beginning of the 21st century, the scientific community has made huge leaps to exploit renewable energy sources, with solar radiation being one of the most important. However, the variability of solar radiation has a significant impact on solar energy conversion systems, such as in photovoltaic systems, characterized by a fast and nonlinear response to incident solar radiation. The performance prediction of these systems is typically based on hourly or daily data because those are usually available at these time scales. The aim of this work is to investigate the stochastic nature and time evolution of the solar radiation process for daily and hourly scale, with the ultimate goal of creating a new cyclostationary stochastic model capable of reproducing the dependence structure and the marginal distribution of hourly solar radiation via the clearness index KT .

    Full text: http://www.itia.ntua.gr/en/getfile/1867/1/documents/adgeo-45-139-2018.pdf (4911 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. N. Quinn, G. Blöschl, A. Bardossy, A. Castellarin, M. Clark, C. Cudennec, D. Koutsoyiannis, U. Lall, L. Lichner, J. Parajka, C.D. Peters-Lidard, G. Sander, H. H. G. Savenije, K. Smettem, H. Vereecken, A. Viglione, P. Willems, A. Wood, R. Woods, C.-Y. Xu, and E. Zehe, Invigorating hydrological research through journal publications, Hydrological Sciences Journal, 63 (8), 1113–1117, doi:10.1080/02626667.2018.1496632, 2018.

    Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union—EGU in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals

    Remarks:

    The Joint Editorial has been published in:

    Full text: http://www.itia.ntua.gr/en/getfile/1865/1/documents/2018_HSJ_InvigoratingHydrologicalResearch.pdf (122 KB)

    Works that cite this document: View on Google Scholar, ResearchGate, Google Scholar (alternative) or ResearchGate (alternative)

  1. E. Klousakou, M. Chalakatevaki, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, G. Karakatsanis, A. Efstratiadis, N. Mamassis, R. Tomani, E. Chardavellas, and D. Koutsoyiannis, A preliminary stochastic analysis of the uncertainty of natural processes related to renewable energy resources, Advances in Geosciences, 45, 193–199, doi:10.5194/adgeo-45-193-2018, 2018.

    The ever-increasing energy demand has led to overexploitation of fossil fuels deposits, while renewables offer a viable alternative. Since renewable energy resources derive from phenomena related to either atmospheric or geophysical processes, unpredictability is inherent to renewable energy systems. An innovative and simple stochastic tool, the climacogram, was chosen to explore the degree of unpredictability. By applying the climacogram across the related timeseries and spatial-series it was feasible to identify the degree of unpredictability in each process through the Hurst parameter, an index that quantifies the level of uncertainty. All examined processes display a Hurst parameter larger than 0.5, indicating increased uncertainty on the long term. This implies that only through stochastic analysis may renewable energy resources be reliably manageable and cost efficient. In this context, a pilot application of a hybrid renewable energy system in the Greek island of Astypalaia is discussed, for which we show how the uncertainty (in terms of variability) of the input hydrometeorological processes alters the uncertainty of the output energy values.

    Full text: http://www.itia.ntua.gr/en/getfile/1864/1/documents/adgeo-45-193-2018.pdf (559 KB)

    See also: https://www.adv-geosci.net/45/193/2018/

    Works that cite this document: View on Google Scholar or ResearchGate

  1. I. Tsoukalas, C. Makropoulos, and D. Koutsoyiannis, Simulation of stochastic processes exhibiting any-range dependence and arbitrary marginal distributions, Water Resources Research, 54 (11), 9484–9513, doi:10.1029/2017WR022462, 2018.

    Hydrometeorological processes are typically characterized by temporal dependence, short‐ or long‐range (e.g., Hurst behavior), as well as by non‐Gaussian distributions (especially at fine time scales). The generation of long synthetic time series that resemble the marginal and joint properties of the observed ones is a prerequisite in many uncertainty‐related hydrological studies, since they can be used as inputs and hence allow the propagation of natural variability and uncertainty to the typically deterministic water‐system models. For this reason, it has been for years one of the main research topics in the field of stochastic hydrology. This work presents a novel model for synthetic time series generation, termed Symmetric Moving Average (neaRly) To Anything (SMARTA), that holds out the promise of simulating stationary univariate and multivariate processes with any‐range dependence and arbitrary marginal distributions, provided that the former is feasible and the latter have finite variance. This is accomplished by utilizing a mapping procedure in combination with the relationship that exists between the correlation coefficients of an auxiliary Gaussian process and a non‐Gaussian one, formalized through the Nataf's joint distribution model. The generality of SMARTA is stressed through two hypothetical simulation studies (univariate and multivariate), characterized by different dependencies and distributions. Furthermore, we demonstrate the practical aspects of the proposed model through two real‐world cases, one that concerns the generation of annual non‐Gaussian streamflow time series at four stations, and another that involves the synthesis of intermittent, non‐Gaussian, daily rainfall series at a single location.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Brunner, M. I., A. Bárdossy, and R. Furrer, Technical note: Stochastic simulation of streamflow time series using phase randomization, Hydrology and Earth System Sciences, 23, 3175-3187, doi:10.5194/hess-23-3175-2019, 2019.
    2. Cheng, Y., P. Feng, J. Li, Y. Guo, and P. Ren, Water supply risk analysis based on runoff sequence simulation with change point under changing environment, Advances in Meteorology, 9619254, doi:10.1155/2019/9619254, 2019.
    3. #Elsayed, H., S. Djordjević, and D. Savić, The Nile water, food and energy nexus – A system dynamics model, 7th International Computing & Control for the Water Industry Conference, Exeter, United Kingdom, 2019.

  1. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Predictability of monthly temperature and precipitation using automatic time series forecasting methods, Acta Geophysica, 66 (4), 807–831, doi:10.1007/s11600-018-0120-7, 2018.

    We investigate the predictability of monthly temperature and precipitation by applying automatic univariate time series forecasting methods to a sample of 985 40-year long monthly temperature and 1552 40-year long monthly precipitation time series. The methods include a naïve one based on the monthly values of the last year, as well as the random walk (with drift), AutoRegressive Fractionally Integrated Moving Average (ARFIMA), exponential smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components (BATS), simple exponential smoothing, Theta and Prophet methods. Prophet is a recently introduced model inspired by the nature of time series forecasted at Facebook and has not been applied to hydrometeorological time series before, while the use of random walk, BATS, simple exponential smoothing and Theta is rare in hydrology. The methods are tested in performing multi-step ahead forecasts for the last 48 months of the data. We further investigate how different choices of handling the seasonality and non-normality affect the performance of the models. The results indicate that (a) all the examined methods apart from the naïve and random walk ones are accurate enough to be used in long-term applications, (b) monthly temperature and precipitation can be forecasted to a level of accuracy which can barely be improved using other methods, (c) the externally applied classical seasonal decomposition results mostly in better forecasts compared to the automatic seasonal decomposition used by the BATS and Prophet methods and (d) Prophet is competitive, especially when it is combined with externally applied classical seasonal decomposition

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, One-step ahead forecasting of geophysical processes within a purely statistical framework, Geoscience Letters, 5, 12, doi:10.1186/s40562-018-0111-1, 2018.

    The simplest way to forecast geophysical processes, an engineering problem with a widely recognized challenging character, is the so-called “univariate time series forecasting” that can be implemented using stochastic or machine learning regression models within a purely statistical framework. Regression models are in general fast-implemented, in contrast to the computationally intensive Global Circulation Models, which constitute the most frequently used alternative for precipitation and temperature forecasting. For their simplicity and easy applicability, the former have been proposed as benchmarks for the latter by forecasting scientists. Herein, we assess the one-step ahead forecasting performance of 20 univariate time series forecasting methods, when applied to a large number of geophysical and simulated time series of 91 values. We use two real-world annual datasets, a dataset composed by 112 time series of precipitation and another composed by 185 time series of temperature, as well as their respective standardized datasets, to conduct several real-world experiments. We further conduct large-scale experiments using 12 simulated datasets. These datasets contain 24,000 time series in total, which are simulated using stochastic models from the families of AutoRegressive Moving Average and AutoRegressive Fractionally Integrated Moving Average. We use the frst 50, 60, 70, 80 and 90 data points for model-ftting and model-validation, and make predictions corresponding to the 51st, 61st, 71st, 81st and 91st respectively. The total number of forecasts produced herein is 2,177,520, among which 47,520 are obtained using the real-world datasets. The assessment is based on eight error metrics and accuracy statistics. The simulation experiments reveal the most and least accurate methods for long-term forecasting applications, also suggesting that the simple methods may be competitive in specifc cases. Regarding the results of the realworld experiments using the original (standardized) time series, the minimum and maximum medians of the absolute errors are found to be 68 mm (0.55) and 189 mm (1.42) respectively for precipitation, and 0.23 °C (0.33) and 1.10 °C (1.46) respectively for temperature. Since there is an absence of relevant information in the literature, the numerical results obtained using the standardized real-world datasets could be used as rough benchmarks for the one-step ahead predictability of annual precipitation and temperature

    Full text: http://www.itia.ntua.gr/en/getfile/1834/1/documents/s40562-018-0111-1.pdf (3083 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. H. Tyralis, P. Dimitriadis, D. Koutsoyiannis, P.E. O’Connell, K. Tzouka, and T. Iliopoulou, On the long-range dependence properties of annual precipitation using a global network of instrumental measurements, Advances in Water Resources, 111, 301–318, doi:10.1016/j.advwatres.2017.11.010, 2018.

    The long-range dependence (LRD) is considered an inherent property of geophysical processes, whose presence increases uncertainty. Here we examine the spatial behaviour of LRD in precipitation by regressing the Hurst parameter estimate of mean annual precipitation instrumental data which span from 1916-2015 and cover a big area of the earth’s surface on location characteristics of the instrumental data stations. Furthermore, we apply the Mann-Kendall test under the LRD assumption (MKt-LRD) to reassess the significance of observed trends. To summarize the results, the LRD is spatially clustered, it seems to depend mostly on the location of the stations, while the predictive value of the regression model is good. Thus when investigating for LRD properties we recommend that the local characteristics should be considered. The application of the MKt-LRD suggests that no significant monotonic trend appears in global precipitation, excluding the climate type D (snow) regions in which positive significant trends appear.

    Remarks:

    Supplementary information files are hosted at: https://doi.org/10.6084/m9.figshare.4892447.v1

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, and D. Koutsoyiannis, Stochastic synthesis approximating any process dependence and distribution, Stochastic Environmental Research & Risk Assessment, 32 (6), 1493–1515, doi:10.1007/s00477-018-1540-2, 2018.

    An extension of the symmetric-moving-average (SMA) scheme is presented for stochastic synthesis of a stationary process for approximating any dependence structure and marginal distribution. The extended SMA model can exactly preserve an arbitrary second-order structure as well as the high order moments of a process, thus enabling a better approximation of any type of dependence (through the second-order statistics) and marginal distribution function (through statistical moments), respectively. Interestingly, by explicitly preserving the coefficient of kurtosis, it can also simulate certain aspects of intermittency, often characterizing the geophysical processes. Several applications with alternative hypothetical marginal distributions, as well as with real world processes, such as precipitation, wind speed and grid-turbulence, highlight the scheme’s wide range of applicability in stochastic generation and Monte-Carlo analysis. Particular emphasis is given on turbulence, in an attempt to simulate in a simple way several of its characteristics regarded as puzzles.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Park, J., C. Onof, and D. Kim, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, 23, 989-1014, doi:10.5194/hess-23-989-2019, 2019.

  1. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, 556, 980–992, doi:10.1016/j.jhydrol.2016.07.015, 2018.

    Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 minute time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-minute time scale. The applicability of the methodology was assessed on a 5-minute rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

    Remarks:

    Temporary free access: https://authors.elsevier.com/c/1WHlB52cuBmT2

    Additional material:

    See also: http://dx.doi.org/10.1016/j.jhydrol.2016.07.015

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Shrestha, A., M. S. Babel, S. Weesakul, and Z. Vojinovic, Developing intensity–duration–frequency (IDF) curves under climate change uncertainty: The case of Bangkok, Thailand, Water, 9(2), 145, doi:10.3390/w9020145, 2017.
    2. Li, X., A. Meshgi, X. Wang, J. Zhang, S. H. X. Tay, G. Pijcke, N. Manocha, M. Ong, M. T. Nguyen, and V. Babovic, Three resampling approaches based on method of fragments for daily-to-subdaily precipitation disaggregation, International Journal of Climatology, doi:10.1002/joc.5438, 2018.
    3. Papalexiou, S. M., Y. Markonis, F. Lombardo, A. AghaKouchak, and E. Foufoula‐Georgiou, Precise temporal Disaggregation Preserving Marginals and Correlations (DiPMaC) for stationary and non‐stationary processes, Water Resources Research, doi:10.1029/2018WR022726, 2018.
    4. Park, J., C. Onof, and D. Kim, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, 23, 989-1014, doi:10.5194/hess-23-989-2019, 2019.
    5. Onof, C., and L.-P. Wang, Modelling rainfall with a Bartlett–Lewis process: New developments, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2019-406, 2019.

  1. T. Iliopoulou, S.M. Papalexiou, Y. Markonis, and D. Koutsoyiannis, Revisiting long-range dependence in annual precipitation, Journal of Hydrology, 556, 891–900, doi:10.1016/j.jhydrol.2016.04.015, 2018.

    Long-range dependence (LRD), the so-called Hurst-Kolmogorov behaviour, is considered to be an intrinsic characteristic of most natural processes. This behaviour manifests itself by the prevalence of slowly decaying autocorrelation function and questions the Markov assumption, often habitually employed in time series analysis. Herein, we investigate the dependence structure of annual rainfall using a large set, comprising more than a thousand stations worldwide of length 100 years or more, as well as a smaller number of paleoclimatic reconstructions covering the last 12,000 years. Our findings suggest weak long-term persistence for instrumental data (average H = 0.59), which becomes stronger with scale, i.e. in the paleoclimatic reconstructions (average H = 0.75).

    Additional material:

    See also: http://dx.doi.org/10.1016/j.jhydrol.2016.04.015

    Works that cite this document: View on Google Scholar or ResearchGate

  1. N. Malamos, I. L. Tsirogiannis, A. Tegos, A. Efstratiadis, and D. Koutsoyiannis, Spatial interpolation of potential evapotranspiration for precision irrigation purposes, European Water, 59, 303–309, 2017.

    Precision irrigation constitutes a breakthrough for agricultural water management since it provides means to optimal water use. In recent years several applications of precision irrigation are implemented based on spatial data from different origins, i.e. meteorological stations networks, remote sensing data and in situ measurements. One of the factors affecting optimal irrigation system design and management is the daily potential evapotranspiration (PET). A commonly used approach is to estimate the daily PET for the representative day of each month during the irrigation period. In the present study, the implementation of the recently introduced non-parametric bilinear surface smoothing (BSS) methodology for spatial interpolation of daily PET is presented. The study area was the plain of Arta which is located at the Region of Epirus at the North West Greece. Daily PET was estimated according to the FAO Penman-Monteith methodology with data collected from a network of six agrometeorological stations, installed in early 2015 in selected locations throughout the study area. For exploration purposes, we produced PET maps for the Julian dates: 105, 135, 162, 199, 229 and 259, thus covering the entire irrigation period of 2015. Also, comparison and cross validation against the calculated FAO Penman-Monteith PET for each station, were performed between BSS and a commonly used interpolation method, i.e. inverse distance weighted (IDW). During the leave-one-out cross validation procedure, BSS yielded very good results, outperforming IDW. Given the simplicity of the BSS, its overall performance is satisfactory, providing maps that represent the spatial and temporal variation of daily PET.

    Full text: http://www.itia.ntua.gr/en/getfile/1776/1/documents/EW_2017_59_41_2HOxTxv.pdf (4259 KB)

    See also: http://ewra.net/ew/pdf/EW_2017_59_41.pdf

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Ndiaye, P. M., A. Bodian, L. Diop, A. Deme, A. Dezetter, K. Djaman, and A. Ogilvie, Trend and sensitivity analysis of reference evapotranspiration in the Senegal river basin using NASA meteorological data, Water, 12(7), 1957, doi:10.3390/w12071957, 2020.
    2. Ndiaye, P. M., A. Bodian, L. Diop, A. Dezetter, E. Guilpart, A. Deme, and A. Ogilvie, Future trend and sensitivity analysis of evapotranspiration in the Senegal River Basin, Journal of Hydrology: Regional Studies, 35, 100820, doi:10.1016/j.ejrh.2021.100820, 2021.
    3. Dimitriadou S., and K. G. Nikolakopoulos, Reference evapotranspiration (ETo) methods implemented as ArcMap models with remote-sensed and ground-based inputs, examined along with MODIS ET, for Peloponnese, Greece, ISPRS International Journal of Geo-Information, 10(6), 390, doi:10.3390/ijgi10060390, 2021.
    4. #Dimitriadou, S., and K. G. Nikolakopoulos, Development of GIS models via optical programming and python scripts to implement four empirical methods of reference and actual evapotranspiration (ETo, ETa) incorporating MODIS LST inputs, Proc. SPIE 11856, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII, 118560K, doi:10.1117/12.2597724, 2021.

  1. G. Papacharalampous, H. Tyralis, and D. Koutsoyiannis, Forecasting of geophysical processes using stochastic and machine learning algorithms, European Water, 59, 161–168, 2017.

    We perform an extensive comparison between four stochastic and two machine learning (ML) forecasting algorithms by conducting a multiple-case study. The latter is composed by 50 single-case studies, which use time series of total monthly precipitation and mean monthly temperature observed in Greece. We apply a fixed methodology to each individual case and, subsequently, we perform a cross-case synthesis to facilitate the detection of systematic patterns. The stochastic algorithms include the Autoregressive order one model, an algorithm from the family of Autoregressive Fractionally Integrated Moving Average models, an Exponential Smoothing State Space algorithm and the Theta algorithm, while the ML algorithms are Neural Networks and Support Vector Machines. We also use the last observation as a Naïve benchmark in the comparisons. We apply the forecasting methods to the deseasonalized time series. We compare the one-step ahead as also the multi-step ahead forecasting properties of the algorithms. Regarding the one-step ahead forecasting properties, the assessment is based on the absolute error of the forecast of the last observation. For the comparison of the multi-step ahead forecasting properties we use five metrics applied to the test set (last twelve observations), i.e. the root mean square error, the Nash-Sutcliffe efficiency, the ratio of standard deviations, the index of agreement and the coefficient of correlation. Concerning the ML algorithms, we also perform a sensitivity analysis for time lag selection. Additionally, we compare more sophisticated ML methods as regards to the hyperparameter optimization to simple ones.

    Full text: http://www.itia.ntua.gr/en/getfile/1768/1/documents/EW_2017_59_22.pdf (1163 KB)

    See also: http://www.ewra.net/ew/issue_59.htm

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Entropy production in stochastics, Entropy, 19 (11), 581, doi:10.3390/e19110581, 2017.

    While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT) or conditionally on the past and present having been observed (CEPLT). We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.

    Full text:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Tegos, N. Malamos, A. Efstratiadis, I. Tsoukalas, A. Karanasios, and D. Koutsoyiannis, Parametric modelling of potential evapotranspiration: a global survey, Water, 9 (10), 795, doi:10.3390/w9100795, 2017.

    We present and validate a global parametric model of potential evapotranspiration (PET) with two parameters which are estimated through calibration, using as explanatory variables temperature and extraterrestrial radiation. The model and the parameters estimation approach were tested over the globe, using the FAO CLIMWAT database that provides monthly averaged values of meteorological inputs at 4300 locations worldwide. A preliminary analysis of these data allowed explaining the major drivers of PET over the globe and across seasons. Next, we developed an automatic optimization software tool to calibrate the model and provide point PET estimations against the given Penman-Monteith values. We also employed extended analysis of model inputs and outputs, including the production of global maps of optimized model parameters and associated performance metrics. Also, we employed interpolated values of the optimized parameters to validate the predictive capacity of our model against monthly meteorological time series, at several stations worldwide. The results were very encouraging, since even with the use of abstract climatic information for model calibration and the use of interpolated parameters as local predictors, the model generally ensures reliable PET estimations. In few cases the model performs poorly in estimating the reference PET, due to irregular interactions between temperature and extraterrestrial radiation, as well as because the associated processes are influenced by additional drivers, e.g. relative humidity and wind speed. However, the analysis of the residuals showed that the model is consistent in terms of parameters estimation and model validation. The provided parameters maps allow the direct use of the parametric model wherever in the world, providing PET estimates in case of missing data, that can be further improved even with a short term acquisition of meteorological data.

    Full text: http://www.itia.ntua.gr/en/getfile/1738/2/documents/water-09-00795.pdf (6428 KB)

    Additional material:

    See also: http://www.mdpi.com/2073-4441/9/10/795

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Elferchichi, A., G. A. Giorgio, N. Lamaddalena, M. Ragosta, and V. Telesca, Variability of temperature and its impact on reference evapotranspiration: the test case of the Apulia region (Southern Italy), Sustainability, 9(12), 2337, doi:10.3390/su9122337, 2017.
    2. Li, M., R. Chu, S. Shen, and A. R. T. Islam, Quantifying climatic impact on reference evapotranspiration trends in the Huai River Basin of Eastern China, Water, 10(2), 144, doi:10.3390/w10020144, 2018.
    3. Yan, N., F. Tian, B. Wu, W. Zhu, and M. Yu, Spatiotemporal analysis of actual evapotranspiration and its causes in the Hai basin, Remote Sensing, 10(2), 332; doi:10.3390/rs10020332, 2018.
    4. Li, M., R. Chu, A.R.M.T. Islam, and S. Shen, Reference evapotranspiration variation analysis and its approaches evaluation of 13 empirical models in sub-humid and humid regions: A case study of the Huai River Basin, Eastern China, Water, 10(4), 493, doi:10.3390/w10040493, 2018.
    5. Hao, X., S. Zhang, W. Li, W. Duan, G. Fang, Y. Zhang , and B. Guo, The uncertainty of Penman-Monteith method and the energy balance closure problem, Journal of Geophysical Research – Atmospheres, 123(14), 7433-7443, doi:10.1029/2018JD028371, 2018.
    6. Giménez, P. O., and S. G. García-Galiano, Assessing Regional Climate Models (RCMs) ensemble-driven reference evapotranspiration over Spain, Water, 10(9), 1181, doi:10.3390/w10091181, 2018.
    7. Storm, M. E., R. Gouws, and L. J. Grobler, Novel measurement and verification of irrigation pumping energy conservation under incentive-based programmes, Journal of Energy in Southern Africa, 29(3), 10–21, doi:10.17159/2413-3051/2018/v29i3a3058, 2018.
    8. Tam, B. Y., K. Szeto, B. Bonsal, G. Flato, A. J. Cannon, and R. Rong, CMIP5 drought projections in Canada based on the Standardized Precipitation Evapotranspiration Index, Canadian Water Resources Journal, 44(1), 90-107, doi:10.1080/07011784.2018.1537812, 2019.
    9. Dalezios, N. R., N. Dercas, A. Blanta, and I. N. Faraslis, Remote sensing in water balance modelling for evapotranspiration at a rural watershed in Central Greece, International Journal of Sustainable Agricultural Management and Informatics, 4(3-4), 306-337, doi:10.1504/IJSAMI.2018.099219, 2019.
    10. Gan, G., Y. Liu, X. Pan, X. Zhao, M. Li, and S. Wang, Testing the symmetric assumption of complementary relationship: A comparison between the linear and nonlinear advection-aridity models in a large ephemeral lake, Water, 11(8), 1574, doi:10.3390/w11081574, 2019.
    11. Zhang, T., Y. Chen, and K. Tha Paw U, Quantifying the impact of climate variables on reference evapotranspiration in Pearl River Basin, China, Hydrological Sciences Journal, 64(16), 1944-1956, doi:10.1080/02626667.2019.1662021, 2019.
    12. Hua, D., X. Hao, Y. Zhang, and J. Qin, Uncertainty assessment of potential evapotranspiration in arid areas, as estimated by the Penman-Monteith method, Journal of Arid Land, 12, 166–180, doi:10.1007/s40333-020-0093-7, 2020.
    13. Shirmohammadi-Aliakbarkhani, Z., and S. F. Saberali, Evaluating of eight evapotranspiration estimation methods in arid regions of Iran, Agricultural Water Management, 239, 106243, doi:10.1016/j.agwat.2020.106243, 2020.
    14. Kim, C.-G., J. Lee, J. E. Lee, and H. Kim, Evaluation of improvement effect on the spatial-temporal correction of several reference evapotranspiration methods, Journal of Korea Water Resources Association, 53(9), 701-715, doi:10.3741/JKWRA.2020.53.9.701, 2020.
    15. Gui, Y., Q. Wang, Y. Zhao, Y. Dong, H. Li, S. Jiang, X. He, and K. Liu, Attribution analyses of reference evapotranspiration changes in China incorporating surface resistance change response to elevated CO2, Journal of Hydrology, 599, 126387, doi:10.1016/j.jhydrol.2021.126387, 2021.
    16. Mohanasundaram, S., M. M. Mekonnen, E. Haacker, C. Ray, S. Lim, and S. Shrestha, An application of GRACE mission datasets for streamflow and baseflow estimation in the Conterminous United States basins, Journal of Hydrology, 601, 126622, doi:10.1016/j.jhydrol.2021.126622, 2021.
    17. Gentilucci, M., M. Bufalini, M. Materazzi, M. Barbieri, D. Aringoli, P. Farabollini, and G. Pambianchi, Calculation of potential evapotranspiration and calibration of the Hargreaves equation using geostatistical methods over the last 10 years in Central Italy, Geosciences, 11(8), 348, doi:10.3390/geosciences11080348, 2021.
    18. Hajek, O. L., and A. K. Knapp, Shifting seasonal patterns of water availability: ecosystem responses to an unappreciated dimension of climate change, New Phytologist, doi:10.1111/nph.17728, 2021.
    19. Dos Santos, A. A., J. L. M. de Souza, and S. L. K. Rosa, Evapotranspiration with the Moretti-Jerszurki-Silva model for the Brazilian subtropical climate, Hydrological Sciences Journal, doi:10.1080/02626667.2021.1988610, 2021.
    20. Stefanidis, S., and V. Alexandridis, Precipitation and potential evapotranspiration temporal variability and their relationship in two forest ecosystems in Greece, Hydrology, 8(4), 160, doi:10.3390/hydrology8040160, 2021.

  1. E. Moschos, G. Manou, P. Dimitriadis, V. Afendoulis, D. Koutsoyiannis, and V. Tsoukala, Harnessing wind and wave resources for a Hybrid Renewable Energy System in remote islands: a combined stochastic and deterministic approach, Energy Procedia, 125, 415–424, doi:10.1016/j.egypro.2017.08.084, 2017.

    Wind and wave resources enclose an important portion of the planet’s energy potential. While wind energy has been effectively harnessed through the last decades to substitute other forms of energy production, the utilization of the synergy between wind and wave resource has not yet been adequately investigated. Such a hybrid energy system could prove efficient in covering the needs of non-connected remote islands. A combined deterministic and stochastic methodology is presented in a case study of a remote Aegean island, by assessing a 100-year climate scenario incorporating uncertainty parameters and exploring the possibilities of fully covering its energy demands.

    Full text: http://www.itia.ntua.gr/en/getfile/1737/1/documents/wave_procedia.pdf (2296 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, Investigation on the stochastic nature of the solar radiation process, Energy Procedia, 125, 398–404, 2017.

    A detailed investigation of the variability of solar radiation can be proven useful towards more efficient and sustainable design of renewable resources systems. In this context, we analyze observations from Athens, Greece and we investigate the marginal distribution of the solar radiation process at a daily and hourly step, the long-term behavior based on the annual scale of the process, as well as the double periodicity (diurnal-seasonal) of the process. Finally, we apply a parsimonious double-cyclostationary stochastic model to generate hourly synthetic time series preserving the marginal statistical characteristics, the double periodicity and the dependence structure of the process.

    Full text: http://www.itia.ntua.gr/en/getfile/1736/1/documents/solar_procedia.pdf (804 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. K. Mavroyeoryos, I. Engonopoulos, H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system, Energy Procedia, 125, 435–442, doi:10.1016/j.egypro.2017.08.095, 2017.

    Here we simulate the electrical energy demand in the remote island of Astypalaia. To this end we obtain information regarding the local socioeconomic conditions and energy demand needs. The available hourly demand load data are analyzed at various time scales (hourly, weekly, daily, seasonal). The cross-correlations between the electricity demand load and the mean daily temperature are computed. An exploratory data analysis including all variables is performed to find hidden relationships. Finally, the demand is simulated. The simulation time series will be used in the development of a framework for planning of a hybrid renewable energy system in Astypalaia.

    Full text: http://www.itia.ntua.gr/en/getfile/1735/1/documents/energy_demand_procedia.pdf (1370 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. G. Karakatsanis, D. Roussis, Y. Moustakis, N. Gournari, I. Parara, P. Dimitriadis, and D. Koutsoyiannis, Energy, variability and weather finance engineering, Energy Procedia, 125, 389–397, doi:10.1016/j.egypro.2017.08.073, 2017.

    Weather derivatives comprise efficient financial tools for managing hydrometeorological uncertainties in various markets. With ~46% utilization by the energy industry, weather derivatives are projected to constitute a critical element for dealing with risks of low and medium impacts –contrary to standard insurance contracts that deal with extreme events. In this context, we design and engineer -via Monte Carlo pricing- a weather derivative for a remote island in Greece -powered by an autonomous diesel-fuelled generator- resembling to a standard call option contract to test the benefits for both the island’s public administration and a bank -as the transaction’s counterparty.

    Full text: http://www.itia.ntua.gr/en/getfile/1734/1/documents/weather_finance_procedia.pdf (872 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. M. Chalakatevaki, P. Stamou, S. Karali, V. Daniil, P. Dimitriadis, K. Tzouka, T. Iliopoulou, D. Koutsoyiannis, P. Papanicolaou, and N. Mamassis, Creating the electric energy mix in a non-connected island, Energy Procedia, 125, 425–434, doi:10.1016/j.egypro.2017.08.089, 2017.

    As the electric energy in the non-connected islands is mainly produced by oil-fueled power plants, the unit cost is extremely high due to import cost. The integration of renewable resources in the energy mix is essential for reducing the financial and environmental cost. In this work, various energy resources (renewable and fossil fuels) are evaluated using technical, environmental and economic criteria with an emphasis to biomass, pumped hydro storage and replacement of oil power plants. Finally, a synthesis is presented as a toy-model in an Aegean island that satisfies the electric energy demand including base and peak electric loads.

    Related works:

    • [378] Initial presentation in EGU conference

    Full text: http://www.itia.ntua.gr/en/getfile/1733/1/documents/electric_mix_energy_procedia.pdf (1118 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Bakanos, P. I., and K. L. Katsifarakis, Optimizing operation of a large-scale pumped storage hydropower system coordinated with wind farm by means of genetic algorithm, Global Nest Journal, 2019.
    2. Giudici, F., A. Castelletti, E. Garofalo, M. Giuliani, and H. R. Maier, Dynamic, multi-objective optimal design and operation of water-energy systems for small, off-grid islands, Applied Energy, 250, 605-616, doi:10.1016/j.apenergy.2019.05.084, 2019.

  1. K. Papoulakos, G. Pollakis, Y. Moustakis, A. Markopoulos, T. Iliopoulou, P. Dimitriadis, D. Koutsoyiannis, and A. Efstratiadis, Simulation of water-energy fluxes through small-scale reservoir systems under limited data availability, Energy Procedia, 125, 405–414, doi:10.1016/j.egypro.2017.08.078, 2017.

    We present a stochastic approach accounting for input uncertainties within water-energy simulations. The stochastic paradigm, which allows for quantifying the inherent uncertainty of hydrometeorological processes, becomes even more crucial in case of missing or inadequate information. Our scheme uses simplified conceptual models which are subject to significant uncertainties, to generate the inputs of the overall simulation problem. The methodology is tested in a hypothetical hybrid renewable energy system across the small Aegean island of Astypalaia, comprising a pumped-storage reservoir serving multiple water uses, where both inflows and demands are regarded as random variables as result of stochastic inputs and parameters.

    Related works:

    • [384] Initial presentation in EGU conference

    Full text: http://www.itia.ntua.gr/en/getfile/1732/1/documents/energy_proc_paper.pdf (2324 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Pouliasis, G., G. A. Torres-Alves, and O. Morales-Napoles, Stochastic modeling of hydroclimatic processes using vine copulas, Water, 13(16), 2156, doi:10.3390/w13162156, 2021.

  1. C. Pappas, M.D. Mahecha, D.C. Frank, F. Babst, and D. Koutsoyiannis, Ecosystem functioning is enveloped by hydrometeorological variability, Nature Ecology & Evolution, 1, 1263–1270, doi:10.1038/s41559-017-0277-5, 2017.

    Terrestrial ecosystem processes, and the associated vegetation carbon dynamics, respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Long-term variability of the terrestrial carbon cycle is not yet well constrained and the resulting climate–biosphere feedbacks are highly uncertain. Here we present a comprehensive overview of hydrometeorological and ecosystem variability from hourly to decadal timescales integrating multiple in situ and remote-sensing datasets characterizing extra-tropical forest sites. We find that ecosystem variability at all sites is confined within a hydrometeorological envelope across sites and timescales. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. However, simulation results with state-of-the-art process-based models do not reflect this long-term persistent behaviour in ecosystem functioning. Accordingly, we develop a cross-time-scale stochastic framework that captures hydrometeorological and ecosystem variability. Our analysis offers a perspective for terrestrial ecosystem modelling and paves the way for new model–data integration opportunities in Earth system sciences.

    Remarks:

    View-only version of the paper can be accessed using the following SharedIt link: http://rdcu.be/vayo

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. H. Tyralis, and D. Koutsoyiannis, On the prediction of persistent processes using the output of deterministic models, Hydrological Sciences Journal, 62 (13), 2083–2102, doi:10.1080/02626667.2017.1361535, 2017.

    A problem frequently met in engineering hydrology is the forecasting of hydrologic variables conditional on their historical observations and the hindcasts and forecasts of a deterministic model. On the contrary, it is a common practice for climatologists to use the output of general circulation models (GCMs) for the prediction of climatic variables despite their inability to quantify the uncertainty of the predictions. Here we apply the well-established Bayesian Processor of Forecasts (BPF) for forecasting hydroclimatic variables using stochastic models through coupling them with GCMs. We extend the BPF to cases where long-term persistence appears, using the Hurst-Kolmogorov process (HKp, also known as fractional Gaussian noise) and we investigate analytically its properties. We apply the framework to calculate the distributions of the mean annual temperature and precipitation stochastic processes for the time period 2016-2100 in the United States of America conditional on historical observations and the respective output of GCMs.

    Full text: http://www.itia.ntua.gr/en/getfile/1727/1/documents/2017HSJ_OnTthePredictionOfPersistentProcesses.pdf (3152 KB)

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Kundzewicz, Z. W., Quo vadis, hydrology?, Hydrological Sciences Journal, doi:10.1080/02626667.2018.1489597, 2018.

  1. F. Lombardo, E. Volpi, D. Koutsoyiannis, and F. Serinaldi, A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall, Water Resources Research, 53 (6), 4586–4605, doi:10.1002/2017WR020529, 2017.

    Generating fine-scale time series of intermittent rainfall that are fully consistent with any give coarse-scale totals is a key and open issue in many hydrological problems. We propose a stationary disaggregation method that simulates rainfall time series with given dependence structure, wet/dry probability, and marginal distribution at a target finer (lower-level) time scale, preserving full consistency with variables at a parent coarser (higher-level) time scale. We account for the intermittent character of rainfall at fine time scales by merging a discrete stochastic representation of intermittency and a continuous one of rainfall depths. This approach yields a unique and parsimonious mathematical framework providing general analytical formulations of mean, variance, and autocorrelation function (ACF) for a mixed-type stochastic process in terms of mean, variance, and ACFs of both continuous and discrete components, respectively. To achieve the full consistency between variables at finer and coarser time scales in terms of marginal distribution and coarse-scale totals, the generated lower-level series are adjusted according to a procedure that does not affect the stochastic structure implied by the original model. To assess model performance, we study rainfall process as intermittent with both independent and dependent occurrences, where dependence is quantified by the probability that two consecutive time intervals are dry. In either case, we provide analytical formulations of main statistics of our mixed-type disaggregation model and show their clear accordance with Monte Carlo simulations. An application to rainfall time series from real world is shown as a proof of concept.

    Additional material:

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Tegos, H. Tyralis, D. Koutsoyiannis, and K. H. Hamed, An R function for the estimation of trend signifcance under the scaling hypothesis- application in PET parametric annual time series, Open Water Journal, 4 (1), 66–71, 6, 2017.

    We present an R function for testing the significant trend of time series. Te function calculates trend significance using a modified Mann-Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. Te function is tested at 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric approach. A significant downward trend was detected at two stations. Te R software is now suitable for extensive use in several fields of the scientific community, allowing a physical consistent of a trend analysis.

    Full text: http://www.itia.ntua.gr/en/getfile/1703/1/documents/2017OW_An_R_FunctionForTrendSignificance.pdf (326 KB)

    Additional material:

    See also: http://scholarsarchive.byu.edu/openwater/vol4/iss1/6/

    Works that cite this document: View on Google Scholar or ResearchGate

  1. H. Tyralis, A. Tegos, A. Delichatsiou, N. Mamassis, and D. Koutsoyiannis, A perpetually interrupted interbasin water transfer as a modern Greek drama: Assessing the Acheloos to Pinios interbasin water transfer in the context of integrated water resources management, Open Water Journal, 4 (1), 113–128, 12, 2017.

    Interbasin water transfer is a primary instrument of water resources management directly related with the integrated development of the economy, society and environment. Here we assess the project of the interbasin water transfer from the river Acheloos to the river Pinios basin which has intrigued the Greek society, the politicians and scientists for decades. Te set of criteria we apply originate from a previous study reviewing four interbasin water transfers and assessing whether an interbasin water transfer is compatible with the concept of integrated water resources management. In this respect, we assess which of the principles of the integrated water resources management the Acheloos to Pinios interbasin water transfer project does or does not satisfy. While the project meets the criteria of real surplus and deficit, of sustainability and of sound science, i.e., the criteria mostly related to the engineering part, it fails to meet the criteria of good governance and balancing of existing rights with needs, i.e., the criteria associated with social aspects of the project. Te non-fulfillment of the latter criteria is the consequence of chronic diseases of the Greek society, which become obvious in the case study

    Full text: http://www.itia.ntua.gr/en/getfile/1702/1/documents/2017OW_AcheloosToPiniosInterbasinWaterTransfer.pdf (2744 KB)

    See also: http://scholarsarchive.byu.edu/openwater/vol4/iss1/11/

    Works that cite this document: View on Google Scholar or ResearchGate

  1. I. Deligiannis, P. Dimitriadis, Ο. Daskalou, Y. Dimakos, and D. Koutsoyiannis, Global investigation of double periodicity οf hourly wind speed for stochastic simulation; application in Greece, Energy Procedia, 97, 278–285, doi:10.1016/j.egypro.2016.10.001, 2016.

    The wind process is considered an important hydrometeorological process and one of the basic resources of renewable energy. In this paper, we analyze the double periodicity of wind, i.e., daily and annual, for numerous wind stations with hourly data around the globe and we develop a four-parameter model. Additionally, we apply this model to several stations in Greece and we estimate their marginal characteristics and stochastic structure best described by an extended-Pareto marginal probability function and a Hurst-Kolmogorov process, respectively.

    Full text: http://www.itia.ntua.gr/en/getfile/1671/1/documents/1-s2.0-S187661021630947X-main.pdf (3319 KB)

    Works that cite this document: View on Google Scholar or ResearchGate

  1. Y. Markonis, S. C. Batelis, Y. Dimakos, E. C. Moschou, and D. Koutsoyiannis, Temporal and spatial variability of rainfall over Greece, Theoretical and Applied Climatology, doi:10.1007/s00704-016-1878-7, 2016.

    Recent studies have showed that there is a significant decrease in rainfall over Greece during the last half of the pervious century, following an overall decrease of the precipitation at the eastern Mediterranean. However, during the last decade an increase in rainfall was observed in most regions of the country, contrary to the general circulation climate models forecasts. An updated high-resolution dataset of monthly sums and annual daily maxima records derived from 136 stations during the period 1940 – 2012 allowed us to present some new evidence for the observed change and its statistical significance. The statistical framework used to determine the significance of the slopes in annual rain was not limited to the time independency assumption (Mann-Kendall test), but we also investigated the effect of short- and long-term persistence through Monte Carlo simulation. Our findings show that (a) change occurs in different scales; most regions show a decline since 1950, an increase since 1980 and remain stable during the last 15 years, (b) the significance of the observed decline is highly dependent to the statistical assumptions used; there are indications that the Mann-Kendall test may be the least suitable method and (c) change in time is strongly linked with the change in space; for scales below 40 years relatively close regions may develop even opposite trends, while in larger scales change is more uniform.

    Additional material:

    See also: http://dx.doi.org/10.1007/s00704-016-1878-7

    Works that cite this document: View on Google Scholar or ResearchGate

  1. Y. Markonis, A. N. Angelakis, J. Christy, and D. Koutsoyiannis, Climatic variability and the evolution of water technologies in Crete, Hellas, Water History, 8 (2), 137–157, doi:10.1007/s12685-016-0159-9, 2016.

    The Greek island of Crete is one of the southernmost regions of Europe with a long and rich history, which begins as early as ca. 3200 BC with the onset of the Minoan civilization. The archeological findings of well-designed water supply and sewerage systems in the Minoan Palaces and other settlements, with impressive architecture and high-level functionality, suggest a good degree of understanding of the basic water management techniques well before the scientific achievements of our times. Here we document characteristic examples of the ancient hydraulic works and the related hydro-technologies throughout the history of Crete. We summarize the pressures on the water resources in Crete in connection with climatic variability and investigate how and what could be learned from the past using recent findings and paleoclimatology. The reconstructions of the Eastern Mediterranean and more specifically of the Cretan climate using different proxy data (e.g. sediment, pollen, and historical archives) demonstrate a series of alternating periods with varying climatic characteristics with fluctuation lengths spanning from a few decades to many centuries. The synthesis of the on-going research on past climate offers the opportunity to create a picture of the Cretan climatic regime for the last 10,000 years, which could be useful to both hydrologists and archeologists. As the past is the key to the future, the information provided could help in developing modern integrated and sustainable water management plans.

    Additional material:

    See also: http://dx.doi.org/10.1007/s12685-016-0159-9

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Angelakis, A. N., G. Antoniou, K. Voudouris, N. Kazakis, N. Delazios, and N. Dercas, History of floods in Greece: causes and measures for protection, Natural Hazards, doi:10.1007/s11069-020-03898-w, 2020.

  1. S.M. Papalexiou, and D. Koutsoyiannis, A global survey on the seasonal variation of the marginal distribution of daily precipitation, Advances in Water Resources, 94, 131–145, doi:10.1016/j.advwatres.2016.05.005, 2016.

    To characterize the seasonal variation of the marginal distribution of daily precipitation, it is important to find which statistical characteristics of daily precipitation actually vary the most from month-to-month and which could be regarded to be invariant. Relevant to the latter issue is the question whether there is a single model capable to describe effectively the nonzero daily precipitation for every month worldwide. To study these questions we introduce and apply a novel test for seasonal variation (SV-Test) and explore the performance of two flexible distributions in a massive analysis of approximately 170,000 monthly daily precipitation records at more than 14,000 stations from all over the globe. The analysis indicates that: (a) the shape characteristics of the marginal distribution of daily precipitation, generally, vary over the months, (b) commonly used distributions such as the Exponential, Gamma, Weibull, Lognormal, and the Pareto, are incapable to describe “universally” the daily precipitation, (c) exponential-tail distributions like the Exponential, mixed Exponentials or the Gamma can severely underestimate the magnitude of extreme events and thus may be a wrong choice, and (d) the Burr type XII and the Generalized Gamma distributions are two good models, with the latter performing exceptionally well.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.advwatres.2016.05.005

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, G. Blöschl, A. Bardossy, C. Cudennec, D. Hughes, A. Montanari, I. Neuweiler, and H. H. G. Savenije, Joint Editorial: Fostering innovation and improving impact assessment for journal publications in hydrology, Hydrological Sciences Journal, 61 (7), 1170–1173, doi:10.1080/02626667.2016.1162953, 2016.

    The Joint Editorial was published in:

    Full text: http://www.itia.ntua.gr/en/getfile/1603/1/documents/2016Joint_editorial_Fostering_innovation.pdf.pdf (235 KB)

    See also: http://dx.doi.org/10.1080/02626667.2016.1162953

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, M. Acreman, A. Castellarin, H. H. G. Savenije, C. Cudennec, G. Blöschl, G. Young, A. Montanari, and F. Watkins, Should auld acquaintance be forgot? Comment on “Farewell, HSJ!—address from the retiring editor” by Z.W. Kundzewicz, Hydrological Sciences Journal, doi:10.1080/02626667.2016.1150032, 2016.

    Full text: http://www.itia.ntua.gr/en/getfile/1602/1/documents/2016HSJ_ShouldAuldAcquaintanceBeForgot.pdf (72 KB)

    See also: http://dx.doi.org/10.1080/02626667.2016.1150032

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, A. Tegos, A. Oikonomou, V. Pagana, A. Koukouvinos, N. Mamassis, D. Koutsoyiannis, and A. Efstratiadis, Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping, Journal of Hydrology, 534, 478–492, doi:10.1016/j.jhydrol.2016.01.020, 2016.

    One-dimensional and quasi-two-dimensional hydraulic freeware models (HEC-RAS, LISFLOOD-FP and FLO-2d) are widely used for flood inundation mapping. These models are tested on a benchmark test with a mixed rectangular-triangular channel cross section. Using a Monte-Carlo approach, we employ extended sensitivity analysis by simultaneously varying the input discharge, longitudinal and lateral gradients and roughness coefficients, as well as the grid cell size. Based on statistical analysis of three output variables of interest, i.e. water depths at the inflow and outflow locations and total flood volume, we investigate the uncertainty enclosed in different model configurations and flow conditions, without the influence of errors and other assumptions on topography, channel geometry and boundary conditions. Moreover, we estimate the uncertainty associated to each input variable and we compare it to the overall one. The outcomes of the benchmark analysis are further highlighted by applying the three models to real-world flood propagation problems, in the context of two challenging case studies in Greece.

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Apel, H., O. Martínez Trepat, N. N. Hung, D. T. Chinh, B. Merz, and N. V. Dung, Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam, Natural Hazards and Earth System Sciences, 16, 941-961, doi:10.5194/nhess-16-941-2016, 2016.
    2. Papaioannou , G., A. Loukas, L. Vasiliades, and G. T. Aronica, Flood inundation mapping sensitivity to riverine spatial resolution and modelling approach, Natural Hazards, 83, 117-132, doi:10.1007/s11069-016-2382-1, 2016.
    3. #Santillan, J. R., A. M. Amora, M. Makinano-Santillan, J. T. Marqueso, L. C. Cutamora, J. L. Serviano, and R. M. Makinano, Assessing the impacts of flooding caused by extreme rainfall events through a combined geospatial and numerical modeling approach, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B8, 2016, XXIII ISPRS Congress, Prague, doi:10.5194/isprs-archives-XLI-B8-1271-2016, 2016.
    4. Cheviron, B. and R. Moussa, Determinants of modelling choices for 1-D free-surface flow and morphodynamics in hydrology and hydraulics: a review, Hydrology and Earth System Sciences, 20, 3799-3830, doi:10.5194/hess-20-3799-2016, 2016.
    5. Anees, M.T., K. Abdullah, M.N.M. Nawawi, N. N. N. Ab Rahman, A. R. Mt. Piah, N. A. Zakaria, M.I. Syakir, and A.K. Mohd. Omar, Numerical modeling techniques for flood analysis, Journal of African Earth Sciences, 124, 478–486, doi:10.1016/j.jafrearsci.2016.10.001, 2016.
    6. Skublics, D., G. Blöschl, and P. Rutschmann, Effect of river training on flood retention of the Bavarian Danube, Journal of Hydrology and Hydromechanics, 64(4), 349-356, doi:10.1515/johh-2016-0035, 2016.
    7. Doong, D.-J., W. Lo, Z. Vojinovic, W.-L. Lee, and S.-P. Lee, Development of a new generation of flood inundation maps—A case study of the coastal City of Tainan, Taiwan, Water, 8(11), 521, doi:10.3390/w8110521, 2016.
    8. #Cartaya, S., and R. Mantuano-Eduarte, Identificación de zonas en riesgo de inundación mediante la simulación hidráulica en un segmento del Río Pescadillo, Manabí, Ecuador, Revista de Investigación, 40(89), 158-170, 2016.
    9. Javadnejad, F., B. Waldron, and A. Hill, LITE Flood: Simple GIS-based mapping approach for real-time redelineation of multifrequency floods, Natural Hazards Review, 18(3), doi:10.1061/(ASCE)NH.1527-6996.0000238, 2017.
    10. Shrestha, A., M. S. Babel, S. Weesakul, and Z. Vojinovic, Developing intensity–duration–frequency (IDF) curves under climate change uncertainty: The case of Bangkok, Thailand, Water, 9(2), 145, doi:10.3390/w9020145, 2017.
    11. Roushangar, K., M. T. Alami, V. Nourani, and A. Nouri, A cost model with several hydraulic constraints for optimizing in practice a trapezoidal cross section, Journal of Hydroinformatics, 19(3), 456-468, doi:10.2166/hydro.2017.081, 2017.
    12. Papaioannou, G., L. Vasiliades, A. Loukas, and G. T. Aronica, Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling, Advances in Geosciences, 44, 23-34, doi:10.5194/adgeo-44-23-2017, 2017.
    13. Anees, M. T., K. Abdullah, M. N. M. Nawawi, N. N. N. Ab Rahman, A. R. Mt. Piah, M. I. Syakir, A. K. M. Omar, and K. Hossain, Applications of remote sensing, hydrology and geophysics for flood analysis, Indian Journal of Science and Technology, 10(17), doi:10.17485/ijst/2017/v10i17/111541, 2017.
    14. Fuentes-Andino, D., K. Beven, S. Halldin, C.-Y. Xu, J. E. Reynolds, and G. Di Baldassarre, Reproducing an extreme flood with uncertain post-event information, Hydrology and Earth System Sciences, 21, 3597-3618, doi:10.5194/hess-21-3597-2017, 2017.
    15. #Anees, M. T., K. Abdullah, M. N. M. Nordin, N. N. N. Ab Rahman, M. I. Syakir, and M. O. A. Kadir, One- and two-dimensional hydrological modelling and their uncertainties, Flood Risk Management, T. Hromadka and P. Rao (editors), Chapter 11, doi:10.5772/intechopen.68924, 2017.
    16. #Papaioannou, G., A. Loukas, L. Vasiliades, and G. T. Aronica, Sensitivity analysis of a probabilistic flood inundation mapping framework for ungauged catchments, Proceedings of the 10th World Congress of EWRA “Panta Rhei”, European Water Resources Association, Athens, 2017.
    17. Bangira, T., S. M. Alfieri , M. Menenti, A. van Niekerk, and Z. Vekerdy, A spectral unmixing method with ensemble estimation of endmembers: Application to flood mapping in the Caprivi floodplain, Remote Sensing, 9, 1013, doi:10.3390/rs9101013, 2017.
    18. Carisi, F., A. Domeneghetti, M. G. Gaeta, and A. Castellarin, Is anthropogenic land subsidence a possible driver of riverine flood-hazard dynamics? A case study in Ravenna, Italy, Hydrological Sciences Journal, 62(15), 2440-2455, doi:10.1080/02626667.2017.1390315, 2017.
    19. Podhoranyi, M., P. Veteska, D. Szturcova, L. Vojacek, and A. Portero, A web-based modelling and monitoring system based on coupling environmental models and hydrological-related data, Journal of Communications, 12(6), 340-346, doi:10.12720/jcm.12.6.340-346, 2017.
    20. Bhuyian, N. M., A. Kalyanapu, and F. Hossain, Evaluating conveyance-based DEM correction technique on NED and SRTM DEMs for flood impact assessment of the 2010 Cumberland river flood, Geosciences, 7(4), 132; doi:10.3390/geosciences7040132, 2017.
    21. Zin, W., A. Kawasaki, W. Takeuchi, Z. M. L. T. San, K. Z. Htun, T. H. Aye, and S. Win, Flood hazard assessment of Bago river basin, Myanmar, Journal of Disaster Research, 13(1), 14-21, doi:10.20965/jdr.2018.p0014, 2018.
    22. #Siregar, R. I., Hydraulic modeling of flow impact on bridge structures: a case study on Citarum bridge, IOP Conference Series: Materials Science and Engineering, 309, 012015, doi:10.1088/1757-899X/309/1/012015, 2018.
    23. Miranda, D., R. F. Camacho, S. Lousada, and R. A. Castanho, Hydraulic studies and their influence for regional urban planning: a practical approach to Funchal’s rivers, Revista Brasiliera de Planejamento e Desenvolvimento, 7(1), 145-164, doi:10.3895/rbpd.v7n1.7179, 2018.
    24. Liu, W., and H. Liu, Integrating Monte Carlo and the hydrodynamic model for predicting extreme water levels in river systems, Preprints 2018, 2018030088, doi:10.20944/preprints201803.0088.v1, 2018.
    25. #Indrawan, I., and R. I. Siregar, Analysis of flood vulnerability in urban area: a case study in Deli watershed, Journal of Physics Conference Series, 978(1), 012036, doi:10.1088/1742-6596/978/1/012036, 2018.
    26. #Siregar, R. I., Land cover change impact on urban flood modeling (case study: Upper Citarum watershed), IOP Conference Series: Earth and Environmental Science, 126(1), 012027, doi:10.1088/1755-1315/126/1/012027, 2018.
    27. #Ng, Z. F.., J. I. Gisen, and A. Akbari, Flood inundation modelling in the Kuantan river basin using 1D-2D flood modeller coupled with ASTER-GDEM, IOP Conference Series: Materials Science and Engineering, 318(1), 012024, doi:10.1088/1757-899X/318/1/012024, 2018.
    28. Chang, M.-J., H.-K. Chang, Y.-C. Chen, G.-F. Lin, P.-A. Chen, J.-S. Lai, and Y.-C. Tan, A support vector machine forecasting model for typhoon flood inundation mapping and early flood warning systems, Water, 10, 1734, doi:10.3390/w10121734, 2018.
    29. Dysarz, T., Application of Python scripting techniques for control and automation of HEC-RAS simulations, Water, 10(10):1382, doi:10.3390/w10101382, 2018.
    30. Hdeib, R., C. Abdallah, F. Colin, L. Brocca, and R. Moussa, Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions, Journal of Hydrology, 565, 160-175, doi:10.1016/j.jhydrol.2018.08.008, 2018.
    31. Tan, F. J., E. J. R. Rarugal, and F. A. A. Uy, One-dimensional (1D) river analysis of a river basin in Southern Luzon Island in the Philippines using Lidar Digital Elevation Model, International Journal of Engineering & Technology, 7(3.7), 29-33, doi:10.14419/ijet.v7i3.7.16200, 2018.
    32. Luo, P., D. Mu, H. Xue, T. Ngo-Duc, K. Dang-Dinh, K. Takara, D. Nover, and G. Schladow, Flood inundation assessment for the Hanoi Central Area, Vietnam under historical and extreme rainfall conditions, Scientific Reports, 8, 12623, doi:10.1038/s41598-018-30024-5, 2018.
    33. Indrawan, I., and R. I. Siregar, Pemodelan Penerapan Terowongan Air (Tunnel) dalam Mengatasi Banjir Akibat Luapan Sungai Deli, Jurnal Teknik Sipil, 25(2), 113-120, doi:10.5614/jts.2018.25.2.4, 2018.
    34. Petroselli, A., M. Vojtek, and J. Vojteková, Flood mapping in small ungauged basins: A comparison of different approaches for two case studies in Slovakia, Hydrology Research, 50(1), 379-392, doi:10.2166/nh.2018.040, 2018.
    35. Agudelo-Otálora, L. M., W. D. Moscoso-Barrera, L. A. Paipa-Galeano, and C. Mesa-Sciarrotta, Comparison of physical models and artificial intelligence for prediction of flood levels, Water Technology and Sciences, 9(4), 209-236, doi:10.24850/j-tyca-2018-04-09, 2018.
    36. Kaya, C. M., G. Tayfur, and O. Gungor, Predicting flood plain inundation for natural channels having no upstream gauged stations, Journal of Water and Climate Change, 10(2), 360-372, doi:10.2166/wcc.2017.307, 2019.
    37. Liu, Z., V. Merwade, and K. Jafarzadegan, Investigating the role of model structure and surface roughness in generating flood inundation extents using 1D and 2D hydraulic models, Journal of Flood Risk Management, 12(1), e12347, doi:10.1111/jfr3.12347, 2019.
    38. Tscheikner-Gratl, F., V. Bellos, A. Schellart, A. Moreno-Rodenas, M. Muthusamy, J. Langeveld, F. Clemens, L. Benedetti, M.A. Rico-Ramirez, R. Fernandes de Carvalho, L. Breuer, J. Shucksmith, G.B.M. Heuvelink, and S. Tait, Recent insights on uncertainties present in integrated catchment water quality modelling, Water Research, 150, 368-379, doi:10.1016/j.watres.2018.11.079, 2019.
    39. Zeleňáková, M., R. Fijko, S. Labant, E. Weiss, G. Markovič, and R. Weiss, Flood risk modelling of the Slatvinec stream in Kružlov village, Slovakia, Journal of Cleaner Production, 212, 109-118, doi:10.1016/j.jclepro.2018.12.008, 2019.
    40. Wang, P., G. Zhang, and H. Leung, Improving super-resolution flood inundation mapping for multispectral remote sensing image by supplying more spectral information, IEEE Geoscience and Remote Sensing Letters, 16(5), 771-775, doi:10.1109/LGRS.2018.2882516, 2019.
    41. Tehrany, M. S., S. Jones, and F. Shabani, Identifying the essential flood conditioning factors for flood prone area mapping using machine learning techniques, Catena, 175, 174-192, doi:10.1016/j.catena.2018.12.011, 2019.
    42. Škarpich, V., T. Galia, S. Ruman, and Z. Máčka, Variations in bar material grain-size and hydraulic conditions of managed and re-naturalized reaches of the gravel-bed Bečva River (Czech Republic), Science of The Total Environment, 649, 672-685, doi:10.1016/j.scitotenv.2018.08.329, 2019.
    43. Yang, Z., K. Yang, L. Su, and H. Hu, The multi-objective operation for cascade reservoirs using MMOSFLA with emphasis on power generation and ecological benefit, Journal of Hydroinformatics, 21(2), 257-278, doi:10.2166/hydro.2019.064, 2019.
    44. Dysarz, T., J. Wicher-Dysarz, M. Sojka, and J. Jaskuła, Analysis of extreme flow uncertainty impact on size of flood hazard zones for the Wronki gauge station in the Warta river, Acta Geophysica, 67(2), 661-676, doi:10.1007/s11600-019-00264-8, 2019.
    45. Fleischmann, A., R. Paiva, and W. Collischonn, Can regional to continental river hydrodynamic models be locally relevant? A cross-scale comparison, Journal of Hydrology X, 3, 100027, doi:10.1016/j.hydroa.2019.100027, 2019.
    46. Gyasi-Agyei, Y., Propagation of uncertainties in interpolated rain fields to runoff errors, Hydrological Sciences Journal, 64(5), 587-606, doi:10.1080/02626667.2019.1593989. 2019.
    47. Langat, P. K., L. Kumar, and R. Koech, Identification of the most suitable probability distribution models for maximum, minimum, and mean streamflow, Water, 11, 734, doi:10.3390/w11040734, 2019.
    48. Papaioannou, G., A. Loukas, and L. Vasiliades, Flood risk management methodology for lakes and adjacent areas: The lake Pamvotida paradigm, Proceedings, 7, 21, doi:10.3390/ECWS-3-05825, 2019.
    49. Hosseini, D., M. Torabi, and M. A. Moghadam, Preference assessment of energy and momentum equations over 2D-SKM method in compound channels, Journal of Water Resource Engineering and Management, 6(1), 24-34, 2019.
    50. Oubennaceur, K., K. Chokmani, M. Nastev, Y. Gauthier, J. Poulin, M. Tanguy, S. Raymond, and R. Lhissou, New sensitivity indices of a 2D flood inundation model using Gauss quadrature sampling, Geosciences, 9(5), 220, doi:10.3390/geosciences9050220, 2019.
    51. Pinho, J. L. S., L. Vieira, J. M. P. Vieira, S. Venâncio, N. E. Simões, J. A. Sá Marques, and F. S. Santos, Assessing causes and associated water levels for an urban flood using hydroinformatic tools, Journal of Hydroinformatics, jh2019019, doi:10.2166/hydro.2019.019, 2019.
    52. Saksena, S., V. Merwade, and P. J. Singhofen, Flood inundation modeling and mapping by integrating surface and subsurface hydrology with river hydrodynamics, Journal of Hydrology, 575, 1155-1177, doi:10.1016/j.jhydrol.2019.06.024, 2019.
    53. #Fijko, R., and M., Zelenakova, Verification of the hydrodynamic model of the Slatvinec River in Kružlov, Air and Water Components of the Environment Conference Proceedings, 91-98, Cluj-Napoca, Romania, doi:10.24193/AWC2019_09, 2019.
    54. Luppichini, M., M. Favalli, I. Isola, L. Nannipieri, R. Giannecchini, and M. Bini, Influence of topographic resolution and accuracy on hydraulic channel flow simulations: Case study of the Versilia River (Italy), Remote Sensing, 11(13), 1630, doi:10.3390/rs11131630, 2019.
    55. Liu, Z., and V. Merwade, Separation and prioritization of uncertainty sources in a raster based flood inundation model using hierarchical Bayesian model averaging, Journal of Hydrology, 578, 124100, doi:10.1016/j.jhydrol.2019.124100, 2019.
    56. #Huțanu, E., A. Urzică, L. E. Paveluc, C. C. Stoleriu, and A. Grozavu, The role of hydro-technical works in diminishing flooded areas. Case study: the June 1985 flood on the Miletin River, 16th International Conference on Environmental Science and Technology, Rhodes, 2019.
    57. Chen, Y.-M., C.-H. Liu, H.-J. Shih, C.-H. Chang, W.-B. Chen, Y.-C. Yu, W.-R. Su, and L.-Y. Lin, An operational forecasting system for flash floods in mountainous areas in Taiwan, Water, 11, 2100, doi:10.3390/w11102100, 2019.
    58. Shustikova, I., A. Domeneghetti, J. C. Neal, P. Bates, and A. Castellarin, Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography, Hydrological Sciences Journal, 64(14), 1769-1782, doi:10.1080/02626667.2019.1671982, 2019.
    59. Papaioannou, G., G. Varlas, G. Terti, A. Papadopoulos, A. Loukas, Y. Panagopoulos, and E. Dimitriou, Flood inundation mapping at ungauged basins using coupled hydrometeorological-hydraulic modelling: The catastrophic case of the 2006 flash flood in Volos City, Greece, Water, 11, 2328, doi:10.3390/w11112328, 2019.
    60. Liu, W.-C., and H.-M. Liu, Integrating hydrodynamic model and Monte Carlo simulation for predicting extreme water levels in a river system, Terrestrial, Atmospheric & Oceanic Sciences, 30(4), 589-604, doi:10.3319/TAO.2019.01.18.01, 2019.
    61. Costabile, P., C. Costanzo, G. De Lorenzo, and F. Macchione, Is local flood hazard assessment in urban areas significantly influenced by the physical complexity of the hydrodynamic inundation model?, Journal of Hydrology, 580, 124231, doi:10.1016/j.jhydrol.2019.124231, 2020.
    62. Stephens, T. A., and B. P. Bledsoe, Probabilistic mapping of flood hazards: depicting uncertainty in streamflow, land use, and geomorphic adjustment, Anthropocene, 29, 100231, doi:10.1016/j.ancene.2019.100231, 2020.
    63. Papaioannou, G., C. Papadaki, and E. Dimitriou, Sensitivity of habitat hydraulic model outputs to DTM and computational mesh resolution, Ecohydrology, 13(2), e2182, doi:10.1002/eco.2182, 2020.
    64. Saksena, S., S. Dey, V. Merwade, and P. J. Singhofen, A computationally efficient and physically based approach for urban flood modeling using a flexible spatiotemporal structure, Water Resources Research, 56(1), e2019WR025769, doi:10.1029/2019WR025769, 2020.
    65. Annis, A., F. Nardi, E. Volpi, and A. Fiori, Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps, Hydrological Sciences Journal, 65(4), 507-523, doi:10.1080/02626667.2019.1709640, 2020.
    66. Syafri, R. R., M. P. Hadi, and S. Suprayogi, Hydrodynamic modelling of Juwana river flooding using HEC-RAS 2D, IOP Conference Series Earth and Environmental Science, 412, 012028, doi:10.1088/1755-1315/412/1/012028, 2020.
    67. Gergeľová, M. B., Ž. Kuzevičová, S. Labant, J. Gašinec, S. Kuzevič, J. Unucka, and P. Liptai, Evaluation of selected sub-elements of spatial data quality on 3D flood event modeling: Case study of Prešov City, Slovakia, Applied Sciences, 10(3), 820, doi:10.3390/app10030820, 2020.
    68. Shaw, J., G. Kesserwani, and P. Pettersson, Probabilistic Godunov-type hydrodynamic modelling under multiple uncertainties: robust wavelet-based formulations, Advances in Water Resources, 137, 103526, doi:10.1016/j.advwatres.2020.103526, 2020.
    69. Li, X., C. Huang, Y. Zhang, J. Pang, and Y. Ma, Hydrological reconstruction of extreme palaeoflood events 9000–8500 a BP in the Danjiang River Valley, tributary of the Danjiangkou Reservoir, China, Arabian Journal of Geosciences, 13, 137, doi:10.1007/s12517-020-5132-3, 2020.
    70. Lousada, S., and L. Loures, Modelling torrential rain flows in urban territories: floods - natural channels (the case study of Madeira island), American Journal of Water Science and Engineering, 6(1), 17-30, doi:10.11648/j.ajwse.20200601.13, 2020.
    71. Pariartha, G., A. Goonetilleke, P. Egodawatta, and H. Mirfenderesk, The prediction of flood damage in coastal urban areas, IOP Conference Series Earth and Environmental Science, 419, 012136, doi:10.1088/1755-1315/419/1/012136, 2020.
    72. Lousada, S., Estudos hidráulicos e a sua influência no planeamento urbano regional: Aplicação prática às Ribeiras do Funchal – Portugal, Revista Americana de Empreendedorismo e Inovação, 2(2), 7-21, 2020.
    73. Gan, B.-R., X.-G. Yang, H.-M. Liao, and J.-W. Zhou, Flood routing process and high dam interception of natural discharge from the 2018 Baige landslide-dammed lake, Water, 12(2), 605, doi:10.3390/w12020605, 2020.
    74. Bellos, V., I. Papageorgaki, I. Kourtis, H. Vangelis, and G. Tsakiris, Reconstruction of a flash flood event using a 2D hydrodynamic model under spatial and temporal variability of storm, Natural Hazards, 101, 711-726, doi:10.1007/s11069-020-03891-3, 2020.
    75. Yalcin, E., Assessing the impact of topography and land cover data resolutions on two-dimensional HEC-RAS hydrodynamic model simulations for urban flood hazard analysis, Natural Hazards, 101, 995-1017, doi:10.1007/s11069-020-03906-z, 2020.
    76. Mateo-Lázaro, J., J. Castillo-Mateo, A. García-Gil, J. A. Sánchez-Navarro, V. Fuertes-Rodríguez, V. Edo-Romero, Comparative hydrodynamic analysis by using two−dimensional models and application to a new bridge, Water, 12(4), 997; doi:10.3390/w12040997, 2020.
    77. Albu, L.-M., A. Enea, M. Iosub, and I.-G. Breabăn, Dam breach size comparison for flood simulations. A HEC-RAS based, GIS approach for Drăcșani lake, Sitna river, Romania, Water, 12(4), 1090, doi:10.3390/w12041090, 2020.
    78. Pal, S., S. Talukdar, and R. Ghosh, Damming effect on habitat quality of riparian corridor, Ecological Indicators, 114, 106300, doi:10.1016/j.ecolind.2020.106300, 2020.
    79. Sarchani, S. K. Seiradakis, P. Coulibaly, and I. Tsanis, Flood inundation mapping in an ungauged basin, Water, 12(6), 1532, doi:10.3390/w12061532, 2020.
    80. Huţanu, E., A. Mihu-Pintilie, A. Urzica, L. E. Paveluc, C. C. Stoleriu, and A. Grozavu, Using 1D HEC-RAS modeling and LiDAR data to improve flood hazard maps’ accuracy: A case study from Jijia floodplain (NE Romania), Water, 12(6), 1624, doi:10.3390/w12061624, 2020.
    81. Fleischmann, A. S., R. C. D. Paiva, W. Collischonn, V. A. Siqueira, A. Paris, D. M. Moreira, F. Papa, A. A. Bitar, M. Parrens, F. Aires, and P. A. Garambois, Trade‐offs between 1D and 2D regional river hydrodynamic models, Water Resources Research, 56(8), e2019WR026812, doi:10.1029/2019WR026812, 2020.
    82. Gralepois, M., What can we learn from planning instruments in flood prevention? Comparative illustration to highlight the challenges of governance in Europe, Water, 12(6), 1841, doi:10.3390/w12061841, 2020.
    83. Rampinelli, C. G., I. Knack, and T. Smith, Flood mapping uncertainty from a restoration perspective: a practical case study, Water, 12(7), 1948, doi:10.3390/w12071948, 2020.
    84. Kalinina, A., M. Spada, D. F. Vetsch, S. Marelli, C. Whealton, P. Burgherr, and B. Sudret, Metamodeling for uncertainty quantification of a flood wave model for concrete dam breaks, Energies, 13(14), 3685, doi:10.3390/en13143685, 2020.
    85. Kitsikoudis, V., B. P. J., Becker, Y. Huismans, P. Archambeau, S. Erpicum, M. Pirotton, and B. Dewals, Discrepancies in flood modelling approaches in transboundary river systems: Legacy of the past or well-grounded choices?, Water Resources Management, 34, 3465-3478, doi:10.1007/s11269-020-02621-5, 2020.
    86. Piacentini, T., C. Carabella, F. Boccabella, S. Ferrante, C. Gregori, V. Mancinelli, A. Pacione, T. Pagliani, and E. Miccadei, Geomorphology-based analysis of flood critical areas in small hilly catchments for civil protection purposes and early warning systems: The case of the Feltrino stream and the Lanciano urban area (Abruzzo, Central Italy), Water, 12(8), 2228, doi:10.3390/w12082228, 2020.
    87. Arseni, M., A. Rosu, M. Calmuc, V. A. Calmuc, C. Iticescu, and L. P. Georgescu, Development of flood risk and hazard maps for the lower course of the Siret river, Romania, Sustainability, 12(16), 6588, doi:10.3390/su12166588, 2020.
    88. Ahmed, M. I., A. Elshorbagy, and A. Pietroniro, A novel model for storage dynamics simulation and inundation mapping in the Prairies, Environmental Modelling & Software, 133, 104850, doi:10.1016/j.envsoft.2020.104850, 2020.
    89. Bellos, V., V. K. Tsakiris, G. Kopsiaftis, and G. Tsakiris, Propagating dam breach parametric uncertainty in a river reach using the HEC-RAS software, Hydrology, 7(4), 72, doi:10.3390/hydrology7040072, 2020.
    90. Demir, V., and A. Ü. Keskin, Obtaining the Manning roughness with terrestrial-remote sensing technique and flood modeling using FLO-2D: A case study Samsun from Turkey, Geofizika, 37, 131-156, doi:10.15233/gfz.2020.37.9, 2020.
    91. Petroselli, A., J. Florek, D. Młyński, L. Książek, and A. Wałęga, New insights on flood mapping procedure: Two case studies in Poland, Sustainability, 12(20), 8454, doi:10.3390/su12208454, 2020.
    92. Beden, N., and A. Ulke Keskin, Flood map production and evaluation of flood risks in situations of insufficient flow data, Natural Hazards, 105, 2381-2408, doi:10.1007/s11069-020-04404-y, 2020.
    93. #Malakeel G. S., K. U. Abdu Rahiman, and S. Vishnudas, Flood risk assessment methods – A review, in: Thomas J., Jayalekshmi B., Nagarajan P. (eds), Current Trends in Civil Engineering. Lecture Notes in Civil Engineering, Vol. 104, Springer, Singapore, doi:10.1007/978-981-15-8151-9_19, 2021.
    94. Musiyam, M., J. Jumadi, Y. A. Wibowo, W. Widiyatmoko, and S. H. Nur Hafida, Analysis of flood-affected areas due to extreme weather in Pacitan, Indonesia, International Journal of GEOMATE, 19(75), 27-34, doi:10.21660/2020.75.25688, 2020.
    95. Ghimire, E., S. Sharma, and N. Lamichhane, Evaluation of one-dimensional and two-dimensional HEC-RAS models to predict flood travel time and inundation area for flood warning system, ISH Journal of Hydraulic Engineering, doi:10.1080/09715010.2020.1824621, 2020.
    96. Lin, X., G. Huang, J. M. Piwowar, X. Zhou, and Y. Zhai, Risk of hydrological failure under the compound effects of instant flow and precipitation peaks under climate change: a case study of Mountain Island Dam, North Carolina, Journal of Cleaner Production, 284, 125305, doi:10.1016/j.jclepro.2020.125305, 2021.
    97. Daksiya, V., P. V. Mandapaka, and E. Y. M. Lo, Effect of climate change and urbanisation on flood protection decision‐making, Journal of Flood Risk Management, 14(1), e12681, doi:10.1111/jfr3.12681, 2021.
    98. Urzică, A., A. Mihu-Pintilie, C. C. Stoleriu, C. I. Cîmpianu, E. Huţanu, C. I. Pricop, and A. Grozavu, Using 2D HEC-RAS modeling and embankment dam break scenario for assessing the flood control capacity of a multi-reservoir system (NE Romania), Water, 13(1), 57, doi:10.3390/w13010057, 2021.
    99. Elhag, M., and N. Yilmaz, Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece, Environmental Earth Sciences, 80, 35, doi:10.1007/s12665-020-09289-5, 2021.
    100. Hdeib, R., R. Moussa, F. Colin, and C. Abdallah, A new cost-performance grid to compare different flood modelling approaches, Hydrological Sciences Journal, 66(3), 434-449, doi:10.1080/02626667.2021.1873346, 2021.
    101. Sharma, V. C., and S. K. Regonda, Two-dimensional flood inundation modeling in the Godavari river basin, India – Insights on model output uncertainty, Water, 13(2), 191, doi:10.3390/w13020191, 2021.
    102. Santos, E. D. S., H. S. K. Pinheiro, and H. G. Junior, Height above the nearest drainage to predict flooding areas in São Luiz do Paraitinga, São Paulo, Floresta e Ambiente, 28(2), doi:10.1590/2179-8087-floram-2020-0070, 2021.
    103. Chang, T.-Y., H. Chen, H.-S. Fu, W.-B. Chen, Y.-C. Yu, W.-R. Su, and L.-Y. Lin, An operational high-performance forecasting system for city-scale pluvial flash floods in the southwestern plain areas of Taiwan, Water, 13(4), 405, doi:10.3390/w13040405, 2021.
    104. Naeem, B., M. Azmat, H. Tao, S. Ahmad, M. U. Khattak, S. Haider, S. Ahmad, Z. Khero, and C. R. Goodell, Flood hazard assessment for the Tori levee breach of the Indus river basin, Pakistan, Water; 13(5), 604, doi:10.3390/w13050604, 2021.
    105. Zhu, Y., X. Niu, C. Gu, B. Dai, and L. Huang, A fuzzy clustering logic life loss risk evaluation model for dam-break floods, Complexity, 2021, 7093256, doi:10.1155/2021/7093256, 2021.
    106. #Malakeel, G. S., K. U.Abdu Rahiman, and S. Vishnudas, Flood risk assessment methods—A review, In: Thomas J., Jayalekshmi B., Nagarajan P. (eds), Current Trends in Civil Engineering, Lecture Notes in Civil Engineering, Vol. 104. Springer, Singapore, doi:10.1007/978-981-15-8151-9_19, 2021, 2021.
    107. Liu, W.-C., T.-H. Hsieh, and H.-M. Liu, Flood risk assessment in urban areas of southern Taiwan, Sustainability, 13(6), 3180, doi:10.3390/su13063180, 2021.
    108. Kumar, S., A. Agarwal, V. G. K. Villuri, S. Pasupuleti, D. Kumar, D. R. Kaushal, A. K. Gosain, A. Bronstert, and B. Sivakumar, Constructed wetland management in urban catchments for mitigating floods, Stochastic Environmental Research and Risk Assessment, 35, 2105-2124, doi:10.1007/s00477-021-02004-1, 2021.
    109. Mourato, S., P. Fernandez, F. Marques, A. Rocha, and L. Pereira, An interactive Web-GIS fluvial flood forecast and alert system in operation in Portugal, International Journal of Disaster Risk Reduction, 58, 102201, doi:10.1016/j.ijdrr.2021.102201, 2021.
    110. Dubey, A. K., P. Kumar, V. Chembolu, S. Dutta, R. P. Singh, and A. S. Rajawata, Flood modeling of a large transboundary river using WRF-Hydro and microwave remote sensing, Journal of Hydrology, 598, 126391, doi:10.1016/j.jhydrol.2021.126391, 2021.
    111. de Arruda Gomes, M. M., L. F. de Melo Verçosa, and J. A. Cirilo, Hydrologic models coupled with 2D hydrodynamic model for high-resolution urban flood simulation, Natural Hazards, 108, 3121-3157, doi:10.1007/s11069-021-04817-3, 2021.
    112. Gao, P., W. Gao, and N. Ke, Assessing the impact of flood inundation dynamics on an urban environment, Natural Hazards, 109, 1047-1072, doi:10.1007/s11069-021-04868-6, 2021.
    113. Zhang, X., T. Wang, and B. Duan, Study on the effect of morphological changes of bridge piers on water movement properties, Water Practice and Technology, 16(4), 1421-1433, doi:10.2166/wpt.2021.08, 2021.
    114. Fadilah, S., Istiarto, and D. Legono, Investigation and modelling of the flood control system in the Aerotropolis of Yogyakarta International Airport, IOP Conference Series Materials Science and Engineering, 1173(1), 012015, doi:10.1088/1757-899X/1173/1/012015, 2021.
    115. Baran-Zgłobicka, B., D. Godziszewska, and W. Zgłobicki, The flash floods risk in the local spatial planning (case study: Lublin Upland, E. Poland), Resources, 10(2), 14, doi:10.3390/resources10020014, 2021.
    116. Liang, C.-Y., Y.-H. Wang, G. J.-Y. You, P.-C. Chen, and E. Lo, Evaluating the cost of failure risk: A case study of the Kang-Wei-Kou stream diversion project, Water, 13(20), 2881, doi:10.3390/w13202881, 2021.
    117. Uciechowska-Grakowicz, A., and O. Herrera-Granados, Riverbed mapping with the usage of deterministic and geo-statistical interpolation methods: The Odra River case study, Remote Sensing, 13(21), 4236, doi:10.3390/rs13214236, 2021.

  1. Y. Markonis, and D. Koutsoyiannis, Scale-dependence of persistence in precipitation records, Nature Climate Change, 6, 399–401, doi:10.1038/nclimate2894, 2016.

    Long-term persistence or Hurst–Kolmogorov behaviour has been identified in many hydroclimatic records. Such time series are intriguing because they are the hallmark of multi-scale dynamical processes that govern the system from which they arise. They are also highly relevant for water resource managers because these systems exhibit persistent, for example, multi-decadal, mean shifts or extremes clustering that must be included into any long-term drought management strategy. During recent years the growing number of palaeoclimatic reconstructions has allowed further investigation of the long-term statistical properties of climate and an understanding of their implications for the observed change. Recently, the consistency of the proxy data for precipitation was strongly doubted, when their persistence property was compared to the corresponding estimates of instrumental records and model results. The latter suggest that droughts or extremely wet periods occur less frequently than depicted in the palaeoclimatic reconstructions. Here, we show how this could be the outcome of a varying scaling law and present some evidence supporting that proxy records can be reliable descriptors of the long-term precipitation variability.

    See also: http://dx.doi.org/10.1038/NCLIMATE2894

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P.E. O’Connell, D. Koutsoyiannis, H. F. Lins, Y. Markonis, A. Montanari, and T.A. Cohn, The scientific legacy of Harold Edwin Hurst (1880 – 1978), Hydrological Sciences Journal, 61 (9), 1571–1590, doi:10.1080/02626667.2015.1125998, 2016.

    Emanating from his remarkable characterization of long-term variability in geophysical records in the early 1950s, Hurst’s scientific legacy to hydrology and other disciplines is explored. A statistical explanation of the so-called ‘Hurst Phenomenon’ did not emerge until 1968 when Mandelbrot and co-authors proposed fractional Gaussian noise based on the hypothesis of infinite memory. A vibrant hydrological literature ensued where alternative modelling representations were explored and debated eg ARMA models, the Broken Line model, shifting mean models with no memory, FARIMA models, and Hurst-Kolmogorov dynamics, acknowledging a link with the work of Kolmogorov in 1940. The diffusion of Hurst’s work beyond hydrology is summarized by discipline and citations, showing that he arguably has the largest scientific footprint of any hydrologist in the last century. Its particular relevance to the modelling of long-term climatic variability in the era of climate change is discussed. Links to various long-term modes of variability in the climate system, driven by fluctuations in sea surface temperatures and ocean dynamics, are explored. A physical explanation of the Hurst Phenomenon in hydrology remains as a challenge for future research.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2015.1125998

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, doi:10.1016/j.wasec.2017.06.001, 2017.

  1. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of turbulence and hydrometeorological processes, Hydrological Sciences Journal, 61 (9), 1623–1640, doi:10.1080/02626667.2015.1085988, 2016.

    Turbulence is considered to generate and drive most geophysical processes. The simplest case is the isotropic turbulence. In this paper, the most common three-dimensional power-spectrum-based models of isotropic turbulence are studied in terms of their stochastic properties. Such models often have a high-order of complexity, lack in stochastic interpretation and violate basic stochastic asymptotic properties, such as the theoretical limits of the Hurst coefficient, in case that Hurst-Kolmogorov behaviour is observed. A simpler and robust model (which incorporates self-similarity structures, e.g. fractal dimension and Hurst coefficient) is proposed using a climacogram-based stochastic framework and tested over high resolution observational data of laboratory scale as well as hydrometeorological observations of wind speed and precipitation intensities. Expressions of other stochastic tools like the autocovariance and power spectrum are also produced from the model and show agreement with data. Finally, uncertainty, discretization and bias related errors are estimated for each stochastic tool, showing lower errors for the climacogram-based ones and larger for power-spectrum ones.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2015.1085988

    Works that cite this document: View on Google Scholar or ResearchGate

  1. N. Malamos, and D. Koutsoyiannis, Bilinear surface smoothing for spatial interpolation with optional incorporation of an explanatory variable. Part 2: Application to synthesized and rainfall data, Hydrological Sciences Journal, 61 (3), 527–540, doi:10.1080/02626667.2015.1080826, 2016.

    The non-parametric mathematical framework of Bilinear Surface Smoothing (BSS) methodology provides flexible means for spatial (two dimensional) interpolation of variables. As presented in a companion paper, interpolation is accomplished by means of fitting consecutive bilinear surfaces into a regression model with known break points and adjustable smoothing terms defined by means of angles formed by those bilinear surfaces. Additionally, the second version of the methodology (BSSE) incorporates, in an objective manner, the influence of an explanatory variable available at a considerable denser dataset. In the present study, both versions are explored and illustrated using both synthesized and real world (hydrological) data, and practical aspects of their application are discussed. Also, comparison and validation against the results of commonly used spatial interpolation methods (Inverse Distance Weighted, Spline, Ordinary Kriging and Ordinary Cokriging) is performed in the context of the real world application. In every case, the method’s efficiency to perform interpolation between data points that are interrelated in a complicated manner was confirmed. Especially during the validation procedure presented in the real world case study, BSSE yielded very good results, outperforming those of the other interpolation methods. Given the simplicity of the approach, the proposed mathematical framework overall performance is quite satisfactory, indicating its applicability for diverse tasks of scientific and engineering hydrology and beyond.

    Full text: http://www.itia.ntua.gr/en/getfile/1567/1/documents/2016HSJ_BilinearPart2Application.pdf (1817 KB)

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2015.1080826

    Works that cite this document: View on Google Scholar or ResearchGate

  1. N. Malamos, and D. Koutsoyiannis, Bilinear surface smoothing for spatial interpolation with optional incorporation of an explanatory variable. Part 1:Theory, Hydrological Sciences Journal, 61 (3), 519–526, doi:10.1080/02626667.2015.1051980, 2016.

    Bilinear surface smoothing is an alternative concept which provides flexible means for spatial interpolation. Interpolation is accomplished by means of fitting a bilinear surface into a regression model with known break points and adjustable smoothing terms. Additionally, as an option, the incorporation in an objective manner, of the influence of an explanatory variable available at a considerable denser dataset is possible. The parameters involved in each case (with or without an explanatory variable) are determined by a nonparametric approach based on the generalized cross-validation (GCV) methodology. A convenient search technique of the smoothing parameters was achieved by transforming them in terms of tension parameters, with values restricted in the interval [0, 1). The mathematical framework, the computational implementation and details concerning both versions of the methodology, as well as practical aspects of their application are presented and discussed. In a companion paper, examples using both synthesized and real world (hydrological) data are presented to illustrate the methodology. The proposed mathematical framework constitutes a simple alternative to existing spatial interpolation methodologies.

    Full text: http://www.itia.ntua.gr/en/getfile/1566/1/documents/2016HSJ_Bilinear_Part1Theory.pdf (188 KB)

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2015.1051980

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, D. Koutsoyiannis, and K. Tzouka, Predictability in dice motion: how does it differ from hydrometeorological processes?, Hydrological Sciences Journal, 61 (9), 1611–1622, doi:10.1080/02626667.2015.1034128, 2016.

    From ancients times dice have been used to denote randomness. A dice throw experiment is set up in order to examine the predictability of the die orientation through time using visualization techniques. We apply and compare a deterministic-chaotic and a stochastic model and we show that both suggest predictability in die motion that deteriorates with time just like in hydrometeorological processes. Namely, die’s trajectory can be predictable for short horizons and unpredictable for long ones. Furthermore, we show that the same models can be applied, with satisfactory results, to high temporal resolution time series of rainfall intensity and wind speed magnitude, occurring during mild and strong weather conditions. The difference among the experimental and two natural processes is in the time length of the high-predictability window, which is of the order of 0.1 s, 10 min and 1 h for dice, rainfall and wind process, respectively.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2015.1034128

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Generic and parsimonious stochastic modelling for hydrology and beyond, Hydrological Sciences Journal, 61 (2), 225–244, doi:10.1080/02626667.2015.1016950, 2016.

    The old principle of parsimonious modelling of natural processes has regained its importance in the last few years. The inevitability of uncertainty and risk, and the value of stochastic modelling in dealing with them, are also again appreciated, after a period of growing hopes for radical reduction of uncertainty. Yet in stochastic modelling of natural processes several families of models are used which are often non-parsimonious, unnatural or artificial, theoretically unjustified and, eventually, unnecessary. Here we develop a general methodology for more theoretically justified stochastic processes, which evolve in continuous time and stem from maximum entropy production considerations. The discrete-time properties thereof are theoretically derived from the continuous-time ones and a general simulation methodology in discrete time is built, which explicitly handles the effects of discretization and truncation. Some additional modelling issues are discussed with focus on model identification and fitting, which are often made using inappropriate methods.

    Remarks:

    The first 50 copies of the paper are available for free at: http://www.tandfonline.com/eprint/HvECb686EkMDE6vdpCrY/full

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2015.1016950

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Serinaldi, F., Can we tell more than we can know? The limits of bivariate drought analyses in the United States, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-015-1124-3, 2015.
    2. Bardsley, E., A finite mixture approach to univariate data simulation with moment matching, Environmental Modelling & Software, 90, 27-33, doi:10.1016/j.envsoft.2016.11.019, 2017.
    3. Brunner, M. I., A. Bárdossy, and R. Furrer, Technical note: Stochastic simulation of streamflow time series using phase randomization, Hydrology and Earth System Sciences, 23, 3175-3187, doi:10.5194/hess-23-3175-2019, 2019.

  1. E. Volpi, A. Fiori, S. Grimaldi, F. Lombardo, and D. Koutsoyiannis, One hundred years of return period: Strengths and limitations, Water Resources Research, doi:10.1002/2015WR017820, 2015.

    One hundred years from its original definition by Fuller [1914], the probabilistic concept of return period is widely used in hydrology as well as in other disciplines of geosciences to give an indication on critical event rareness. This concept gains its popularity, especially in engineering practice for design and risk assessment, due to its ease of use and understanding; however, return period relies on some basic assumptions that should be satisfied for a correct application of this statistical tool. Indeed, conventional frequency analysis in hydrology is performed by assuming as necessary conditions that extreme events arise from a stationary distribution and are independent of one another. The main objective of this paper is to investigate the properties of return period when the independence condition is omitted; hence, we explore how the different definitions of return period available in literature affect results of frequency analysis for processes correlated in time. We demonstrate that, for stationary processes, the independence condition is not necessary in order to apply the classical equation of return period (i.e. the inverse of exceedance probability). On the other hand, we show that the time-correlation structure of hydrological processes modifies the shape of the distribution function of which the return period represents the first moment. This implies that, in the context of time-dependent processes, the return period might not represent an exhaustive measure of the probability of failure, and that its blind application could lead to misleading results. To overcome this problem, we introduce the concept of Equivalent Return Period, which controls the probability of failure still preserving the virtue of effectively communicating the event rareness.

    Additional material:

    See also: http://dx.doi.org/10.1002/2015WR017820

    Works that cite this document: View on Google Scholar or ResearchGate

  1. P. Dimitriadis, and D. Koutsoyiannis, Application of stochastic methods to double cyclostationary processes for hourly wind speed simulation, Energy Procedia, 76, 406–411, doi:10.1016/j.egypro.2015.07.851, 2015.

    In this paper, we present a methodology to analyze processes of double cyclostationarity (e.g. daily and seasonal). This method preserves the marginal characteristics as well as the dependence structure of a process (through the use of climacogram). It consists of a normalization scheme with two periodicities. Furthermore, we apply it to a meteorological station in Greece and construct a stochastic model capable of preserving the Hurst-Kolmogorov behaviour. Finally, we produce synthetic time-series (based on aggregated Markovian processes) for the purpose of wind speed and energy production simulation (based on a proposed industrial wind turbine).

    Remarks:

    The pdf file with the full text contains a correction of an erratum in Equation (2)

    Full text: http://www.itia.ntua.gr/en/getfile/1570/1/documents/1-s2.0-S1876610215016276-main-2.pdf (1143 KB)

    See also: http://dx.doi.org/10.1016/j.egypro.2015.07.851

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Tegos, A. Efstratiadis, N. Malamos, N. Mamassis, and D. Koutsoyiannis, Evaluation of a parametric approach for estimating potential evapotranspiration across different climates, Agriculture and Agricultural Science Procedia, 4, 2–9, doi:10.1016/j.aaspro.2015.03.002, 2015.

    Potential evapotranspiration (PET) is key input in water resources, agricultural and environmental modelling. For many decades, numerous approaches have been proposed for the consistent estimation of PET at several time scales of interest. The most recognized is the Penman-Monteith formula, which is yet difficult to apply in data-scarce areas, since it requires simultaneous observations of four meteorological variables (temperature, sunshine duration, humidity, wind velocity). For this reason, parsimonious models with minimum input data requirements are strongly preferred. Typically, these have been developed and tested for specific hydroclimatic conditions, but when they are applied in different regimes they provide much less reliable (and in some cases misleading) estimates. Therefore, it is essential to develop generic methods that remain parsimonious, in terms of input data and parameterization, yet they also allow for some kind of local adjustment of their parameters, through calibration. In this study we present a recent parametric formula, based on a simplified formulation of the original Penman-Monteith expression, which only requires mean daily or monthly temperature data. The method is evaluated using meteorological records from different areas worldwide, at both the daily and monthly time scales. The outcomes of this extended analysis are very encouraging, as indicated by the substantially high validation scores of the proposed approach across all examined data sets. In general, the parametric model outperforms well-established methods of the everyday practice, since it ensures optimal approximation of potential evapotranspiration.

    Full text: http://www.itia.ntua.gr/en/getfile/1549/1/documents/IRLA_paper.pdf (560 KB)

    See also: http://dx.doi.org/10.1016/j.aaspro.2015.03.002

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Stan, F.I., G. Neculau, L. Zaharia, G. Ioana-Toroimac, and S. Mihalache, Study on the evaporation and evapotranspiration measured on the Căldăruşani Lake (Romania), Procedia Environmental Sciences, 32, 281–289, doi:10.1016/j.proenv.2016.03.033, 2016.
    2. Esquivel-Hernández, G., R. Sánchez-Murillo, C. Birkel, S. P. Good, and J. Boll, Hydro-climatic and ecohydrological resistance/resilience conditions across tropical biomes of Costa Rica, Ecohydrology, 10(6), e1860, doi:10.1002/eco.1860, 2017.
    3. Hodam, S., S. Sarkar, A.G.R. Marak, A. Bandyopadhyay, and A. Bhadra, Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods, Journal of The Institution of Engineers (India): Series A, 98(4), 551-524, doi:10.1007/s40030-017-0241-z, 2017.
    4. Deng, H., and J. Shao, Evapotranspiration and humidity variations in response to land cover conversions in the Three Gorges Reservoir Region, Journal of Mountain Science, 15(3), 590-605, doi:10.1007/s11629-016-4272-0, 2018.
    5. Nadyozhina, E. D., I. M. Shkolnik, A. V. Sternzat, B. N. Egorov, and A. A. Pikaleva, Evaporation from irrigated lands in arid regions as inferred from the regional climate model and atmospheric boundary layer model simulations, Russian Meteorology and Hydrology, 43(6), 404-411, doi:10.3103/S1068373918060080, 2018.
    6. Bashir, R., F. Ahmad, and R. Beddoe, Effect of climate change on a monolithic desulphurized tailings cover, Water, 2(9), 2645, doi:10.3390/w12092645, 2020.

  1. K. Kollyropoulos, G. Antoniou, I. Kalavrouziotis, J. Krasilnikoff, D. Koutsoyiannis, and A. N. Angelakis, Hydraulic characteristics of the drainage systems of ancient Hellenic theatres: Case study of the theatre of Dionysus and its implications, Journal of Irrigation and Drainage Engineering (ASCE), 141 (11), doi:10.1061/(ASCE)IR.1943-4774.0000906, 2015.

    The content of this article provides interesting history, facts, and information about the drainage systems of ancient theaters in mainland Greece and Asia Minor from prehistoric times until the Hellenistic period. This study comprises representative examples of drainage systems in theaters at Knossos, Phaistos, Dionysus in Athens, Arcadian Orchomenos, Ephesus, and Delos. Moreover, the aim is to demonstrate that these drainage systems represent evolutionary techniques and principles that can still be used today to avoid wasting water resources. Moreover, these techniques may prove attractive for the development of sustainable strategies to counter mounting problems, especially those of a socioeconomic nature. In addition, the article presents evidence for the conception that adaptations to individual environmental and hydraulic characteristics of specific locations were considered in relation to drainage systems of ancient theaters. Thus, through a case study of the carrying capacity of drainage channels at Dionysus ’s theater in Athens, the sustainable nature of this construction is demonstrated, including its capacity for the management of stormwater.

    Additional material:

    See also: http://dx.doi.org/10.1061/(ASCE)IR.1943-4774.0000906

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Tegos, N. Malamos, and D. Koutsoyiannis, A parsimonious regional parametric evapotranspiration model based on a simplification of the Penman-Monteith formula, Journal of Hydrology, 524, 708–717, doi:10.1016/j.jhydrol.2015.03.024, 2015.

    Evapotranspiration is a key hydrometeorological process and its estimation is important in many fields of hydrological and agricultural sciences. Simplified estimation proves very useful in absence of a complete data set. In this respect, a parametric model based on simplification of the Penman-Monteith formulation is presented. The basic idea of the parametric model is the replacement of some of the variables and constants that are used in the standard Penman-Monteith model by regionally varying parameters, which are estimated through calibration. The model is implemented in various climates on monthly time step (USA, Germany, Spain) and compared on the same basis with four radiation-based methods (Jensen-Haise, McGuiness and Bordne, Hargreaves and Oudin) and two temperature-based (Thornthwaite and Blaney-Criddle). The methodology yields very good results with high efficiency indexes, outperforming the other models. Finally, a spatial analysis including the correlation of parameters with latitude and elevation together with their regionalization through three common spatial interpolation techniques along with a recent approach (Bilinear Surface Smoothing), is performed. Also, the model is validated against Penman-Monteith estimates in eleven stations of the well-known CIMIS network. The total framework which includes the development, the implementation, the comparison and the mapping of parameters illustrates a new parsimonious and high efficiency methodology in the assessment of potential evapotranspiration field.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.jhydrol.2015.03.024

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Hodam, S., S. Sarkar, A.G.R. Marak, A. Bandyopadhyay, and A. Bhadra, Spatial interpolation of reference evapotranspiration in India: Comparison of IDW and Kriging methods, Journal of The Institution of Engineers (India): Series A, 98(4), 551-524, doi:10.1007/s40030-017-0241-z, 2017.
    2. Deng, H., and J. Shao, Evapotranspiration and humidity variations in response to land cover conversions in the Three Gorges Reservoir Region, Journal of Mountain Science, 15(3), 590–605, doi:10.1007/s11629-016-4272-0, 2018.
    3. Giménez, P. O., and S. G. García-Galiano, Assessing Regional Climate Models (RCMs) ensemble-driven reference evapotranspiration over Spain, Water, 10(9), 1181, doi:10.3390/w10091181, 2018.
    4. Zhang, T., Y. Chen, and K. Tha Paw U, Quantifying the impact of climate variables on reference evapotranspiration in Pearl River Basin, China, Hydrological Sciences Journal, doi:10.1080/02626667.2019.1662021, 2019.

  1. P. Dimitriadis, and D. Koutsoyiannis, Climacogram versus autocovariance and power spectrum in stochastic modelling for Markovian and Hurst–Kolmogorov processes, Stochastic Environmental Research & Risk Assessment, 29 (6), 1649–1669, doi:10.1007/s00477-015-1023-7, 2015.

    Three common stochastic tools, the climacogram i.e. variance of the time averaged process over averaging time scale, the autocovariance function and the power spectrum are compared to each other to assess each one’s advantages and disadvantages in stochastic modelling and statistical inference. Although in theory, all three are equivalent to each other (transformations one another expressing second order stochastic properties), in practical application their ability to characterize a geophysical process and their utility as statistical estimators may vary. In the analysis both Markovian and non Markovian stochastic processes, which have exponential and power-type autocovariances, respectively, are used. It is shown that, due to high bias in autocovariance estimation, as well as effects of process discretization and finite sample size, the power spectrum is also prone to bias and discretization errors as well as high uncertainty, which may misrepresent the process behaviour (e.g. Hurst phenomenon) if not taken into account. Moreover, it is shown that the classical climacogram estimator has small error as well as an expected value always positive, well-behaved and close to its mode (most probable value), all of which are important advantages in stochastic model building. In contrast, the power spectrum and the autocovariance do not have some of these properties. Therefore, when building a stochastic model, it seems beneficial to start from the climacogram, rather than the power spectrum or the autocovariance. The results are illustrated by a real world application based on the analysis of a long time series of high-frequency turbulent flow measurements.

    Additional material:

    See also: http://dx.doi.org/10.1007/s00477-015-1023-7

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Serinaldi, F., Can we tell more than we can know? The limits of bivariate drought analyses in the United States, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-015-1124-3, 2015.
    2. Park, J., C. Onof, and D. Kim, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, 23, 989-1014, doi:10.5194/hess-23-989-2019, 2019.

  1. A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Hydrological modelling of temporally-varying catchments: Facets of change and the value of information, Hydrological Sciences Journal, 60 (7-8), 1438–1461, doi:10.1080/02626667.2014.982123, 2015.

    River basins are by definition temporally varying systems: changes are apparent at every temporal scale, in terms of changing meteorological inputs and catchment characteristics, respectively due to inherently uncertain natural processes and anthropogenic interventions. In an operational context, the ultimate goal of hydrological modelling is predicting responses of the basin under conditions that are similar or different from those observed in the past. Since water management studies require that anthropogenic effects are considered known and a long hypothetical period is simulated, the combined use of stochastic models, for generating the inputs, and deterministic models that also represent the human interventions in modified basins, is found to be a powerful approach for providing realistic and statistically consistent simulations (in terms of product moments and correlations, at multiple time scales, and long-term persistence). The proposed framework is investigated on the Ferson Creek basin (USA) that exhibits significantly growing urbanization during the last 30 years. Alternative deterministic modelling options include a lumped water balance model with one time-varying parameter and a semi-distributed scheme based on the concept of hydrological response units. Model inputs and errors are respectively represented through linear and non-linear stochastic models. The resulting nonlinear stochastic framework maximizes the exploitation of the existing information, by taking advantage of the calibration protocol used in this issue.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2014.982123

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Thirel, G., V. Andréassian, and C. Perrin, On the need to test hydrological models under changing conditions, Hydrological Sciences Journal, 60(7-8), 1165-1173, doi:10.1080/02626667.2015.1050027, 2015.
    2. Biao, I. E., S. Gaba, A. E. Alamou, and A. Afouda, Influence of the uncertainties related to the random component of rainfall inflow in the Ouémé River Basin (Benin, West Africa), International Journal of Current Engineering and Technology, 5(3), 1618-1629, 2015.
    3. #Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers using radial basis function metamodels, Proceedings of 9th World Congress EWRA “Water Resources Management in a Changing World: Challenges and Opportunities”, Istanbul, 2015.
    4. Christelis, V., and A. Mantoglou, Coastal aquifer management based on the joint use of density-dependent and sharp interface models, Water Resources Management, 30(2), 861-876, doi:10.1007/s11269-015-1195-4, 2016.
    5. McMillan, H., A. Montanari, C. Cudennec, H. Savenjie, H. Kreibich, T. Krüger, J. Liu, A. Meija, A. van Loon, H. Aksoy, G. Di Baldassarre, Y. Huang, D. Mazvimavi, M. Rogger, S. Bellie, T. Bibikova, A. Castellarin, Y. Chen, D. Finger, A. Gelfan, D. Hannah, A. Hoekstra, H. Li, S. Maskey, T. Mathevet, A. Mijic, A. Pedrozo Acuña, M. J. Polo, V. Rosales, P. Smith, A. Viglione, V. Srinivasan, E. Toth, R. van Nooyen, and J. Xia, Panta Rhei 2013-2015: Global perspectives on hydrology, society and change, Hydrological Sciences Journal, 61(7), 1174-1191, doi:10.1080/02626667.2016.1159308, 2016.
    6. Biao, I. E., A. E. Alamou, and A. Afouda, Improving rainfall–runoff modelling through the control of uncertainties under increasing climate variability in the Ouémé River basin (Benin, West Africa), Hydrological Sciences Journal, 61(16), 2902-2915, doi:10.1080/02626667.2016.1164315, 2016.
    7. Pathiraja, S., L. Marshall, A. Sharma, and H. Moradkhani, Detecting non-stationary hydrologic model parameters in a paired catchment system using data assimilation, Advances in Water Resources, 94, 103–119, doi:10.1016/j.advwatres.2016.04.021, 2016.
    8. Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers assisted by adaptive metamodelling methods and radial basis functions, Water Resources Management, 30(15), 5845–5859, doi:10.1007/s11269-016-1337-3, 2016.
    9. Seibert, J., and I. van Meerveld, Hydrological change modeling: Challenges and opportunities, Hydrological Processes, 30(26), 4966–4971, doi:10.1002/hyp.10999, 2016.
    10. Ceola, S., A. Montanari, T. Krueger, F. Dyer, H. Kreibich, I. Westerberg, G. Carr, C. Cudennec, A. Elshorbagy, H. Savenije, P. van der Zaag, D. Rosbjerg, H. Aksoy, F. Viola, G. Petrucci, K. MacLeod, B. Croke, D. Ganora, L. Hermans, M. J. Polo, Z. Xu, M. Borga, J. Helmschrot, E. Toth, R., A. Castellarin, A. Hurford, M. Brilly, A. Viglione, G. Blöschl, M. Sivapalan, A. Domeneghetti, A. Marinelli, and G. Di Baldassarre, Adaptation of water resources systems to changing society and environment: a statement by the International Association of Hydrological Sciences, Hydrological Sciences Journal, 61(16), 2803-2817, doi:10.1080/02626667.2016.1230674, 2016.
    11. #Christelis, V., V. Bellos, and G. Tsakiris, Employing surrogate modelling for the calibration of a 2D flood simulation model, Sustainable Hydraulics in the Era of Global Change: Proceedings of the 4th IAHR Europe Congress (Liege, Belgium, 27-29 July 2016), A. S. Erpicum, M. Pirotton, B. Dewals, P. Archambeau (editors), CRC Press, 2016.
    12. Nauditt, A., C. Birkel, C. Soulsby, and L. Ribbe, Conceptual modelling to assess the influence of hydroclimatic variability on runoff processes in data scarce semi-arid Andean catchments, Hydrological Sciences Journal, 62(4), 515-532, doi:10.1080/02626667.2016.1240870, 2017.
    13. Sophocleous C., and I. Nalbantis, Effect of land use change on flood extent in the inflow stream of lake Paralimni, Cyprus, European Water, 60, 147-153, 2017.
    14. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.
    15. Pathiraja, S., D. Anghileri, P. Burlando, A. Sharma, L. Marshall, and H. Moradkhani, Insights on the impact of systematic model errors on data assimilation performance in changing catchments, Advances in Water Resources, 113, 202-222, doi:10.1016/j.advwatres.2017.12.006, 2018.
    16. Salas, J. D., J. Obeysekera, and R. M. Vogel, Techniques for assessing water infrastructure for nonstationary extreme events: a review, Hydrological Sciences Journal, 63(3), 325-352, doi:10.1080/02626667.2018.1426858, 2018.
    17. Pathiraja, S., D. Anghileri, P. Burlando, A. Sharma, L. Marshall, and H. Moradkhani, Time varying parameter models for catchments with land use change: the importance of model structure, Hydrology and Earth System Sciences, 22, 2903-2919, doi:10.5194/hess-2017-382, 2018.
    18. Varouchakis, E. A., K. Yetilmezsoy, and G. P. Karatzas, A decision-making framework for sustainable management of groundwater resources under uncertainty: combination of Bayesian risk approach and statistical tools, Water Policy, 21(3), 602-622, doi:10.2166/wp.2019.128, 2019.
    19. Sadegh, M., A. AghaKouchak, A. Flores, I. Mallakpour, and M. R. Nikoo, A multi-model nonstationary rainfall-runoff modeling framework: analysis and toolbox, Water Resources Management, 33(9), 3011-3024, doi:10.1007/s11269-019-02283-y, 2019.
    20. Zhao, B., J. Mao, Q. Dai, D. Han, H. Daiand, and G. Rong, Exploration on hydrological model calibration by considering the hydro-meteorological variability, Hydrology Research, 51(1), 30-46, doi:10.2166/nh.2019.047, 2020.
    21. Nicolle, P., V. Andréassian, P. Royer-Gaspard, C. Perrin, G. Thirel, L. Coron, and L. Santos, Technical Note – RAT: a Robustness Assessment Test for calibrated and uncalibrated hydrological models, Hydrology and Earth System Sciences, 25, 5013–5027, doi:10.5194/hess-25-5013-2021, 2021.

  1. D. Koutsoyiannis, and A. Montanari, Negligent killing of scientific concepts: the stationarity case, Hydrological Sciences Journal, 60 (7-8), 1174–1183, doi:10.1080/02626667.2014.959959, 2015.

    In the scientific vocabulary, the term “process” is used to denote change in time. Even a stationary process describes a system changing in time, rather than a static one which keeps a constant state all the time. However, this is often missed, which has led to misusing the term “nonstationarity” as a synonym of “change”. A simple rule to avoid such misuse is to answer the question: can the change be predicted in deterministic terms? Only if the answer is positive it is legitimate to invoke nonstationarity. In addition, we should have in mind that models are made to simulate the future rather than to describe the past; the past is rather characterized by observations (data). Usually future changes are not deterministically predictable and thus the models should, on the one hand, be stationary and, on the other hand, describe in stochastic terms the full variability, originating from all agents of change. Even if the past evolution of the process of interest contains changes explainable in deterministic terms (e.g. urbanization), again it is better to describe the future conditions in stationary terms, after “stationarizing” the past observations, i.e. adapting them to represent the future conditions.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2014.959959

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Thirel, G., V. Andréassian, and C. Perrin, On the need to test hydrological models under changing conditions, Hydrological Sciences Journal, doi:10.1080/02626667.2015.1050027, 2015.
    2. Andrés-Doménech, I., R. García-Bartual, A. Montanari and J. B. Marco, Climate and hydrological variability: the catchment filtering role, Hydrol. Earth Syst. Sci., 19 (1), 379-387, 2015.
    3. Serinaldi, F., and C.G. Kilsby, Stationarity is undead: Uncertainty dominates the distribution of extremes, Advances in Water Resources, 77, 17-36, 2015.
    4. Steinschneider, S., and U. Lall, A hierarchical Bayesian regional model for nonstationary precipitation extremes in Northern California conditioned on tropical moisture exports, Water Resources Research, 51 (3), 1472-1492, 2015.
    5. Ceola, S., B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione and T. Wagener, Virtual laboratories: New opportunities for collaborative water science, Hydrology and Earth System Sciences, 19 (4), 2101-2117, 2015.
    6. Serinaldi, F., Can we tell more than we can know? The limits of bivariate drought analyses in the United States, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-015-1124-3, 2015.
    7. Kundzewicz, Z. W., V. Krysanova, R. Dankers, Y. Hirabayashi, S. Kanae, F. F. Hattermann, S. Huang, P. C. D. Milly, M. Stoffel, P. P. J. Driessen, P. Matczak, P. Quevauviller, and H.-J. Schellnhuber, Differences in flood hazard projections in Europe – their causes and consequences for decision making, Hydrological Sciences Journal, doi:10.1080/02626667.2016.1241398, 2016.

  1. N. Malamos, and D. Koutsoyiannis, Broken line smoothing for data series interpolation by incorporating an explanatory variable with denser observations: Application to soil-water and rainfall data, Hydrological Sciences Journal, doi:10.1080/02626667.2014.899703, 2015.

    Broken line smoothing is a simple technique for smoothing a broken line fit to observational data and provides flexible means for interpolation. Here an extension of this technique is proposed, which can be utilized to perform various interpolation tasks, by incorporating, in an objective manner, an explanatory variable available at a considerably denser dataset than the initial main variable. The technique incorporates smoothing terms with adjustable weights, defined by means of the angles formed by the consecutive segments of two broken lines. The mathematical framework and details of the method as well as practical aspects of its application are presented and discussed. Also, examples using both synthesized and real world (soil water dynamics and hydrological) data are presented to explore and illustrate the methodology.

    Full text: http://www.itia.ntua.gr/en/getfile/1436/1/documents/2014HSJ_BrokenLineSmoothing.pdf (507 KB)

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2014.899703

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Sikorska, A. Montanari, and D. Koutsoyiannis, Estimating the uncertainty of hydrological predictions through data-driven resampling techniques, Journal of Hydrologic Engineering (ASCE), 20 (1), doi:10.1061/(ASCE)HE.1943-5584.0000926, 2015.

    Estimating the uncertainty of hydrological models remains a relevant challenge in applied hydrology, mostly because it is not easy to parameterize the complex structure of hydrological model errors. A non-parametric technique is proposed as an alternative to parametric error models to estimate the uncertainty of hydrological predictions. Within this approach, the above uncertainty is assumed to depend on input data uncertainty, parameter uncertainty and model error, where the latter aggregates all sources of uncertainty that are not considered explicitly. Errors of hydrological models are simulated by resampling from their past realizations using a nearest neighbor approach, therefore avoiding a formal description of their statistical properties. The approach is tested using synthetic data which refer to the case study located in Italy. The results are compared with those obtained using a formal statistical technique (meta-Gaussian approach) from the same case study. Our findings prove that the nearest neighbor approach provides simplicity in application and a significant improvement in regard to the meta-Gaussian approach. Resampling techniques appear therefore to be an interesting option for uncertainty assessment in hydrology, provided that historical data are available to provide a consistent description of the model error.

    Additional material:

    See also: http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000926

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari and G. and Blöschl, Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene, Hydrol. Earth Syst. Sci., 17, 5013-5039, 2013.
    2. Sikorska, A.E., D. Del Giudice, K. Banasik, and J. Rieckermann, The value of streamflow data in improving TSS predictions - Bayesian multi-objective calibration, Journal of Hydrology, doi:10.1016/j.jhydrol.2015.09.051, 2015.
    3. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, doi:10.1016/j.wasec.2017.06.001, 2017.

  1. A. Montanari, and D. Koutsoyiannis, Modeling and mitigating natural hazards: Stationarity is immortal!, Water Resources Research, 50 (12), 9748–9756, doi:10.1002/2014WR016092, 2014.

    Environmental change is a reason of relevant concern as it is occurring at an unprecedented pace and might increase natural hazards. Moreover, it is deemed to imply a reduced representativity of past experience and data on extreme hydroclimatic events. The latter concern has been epitomized by the statement that “stationarity is dead”. Setting up policies for mitigating natural hazards, including those triggered by floods and droughts, is an urgent priority in many countries, which implies practical activities of management, engineering design and construction. These latter necessarily need to be properly informed and therefore the research question on the value of past data is extremely important. We herein argue that there are mechanisms in hydrological systems that are time invariant, which may need to be interpreted through data inference. In particular, hydrological predictions are based on assumptions which should include stationarity, as any hydrological model, including deterministic and non-stationary approaches, is affected by uncertainty and therefore should include a random component that is stationary. Given that an unnecessary resort to non-stationarity may imply a reduction of predictive capabilities, a pragmatic approach, based on the exploitation of past experience and data is a necessary prerequisite for setting up mitigation policies for environmental risk.

    Additional material:

    See also: http://dx.doi.org/10.1002/2014WR016092

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Andrés-Doménech, I., R. García-Bartual, A. Montanari and J. B. Marco, Climate and hydrological variability: the catchment filtering role, Hydrol. Earth Syst. Sci., 19 (1), 379-387, 2015.
    2. Serinaldi, F., and C.G. Kilsby, Stationarity is undead: Uncertainty dominates the distribution of extremes, Advances in Water Resources, 77, 17-36, 2015.
    3. Yang, L., F. Tian and D. Niyogi, A need to revisit hydrologic responses to urbanization by incorporating the feedback on spatial rainfall patterns, Urban Climate, 12, 128-140, 2015.
    4. Ceola, S., B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione and T. Wagener, Virtual laboratories: New opportunities for collaborative water science, Hydrology and Earth System Sciences, 19 (4), 2101-2117, 2015.
    5. Dhakal, N., S. Jain, A. Gray, M. Dandy and E. Stancioff, Nonstationarity in seasonality of extreme precipitation: A nonparametric circular statistical approach and its application, Water Resources Research, 51 (6), 4499-4515, 2015.
    6. Prosdocimi, I., T.R. Kjeldsen and J.D. Miller, Detection and attribution of urbanization effect on flood extremes using nonstationary flood-frequency models, Water Resources Research, 51 (6), 4244-4262, 2015.
    7. Bayazit, M., Nonstationarity of hydrological records and recent trends in trend analysis: a state-of-the-art review, Environmental Processes, 2 (3), 527-542, 10.1007/s40710-015-0081-7, 2015.
    8. Serinaldi, F., Can we tell more than we can know? The limits of bivariate drought analyses in the United States, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-015-1124-3, 2015.
    9. Kundzewicz, Z. W., Quo vadis, hydrology?, Hydrological Sciences Journal, doi:10.1080/02626667.2018.1489597, 2018.

  1. A. Efstratiadis, Y. Dialynas, S. Kozanis, and D. Koutsoyiannis, A multivariate stochastic model for the generation of synthetic time series at multiple time scales reproducing long-term persistence, Environmental Modelling and Software, 62, 139–152, doi:10.1016/j.envsoft.2014.08.017, 2014.

    A time series generator is presented, employing a robust three-level multivariate scheme for stochastic simulation of correlated processes. It preserves the essential statistical characteristics of historical data at three time scales (annual, monthly, daily), using a disaggregation approach. It also reproduces key properties of hydrometeorological and geophysical processes, namely the long-term persistence (Hurst-Kolmogorov behaviour), the periodicity and intermittency. Its efficiency is illustrated through two case studies in Greece. The first aims to generate monthly runoff and rainfall data at three reservoirs of the hydrosystem of Athens. The second involves the generation of daily rainfall for flood simulation at five rain gauges. In the first emphasis is given to long-term persistence – a dominant characteristic in the management of large-scale hydrosystems, comprising reservoirs with carry-over storage capacity. In the second we highlight to the consistent representation of intermittency and asymmetry of daily rainfall, and the distribution of annual daily maxima.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.envsoft.2014.08.017

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Huo, S.-C., S.-L. Lo, C.-H. Chiu, P.-T. Chiueh, and C.-S. Yang, Assessing a fuzzy model and HSPF to supplement rainfall data for nonpoint source water quality in the Feitsui reservoir watershed, Environmental Modelling and Software, 72, 110-116, doi:10.1016/j.envsoft.2015.07.002, 2015.
    2. Read, L., and R. M. Vogel, Reliability, return periods, and risk under nonstationarity, Water Resources Research, 51(8), 6381–6398, doi:10.1002/2015WR017089, 2015.
    3. Steidl, J., J. Schuler, U. Schubert, O. Dietrich, and P. Zander, Expansion of an existing water management model for the analysis of opportunities and impacts of agricultural irrigation under climate change conditions, Water, 7, 6351-6377, doi:10.3390/w7116351, 2015.
    4. Hao, Z., and V. P. Singh, Review of dependence modeling in hydrology and water resources, Progress in Physical Geography, 40(4), 549-578, doi:10.1177/0309133316632460, 2016.
    5. Srivastav, R., K. Srinivasan, and S. P. Sudheer, Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling, Journal of Hydrology, 542, 506-531, doi:10.1016/j.jhydrol.2016.09.025, 2016.
    6. Dialynas, Y. G., S. Bastola, R. L. Bras, E. Marin-Spiotta, W. L. Silver, E. Arnone, and L. V. Noto, Impact of hydrologically driven hillslope erosion and landslide occurrence on soil organic carbon dynamics in tropical watersheds, Water Resources Research, 52(11), 8895–8919, doi:10.1002/2016WR018925, 2016.
    7. Stojković, M., S. Kostić, J. Plavšić, and S. Prohaska, A joint stochastic-deterministic approach for long-term and short-term modelling of monthly flow rates, Journal of Hydrology, 544, 555–566, doi:10.1016/j.jhydrol.2016.11.025, 2017.
    8. Bardsley, E., A finite mixture approach to univariate data simulation with moment matching, Environmental Modelling & Software, 90, 27-33, doi:10.1016/j.envsoft.2016.11.019, 2017.
    9. Dialynas, Y. D., R. L. Bras, and D. deB. Richter, Hydro-geomorphic perturbations on the soil-atmosphere CO2 exchange: How (un)certain are our balances?, Water Resources Research, 53(2), 1664–1682, doi:10.1002/2016WR019411, 2017.
    10. Feng , M., P. Liu, S. Guo, Z. Gui, X. Zhang, W. Zhang, and L. Xiong, Identifying changing patterns of reservoir operating rules under various inflow alteration scenarios, Advances in Water Resources, 104, 23-26, doi:10.1016/j.advwatres.2017.03.003, 2017.
    11. Stojković, M., J. Plavšić, and S. Prohaska, Annual and seasonal discharge prediction in the middle Danube River basin based on a modified TIPS (Tendency, Intermittency, Periodicity, Stochasticity) methodology, Journal of Hydrology and Hydromechanics, 65(2), doi:10.1515/johh-2017-0012, 2017.
    12. Hanel, M., R. Kožín, M. Heřmanovský, and R. Roub, An R package for assessment of statistical downscaling methods for hydrological climate change impact studies, Environmental Modelling & Software, 95, 22–28, doi:10.1016/j.envsoft.2017.03.036, 2017.
    13. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, 1, 28-35, doi:10.1016/j.wasec.2017.06.001, 2017.
    14. #McLachlan, S., K. Dube, T. Gallagher, B. Daley, and J. Walonoski, The ATEN Framework for creating the realistic synthetic electronic health record, 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), Madeira, Portugal, 2018.
    15. Salas, J. D., J. Obeysekera, and R. M. Vogel, Techniques for assessing water infrastructure for nonstationary extreme events: a review, Hydrological Sciences Journal, 63(3), 325-352, doi:10.1080/02626667.2018.1426858, 2018.
    16. #Hnilica, J., M. Hanel, and V. Puš, Technical note: Changes of cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2018-7, 2018.
    17. Hua, Y., and B. Cui, Environmental flows and its satisfaction degree forecasting in the Yellow River, Ecological Indicators, 92, 207-220, doi:10.1016/j.ecolind.2017.02.017, 2018.
    18. Ilich, N., A. Gharib, and E. G. R. Davies, Kernel distributed residual function in a revised multiple order autoregressive model and its applications in hydrology, Hydrological Sciences Journal, 63(12), 1745-1758, doi:10.1080/02626667.2018.1541090, 2018.
    19. Henao, F., Y. Rodriguez, J. P. Viteri, and I. Dyner, Optimising the insertion of renewables in the Colombian power sector, Renewable Energy, 132, 81-92, doi:10.1016/j.renene.2018.07.099, 2019.
    20. Park, J., C. Onof, and D. Kim, A hybrid stochastic rainfall model that reproduces some important rainfall characteristics at hourly to yearly timescales, Hydrology and Earth System Sciences, 23, 989-1014, doi:10.5194/hess-23-989-2019, 2019.
    21. Ferreira, D. M., C. V. S. Fernandes, E. Kaviski, and D. Fontane, Water quality modelling under unsteady state analysis: Strategies for planning and management, Journal of Environmental Management, 239, 150-158, doi:10.1016/j.jenvman.2019.03.047, 2019.
    22. Seo, S. B., Y.-O. Kim, and S.-U. Kang, Time-varying discrete hedging rules for drought contingency plan considering long-range dependency in streamflow, Water Resources Management, 33(8), 2791-2807, doi:10.1007/s11269-019-02244-5, 2019.
    23. #McLachlan, S., K. Dube, T. Gallagher, J. A. Simmonds, and N. E. Fenton, The ATEN Framework for creating the realistic synthetic electronic health record, Biomedical Engineering Systems and Technologies, BIOSTEC 2018, Communications in Computer and Information Science, Vol. 1024, Springer, Cham, doi:10.1007/978-3-030-29196-9_25, 2019.
    24. Yu, Z., S. Miller, F. Montalto, and U. Lall, Development of a non-parametric stationary synthetic rainfall generator for use in hourly water resource simulations, Water, 11, 1728, doi:10.3390/w11081728, 2019.
    25. Bermúdez, M., L. Cea, and J. Sopelana, Quantifying the role of individual flood drivers and their correlations in flooding of coastal river reaches, Stochastic Environmental Research and Risk Assessment, 33(10), 1851-1861, doi:10.1007/s00477-019-01733-8, 2019.
    26. Henao, F., and I. Dyner, Renewables in the optimal expansion of Colombian power considering the Hidroituango crisis, Renewable Energy, 158, 612-627, doi:10.1016/j.renene.2020.05.055, 2020.
    27. Peng, Y., X. Yu, H. Yan, and J. Zhang, Stochastic simulation of daily suspended sediment concentration using multivariate copulas, Water Resources Management, 34, 3913-3932, doi:10.1007/s11269-020-02652-y, 2020.
    28. Sobhaniyeh, Z., M. H. Niksokhan, and B. Omidvar, Investigation of uncertainties in a rainfall-runoff conceptual model for simulation of basin using Bayesian method, Iranian Journal of Ecohydrology, 7(1), 223-236, doi:10.22059/ije.2020.294740.1264, 2020.
    29. Wang, Q., J. Zhou, K. Huang, L. Dai, B. Jia, L. Chen, and H. Qin, A procedure for combining improved correlated sampling methods and a resampling strategy to generate a multi-site conditioned streamflow process, Water Resources Management, 35, 1011-1027, doi:10.1007/s11269-021-02769-8, 2021.
    30. Brunner, M. I., L. Slater, L. M. Tallaksen, and M. Clark, Challenges in modeling and predicting floods and droughts: A review, Wiley Interdisciplinary Reviews: Water, 8(3), e1520, doi:10.1002/wat2.1520, 2021.
    31. Wang, Q., J. Zhou, L. Dai, K. Huang, and G. Zha, Risk assessment of multireservoir joint flood control system under multiple uncertainties, Journal of Flood Risk Management, e12740, doi:10.1111/jfr3.12740, 2021.
    32. Bahrpeyma, F., M. Roantree, P. Cappellari, M. Scriney, and A. McCarren, A methodology for validating diversity in synthetic time series generation, MethodsX, 101459, doi:10.1016/j.mex.2021.101459, 2021.
    33. Pouliasis, G., G. A. Torres-Alves, and O. Morales-Napoles, Stochastic modeling of hydroclimatic processes using vine copulas, Water, 13(16), 2156, doi:10.3390/w13162156, 2021.
    34. Santana, R. F., and A. B. Celeste, Stochastic reservoir operation with data-driven modeling and inflow forecasting, Journal of Applied Water Engineering and Research, doi:10.1080/23249676.2021.1964389, 2021.

  1. S. Ceola, A. Montanari, and D. Koutsoyiannis, Toward a theoretical framework for integrated modeling of hydrological change, WIREs Water, 1 (5), 427–438, doi:10.1002/wat2.1038, 2014.

    In an attempt to provide a unified scheme for the simulation of changing behaviors of hydrological systems, a theoretical framework for stationary and non-stationary modeling is presented. The main triggers for hydrological change are reviewed, their impact on the long-term properties of the inherent system are analyzed, and theoretical solutions are proposed for their representation. Model calibration is also discussed along with the impact of hydrological change on simulation uncertainty. Non-stationarity and its simulation are examined as well. We propose a stochastic approach that is general, and allows a comprehensive treatment of uncertainty. The proposed framework is relevant to integrated modeling of hydrology and human impacts and therefore fits into the concepts of ‘Panta Rhei’, the scientific decade 2013–2022 promoted by the International Association of Hydrological Sciences.

    Additional material:

    See also: http://dx.doi.org/10.1002/wat2.1038

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Ceola, S., B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione and T. Wagener, Virtual laboratories: New opportunities for collaborative water science, Hydrology and Earth System Sciences, 19 (4), 2101-2117, 2015.
    2. Yuan, X., E.F. Wood and Z. Ma, A review on climate-model-based seasonal hydrologic forecasting: physical understanding and system development, WIREs Water, 2, 523–536, 10.1002/wat2.1088, 2015.

  1. C. Pappas, S.M. Papalexiou, and D. Koutsoyiannis, A quick gap-filling of missing hydrometeorological data, Journal of Geophysical Research-Atmospheres, 119 (15), 9290–9300, doi:10.1002/2014JD021633, 2014.

    Data-gaps are ubiquitous in hydrometeorological time series and filling these values remains still a challenge. Since datasets without missing values may be a prerequisite in performing many analyses, a quick and efficient gap-filling methodology is required. In this study the problem of filling sporadic, single-value gaps using time-adjacent observations from the same location is investigated. The applicability of a local average (i.e., based on few neighboring in time observations) is examined and its advantages over the sample average (i.e., using the whole dataset) are illustrated. The analysis reveals that a quick and very efficient (i.e., minimum mean squared estimation error) gap-filling is achieved by combining a strictly local average (i.e., using one observation before and one after the missing value) with the sample mean.

    Additional material:

    See also: http://dx.doi.org/10.1002/2014JD021633

    Works that cite this document: View on Google Scholar or ResearchGate

  1. D. Koutsoyiannis, Social vs. scientific perception of change in hydrology and climate — Reply to the Discussion by Arie Ben-Zvi on the Opinion Paper “Hydrology and Change”, Hydrological Sciences Journal, 59 (8), 1625–1626, doi:10.1080/02626667.2014.935382, 2014.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2014.935382

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Montanari, and D. Koutsoyiannis, Reply to comment by G. Nearing on ‘‘A blueprint for process-based modeling of uncertain hydrological systems’’, Water Resources Research, 50 (7), 6264–6268, doi:10.1002/2013WR014987, 2014.

    Full text: http://www.itia.ntua.gr/en/getfile/1464/1/documents/2014WRR_ReplyToNearing.pdf (204 KB)

    Additional material:

    See also: http://dx.doi.org/10.1002/2013WR014987

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Ceola, S., B. Arheimer, E. Baratti, G. Blöschl, R. Capell, A. Castellarin, J. Freer, D. Han, M. Hrachowitz, Y. Hundecha, C. Hutton, G. Lindström, A. Montanari, R. Nijzink, J. Parajka, E. Toth, A. Viglione and T. Wagener, Virtual laboratories: New opportunities for collaborative water science, Hydrology and Earth System Sciences, 19 (4), 2101-2117, 2015.

  1. G. Blöschl, A. Bardossy, D. Koutsoyiannis, Z. W. Kundzewicz, I. G. Littlewood, A. Montanari, and H. H. G. Savenije, Joint Editorial—On the future of journal publications in hydrology, Hydrological Sciences Journal, 59 (5), 955–958, doi:10.1080/02626667.2014.908041, 2014.

    Remarks:

    The Joint Editorial was also published in:

    Full text: http://www.itia.ntua.gr/en/getfile/1448/1/documents/2014JointEditorial.pdf (67 KB)

    See also: http://dx.doi.org/10.1080/02626667.2014.908041

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Montanari, A., Water Resources Research in 2013,Water Resour. Res., 50, 10.1002/2014WR015648, 2014.
    2. Hughes, D. A., K. V. Heal and C. Leduc, Improving the visibility of hydrological sciences from developing countries, Hydrological Sciences Journal, 10.1080/02626667.2014.938653, 2014.
    3. Cudennec, C., and A. De Lavenne, Editorial: Hydrogeomorphology - A long-term scientific interface, Hydrology Research, 46 (2), 175-179, 2015.

  1. D. Koutsoyiannis, Entropy: from thermodynamics to hydrology, Entropy, 16 (3), 1287–1314, doi:10.3390/e16031287, 2014.

    Some known results from statistical thermophysics as well as from hydrology are revisited from a different perspective trying: (a) to unify the notion of entropy in thermodynamic and statistical/stochastic approaches of complex hydrological systems and (b) to show the power of entropy and the principle of maximum entropy in inference, both deductive and inductive. The capability for deductive reasoning is illustrated by deriving the law of phase change transition of water (Clausius-Clapeyron) from scratch by maximizing entropy in a formal probabilistic frame. However, such deductive reasoning cannot work in more complex hydrological systems with diverse elements, yet the entropy maximization framework can help in inductive inference, necessarily based on data. Several examples of this type are provided in an attempt to link statistical thermophysics with hydrology with a unifying view of entropy.

    Related works:

    • [444] Predecessor talk

    Full text: http://www.itia.ntua.gr/en/getfile/1432/1/documents/entropy-16-01287_dk.pdf (1265 KB)

    See also: http://dx.doi.org/10.3390/e16031287

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Kundzewicz, Z. W., Quo vadis, hydrology?, Hydrological Sciences Journal, doi:10.1080/02626667.2018.1489597, 2018.

  1. A. Efstratiadis, A. D. Koussis, D. Koutsoyiannis, and N. Mamassis, Flood design recipes vs. reality: can predictions for ungauged basins be trusted?, Natural Hazards and Earth System Sciences, 14, 1417–1428, doi:10.5194/nhess-14-1417-2014, 2014.

    Despite the great scientific and technological advances in flood hydrology, everyday engineering practices still follow simplistic approaches that are easy to formally implement in ungauged areas. In general, these "recipes" have been developed many decades ago, based on field data from typically few experimental catchments. However, many of them have been neither updated nor validated across all hydroclimatic and geomorphological conditions. This has an obvious impact on the quality and reliability of hydrological studies, and, consequently, on the safety and cost of the related flood protection works. Preliminary results, based on historical flood data from Cyprus and Greece, indicate that a substantial revision of many aspects of flood engineering procedures is required, including the regionalization formulas as well as the modelling concepts themselves. In order to provide a consistent design framework and to ensure realistic predictions of the flood risk (a key issue of the 2007/60/EU Directive) in ungauged basins, it is necessary to rethink the current engineering practices. In this vein, the collection of reliable hydrological data would be essential for re-evaluating the existing "recipes", taking into account local peculiarities, and for updating the modelling methodologies as needed.

    Full text: http://www.itia.ntua.gr/en/getfile/1413/7/documents/nhess-14-1417-2014.pdf (207 KB)

    Additional material:

    See also: http://www.nat-hazards-earth-syst-sci.net/14/1417/2014/

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. van Emmerik, T. H. M., G. Mulder, D. Eilander, M. Piet, and H. Savenije, Predicting the ungauged basin: Model validation and realism assessment, Frontiers in Earth Sciences, 3:62, doi:10.3389/feart.2015.00062, 2015.
    2. Biondi, D., and L. Da Luca, Process-based design flood estimation in ungauged basins by conditioning model parameters on regional hydrological signatures, Natural Hazards, 79(2), 1015-1038, doi:10.1007/s11069-015-1889-1, 2015.
    3. Yannopoulos, S., E. Eleftheriadou, S. Mpouri, and I. Giannopoulou, Implementing the requirements of the European Flood Directive: the case of ungauged and poorly gauged watersheds, Environmental Processes, 2(1), 191-207, doi:10.1007/s40710-015-0094-2, 2015.
    4. Wałęga, A., and A. Rutkowska, Usefulness of the modified NRCS-CN method for the assessment of direct runoff in a mountain catchment, Acta Geophysica, 63(5), 1423–1446, doi:10.1515/acgeo-2015-0043, 2015.
    5. Walega, A., B. Michalec, A. Cupak, and M. Grzebinoga, Comparison of SCS-CN determination methodologies in a heterogeneous catchment, Journal of Mountain Science, 12(5), 1084-1094, doi:10.1007/s11629-015-3592-9, 2015.
    6. Awadallah, A.G., H. Saad, A. Elmoustafa, and A. Hassan, Reliability assessment of water structures subject to data scarcity using the SCS-CN model, Hydrological Sciences Journal, 61(4), 696-710, doi:10.1080/02626667.2015.1027709, 2016.
    7. Merheb, M., R. Moussa, C. Abdallah, F. Colin, C. Perrin, and N. Baghdadi, Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis, Hydrological Sciences Journal, 61(14), 2520-2539, doi:10.1080/02626667.2016.1140174, 2016.
    8. Kjeldsen, T., H. Kim, C. Jang, and H. Lee, Evidence and implications of nonlinear flood response in a small mountainous watershed, Journal of Hydrologic Engineering, 21(8), 04016024, doi:10.1061/(ASCE)HE.1943-5584.0001343, 2016.
    9. Taghvaye Salimi, E., A. Nohegar, A. Malekian, M. Hoseini, and A. Holisaz, Estimating time of concentration in large watersheds, Paddy and Water Environment, 15(1), 123-132, doi:10.1007/s10333-016-0534-2, 2017.
    10. Biondi, D., and D. L. De Luca, Rainfall-runoff model parameter conditioning on regional hydrological signatures: application to ungauged basins in southern Italy, Hydrology Research, 48(3) 714-725, doi:10.2166/nh.2016.097, 2017.
    11. Attakora-Amaniampong, E., E. Owusu-Sekyere, and D. Aboagye, Urban floods and residential rental values nexus in Kumasi, Ghana, Ghana Journal of Development Studies, 13(2), 176-194, 2016.
    12. #Destro, E., E. I. Nikolopoulos, J. D. Creutin, and M. Borga, Floods, Environmental Hazards Methodologies for Risk Assessment and Management, Dalezios, N. R. (editor), Chapter 4, IWA Publishing, 2017.
    13. van Noordwijk, M., L. Tanika, L., and B. Lusiana, Flood risk reduction and flow buffering as ecosystem services – Part 1: Theory on flow persistence, flashiness and base flow, Hydrology and Earth System Sciences, 21, 2321-2340, doi:10.5194/hess-21-2321-2017, 2017.
    14. Verma, S., R. K. Verma, S. K. Mishra, A. Singh, and G. K. Jayaraj, A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation, Hydrological Sciences Journal, 62(12), 1891-1930, doi:10.1080/02626667.2017.1334166, 2017.
    15. De Luca, D. L., and D. Biondi, Bivariate return period for design hyetograph and relationship with T-year design flood peak, Water, 9, 673, doi:10.3390/w9090673, 2017.
    16. #Danııl E., S. Michas, and G. Aerakis, Hydrologic issues in demarcation studies of watercourses in Greece, 15th International Conference on Environmental Science and Technology, CEST2017_00869, Rhodes, 2017.
    17. Wałęga, A., A. Cupak, D. M. Amatya, and E. Drożdżal, Comparison of direct outflow calculated by modified SCS-CN methods for mountainous and highland catchments in Upper Vistula basin, Poland and Lowland catchment in South Carolina, U.S.A., Acta Sci. Pol. Formatio Circumiectus, 16(1), 187–207, doi:10.15576/ASP.FC/2017.16.1.187, 2017.
    18. #Walker, N. J., K. N. Iipinge, J. D. S. Cullis, D. Scott, J. Mfune, P. Wolski, and C. Jack, Integrating climate change information into long term planning and design for critical water related infrastructure in Windhoek and other African cities, 18th WaterNet/WARFSA/GWP-SA Symposium, Swakopmund, Namibia, 2017.
    19. Garrote, J., A. Díez-Herrero, J. M. Bodoque, M. A. Perucha, P. L. Mayer, and M. Génova, Flood hazard management in public mountain recreation areas vs. ungauged fluvial basins: Case study of the Caldera de Taburiente National Park, Canary Islands (Spain), Geosciences, 8(1), 6, doi:10.3390/geosciences8010006, 2018.
    20. Petroselli, A., and S. Grimaldi, Design hydrograph estimation in small and fully ungauged basins: a preliminary assessment of the EBA4SUB framework, Journal of Flood Risk Management, 11(51), S197–S210, doi:10.1111/jfr3.12193, 2018.
    21. Zin, W., A. Kawasaki, W. Takeuchi, Z. M. L. T. San, K. Z. Htun, T. H. Aye, and S. Win, Flood hazard assessment of Bago river basin, Myanmar, Journal of Disaster Research, 13(1), 14-21, doi:10.20965/jdr.2018.p0014, 2018.
    22. Alipour, M. H., and K. M. Kibler, A framework for streamflow prediction in the world’s most severely data-limited regions: test of applicability and performance in a poorly-gauged region of China, Journal of Hydrology, 557, 41-54, doi:10.1016/j.jhydrol.2017.12.019, 2018.
    23. Hdeib, R., C. Abdallah, F. Colin, L. Brocca, and R. Moussa, Constraining coupled hydrological-hydraulic flood model by past storm events and post-event measurements in data-sparse regions, Journal of Hydrology, 565, 160-175, doi:10.1016/j.jhydrol.2018.08.008, 2018.
    24. Petroselli, A., M. Vojtek, and J. Vojteková, Flood mapping in small ungauged basins: A comparison of different approaches for two case studies in Slovakia, Hydrology Research, 50(1), 379-392, doi:10.2166/nh.2018.040, 2018.
    25. Gericke, O. J., Catchment response time and design rainfall: the key input parameters for design flood estimation in ungauged catchments, Journal of the South African Institution of Civil Engineering, 60(4), 51-67, doi:10.17159/2309-8775/2018/v60n4a6, 2018.
    26. #Trifonova, T. A., D. V. Trifonov, S. I. Abrakhin, V. N. Koneshov, A. V. Nikolaev, and S. M. Arakelian, New verification of the groundwater and tectonic processes possible impact on a series of recent catastrophic floods and debris flows (2011-2017), Debris Flows: Disasters, Risk, Forecast, Protection – Proceedings of the 5th International Conference, S. S. Chernomorets and G. V. Gavardashvili (editors), 606-618, Tbilisi, Georgia, 2018.
    27. Papaioannou, G., A. Loukas, and L. Vasiliades, Flood risk management methodology for lakes and adjacent areas: The lake Pamvotida paradigm, Proceedings, 7, 21, doi:10.3390/ECWS-3-05825, 2019.
    28. Jiang, X., L., Yang, and H. Tatano, Assessing spatial flood risk from multiple flood sources in a small river basin: A method based on multivariate design rainfall, Water, 11(5), 1031, doi:10.3390/w11051031, 2019.
    29. Sarchani, S., and I. Tsanis, Analysis of a flash flood in a small basin in Crete, Water, 11(11), 2253, doi:10.3390/w11112253, 2019.
    30. Walega, A., and T. Salata, Influence of land cover data sources on estimation of direct runoff according to SCS-CN and modified SME methods, Catena, 172, 232-242, doi:10.1016/j.catena.2018.08.032, 2019.
    31. Pinho, J. L. S., L. Vieira, J. M. P. Vieira, S. Venâncio, N. E. Simões, J. A. Sá Marques, and F. S. Santos, Assessing causes and associated water levels for an urban flood using hydroinformatic tools, Journal of Hydroinformatics, 22(1), 61-76, doi:10.2166/hydro.2019.019, 2020.
    32. Wanniarachchi, S. S., and N. T. S. Wijesekera, Challenges in field approximations of regional scale hydrology, Journal of Hydrology: Regional Studies, 27, 100647, doi:10.1016/j.ejrh.2019.100647, 2020.
    33. Fortesa, J., J. Latron, J. García-Comendador, M. Tomàs-Burguera, J. Company, A. Calsamiglia, and J. Estrany, Multiple temporal scales assessment in the hydrological response of small Mediterranean-climate catchments, Water, 12(1), 299, doi:10.3390/w12010299, 2020.
    34. Trifonova, T., D. Trifonov, D. Bukharov, S. Abrakhin, M. Arakelian, and S. Arakelian, Global and regional aspects for genesis of catastrophic floods: The problems of forecasting and estimation for mass and water balance (surface water and groundwater contribution), IntechOpen, doi:10.5772/intechopen.91623, 2020.
    35. Kastridis, A., C. Kirkenidis, and M. Sapountzis, An integrated approach of flash flood analysis in ungauged Mediterranean watersheds using post‐flood surveys and Unmanned Aerial Vehicles (UAVs), Hydrological Processes, 34(25), 4920-4939, doi:10.1002/hyp.13913, 2020.
    36. Bertini, C., L. Buonora, E. Ridolfi, F. Russo, and F. Napolitano, On the use of satellite rainfall data to design a dam in an ungauged site, Water, 12(11), 3028, doi:10.3390/w12113028, 2020.
    37. Ramadan, A. N. A., D. Nurmayadi, A. Sadili, R. R. Solihin, and Z. Sumardi, Pataruman watershed Curve Number determination study based on Indonesia land map unit, Media Komunikasi Teknik Sipil, 26(2), 258-266, doi:10.14710/mkts.v26i2.26563, 2020.
    38. Bournas, A., and E. Baltas, Comparative analysis of rain gauge and radar precipitation estimates towards rainfall-runoff modelling in a peri-urban basin in Attica, Greece, Hydrology, 8(1), 29, doi:10.3390/hydrology8010029, 2021.
    39. Devkota, N., and N. M. Shakya, Development of rainfall-runoff model for extreme storm events in the Bagmati River Basin, Nepal, Journal of Engineering Issues and Solutions, 1(1), 158-173, doi:10.3126/joeis.v1i1.36835, 2021.
    40. Almedeij, J., Modified NRCS abstraction method for flood hydrograph generation, Journal of Irrigation and Drainage Engineering, 47(10), 04021042-1, doi:10.1061/(ASCE)IR.1943-4774.0001609, 2021.
    41. Zahraei, A., R. Baghbani, and A. Linhoss, Applying a graphical method in evaluation of empirical methods for estimating time of concentration in an arid region, Water, 13(19), 2624, doi:10.3390/w13192624, 2021.
    42. Salazar-Galán, S., R. García-Bartual, J. L. Salinas, and F. Francés, A process-based flood frequency analysis within a trivariate statistical framework. Application to a semi-arid Mediterranean case study, Journal of Hydrology, doi:10.1016/j.jhydrol.2021.127081, 2021.

  1. D. Koutsoyiannis, Reconciling hydrology with engineering, Hydrology Research, 45 (1), 2–22, doi:10.2166/nh.2013.092, 2014.

    Hydrology has played an important role in the birth of science. Yet practical hydrological knowledge, related to human needs for water storage, transfer and management, existed before the development of natural philosophy and science. In contemporary times, hydrology has had strong links with engineering as its development has been related to the needs of the design and management of water infrastructures. In the 1980s these links were questioned and it was suggested that separating hydrology from engineering would be beneficial for both. It is argued that, thereafter, hydrology, instead of becoming an autonomous science, developed new dependencies, particularly on politically driven agendas. This change of direction in effect demoted the role of hydrology, for example in studying hypothetical or projected climate-related threats. Revisiting past experiences suggests that re-establishing the relationship of hydrology with engineering could be beneficial. The study of change and the implied uncertainty and risk could constitute a field of mutual integration of hydrology and engineering. Engineering experience may help hydrology to appreciate that change is essential for progress and evolution, rather than only having adverse impacts. While the uncertainty and risk cannot be eliminated they can be dealt with in a quantitative and rigorous manner.

    Related works:

    • [236] Predecessor talk

    Additional material:

    See also: http://dx.doi.org/10.2166/nh.2013.092

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Littlewood, I. G., and C.-Y. Xu, Editorial: New category of invited papers, Hydrology Research, 45 (1), p. 1, 2014.
    2. François, B., M. Borga,, S. Anquetin, J.D. Creutin, K. Engeland, A.C. Favre, B. Hingray, M.H. Ramos, D. Raynaud, B. Renard, E. Sauquet, J. F. Sauterleute, J. P. Vidal and G. Warland, Integrating hydropower and intermittent climate-related renewable energies: A call for hydrology, Hydrological Processes, 28 (21), 5465-5468, 2014.
    3. Yao, Y., S. Zhao, Y. Zhang, K. Jia and M. Liu, Spatial and decadal variations in potential evapotranspiration of China based on reanalysis datasets during 1982–2010, Atmosphere, 5(4), 737-754, 2014.
    4. Cudennec, C., and A. De Lavenne, Editorial: Hydrogeomorphology - A long-term scientific interface, Hydrology Research, 46 (2), 175-179, 2015.
    5. Vogel, R.M., U. Lall, X. Cai, B. Rajagopalan, P.K. Weiskel, R.P. Hooper and N.C. Matalas, Hydrology: The interdisciplinary science of water, Water Resources Research, 51 (6), 4409-4430, 2015.

  1. G. Tsekouras, and D. Koutsoyiannis, Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy, Renewable Energy, 63, 624–633, doi:10.1016/j.renene.2013.10.018, 2014.

    The current model for energy production, based on the intense use of fossil fuels, is both unsustainable and environmentally harmful and consequently, a shift is needed in the direction of integrating the renewable energy sources into the energy balance. However, these energy sources are unpredictable and uncontrollable as they strongly depend on time varying and uncertain hydrometeorological variables such as wind speed, sunshine duration and solar radiation. To study the design and management of renewable energy systems we investigate both the properties of marginal distributions and the dependence properties of these natural processes, including possible long-term persistence by estimating and analyzing the Hurst coefficient. To this aim we use time series of wind speed and sunshine duration retrieved from European databases of daily records. We also study a stochastic simulation framework for both wind and solar systems using the software system Castalia, which performs multivariate and multi-time-scale stochastic simulation, in order to conduct simultaneous generation of synthetic time series of wind speed and sunshine duration, on yearly, monthly and daily scale.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.renene.2013.10.018

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Varotsos, C. A., and M. N. Efstathiou, Symmetric scaling properties in global surface air temperature anomalies, Theoretical and Applied Climatology, 10.1007/s00704-014-1274-0, 2014.
    2. Abdelaziz, A. Y., Y. G. Hegazy, W. El-Khattam and M.M. Othman, Optimal allocation of stochastically dependent renewable energy based distributed generators in unbalanced distribution networks, Electric Power Systems Research, 119, 34-44, 2015.
    3. #Fortuna, L., S. Nunnari and A. Gallo, A typical day based approach to detrend solar radiation time series, MAED '14 Proceedings of the 3rd ACM International Workshop on Multimedia Analysis for Ecological Data, 25-30, ACM New York, NY, USA, 2014.
    4. Othman, M.M., A.Y. Abdelaziz, Y. G. Hegazi and W. El-Khattam, Approach for modelling stochastically dependent renewable energy-based generators using diagonal band copula, IET Renewable Power Generation, 9 (7), 809-820, 10.1049/iet-rpg.2014.0205, 2015.
    5. Bardsley, E., A finite mixture approach to univariate data simulation with moment matching, Environmental Modelling & Software, 90, 27-33, doi:10.1016/j.envsoft.2016.11.019, 2017.

  1. H. Tyralis, and D. Koutsoyiannis, A Bayesian statistical model for deriving the predictive distribution of hydroclimatic variables, Climate Dynamics, 42 (11-12), 2867–2883, doi:10.1007/s00382-013-1804-y, 2014.

    Recent publications have provided evidence that hydrological processes exhibit a scaling behaviour, also known as the Hurst phenomenon. An appropriate way to model this behaviour is to use the Hurst-Kolmogorov stochastic process. The Hurst-Kolmogorov process entails high autocorrelations even for large lags, as well as high variability even at climatic scales. A problem that, thus, arises is how to incorporate the observed past hydroclimatic data in deriving the predictive distribution of hydroclimatic processes at climatic time scales. Here with the use of Bayesian techniques we create a framework to solve the aforementioned problem. We assume that there is no prior information for the parameters of the process and use a non-informative prior distribution. We apply this method with real-world data to derive the posterior distribution of the parameters and the posterior predictive distribution of various 30-year moving average climatic variables. The marginal distributions we examine are the normal and the truncated normal (for nonnegative variables). We also compare the results with two alternative models, one that assumes independence in time and one with Markovian dependence, and the results are dramatically different. The conclusion is that this framework is appropriate for the prediction of future hydroclimatic variables conditional on the observations.

    Additional material:

    See also: http://dx.doi.org/10.1007/s00382-013-1804-y

    Works that cite this document: View on Google Scholar or ResearchGate

  1. A. Efstratiadis, A. Tegos, A. Varveris, and D. Koutsoyiannis, Assessment of environmental flows under limited data availability – Case study of the Acheloos River, Greece, Hydrological Sciences Journal, 59 (3-4), 731–750, doi:10.1080/02626667.2013.804625, 2014.

    The lower course of Acheloos River is an important hydrosystem of Greece, heavily modified by a cascade of four hydropower dams, which is now being extended by two more dams in the upper course. The design of the dams and hydropower facilities that are in operation has not considered any environmental criteria. However, in the last fifty years, numerous methodologies have been proposed to assess the negative impacts of such projects to both the abiotic and biotic environment, and to provide decision support towards establishing appropriate constraints on their operation, typically in terms of minimum flow requirements. In this study, seeking for a more environmental-friendly operation of the hydrosystem, we investigate the outflow policy from the most downstream dam, examining alternative environmental flow approaches. Accounting for data limitations, we recommend the Basic Flow Method, which is parsimonious and suitable for Mediterranean rivers, whose flows exhibit strong variability across seasons. We also show that the wetted perimeter – discharge method, which is an elementary hydraulic approach, provides consistent results, even without using any flow data. Finally, we examine the adaptation of the proposed flow policy (including artificial flooding) to the real-time hydropower generation schedule, and the management of the resulting conflicts.

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2013.804625

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Acreman, M. C., I. C. Overton, J. King, P. Wood, I. G. Cowx, M. J. Dunbar, E. Kendy, and W. Young, The changing role of ecohydrological science in guiding environmental flows, Hydrological Sciences Journal, 59(3–4), 1–18, 2014.
    2. #Egüen, M., M. J. Polo, Z. Gulliver, E. Contreras, C. Aguilar, and M. A. Losada, Flood risk trends in coastal watersheds in South Spain: direct and indirect impact of river regulation, Changes in Flood Risk and Perception in Catchments and Cities, Proc. IAHS, 370, 51-56, doi:10.5194/piahs-370-51-2015, 2015.
    3. Aguilar, C., and M. J. Polo, Assessing minimum environmental flows in nonpermanent rivers: The choice of thresholds, Environmental Modelling and Software, 79, 120-134, doi:10.1016/j.envsoft.2016.02.003, 2016.
    4. Nerantzaki, S. D., G. V. Giannakis, N. P. Nikolaidis, I. Zacharias, G. P. Karatzas, and I. A. Sibetheros, Assessing the impact of climate change on sediment loads in a large Mediterranean watershed, Soil Science, 181(7), 306-314, 2016.
    5. Poncelet, C., V. Andréassian, L. Oudin, and C. Perrin, The Quantile Solidarity approach for the parsimonious regionalization of flow duration curves, Hydrological Sciences Journal, 62(9), 1364-1380, doi:10.1080/02626667.2017.1335399, 2017.
    6. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.
    7. Gemitzi, A., and V. Lakshmi, Evaluating renewable groundwater stress with GRACE data in Greece, Groundwater, 56(3), 501-514, doi:10.1111/gwat.12591, 2018.
    8. Theodoropoulos, C., N. Skoulikidis, P. Rutschmann, and A. Stamou, Ecosystem-based environmental flow assessment in a Greek regulated river with the use of 2D hydrodynamic habitat modelling, River Research and Applications, 34(6), 538-547, doi:10.1002/rra.3284, 2018.
    9. Zhao, C., S. Yang, J. Liu, C. Liu, F. Hao, Z. Wang, H. Zhang, J. Song, S. M. Mitrovic, and R. P. Lim, Linking fish tolerance to water quality criteria for the assessment of environmental flows: A practical method for streamflow regulation and pollution control, Water Research, 141, 96-108, doi:10.1016/j.watres.2018.05.025, 2018.
    10. Operacz, A., A. Wałęga, A. Cupak, and B. Tomaszewska, The comparison of environmental flow assessment - The barrier for investment in Poland or river protection? Journal of Cleaner Production, 193, 575-592, doi:10.1016/j.jclepro.2018.05.098, 2018.
    11. Książek, L., A. Woś, J. Florek, M. Wyrębek, D. Młyński, and A. Wałęga, Combined use of the hydraulic and hydrological methods to calculate the environmental flow: Wisloka river, Poland: case study, Environmental Monitoring and Assessment, 191:254, doi:10.1007/s10661-019-7402-7, 2019.
    12. Shinozaki, Y., and N. Shirakawa, Current state of environmental flow methodologies: objectives, methods and their approaches, Journal of Japan Society of Civil Engineers – Ser. B1 (Hydraulic Engineering), 75(1), 15-30, doi:10.2208/jscejhe.75.15, 2019.
    13. Kan, H., F. Hedenus, and L. Reichenberg, The cost of a future low-carbon electricity system without nuclear power – The case of Sweden, Energy, 195, 117015, doi:10.1016/j.energy.2020.117015, 2020.
    14. Aryal, S. K., Y. Zhang, and F. Chiew, Enhanced low flow prediction for water and environmental management, Journal of Hydrology, 584, 124658, doi:10.1016/j.jhydrol.2020.124658, 2020.
    15. #Ivanova, E., and D. Myronidis, Spatial interpolation approach for environmental flow assessment in Bulgarian-Greek Rhodope mountain range, Proceeding of the 9th International Conference on Information and Communication Technologies in Agriculture, Food & Environment (HAICTA 2020), 274-285, Thessaloniki, 2020.
    16. Moccia, D., L. Salvadori, S. Ferrari, A. Carucci, and A. Pusceddu, Implementation of the EU ecological flow policy in Italy with a focus on Sardinia, Advances in Oceanography and Limnology, 11(1), doi:10.4081/aiol.2020.8781, 2020.
    17. Koskinas, A., Stochastics and ecohydrology: A study in optimal reservoir design, Dams and Reservoirs, 30(2), 53-59, doi:10.1680/jdare.20.00009, 2020.
    18. Dash, S. S., D. R. Sena, U. Mandal, A. Kumar, G. Kumar, P. K. Mishra, and M. Rawat, A hydrological modelling-based approach for vulnerable area identification under changing climate scenarios, Journal of Water and Climate Change, 12(2), 433-452, doi:10.2166/wcc.2020.202, 2021.
    19. Senent-Aparicio, J., C. George, and R. Srinivasan, Introducing a new post-processing tool for the SWAT+ model to evaluate environmental flows, Environmental Modelling and Software, 136, 104944, doi:10.1016/j.envsoft.2020.104944, 2021.
    20. Operacz, A, Possibility of hydropower development: a simple-to-use index, Energies, 14(10), 2764, doi:10.3390/en14102764, 2021.
    21. Kan, X., L. Reichenberg, and F. Hedenus, The impacts of the electricity demand pattern on electricity system cost and the electricity supply mix: a comprehensive modeling analysis for Europe, Energy, 235, 121329, doi:10.1016/j.energy.2021.121329, 2021.
    22. Greco, M., F. Arbia, and R. Giampietro, Definition of ecological flow Using IHA and IARI as an operative procedure for water management, Environments, 8(8), 77, doi:10.3390/environments8080077, 2021.

  1. F. Lombardo, E. Volpi, D. Koutsoyiannis, and S.M. Papalexiou, Just two moments! A cautionary note against use of high-order moments in multifractal models in hydrology, Hydrology and Earth System Sciences, 18, 243–255, doi:10.5194/hess-18-243-2014, 2014.

    The need of understanding and modelling the space–time variability of natural processes in hydrological sciences produced a large body of literature over the last thirty years. In this context, a multifractal framework provides parsimonious models which can be applied to a widescale range of hydrological processes, and are based on the empirical detection of some patterns in observational data, i.e. a scale invariant mechanism repeating scale after scale. Hence, multifractal analyses heavily rely on available data series and their statistical processing. In such analyses, high order moments are often estimated and used in model identification and fitting as if they were reliable. This paper warns practitioners against the blind use in geophysical time series analyses of classical statistics, which is based upon independent samples typically following distributions of exponential type. Indeed, the study of natural processes reveals scaling behaviours in state (departure from exponential distribution tails) and in time (departure from independence), thus implying dramatic increase of bias and uncertainty in statistical estimation. Surprisingly, all these differences are commonly unaccounted for in most multifractal analyses of hydrological processes, which may result in inappropriate modelling, wrong inferences and false claims about the properties of the processes studied. Using theoretical reasoning and Monte Carlo simulations, we find that the reliability of multifractal methods that use high order moments (> 3) is questionable. In particular, we suggest that, because of estimation problems, the use of moments of order higher than two should be avoided, either in justifying or fitting models. Nonetheless, in most problems the first two moments provide enough information for the most important characteristics of the distribution.

    Remarks:

    Replies to discussions can also be found in:

    http://dx.doi.org/10.13140/RG.2.1.3505.4325

    http://dx.doi.org/10.13140/RG.2.1.2391.3207

    Full text: http://www.itia.ntua.gr/en/getfile/1343/1/documents/hess-18-243-2014.pdf (731 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-18-243-2014

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Cheng, Q., Generalized binomial multiplicative cascade processes and asymmetrical multifractal distributions, Nonlin. Processes Geophys., 21, 477-487, 10.5194/npg-21-477-2014, 2014.
    2. Verrier, S., M. Crépon and S. Thiria, Scaling and stochastic cascade properties of NEMO oceanic simulations and their potential value for GCM evaluation and downscaling, Journal of Geophysical Research: Oceans, 10.1002/2014JC009811, 2014.
    3. Sassi, M.G., H. Leijnse and R. Uijlenhoet, Sensitivity of power functions to aggregation: Bias and uncertainty in radar rainfall retrieval, Water Resources Research, 50 (10), 8050-8065. 2014.
    4. Ariza-Villaverde, A.B., F.J. Jiménez-Hornero and E. Gutiérrez de Ravé, Influence of DEM resolution on drainage network extraction: A multifractal analysis, Geomorphology, 241, 243-254, 2015.
    5. Adirosi, E., L. Baldini, L. Lombardo, F. Russo, F. Napolitano, E. Volpi and A. Tokay, Comparison of different fittings of drop spectra for rainfall retrievals, Advances in Water Resources, 83, 55-67, 2015.
    6. Poveda, G., and H.D. Salas, Statistical scaling, Shannon entropy, and generalized space-time q-entropy of rainfall fields in tropical South America, Chaos, 25 (7), art. no. 075409, 10.1063/1.4922595, 2015.

  1. M. Rianna, A. Efstratiadis, F. Russo, F. Napolitano, and D. Koutsoyiannis, A stochastic index method for calculating annual flow duration curves in intermittent rivers, Irrigation and Drainage, 62 (S2), 41–49, doi:10.1002/ird.1803, 2013.

    Flow duration curves are useful tools to estimate available surface water resources, at the basin scale. These represent the percentage of time during which discharge values are exceeded, irrespective of their temporal sequence. Annual flow duration curves are useful tools for evaluating all flow quantiles of a river and their confidence intervals, by removing the effects of variability from year to year. However, these tools fail to represent the hydrological regime of ephemeral rivers, since they cannot account for zero flows. In this work we propose a technique for calculating annual flow duration curves and their standard deviation in the case of intermittent rivers. In particular, we propose a generalization of the stochastic index method, in which we use the concept of total probability and order statistics. The method is proposed to determine the conditional distribution of positive flows, for given probability dry, and is implemented on three catchments in Italy and Greece, with low (<5%) and high (>40%) frequency of zero flows, respectively.

    See also: http://dx.doi.org/10.1002/ird.1803

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Ubertini, L., and F. R. Miralles-Wilhelm, New frontiers of hydrology: Soil, water, and vegetation monitoring and modelling, Irrigation and Drainage, 62(S2), iii-iv, 2013.
    2. Müller, M. F., D. N. Dralle, and S. E. Thompson, Analytical model for flow duration curves in seasonally dry climates, Water Resources Research, 50(7), 5510-5531, 2014.
    3. Atieh, M., B. Gharabaghi, and R. Rudra, Entropy-based neural networks model for flow duration curves at ungauged sites, Journal of Hydrology, 529(3), 1007–1020, doi:10.1016/j.jhydrol.2015.08.068, 2015
    4. Varouchakis, E. A., K. Spanoudaki, D. Hristopulos, G. P. Karatzas, and G. A. Corzo Perez, Stochastic modeling of aquifer level temporal fluctuations based on the conceptual basis of the soil-water balance equation, Soil Science, 181(6), 224–231, doi:10.1097/SS.0000000000000157, 2016.
    5. #Rianna, M., F. Lombardo, B. Boccanera, and M. Giglioni, On the evaluation of FDC by the use of spot measurements, AIP Conference Proceedings, 1738, 430005, Rhodes, 2016.
    6. Ridolfi, E., M. Rianna, G. Trani, L. Alfonso, G. Di Baldassarre, F. Napolitano, and F. Russo, A new methodology to define homogeneous regions through an entropy based clustering method, Advances in Water Resources, 96, 237-250, doi:10.1016/j.advwatres.2016.07.007, 2016.
    7. #Rianna, M., E. Ridolfi, and F. Napolitano, Comparison of different hydrological similarity measures to estimate flow quantiles, AIP Conference Proceedings, 1863(1), 470002, doi:10.1063/1.4992633, 2017.
    8. Ridolfi, E., H. Kumar, and A. Bárdossy, A methodology to estimate flow duration curves at partially ungauged basins, Hydrology and Earth System Sciences, 24, 2043–2060, doi:10.5194/hess-24-2043-2020, 2020.
    9. Tramblay, Y., N. Rouché, J.-E. Paturel, G. Mahé, J.-F. Boyer, E. Amoussou, A. Bodian, H. Dacosta, H. Dakhlaoui, A. Dezetter, D. Hughes, L. Hanich, C. Peugeot, R. Tshimanga, and P. Lachassagne, ADHI: the African Database of Hydrometric Indices (1950–2018), Earth System Science Data, 13, 1547-1560, doi:10.5194/essd-13-1547-2021, 2021.

  1. D. Koutsoyiannis, Physics of uncertainty, the Gibbs paradox and indistinguishable particles, Studies in History and Philosophy of Modern Physics, 44, 480–489, doi:10.1016/j.shpsb.2013.08.007, 2013.

    The idea that, in the microscopic world, particles are indistinguishable, interchangeable and without identity has been central in quantum physics. The same idea has been enrolled in statistical thermodynamics even in a classical framework of analysis to make theoretical results agree with experience. In thermodynamics of gases, this hypothesis is associated with several problems, logical and technical. For this case, an alternative theoretical framework is provided, replacing the indistinguishability hypothesis with standard probability and statistics. In this framework, entropy is a probabilistic notion applied to thermodynamic systems and is not extensive per se. Rather, the extensive entropy used in thermodynamics is the difference of two probabilistic entropies. According to this simple view, no paradoxical behaviours, such as the Gibbs paradox, appear. Such a simple probabilistic view within a classical physical framework, in which entropy is none other than uncertainty applicable irrespective of particle size, enables generalization of mathematical descriptions of processes across any type and scale of systems ruled by uncertainty.

    Additional material:

    See also: http://dx.doi.org/10.1016/j.shpsb.2013.08.007

    Works that cite this document: View on Google Scholar or ResearchGate

  1. E. Kountouri, N. Petrochilos, N. Liaros, V. Oikonomou, D. Koutsoyiannis, N. Mamassis, N. Zarkadoulas, A. Vött, H. Hadler, P. Henning, and T. Willershäuser, The Mycenaean drainage works of north Kopais, Greece: a new project incorporating surface surveys, geophysical research and excavation, Water Science and Technology: Water Supply, 13 (3), 710–718, doi:10.2166/ws.2013.110, 2013.

    The attempt to drain the Kopais Lake was one of the most impressive and ambitious technical works of prehistoric times in Greece, inspiring myths and traditions referring to its construction and operation. The impressive remnants of the Mycenaean hydraulic works represent the most important land reclamation effort during prehistoric Greek antiquity, thus attracting the attention of the international scientific community. Nevertheless, in spite of the minor or extended contemporary surveys, the picture of the prehistoric drainage works in Kopais has remained ambiguous. Concerning the function of these works and their precise date within the Bronze Age, the proposed theories were based solely on indications from surface survey; data stemming from archaeological or geophysical research methods have been largely neglected. A new interdisciplinary project focusing on the interpretation of the Mycenaean drainage works of Kopais has been established and paper presents the results of thefirst study season.

    Additional material:

    See also: http://dx.doi.org/10.2166/ws.2013.110

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Voudouris, K. S., Y. Christodoulakos, F. Steiakakis and A. N. Angelakis, Hydrogeological characteristics of Hellenic aqueducts-like Qanats, Water, 5, 1326-1345, 2013.

  1. A. Montanari, G. Young, H. H. G. Savenije, D. Hughes, T. Wagener, L. L. Ren, D. Koutsoyiannis, C. Cudennec, E. Toth, S. Grimaldi, G. Blöschl, M. Sivapalan, K. Beven, H. Gupta, M. Hipsey, B. Schaefli, B. Arheimer, E. Boegh, S. J. Schymanski, G. Di Baldassarre, B. Yu, P. Hubert, Y. Huang, A. Schumann, D. Post, V. Srinivasan, C. Harman, S. Thompson, M. Rogger, A. Viglione, H. McMillan, G. Characklis, Z. Pang, and V. Belyaev, “Panta Rhei – Everything Flows”, Change in Hydrology and Society – The IAHS Scientific Decade 2013-2022, Hydrological Sciences Journal, 58 (6), 1256–1275, doi:10.1080/02626667.2013.809088, 2013.

    The new scientific decade 2013–2022 of IAHS, entitled “Panta Rhei – Everything Flows”, is dedicated to research activities on change in hydrology and society. The purpose of Panta Rhei is to reach an improved interpretation of the processes governing the water cycle by focusing on their changing dynamics in connection with rapidly changing human systems. The practical aim is to improve our capability to make predictions of water resources dynamics to support sustainable societal development in a changing environment. The concept implies a focus on hydrological systems as a changing interface between environment and society, whose dynamics are essential to determine water security, human safety and development, and to set priorities for environmental management. The Scientific Decade 2013–2022 will devise innovative theoretical blueprints for the representation of processes including change and will focus on advanced monitoring and data analysis techniques. Interdisciplinarity will be sought by increased efforts to bridge with the socio–economic sciences and geosciences in general. This paper presents a summary of the Science Plan of Panta Rhei, its targets, research questions and expected outcomes.

    Full text: http://www.itia.ntua.gr/en/getfile/1352/1/documents/2013HSJ_PantaRhei.pdf (803 KB)

    See also: http://dx.doi.org/10.1080/02626667.2013.809088

    Works that cite this document: View on Google Scholar or ResearchGate

    Other works that reference this work (this list might be obsolete):

    1. Hrachowitz, M., H.H.G. Savenije, G. Blöschl, J.J. McDonnell, M. Sivapalan, J.W. Pomeroy, B. Arheimer, T. Blume, M.P. Clark, U. Ehret, F. Fenicia, J.E. Freer, A. Gelfan, H.V. Gupta, D.A. Hughes, R.W. Hut, A. Montanari, S. Pande, D. Tetzlaff, P.A. Troch, S. Uhlenbrook, T. Wagener, H.C. Winsemius, R.A. Woods, E. Zehe, and C. Cudennec, A decade of Predictions in Ungauged Basins (PUB) — a review, Hydrological Sciences Journal, 58(6), 2013.
    2. Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari and G. and Blöschl, Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene, Hydrol. Earth Syst. Sci., 17, 5013-5039, 2013.
    3. Di Baldassarre, G., M. Kooy, J. S. Kemerink and L. Brandimarte, Towards understanding the dynamic behaviour of floodplains as human-water systems, Hydrol. Earth Syst. Sci., 17, 3235-3244, 10.5194/hess-17-3235-2013, 2013.
    4. Di Baldassarre, G., A. Viglione, G. Carr, L. Kuil, J. L. Salinas and G. Blöschl, Socio-hydrology: conceptualising human-flood interactions, Hydrol. Earth Syst. Sci., 17, 3295-3303, 10.5194/hess-17-3295-2013, 2013.
    5. Hughes, D. A., A review of 40 years of hydrological science and practice in Southern Africa using the Pitman rainfall-runoff model, Journal of Hydrology, 501, 111-124, 2013.
    6. #Arheimer, B., A. Collins, V. Krysanova, E. Lakshmanan, M. Meybeck and M. Stone, Preface, IAHS-AISH Proceedings and Reports, 361, v-vii, 2013.
    7. #Strasser, U., and H. Kunstmann, Tackling complexity in modelling mountain hydrology: Where do we stand, where do we go?, IAHS-AISH Proceedings and Reports, 360, 3-12, 2013.
    8. #Viglione, A., A. Montanari and G. Blöschl, Challenges of reservoir planning and management in a changing world, Considering Hydrological Change in Reservoir Planning and Management, Proceedings of H09, IAHS-IAPSO-IASPEI Assembly (IAHS Publ. 362), Gothenburg, Sweden, 2013.
    9. Spence, C., P. H. Whitfield, J. W. Pomeroy, A. Pietroniro, D. H. Burn, D. L. Peters and A. St-Hilaire, A review of the Prediction in Ungauged Basins (PUB) decade in Canada, Canadian Water Resources Journal, 38 (4), 253-262, 2013.
    10. Ehret, U., H. V. Gupta, M. Sivapalan, S. V. Weijs, S. J. Schymanski, G. Blöschl, A. N. Gelfan, C. Harman, A. Kleidon, T. A. Bogaard, D. Wang, T. Wagener, U. Scherer, E. Zehe, M. F. P. Bierkens, G. Di Baldassarre, J. Parajka, L. P. H. van Beek, A. van Griensven, M. C. Westhoff and H. C. Winsemius, Advancing catchment hydrology to deal with predictions under change, Hydrol. Earth Syst. Sci., 18, 649-671, 2014.
    11. Coron, L., V. Andréassian, C. Perrin, M. Bourqui, and F. Hendrickx, On the lack of robustness of hydrologic models regarding water balance simulation – a diagnostic approach on 20 mountainous catchments using three models of increasing complexity, Hydrology and Earth System Sciences, 18, 727-746, 2014.
    12. Kundzewicz, Z.W., S. Kanae, S. I. Seneviratne, J. Handmer, N. Nicholls, P. Peduzzi, R. Mechler, L. M. Bouweri, N. Arnell, K. Mach, R. Muir-Wood, G. R. Brakenridge, W. Kron, G. Benito, Y. Honda, K. Takahashi, and B. Sherstyukov, Flood risk and climate change: global and regional perspectives, Hydrological Sciences Journal, 10.1080/02626667.2013.857411, 2014.
    13. Tshimanga, R. M., and D. A. Hughes, Basin-scale performance of a semidistributed rainfall-runoff model for hydrological predictions and water resources assessment of large rivers: The Congo River, Water Resources Research,10.1002/2013WR014310, 2014.
    14. Elshafei, Y., M. Sivapalan, M. Tonts and M. R. Hipsey, A prototype framework for models of socio-hydrology: identification of key feedback loops with application to two Australian case-studies, Hydrol. Earth Syst. Sci., 18, 2141-2166, 2014.
    15. Di Baldassarre, G., J. S. Kemerink, M. Kooy and L. Brandimarte, Floods and societies: the spatial distribution of water-related disaster risk and its dynamics, WIREs Water, 10.1002/wat2.1015, 2014.
    16. Savenije, H. H. G., A. Y. Hoekstra and P. van der Zaag, Evolving water science in the Anthropocene, Hydrol. Earth Syst. Sci., 18, 319-332, 2014.
    17. Hall, J., B. Arheimer, M. Borga, R. Brázdil, P. Claps, A. Kiss, T. R. Kjeldsen, J. Kriaučiūnienė, Z.W. Kundzewicz, M. Lang, M. C. Llasat, N. Macdonald, N. McIntyre, L. Mediero, B. Merz, R. Merz, P. Molnar, A. Montanari, C. Neuhold, J. Parajka, R. A. P. Perdigão, L. Plavcová, M. Rogger, J. L. Salinas, E. Sauquet, C. Schär, J. Szolgay, A. Viglione and G. Blöschl, Understanding flood regime changes in Europe: a state-of-the-art assessment, Hydrol. Earth Syst. Sci., 18, 2735-2772, 10.5194/hess-18-2735-2014, 2014.
    18. Di Baldassarre, G., L. Brandimarte, L. Kuil, G. Carr, J. L. Salinas, A. Scolobig and G. Blöschl, Insights from socio-hydrology modelling on dealing with flood risk – roles of collective memory, risk-taking attitude and trust, Journal of Hydrology, 10.1016/j.jhydrol.2014.01.018, 2014.
    19. Gupta, H. V., C. Perrin, G. Blöschl, A. Montanari, R. Kumar, M. Clark and V. Andréassian, Large-sample hydrology: a need to balance depth with breadth, Hydrol. Earth Syst. Sci. , 18, 463-477, 2014.
    20. Liu, S., X. Mo, C. Liu, J. Xia and W. Zhao, On a PUB methodology from Chinese lessons, Hydrological Sciences Journal, 10.1080/02626667.2014.899702, 2014.
    21. Kandasamy, J., D. Sounthararajah, P. Sivabalan, A. Chanan, S. Vigneswaran and M. Sivapalan, Socio-hydrologic drivers of the pendulum swing between agricultural development and environmental health: A case study from Murrumbidgee River basin, Australia, Hydrology and Earth System Sciences, 18 (3), 1027-1041, 2014.
    22. Chifflard, P., and D. Karthe, Water in research and practice, Erdkunde, 68 (1), 1-2, 2014.
    23. Pagano, T., A. Wood, M. Ramos, H. Cloke, F. Pappenberger, M. Clark, M. Cranston, D. Kavetski, T. Mathevet, S. Sorooshian, and J. Verkade, Challenges of operational river forecasting, J. Hydrometeor., 10.1175/JHMD-13-0188.1, 2014.
    24. Harrigan, S., C. Murphy, J. Hall, R. L. Wilby and J. Sweeney, Attribution of detected changes in streamflow using multiple working hypotheses, Hydrol. Earth Syst. Sci., 18, 1935-1952, 2014.
    25. Sivakumar, B., Networks: a generic theory for hydrology?, Stochastic Environmental Research and Risk Assessment, 10.1007/s00477-014-0902-7, 2014.
    26. Kornelsen, K.C., and P. Coulibaly, Synthesis review on groundwater discharge to surface water in the Great Lakes Basin, Journal of Great Lakes Research, 40 (2), 247-256, 2014.
    27. Makurira, H., B. Mapani, D. Mazvimavi, M. Mul, B. Tapela and V. Wepener, Implementing water science research to benefit all, Physics and Chemistry of the Earth, 67-69, 1-3, 2014.
    28. Johnston, R., and V. Smakhtin, Hydrological modeling of large river basins: how much is enough?, Water Resources Management, 10.1007/s11269-014-0637-8, 2014.
    29. #Guillaume, J. H. A., M. Kummu, M. Porkka and O. Varis, A conceptual model to guide exploration of global food-water security, Proceedings of 7th International Congress on Environmental Modelling and Software, D. P. Ames, N. W.T. Quinn and A. E. Rizzoli (eds.), San Diego, CA, USA, 2014.
    30. Ronco, P., V. Gallina, S. Torresan, A. Zabeo, E. Semenzin, A. Critto and A. Marcomini, The KULTURisk Regional Risk Assessment methodology for water-related natural hazards – Part 1: Physical-environmental assessment, Hydrol. Earth Syst. Sci., 18 (12), 5399-5414, 2014.
    31. Javelle, P., J. Demargne, D. Defrance, J. Pansu and P. Arnaud, Evaluating flash-flood warnings at ungauged locations using post-event surveys: A case study with the AIGA warning system, Hydrological Sciences Journal, 59 (7), 1390-1402, 2014.
    32. Hughes, D. A., K. V. Heal and C. Leduc, Improving the visibility of hydrological sciences from developing countries, Hydrological Sciences Journal, 10.1080/02626667.2014.938653, 2014.
    33. Saraiva Okello, A. M. L., I. Masih, S. Uhlenbrook, G. W. P. Jewitt, P. van der Zaag and E. Riddell, Drivers of spatial and temporal variability of streamflow in the Incomati River Basin, Hydrol. Earth Syst. Sci., 19 (2), 657-673, 10.5194/hess-19-657-2015, 2015.
    34. Barthel, R., HESS Opinions "Integration of groundwater and surface water research: an interdisciplinary problem?", Hydrol. Earth Syst. Sci., 18, 2615-2628, 10.5194/hess-18-2615-2014, 2014.
    35. #Montanari, A., S. Ceola and E. Baratti, Panta Rhei: An evolving scientific decade with a focus on water systems, IAHS-AISH Proceedings and Reports, 364, 279-284, 2014.
    36. #Croke, B. F. W., R. S. Blakers, S. El Sawah, B. Fu, J. H. A. Guillaume, R. A. Kelly, M. J. Patrick, A. Ross, J. Ticehurst, R. Barthel and A. J. Jakeman, Marrying Hydrological Modelling and Integrated Assessment for the needs of Water Resource Management, IAHS-AISH Proceedings and Reports, 364, 351-356, 2014.
    37. #Arheimer, B., and G. Lindström, Electricity vs Ecosystems - Understanding and predicting hydropower impact on Swedish river flow, IAHS-AISH Proceedings and Reports, 364, 313-319, 2014.
    38. #Di Baldassarre, G., K. Yan, M. R. Ferdous and L. Brandimarte, The interplay between human population dynamics and flooding in Bangladesh: A spatial analysis, IAHS-AISH Proceedings and Reports, 364, 188-191, 2014.
    39. #Masoero, A., P. Claps, E. Gallo, D. Ganora and F. Laio, Along-the-net reconstruction of hydropower potential with consideration of anthropic alterations, IAHS-AISH Proceedings and Reports, 364, 339-344, 2014.
    40. Müller, E. N., L. van Schaik, T. Blume, A. Bronstert, J. Carus, J. H. Fleckenstein, N. Fohrer, K. Geissler, H. H. Gerke, T. Graeff, C. Hesse, A. Hildebrandt, F. Holker, P. Hunke, K. Korner, J. Lewandowski, D. Lohmann, K. Meinikmann, A. Schibalski, B. Schmalz, B. Schroder and B. Tietjen, Skalen, Schwerpunkte, Rückkopplungen und Herausforderungen der ökohydrologischen Forschung in Deutschland [Scales, key aspects, feedbacks and challenges of ecohydrological research in Germany], Hydrologie und Wasserbewirtschaftung, 58 (4) 221-240, 10.5675/HyWa_2014,4_2, 2014.
    41. Tramblay, Y., E. Amoussou, W. Dorigo and G. Mahé, Flood risk under future climate in data sparse regions: Linking extreme value models and flood generating processes, Journal of Hydrology, 519A, 549-558, 2014.
    42. Pande, S., M. Ertsen and M. Sivapalan, Endogenous technological and population change under increasing water scarcity, Hydrol. Earth Syst. Sci., 18, 3239-3258, 10.5194/hess-18-3239-2014, 2014.
    43. Beven, K., What we see now: Event-persistence and the predictability of hydro-eco-geomorphological systems, Ecological Modelling, 10.1016/j.ecolmodel.2014.07.019, 2014.
    44. Zhang, J., X. Song, G. Wang, R. He and X. Wang, Development and challenges of urban hydrology in a changing environment: I: Hydrological response to urbanization, Shuikexue Jinzhan/Advances in Water Science, 25 (4), 594-605, 2014.
    45. Coron, L., V. Andréassian, C. Perrin and N. Le Moine, Graphical tools based on Turc-Budyko plots to detect changes in catchment behaviour, Hydrological Sciences Journal, 10.1080/02626667.2014.964245, 2014.
    46. Bartholomeus, R. P., J. H. Stagge, L. M. Tallaksen and J. P. M. Witte, How over 100 years of climate variability may affect estimates of potential evaporation, Hydrol. Earth Syst. Sci. Discuss., 11, 10787-10828, 10.5194/hessd-11-10787-2014, 2014.
    47. Thirel, G., V. Andréassian, C. Perrin, J.-N. Audouy, L. Berthet, P. Edwards, N. Folton, C. Furusho, A. Kuentz, J. Lerat, G. Lindström, E. Martin, T. Mathevet, R. Merz, J. Parajka, D. Ruelland, and J. Vaze, Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments, Hydrological Sciences Journal, doi:10.1080/02626667.2014.9672482014, 2014.
    48. Willems, P., O. Batelaan, D. A. Hughes, P. W. Swarzenski , Editorial for Journal of Hydrology: Regional Studies, Journal of Hydrology: Regional Studies, 1, A1–A5, 2014.
    49. Li, H. Y., M. Sivapalan, F. Tian and C. Harman, Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume, Water Resources Research, 10.1002/2014WR016307, 2014.
    50. Delsman, J. R., M. J. Waterloo, M. M. A. Groen, J. Groen and P. J. Stuyfzand, Investigating summer flow paths in a Dutch agricultural field using high frequency direct measurements, Journal of Hydrology, 10.1016/j.jhydrol.2014.10.058, 2014.
    51. Rockström, J., M. Falkenmark, T. Allan, C. Folke, L. Gordon, A. Jägerskog, M. Kummu, M. Lannerstad, M. Meybeck, D. Molden, S. Postel, H.H.G. Savenije, U. Svedin, A. Turton and O. Varis, The unfolding water drama in the Anthropocene: Towards a resilience-based perspective on water for global sustainability, Ecohydrology, 7 (5), 1249-1261, 2014.
    52. Rodrigues, D.B.B., H.V. Gupta and E.M. Mendiondo, A blue/green water-based accounting framework for assessment of water security, Water Resources Research, 50 (9), 7187-7205, 2014.
    53. Tauro, F., M. Porfiri and S. Grimaldi, Orienting the camera and firing lasers to enhance large scale particle image velocimetry for streamflow monitoring, Water Resources Research, 50 (9), 7470-7483, 2014.
    54. Jaramillo, F., and G. Destouni, Developing water change spectra and distinguishing change drivers worldwide, Geophysical Research Letters, 41 (23), 8377-8386, 2014.
    55. François, B., M. Borga,, S. Anquetin, J.D. Creutin, K. Engeland, A.C. Favre, B. Hingray, M.H. Ramos, D. Raynaud, B. Renard, E. Sauquet, J. F. Sauterleute, J. P. Vidal and G. Warland, Integrating hydropower and intermittent climate-related renewable energies: A call for hydrology, Hydrological Processes, 28 (21), 5465-5468, 2014.
    56. Bierkens, M.F.P., V.A. Bell, P. Burek, N. Chaney, L.E. Condon, C.H. David, A. de Roo, P. Döll, N. Drost, J.S. Famiglietti, M. Flörke, D.J. Gochis, P. Houser, R. Hut, J. Keune, S. Kollet, R.M. Maxwell, J.T. Reager, L. Samaniego, E. Sudicky, E.H. Sutanudjaja, N. van de Giesen, H. Winsemius and E.F. Wood, Hyper-resolution global hydrological modelling: What is next?: "Everywhere and locally relevant", Hydrological Processes, 29 (2), 310-320, 2015.
    57. Chiew, F. H. S., and J. Vaze, Hydrologic nonstationarity and extrapolating models to predict the future: overview of session and proceeding, Proc. IAHS, 371, 17–21, doi:10.5194/piahs-371-17-2015, 2015.
    58. Hamel, P., and A.J. Guswa, Uncertainty analysis of a spatially explicit annual water-balance model: Case study of the Cape Fear basin, North Carolina, Hydrology and Earth System Sciences, 19 (2), 839-853, 2015.
    59.