Andreas Efstratiadis

Assistant Professor, Civil Engineer, MSc., Dr. Engineer
A.Efstratiadis@itia.ntua.gr
+30-2107722861

Participation in research projects

Participation as Project Director

  1. Modernization of the management of the water supply system of Athens - Update

Participation as Principal Investigator

  1. Open Hydrosystem Information Network (OpenHi.net)
  2. Nonlinear methods in multicriteria water resource optimization problems

Participation as Researcher

  1. DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools
  2. EU COST Action ES0901: European procedures for flood frequency estimation (FloodFreq)
  3. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system
  4. Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information"
  5. OpenMI Life
  6. Cost of raw water of the water supply of Athens
  7. Observations, Analysis and Modeling of Lightning Activity in Thunderstorms, for Use in Short Term Forecasting of Flash Floods
  8. Flood risk estimation and forecast using hydrological models and probabilistic methods
  9. Support on the compilation of the national programme for water resources management and preservation
  10. Investigation of management scenarios for the Smokovo reservoir
  11. Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)
  12. Modernisation of the supervision and management of the water resource system of Athens
  13. Investigation of scenarios for the management and protection of the quality of the Plastiras Lake
  14. Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3

Participation in engineering studies

  1. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Ανατολικής Πελοποννήσου (GR03)
  2. Consultancy Services for Conceptual Design, Preparation of Bidding Documents, Assistance during the Selection of Contractor & Monitoring/Supervision of Construction, Instalation, Operation & Maintainance for Traffic Control (CTC) for Greater Gaborone City
  3. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Κρήτης (GR13)
  4. Παροχή Συμβουλευτικών Υπηρεσιών για την Κατάρτιση του 2ου Σχεδίου Διαχείρισης Λεκάνης Απορροής Ποταμού της Κύπρου για την Εφαρμογή της Οδηγίας 2000/60/ΕΚ και για την Κατάρτιση του Σχεδίου Διαχείρισης Κινδύνων Πλημμύρας για την Εφαρμογή της Οδηγίας 2007/60
  5. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Δυτικής Πελοποννήσου (GR01)
  6. Έργα Ορεινής Υδρονομίας Ρεμάτων Ορεινών Λεκανών Απορροής Αλμωπίας
  7. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Βόρειας Πελοποννήσου (GR02)
  8. Pleriminary study of Almopaios dam
  9. Hydrological study of the ski center area of Parnassos
  10. Water supply works from Gadouras dam - Phase B
  11. Specific Technical Study for the Ecological Flow from the Dam of Stratos
  12. Μελέτες Διερεύνησης Προβλημάτων Άρδευσης και Δυνατότητας Κατασκευής Ταμιευτήρων Νομού Βοιωτίας
  13. Water resource management of the Integrated Tourist Development Area in Messenia
  14. Hydrological and hydraulic study for the flood protection of the new railway in the region of Sperhios river
  15. Engineering consultant for the project "Water supply of Heracleio and Agios Nicolaos from the Aposelemis dam"
  16. Preliminary Water Supply Study of the Thermoelectric Livadia Power Plant
  17. Complementary study of environmental impacts from the diversion of Acheloos to Thessaly

Published work

Publications in scientific journals

  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.
  2. G.-K. Sakki, I. Tsoukalas, and A. Efstratiadis, A reverse engineering approach across small hydropower plants: a hidden treasure of hydrological data?, Hydrological Sciences Journal, 2021, (in press).
  3. 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.
  4. G. Papaioannou, L. Vasiliades, A. Loukas, A. Alamanos, A. Efstratiadis, A. Koukouvinos, I. Tsoukalas, and P. Kossieris, A flood inundation modelling approach for urban and rural areas in lake and large-scale river basins, Water, 13 (9), 1264, doi:10.3390/w13091264, 2021.
  5. 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.
  6. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.
  7. A. Tegos, W. Schlüter, N. Gibbons, Y. Katselis, and A. Efstratiadis, Assessment of environmental flows from complexity to parsimony - Lessons from Lesotho, Water, 10 (10), 1293, doi:10.3390/w10101293, 2018.
  8. 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.
  9. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A framework for dry period low flow forecasting in Mediterranean streams, Water Resources Management, 32 (15), 4911–1432, doi:10.1007/s11269-018-2060-z, 2018.
  10. I. Tsoukalas, S.M. Papalexiou, A. Efstratiadis, and C. Makropoulos, A cautionary note on the reproduction of dependencies through linear stochastic models with non-Gaussian white noise, Water, 10 (6), 771, doi:10.3390/w10060771, 2018.
  11. G. Papaioannou, A. Efstratiadis, L. Vasiliades, A. Loukas, S.M. Papalexiou, A. Koukouvinos, I. Tsoukalas, and P. Kossieris, An operational method for Floods Directive implementation in ungauged urban areas, Hydrology, 5 (2), 24, doi:10.3390/hydrology5020024, 2018.
  12. E. Michailidi, S. Antoniadi, A. Koukouvinos, B. Bacchi, and A. Efstratiadis, Timing the time of concentration: shedding light on a paradox, Hydrological Sciences Journal, 63 (5), 721–740, doi:10.1080/02626667.2018.1450985, 2018.
  13. E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, The curve number concept as a driver for delineating hydrological response units, Water, 10 (2), 194, doi:10.3390/w10020194, 2018.
  14. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Stochastic periodic autoregressive to anything (SPARTA): Modelling and simulation of cyclostationary processes with arbitrary marginal distributions, Water Resources Research, 54 (1), 161–185, WRCR23047, doi:10.1002/2017WR021394, 2018.
  15. 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.
  16. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, European Water, 57, 337–343, 2017.
  17. 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.
  18. 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.
  19. 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.
  20. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. J. A. P. Pollacco, B. P. Mohanty, and A. Efstratiadis, Weighted objective function selector algorithm for parameter estimation of SVAT models with remote sensing data, Water Resources Research, 49 (10), 6959–6978, doi:10.1002/wrcr.20554, 2013.
  28. N. Mamassis, A. Efstratiadis, and E. Apostolidou, Topography-adjusted solar radiation indices and their importance in hydrology, Hydrological Sciences Journal, 57 (4), 756–775, doi:10.1080/02626667.2012.670703, 2012.
  29. A. Efstratiadis, and K. Hadjibiros, Can an environment-friendly management policy improve the overall performance of an artificial lake? Analysis of a multipurpose dam in Greece, Environmental Science and Policy, 14 (8), 1151–1162, doi:10.1016/j.envsci.2011.06.001, 2011.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.
  40. 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.
  41. 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.
  42. 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.
  43. 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.

Book chapters and fully evaluated conference publications

  1. 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.
  2. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Development of a distributed hydrological software application employing novel velocity-based techniques, 11th World Congress on Water Resources and Environment “Managing Water Resources for a Sustainable Future”, Madrid, European Water Resources Association, 2019.
  3. C. Rebolho, V. Andréassian, I. Tsoukalas, et A. Efstratiadis, La crue du Loing de Juin 2016 était-elle exceptionnelle?, De la prévision des crues à la gestion de crise, Avignon, Société Hydrotechnique de France, 2018.
  4. 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.
  5. I. Tsoukalas, C. Makropoulos, and A. Efstratiadis, Stochastic simulation of periodic processes with arbitrary marginal distributions, 15th International Conference on Environmental Science and Technology (CEST2017), Rhodes, Global Network on Environmental Science and Technology, 2017.
  6. G. Papaioannou, L. Vasiliades, A. Loukas, A. Efstratiadis, S.M. Papalexiou, Y. Markonis, and A. Koukouvinos, A methodological approach for flood risk management in urban areas: The Volos city paradigm, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  7. 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.
  8. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.
  9. T. Vergou, A. Efstratiadis, and D. Dermatas, Water balance model for evaluation of landfill malfunction due to leakage, Proceedings of ISWA 2016 World Congress, Novi Sad, Ιnternational Solid Waste Association, 2016.
  10. S. Mihas, A. Efstratiadis, K. Nikolaou, and N. Mamassis, Drought and water scarcity management plan for the Peloponnese river basin districts, 12th International Conference “Protection & Restoration of the Environment”, Skiathos, Dept. of Civil Engineering and Dept. of Planning & Regional Development, Univ. Thessaly, Stevens Instute of Technology, 2014.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, V. Kaffes, C. Papathanasiou, and M. Mimikou, Multi-reservoir management with Open-MI, Proceedings of the 11th International Conference on Environmental Science and Technology, Chania, A, 788–795, Department of Environmental Studies, University of the Aegean, 2009.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.

Conference publications and presentations with evaluation of abstract

  1. K.-K. Drakaki, G.-K. Sakki, I. Tsoukalas, P. Kossieris, and A. Efstratiadis, Setting the problem of energy production forecasting for small hydropower plants in the Target Model era, EGU General Assembly 2021, online, EGU21-3168, doi:10.5194/egusphere-egu21-3168, European Geosciences Union, 2021.
  2. V. Kourakos, A. Efstratiadis, and I. Tsoukalas, Can hydrological model identifiability be improved? Stress-testing the concept of stochastic calibration, EGU General Assembly 2021, online, EGU21-11704, doi:10.5194/egusphere-egu21-11704, European Geosciences Union, 2021.
  3. K. Risva, G.-K. Sakki, A. Efstratiadis, and N. Mamassis, Hydropower potential assessment made easy via the unit geo-hydro-energy index, EGU General Assembly 2021, online, EGU21-4462, doi:10.5194/egusphere-egu21-4462, European Geosciences Union, 2021.
  4. G.-K. Sakki, I. Tsoukalas, P. Kossieris, and A. Efstratiadis, A dilemma of small hydropower plants: Design with uncertainty or uncertainty within design?, EGU General Assembly 2021, online, EGU21-2398, doi:10.5194/egusphere-egu21-2398, European Geosciences Union, 2021.
  5. 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.
  6. M. Nezi, C. Ntigkakis, I. Tsoukalas, and A. Efstratiadis, Multidimensional context for extreme analysis of daily streamflow, rainfall and accumulated rainfall across USA, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-19674, doi:egusphere-egu2020-19674, 2020.
  7. C. Ntigkakis, M. Nezi, and A. Efstratiadis, Post-extraction of flood hydrographs under limited and heterogeneous information: Case study of Western Attica event, November 2017, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-18262, doi:egusphere-egu2020-18262, 2020.
  8. A. G. Pettas, P. Mavritsakis, I. Tsoukalas, N. Mamassis, and A. Efstratiadis, Empirical metric for uncertainty assessment of wind forecasting models in terms of power production and economic efficiency, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-8018, doi:10.5194/egusphere-egu2020-8018, 2020.
  9. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Distributed hydrological modelling using spatiotemporally varying velocities, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-13402, doi:10.5194/egusphere-egu2020-13402, 2020.
  10. E. Manta, R. Ioannidis, G.-F. Sargentis, and A. Efstratiadis, Aesthetic evaluation of wind turbines in stochastic setting: Case study of Tinos island, Greece, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-5484, doi:10.5194/egusphere-egu2020-5484, 2020.
  11. G.-K. Sakki, V. Papalamprou, I. Tsoukalas, N. Mamassis, and A. Efstratiadis, Stochastic modelling of hydropower generation from small hydropower plants under limited data availability: from post-assessment to forecasting, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-8129, doi:10.5194/egusphere-egu2020-8129, 2020.
  12. 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.
  13. 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.
  14. L. M. Tsiami, E. Zacharopoulou, D. Nikolopoulos, I. Tsoukalas, N. Mamassis, A. Kallioras, and A. Efstratiadis, The use of Artificial Neural Networks with different sources of spatiotemporal information for flash flood predictions, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-7315, European Geosciences Union, 2019.
  15. P. Mavritsakis, A. G. Pettas, I. Tsoukalas, G. Karakatsanis, N. Mamassis, and A. Efstratiadis, A stochastic simulation framework for representing water, energy and financial fluxes across a non-connected island, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-8758, European Geosciences Union, 2019.
  16. 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.
  17. 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.
  18. 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.
  19. A. Ataliotis, E. Koumaki, P. Dimitriadis, A. Efstratiadis, and K. Noutsopoulos, Investigation of the major uncertainty sources of an integrated plant-wide wastewater treatment model, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18719-1, European Geosciences Union, 2018.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. D. Nikolopoulos, A. Efstratiadis, G. Karavokiros, N. Mamassis, and C. Makropoulos, Stochastic simulation-optimization framework for energy cost assessment across the water supply system of Athens, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-12290, European Geosciences Union, 2018.
  25. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, Low-flow analysis in Mediterranean basins, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18880, European Geosciences Union, 2018.
  26. 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.
  27. E. Michailidi, S. Antoniadi, A. Koukouvinos, B. Bacchi, and A. Efstratiadis, Velocity-based approach for establishing a varying time of concentration: Α study in three Mediterranean countries, Le Giornate dell’ Idrologia 2017, Favignana, Società Idrologica Italiana, 2017.
  28. 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.
  29. 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.
  30. E. Michailidi, S. Antoniadi, A. Koukouvinos, B. Bacchi, and A. Efstratiadis, Adaptation of the concept of varying time of concentration within flood modelling: Theoretical and empirical investigations across the Mediterranean, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10663-1, European Geosciences Union, 2017.
  31. Y. Moustakis, P. Kossieris, I. Tsoukalas, and A. Efstratiadis, Quasi-continuous stochastic simulation framework for flood modelling, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-534, European Geosciences Union, 2017.
  32. T. Vergou, A. Efstratiadis, and D. Dermatas, Water balance model for evaluation of landfill malfunction due to leakage, 13th International Conference on Protection and Restoration of the Environment, Mykonos, 2016.
  33. M. Giglioni, A. Efstratiadis, F. Lombardo, F. Napolitano, and F. Russo, Comparative assessment of different drought indices across the Mediterranean, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-18537, European Geosciences Union, 2016.
  34. 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.
  35. A. Efstratiadis, S.M. Papalexiou, Y. Markonis, A. Koukouvinos, L. Vasiliades, G. Papaioannou, and A. Loukas, Flood risk assessment at the regional scale: Computational challenges and the monster of uncertainty, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-12218, European Geosciences Union, 2016.
  36. 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.
  37. E. Rozos, D. Nikolopoulos, A. Efstratiadis, A. Koukouvinos, and C. Makropoulos, Flow based vs. demand based energy-water modelling, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-6528, European Geosciences Union, 2015.
  38. 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.
  39. 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.
  40. A. Drosou, P. Dimitriadis, A. Lykou, P. Kossieris, I. Tsoukalas, A. Efstratiadis, and N. Mamassis, Assessing and optimising flood control options along the Arachthos river floodplain (Epirus, Greece), European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-9148, European Geosciences Union, 2015.
  41. 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.
  42. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Handling time-expensive global optimization problems through the surrogate-enhanced evolutionary annealing-simplex algorithm, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5923, European Geosciences Union, 2015.
  43. 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.
  44. 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.
  45. 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.
  46. 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.
  47. 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.
  48. 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.
  49. 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.
  50. 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.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. 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.
  56. 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.
  57. 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.
  58. 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.
  59. M. Mathioudaki, A. Efstratiadis, and N. Mamassis, Investigation of hydrological design practices based on historical flood events in an experimental basin of Greece (Lykorema, Penteli), Advanced methods for flood estimation in a variable and changing environment, Volos, University of Thessaly, 2012.
  60. 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.
  61. 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.
  62. 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.
  63. A. Christofides, S. Kozanis, G. Karavokiros, Y. Markonis, and A. Efstratiadis, Enhydris: A free database system for the storage and management of hydrological and meteorological data, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, 8760, European Geosciences Union, 2011.
  64. M. Rianna, E. Rozos, A. Efstratiadis, and F. Napolitano, Assessing different levels of model complexity for the Liri-Garigliano catchment simulation, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, 4067, European Geosciences Union, 2011.
  65. E. Galiouna, A. Efstratiadis, N. Mamassis, and K. Aristeidou, Investigation of extreme flows in Cyprus: empirical formulas and regionalization approaches for peak flow estimation, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, 2077, European Geosciences Union, 2011.
  66. A. Efstratiadis, New insights on model evaluation inspired by the stochastic simulation paradigm, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, 1852, European Geosciences Union, 2011.
  67. K. Hadjibiros, and A. Efstratiadis, Balancing between nature, economy and society conflicting priorities: the Plastiras lake landscape, International Conference in Landscape Ecology, Brno, 2013, Czech Association for Landscape Ecology (CZ-IALE), 2010.
  68. 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.
  69. 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.
  70. A. Efstratiadis, and S.M. Papalexiou, The quest for consistent representation of rainfall and realistic simulation of process interactions in flood risk assessment, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 11101, European Geosciences Union, 2010.
  71. 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.
  72. 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.
  73. 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.
  74. 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.
  75. 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.
  76. 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.
  77. 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.
  78. 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.
  79. 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.
  80. 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.
  81. 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.
  82. 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.
  83. 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.
  84. 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.
  85. 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.
  86. 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.
  87. 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.
  88. 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.
  89. 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.
  90. 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.
  91. 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.
  92. 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.

Presentations and publications in workshops

  1. 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.
  2. 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.
  3. A. Efstratiadis, Dams and their environmental impacts in Greece: insights, problems and challenges, Adaptive Management of Barriers in European Rivers (AMBER) River conservation actions – Greece AMBER National Workshop, Ministry of Environment & Energy, doi:10.13140/RG.2.2.22475.44323, Athens, 2019.
  4. 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.
  5. A. Efstratiadis, Hydrologists against the terrifying uncertainty: Is the beast invincible?, School for Young Scientists “Modelling and forecasting of river flows and managing hydrological risks: Towards a new generation of methods” (2017), Moscow State University, Russian Academy of Sciences, Lomonosov Moscow State University, 2017.
  6. A. Efstratiadis, Water resources management in practice: From sophisticated simulations to simple decisions, School for Young Scientists “Modelling and forecasting of river flows and managing hydrological risks: Towards a new generation of methods” (2017), Moscow State University, Russian Academy of Sciences, Lomonosov Moscow State University, 2017.
  7. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 5th Hellenic Conference of Surveying Enginners, Athens, 2017.
  8. 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.
  9. 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.
  10. A. D. Koussis, and A. Efstratiadis, Hydrological simulation and forecasting models, Workshop - Deucalion research project, Goulandris National Histroy Museum, 2014.
  11. A. Efstratiadis, Adaptation of regional hydrological formulas to Greek basins, Workshop - Deucalion research project, Goulandris National Histroy Museum, 2014.
  12. 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.
  13. 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.
  14. 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.
  15. A. Efstratiadis, Models in practice: Experience from the water supply system of Athens, Invited lecture, Tokyo, Tokyo Metropolitan University, 2010.
  16. A. Loukas, A. Efstratiadis, and L. Vasiliades, Review of existing simulation based flood-frequency frameworks in Greece, EU COST Action ES0901: European Procedures for Flood Frequency Estimation (FloodFreq) - 3rd Management Committee Meeting, Prague, 2010.
  17. A. Efstratiadis, L. Vasiliades, and A. Loukas, Review of existing statistical methods for flood frequency estimation in Greece, EU COST Action ES0901: European Procedures for Flood Frequency Estimation (FloodFreq) - 3rd Management Committee Meeting, Prague, 2010.
  18. 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.
  19. E. Safiolea, A. Efstratiadis, S. Kozanis, I. Liagouris, and C. Papathanasiou, Integrated modelling of a River-Reservoir system using OpenMI, OpenMI-LIFE Pinios Workshop, Volos, 2009.
  20. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, and V. Kaffes, Multi-reservoir management with OpenMI, OpenMI-LIFE Pinios Workshop, Volos, 2009.
  21. 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.
  22. 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.
  23. E. Safiolea, I. Liagouris, A. Efstratiadis, and S. Kozanis, Impact of climate change scenarios on the reliability of a reservoir, 2nd OpenMI-Life and Association Workshops On Integrated Modelling for Integrated Water Management, CEH, Wallingford, UK, 2007.
  24. A. Efstratiadis, S. Kozanis, I. Liagouris, and E. Safiolea, Migration of a reservoir management model (RMM-NTUA), 1st OpenMI Life Workshop, Aquafin, Aartselaar, Belgium, 2007.
  25. 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.
  26. S. Kozanis, and A. Efstratiadis, Zygos: A basin processes simulation model, 21st European Conference for ESRI Users, Athens, Greece, 2006.
  27. A. Efstratiadis, Strategies and algorithms for multicriteria calibration of complex hydrological models, Presentation of research activities of the Department of Water Resources, Athens, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 2006.
  28. A. Efstratiadis, HYDROGEIOS: Geo-hydrological model for watershed simulation, 15th meeting of the Greek users of Geographical Information Systems (G.I.S.) ArcInfo - ArcView - ArcIMS, Athens, Marathon Data Systems, 2005.
  29. A. Efstratiadis, Nonlinear methods in multicriteria water resource problems, "Hydromedon" - First meeting of PhD students, Patra, University of Patra, 2005.
  30. 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.
  31. 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.
  32. 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.

Various publications

  1. 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.

Books

  1. 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.

Educational notes

  1. 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.
  2. A. Efstratiadis, G.-F. Sargentis, and N. Mamassis, Lecture notes on Environmental Impacts: Analysis of environmental impacts from large hydraulic structures, 37 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2019.
  3. A. Efstratiadis, Lecture notes on Urban Hydrology: Urban sewage works, 31 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, May 2019.
  4. C. Makropoulos, A. Efstratiadis, and P. Kossieris, Lecture notes on Hydraulics and Hydraulic Works: Water Supply, 80 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, December 2019.
  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, and A. Efstratiadis, Lecture notes on Energy Technology, 267 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, October 2018.
  7. C. Makropoulos, and A. Efstratiadis, Lecture notes on Water Resource Systems Optimzation - Hydroinformatics, 151 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2018.
  8. 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.
  9. A. Efstratiadis, and P. Papanicolaou, Lecture notes on Hydraulic Structures and Dams, 93 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2018.
  10. N. Mamassis, A. Koukouvinos, and A. Efstratiadis, Lecture notes: Geographical Information Systems for Hydrology, School of Pedagogical & Technological Education (ASPAITE), 2017.
  11. 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.
  12. A. Efstratiadis, The water supply system of Athens: Management complexities and modelling challenges vs. low risk & cost decisions, October 2016.
  13. 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.
  14. S. Mihas, A. Efstratiadis, and D. Dermatas, Lecture notes on "Hydraulic Structures - Dams", 460 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, December 2015.
  15. 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.
  16. A. Efstratiadis, Applications of stochastic simulation in water resource systems - The software "Castalia", 19 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, March 2014.
  17. A. Efstratiadis, Flood simulation models, 24 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, May 2013.
  18. A. Efstratiadis, Hydrogeios as an operational tool for hydrological simulation and management of human-modified basins, 24 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, May 2012.
  19. A. Efstratiadis, Environment-friendly policies and water resources development: The case of Plastiras reservoir , 14 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, May 2012.
  20. A. Efstratiadis, Simulation and optimization of the management of the water resource system of Athens, 28 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, January 2012.
  21. A. Efstratiadis, Lecture notes on flood hydrology and design of sewage networks, 44 pages, June 2011.
  22. C. Makropoulos, and A. Efstratiadis, Lecture notes on Water Resource System Optimization and Hydroinformatics, 307 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, April 2011.
  23. 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.
  24. A. Efstratiadis, Hydrological and hydrogeological simulation of modified river basins - The Hydrogeios model, 40 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, April 2010.
  25. 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.
  26. 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.
  27. A. Efstratiadis, Hydrological investigation of the Plastiras reservoir operation, 16 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, May 2006.
  28. A. Efstratiadis, and D. Koutsoyiannis, Lecture notes on Water Resource System Optimisation - Part 2, 140 pages, National Technical University of Athens, Athens, 2004.
  29. A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Presentation of the research project "Investigation of scenarios for the management and protection of the quality of the Plastiras Lake", 79 pages, 1 April 2003.

Academic works

  1. A. Efstratiadis, Non-linear methods in multiobjective water resource optimization problems, with emphasis on the calibration of hydrological models, PhD thesis, 391 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, February 2008.
  2. A. Efstratiadis, Investigation of global optimum seeking methods in water resources problems, MSc thesis, 139 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 2001.
  3. A. Efstratiadis, and N. Zervos, Optimal management of reservoir systems - Application to the Acheloos-Thessalia system, Diploma thesis, 181 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 1999.

Research reports

  1. A. Efstratiadis, N. Mamassis, I. Tsoukalas, and S. Manouri, [No English title available], Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 35 pages, May 2021.
  2. A. Efstratiadis, I. Tsoukalas, and S. Manouri, Investigation of the water supply system's management for period March-September 2021, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 38 pages, March 2021.
  3. A. Efstratiadis, I. Papakonstantis, P. Papanicolaou, N. Mamassis, D. Nikolopoulos, I. Tsoukalas, and P. Kossieris, First year synopsis, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 55 pages, December 2020.
  4. A. Efstratiadis, S. Manouri, D. Nikolopoulos, and I. Tsoukalas, Investigation of the water supply system's management for period March-September 2020, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 31 pages, March 2020.
  5. A. Efstratiadis, and I. Tsoukalas, Update of water balance of Hylike and Paralimni and assesment of their risk of spilling during the current hydrological year, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 56 pages, November 2019.
  6. A. Efstratiadis, N. Mamassis, and C. Makropoulos, Synoptic report on the estimation of the capacity of water supply system of Athens, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 30 pages, October 2019.
  7. A. Efstratiadis, N. Mamassis, and I. Tsoukalas, Synoptic report on the evaluation of the flood risk for areas affected by the ongoing spilling of the Hylike-Paralimni system, Modernization of the management of the water supply system of Athens - Update, Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 25 pages, March 2019.
  8. 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.
  9. 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.
  10. D. Dermatas, N. Mamassis, I. Panagiotakis, and A. Efstratiadis, Evaluation of environmental impracts due to water flows through Mavrorachi landfill, Investigation of the qualitative adequacy of the bottom of cell A3 and of the transitional bonding with cell A1 as well as the environmental impacts from the operation of the landfill , Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, March 2017.
  11. 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.
  12. A. Siskos, G. Karavokiros, A. Christofides, and A. Efstratiadis, Development of decision support system for renewable energy managment, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 103 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2015.
  13. A. Efstratiadis, N. Mamassis, Y. Markonis, P. Kossieris, and H. Tyralis, Methodological framework for optimal planning and management of water and renewable energy resources, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 154 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, April 2015.
  14. Y. Markonis, S. Lykoudis, A. Efstratiadis, and A. Koukouvinos, Description of rainfall and meteorological data and processing, 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, 54 pages, September 2014.
  15. 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.
  16. A. Efstratiadis, A. Koukouvinos, P. Dimitriadis, E. Rozos, and A. D. Koussis, Theoretical documentation of hydrological-hydraulic simulation model, 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, 108 pages, September 2014.
  17. 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.
  18. 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.
  19. N. Mamassis, A. Efstratiadis, G. Karavokiros, S. Kozanis, and A. Koukouvinos, Final report, Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system, Contractors: , Report 2, 84 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, November 2011.
  20. C. Makropoulos, D. Damigos, A. Efstratiadis, A. Koukouvinos, and A. Benardos, Synoptic report and final conclusions, Cost of raw water of the water supply of Athens, 32 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2010.
  21. C. Makropoulos, A. Efstratiadis, and A. Koukouvinos, Appraisal of financial cost and proposals for a rational management of the hydrosystem, Cost of raw water of the water supply of Athens, 73 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, October 2010.
  22. C. Makropoulos, A. Koukouvinos, A. Efstratiadis, and N. Chalkias, Mehodology for estimation of the financial cost , Cost of raw water of the water supply of Athens, 40 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2010.
  23. S. Kozanis, A. Christofides, and A. Efstratiadis, Scientific documentation of the Hydrognomon software (version 4 ), Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information" , Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 173 pages, Athens, June 2010.
  24. A. Koukouvinos, A. Efstratiadis, and E. Rozos, Hydrogeios - Version 2.0 - User manual, Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information" , Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 100 pages, November 2009.
  25. S.M. Papalexiou, and A. Efstratiadis, Final report, Flood risk estimation and forecast using hydrological models and probabilistic methods , 116 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, November 2009.
  26. A. Efstratiadis, E. Rozos, and A. Koukouvinos, Hydrogeios: Hydrological and hydrogeological simulation model - Documentation report, Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information" , 139 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, November 2009.
  27. A. Efstratiadis, G. Karavokiros, and N. Mamassis, Master plan of the Athens water resource system - Year 2009, Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system, Contractors: , Report 1, 116 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, April 2009.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. G. Karavokiros, A. Efstratiadis, and I. Vazimas, HYDRONOMEAS - Computer System for Simulation and Optimal Management of Water Resources - User Manual - Version 4.0, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, 144 pages, January 2007.
  33. 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.
  34. 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.
  35. A. Efstratiadis, A. Tegos, G. Karavokiros, I. Kyriazopoulou, and I. Vazimas, Master Plan for water resources management for the area of Karditsa, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Report 16, 132 pages, NAMA, Athens, December 2006.
  36. A. Efstratiadis, A. Koukouvinos, E. Rozos, A. Tegos, and I. Nalbantis, Theoretical documentation of model for simulating hydrological-hydrogeological processes of river basin "Hydrogeios", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 4a, 103 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2006.
  37. A. Koukouvinos, A. Efstratiadis, L. Lazaridis, and N. Mamassis, Data report, Investigation of management scenarios for the Smokovo reservoir, Report 1, 66 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2006.
  38. 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.
  39. S. Kozanis, A. Christofides, and A. Efstratiadis, Description of the data management and processing system "Hydrognomon", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 2, 141 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2005.
  40. R. Mavrodimou, I. Nalbantis, and A. Efstratiadis, Guidelines for the assessment of water resource projects, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 13, 72 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, June 2005.
  41. 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.
  42. 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.
  43. 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.
  44. A. Efstratiadis, I. Nalbantis, and E. Rozos, Model for simulating the hydrological cycle in Boeoticos Kephisos and Yliki basins, Modernisation of the supervision and management of the water resource system of Athens, Report 21, 196 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  45. A. Efstratiadis, and N. Mamassis, Hydrometeorological data processing, Modernisation of the supervision and management of the water resource system of Athens, Report 17, 72 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  46. 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.
  47. 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.
  48. 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.
  49. 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.
  50. 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.
  51. 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.
  52. 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.
  53. 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.
  54. 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.
  55. A. Efstratiadis, I. Nalbantis, and N. Mamassis, Hydrometeorological data processing, Modernisation of the supervision and management of the water resource system of Athens, Report 8, 129 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2000.
  56. G. Karavokiros, A. Efstratiadis, A. Koukouvinos, N. Mamassis, I. Nalbantis, N. Damianoglou, K. Constantinidou, S. Nalpantidou, A. Xanthakis, and S Politaki, Analysis of the system requirements, Modernisation of the supervision and management of the water resource system of Athens, Report 1, 74 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2000.
  57. 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.
  58. 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.
  59. 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.

Miscellaneous works

  1. A. Efstratiadis, Modelling renewable energy systems: Methodological challenges and research questions, 29 pages, Athens, October 2018.
  2. E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, A curve number approach to formulate hydrological response units within distributed hydrological modelling, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2016-627, 2016.
  3. A. Efstratiadis, "Investigation of global optimum seeking methods in water resources problems" and "Parallel memetic algorithms - Parallel evolutionary algorithms and other techniques": Comparative presentation, September 2012.
  4. H. Tyralis, and A. Efstratiadis, "National Programme for the Management and Protection of Water Resources" and "Impacts of climate change to surface and groundwater resources of Greece": Comparative presentation, September 2012.
  5. A. Efstratiadis, and N. Mamassis, Evaluating models or evaluating modelling practices? - Interactive comment on HESS Opinions “Crash tests for a standardized evaluation of hydrological models”, Hydrology and Earth System Sciences Discussions, 6, C1404–C1409, 2009.
  6. 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.
  7. 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.

Engineering reports

  1. A. Efstratiadis, and N. Mamassis, Preliminary hydrological investigation of Livadi - Arachova watershed, 55 pages, Fokiki energeiaki S.A., Athens, July 2019.
  2. A. Efstratiadis, A. Koukouvinos, and N. Mamassis, Estimation of flood hydrographs at selected streams crossing Trans Adriatic Pipeline (TAP) – Section 1, Detailed design of TAP - Section 1, Commissioner: Asprofos Engineering, Contractors: , September 2016.
  3. A. Efstratiadis, and A. Koukouvinos, Gaborone storm study, Consultancy Services for Conceptual Design, Preparation of Bidding Documents, Assistance during the Selection of Contractor & Monitoring/Supervision of Construction, Instalation, Operation & Maintainance for Traffic Control (CTC) for Greater Gaborone City, Contractor: Erasmos Consulting Engineering, 7 pages, July 2015.
  4. N. Mamassis, A. Efstratiadis, S.M. Papalexiou, C. Andrikopoulos, E. Tsilimandos, and A. Radaios, [No English title available], , Commissioner: Specific Secreteriat of Water – Ministry of Environment, Energy and Climate Change, Contractor: ADT-OMEGA, 77 pages, April 2015.
  5. 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.
  6. 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.
  7. 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.
  8. N. Mamassis, and A. Efstratiadis, Drought and water shortage study, , Commissioner: Ministry of Environment, Energy and Climate Change, Contractor: Ydroexigiantiki, 145 pages, June 2012.
  9. A. Efstratiadis, Hydrological study, Hydrological study of the ski center area of Parnassos, Contractor: Lazaridis and Collaborators, June 2010.
  10. A. Efstratiadis, and E. Rozos, Hydrological investigation, Water supply works from Gadouras dam - Phase B, Commissioner: Ministry of Environment, Planning and Public Works, Contractor: Ydroexigiantiki, 57 pages, July 2010.
  11. 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.
  12. 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.
  13. N. Mamassis, A. Koukouvinos, and A. Efstratiadis, Hydrological study, , Commissioner: Ministry of Agricultural Development and Food, Contractor: ETME- Antoniou Peppas and Co., Athens, 2006.
  14. D. Argyropoulos, N. Mamassis, A. Efstratiadis, and E. Rozos, Water resource management of Xerias and Yannouzagas basins, Water resource management of the Integrated Tourist Development Area in Messenia, Commissioner: TEMES - Tourist Enterprises of Messinia, Contractor: D. Argyropoulos, 73 pages, Athens, 2005.
  15. D. Argyropoulos, E. Lagadinou, and A. Efstratiadis, Water resources management of the Selas catchment, Water resource management of the Integrated Tourist Development Area in Messenia, Commissioner: TEMES - Tourist Enterprises of Messinia, Contractor: D. Argyropoulos, 48 pages, Athens, 2005.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.

Details on research projects

Participation as Project Director

  1. Modernization of the management of the water supply system of Athens - Update

    Duration: May 2019–April 2024

    Budget: €120 000

    Commissioned by: Water Supply and Sewerage Company of Athens

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: A. Efstratiadis

    Principal investigator: I. Papakonstantis

    The project aims to revise, upgrade and expand the software tools that have been developed in the context of previous research programs, and the overall support of the Water Supply Directorate of EYDAP S.A. in topics associated with the management of the water resource system of Athens. In this vein we are planning to employ advanced hydrological and water management analyses, improve the existing computational systems and associated methodologies for stochastic simulation and optimization, the elaboration of Master Plans, on annual basis or less, in case of emergency, and the theoretical investigation with respect to the development of a decision support tool for the hydraulic propagation of water flows across the hydrosystem, to be tested in part of Mornos’ channel.

Participation as Principal Investigator

  1. Open Hydrosystem Information Network (OpenHi.net)

    Duration: January 2018–December 2020

    Budget: €320 000

    Commissioned by: Special Secretary of ERDF & CF

    Contractor: Department of Water Resources and Environmental Engineering

    Collaborators:

    1. National Observatory of Athens
    2. Hellenic Centre for Marine Research
    3. Institute of Communication and Computer Systems
    4. Technological Educational Institute of Epirus

    Project director: N. Mamassis

    Principal investigator: A. Efstratiadis

    OpenHi.net is sub-project of the national research infrastructure “Hellenic Integrated Marine and Inland Water Resources Observing, Forecasting and Offshore Technology Systems” (HIMIOFoTS). Its objective is the design of an integrated e-infrastructure for collection, management and dissemination of hydrological and environmental information for the surface water resources of Greece, and the coordination of sub-projects that are involved in the development and initial operation of the system. The sub-project comprises the recording and evaluation of the existing infrastructures of the country (monitoring networks, databases), the analysis of specifications and assessment of the information system, the organization and processing of geographical data with respect to surface water bodies and hydrosystems of Greece, and their implementation within OpenHi. The system design will foresee the incorporation of all related infrastructure of the country, in a forthcoming phase, in order to provide free access to all hydrological, environmental and geographical data of surface water resources of Greece.

  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

Participation as Researcher

  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. EU COST Action ES0901: European procedures for flood frequency estimation (FloodFreq)

    Duration: February 2010–December 2013

    Project director: T. Kjeldsen

    The main objective is to undertake a pan-European comparison and evaluation of methods for flood frequency estimation under the various climatologic and geographic conditions found in Europe, and different levels of data availability. A scientific framework for assessing the ability of these methods to predict the impact of environmental change (climate change, land-use and river engineering works) on future flood frequency characteristics (flood occurrence and magnitude) will be developed and tested. The availability of such procedures is crucial for the formulation of robust flood risk management strategies as required by the Directive of the European Parliament on the assessment and management of floods. The outputs from FloodFreq will be disseminated to: academics, professionals involved in operational flood risk management from private and public institutions, and relevant policy makers from national and international regulatory bodies. This Action enables cooperation between researchers involved in nationally funded research projects to, thereby enabling testing of methods free from the constraints of administrative boundaries, and allowing a more efficient use of European flood research funding.

    Project web-page: http://www.costfloodfreq.eu/

  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. 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. OpenMI Life

    Duration: January 2006–December 2010

    The project's rationale lies in the Water Framework Directive,which demands an integrated approach to water management. This requires an ability to predict how catchment processes will interact. In most contexts, it is not feasible to build a single predictive model that adequately represents all the processes; therefore, a means of linking models of individual processes is required.The FP5 HarmonIT project's innovative and acclaimed solution, the Open Modelling Interface and Environment (OpenMI) met this need by simplifying the linking of hydrology related models.Its establishment will support and assist the strategic planning and integrated catchment management.

  1. Cost of raw water of the water supply of Athens

    Duration: June 2010–December 2010

    Budget: €110 000

    Commissioned by: Fixed Assets Company EYDAP

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: C. Makropoulos

  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. 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. 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. 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. 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. 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.

Details on engineering studies

  1. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Ανατολικής Πελοποννήσου (GR03)

    Commissioned by: Specific Secreteriat of Water

    Contractor: ADT-OMEGA

  1. Consultancy Services for Conceptual Design, Preparation of Bidding Documents, Assistance during the Selection of Contractor & Monitoring/Supervision of Construction, Instalation, Operation & Maintainance for Traffic Control (CTC) for Greater Gaborone City

    Contractor: Erasmos Consulting Engineering

  1. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Κρήτης (GR13)

    Commissioned by: Specific Secreteriat of Water

    Contractor: ADT-OMEGA

  1. Παροχή Συμβουλευτικών Υπηρεσιών για την Κατάρτιση του 2ου Σχεδίου Διαχείρισης Λεκάνης Απορροής Ποταμού της Κύπρου για την Εφαρμογή της Οδηγίας 2000/60/ΕΚ και για την Κατάρτιση του Σχεδίου Διαχείρισης Κινδύνων Πλημμύρας για την Εφαρμογή της Οδηγίας 2007/60

    Commissioned by: Depatment of Water Development of Cyprus

    Contractor: LDK & ECOS

  1. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Δυτικής Πελοποννήσου (GR01)

    Commissioned by: Specific Secreteriat of Water

    Contractor: ADT-OMEGA

  1. Έργα Ορεινής Υδρονομίας Ρεμάτων Ορεινών Λεκανών Απορροής Αλμωπίας

  1. Σχέδιο Διαχείρισης Κινδύνων Πλημμύρας των Λεκανών Απορροής Ποταμών του Υδατικού Διαμερίσματος Βόρειας Πελοποννήσου (GR02)

    Commissioned by: Specific Secreteriat of Water

    Contractor: ADT-OMEGA

  1. Pleriminary study of Almopaios dam

    Duration: July 2014–July 2014

    Commissioned by: Roikos Consulting Engeineers S.A.

  1. Hydrological study of the ski center area of Parnassos

    Duration: June 2010–July 2010

    Contractor: Lazaridis and Collaborators

  1. Water supply works from Gadouras dam - Phase B

    Duration: July 2009–July 2010

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Ydroexigiantiki

  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. Μελέτες Διερεύνησης Προβλημάτων Άρδευσης και Δυνατότητας Κατασκευής Ταμιευτήρων Νομού Βοιωτίας

    Duration: January 2006–December 2006

    Commissioned by: Ministry of Agricultural Development and Food

    Contractor: ETME- Antoniou Peppas and Co.

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

    Duration: January 2001–December 2001

    Contractor: Ypologistiki Michaniki

  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

Published work in detail

Publications in scientific journals

  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. G.-K. Sakki, I. Tsoukalas, and A. Efstratiadis, A reverse engineering approach across small hydropower plants: a hidden treasure of hydrological data?, Hydrological Sciences Journal, 2021, (in press).

    The limited availability of hydrometric data makes the design, management, and real-time operation of water systems a difficult task. Here, we propose a generic stochastic framework for the so-called inverse problem of hydroelectricity, using energy production data from small hydropower plants (SHPPs) to retrieve the upstream inflows. In this context, we investigate the alternative configurations of water-energy transformations across SHPPs of negligible storage capacity, which are subject to multiple uncertainties. We focus on two key sources, i.e. observational errors in energy production and uncertain efficiency curves of turbines. In order to extract the full hydrograph, we also extrapolate the high and low flows outside of the range of operation of turbines, by employing empirical rules for representing the rising and falling limbs of the simulated hydrographs. This framework is demonstrated to a real-world system at Evinos river basin, Greece. By taking advantage of the proposed methodology, SHPPs may act as potential hydrometric stations and improve the existing information in poorly gauged areas.

  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. G. Papaioannou, L. Vasiliades, A. Loukas, A. Alamanos, A. Efstratiadis, A. Koukouvinos, I. Tsoukalas, and P. Kossieris, A flood inundation modelling approach for urban and rural areas in lake and large-scale river basins, Water, 13 (9), 1264, doi:10.3390/w13091264, 2021.

    Fluvial floods are one of the primary natural hazards to our society, and the associated flood risk should always be evaluated for present and future conditions. The European Union’s Floods Di-rective highlights the importance of flood mapping as a key-stage for detecting vulnerable areas, assessing floods’ impacts, and identifying damages and compensation plans. The implementation of the E.U. Flood Directive in Greece is challenging, because of its geophysical and climatic var-iability and diverse hydrologic and hydraulic conditions. This study addresses this challenge by modelling of design rainfall at sub-watershed level and subsequent estimation of flood design hydrographs using the NRCS Unit Hydrograph Procedure. HEC-RAS 2D model is used for flood routing, estimation of flood attributes (i.e., water depths and flow velocities) and mapping of inundated areas. The modelling approach has been applied at two complex and ungauged rep-resentative basins: Lake Pamvotida basin located in the Epirus Region of the wet western Greece and Pinios River basin located in Thessaly Region of the drier central Greece, a basin with a complex dendritic hydrographic system, expanding to more than 1188 river-km. The proposed modelling approach aims to better estimation and mapping of flood inundation areas including relative uncertainties and providing guidance to professionals and academics.

    Full text: http://www.itia.ntua.gr/en/getfile/2121/1/documents/water-13-01264-v2.pdf (45029 KB)

    See also: https://www.mdpi.com/2073-4441/13/9/1264

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

    1. Varlas, G., A. Papadopoulos, G. Papaioannou, and E. Dimitriou, Evaluating the forecast skill of a hydrometeorological modelling system in Greece, Atmosphere, 12(7), 902, doi:10.3390/atmos12070902, 2021.
    2. Karamvasis, K., and V. Karathanassi, FLOMPY: An open-source toolbox for floodwater mapping using Sentinel-1 intensity time series, Water, 13(21), 2943, doi:10.3390/w13212943, 2021.

  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. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.

    The generation of hydrometeorological time series that exhibit a given probabilistic and stochastic behavior across multiple temporal levels, traditionally expressed in terms of specific statistical characteristics of the observed data, is a crucial task for risk-based water resources studies, and simultaneously a puzzle for the community of stochastics. The main challenge stems from the fact that the reproduction of a specific behavior at a certain temporal level does not imply the reproduction of the desirable behavior at any other level of aggregation. In this respect, we first introduce a pairwise coupling of Nataf-based stochastic models within a disaggregation scheme, and next we propose their puzzle-type configuration to provide a generic stochastic simulation framework for multivariate processes exhibiting any distribution and any correlation structure. Within case studies we demonstrate two characteristic configurations, i.e., a three-level one, operating at daily, monthly and annual basis, and a two-level one to disaggregate daily to hourly data. The first configuration is applied to generate correlated daily rainfall and runoff data at the river basin of Achelous, Western Greece, which preserves the stochastic behavior of the two processes at the three temporal levels. The second configuration disaggregates daily rainfall, obtained from a meteorological station at Germany, to hourly. The two studies reveal the ability of the proposed framework to represent the peculiar behavior of hydrometeorological processes at multiple temporal resolutions, as well as its flexibility on formulating generic simulation schemes.

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

    1. Macian-Sorribes, H., J.-L. Molina, S. Zazo, and M. Pulido-Velázquez, Analysis of spatio-temporal dependence of inflow time series through Bayesian causal modelling, Journal of Hydrology, 597, 125722, doi:10.1016/j.jhydrol.2020.125722, 2021.
    2. 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.
    3. Brereton, R. G., P values and multivariate distributions: Non-orthogonal terms in regression models, Chemometrics and Intelligent Laboratory Systems, 210, 104264, doi:10.1016/j.chemolab.2021.104264, 2021.
    4. 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.
    5. Biondi, D., E. Todini, and A. Corina, A parsimonious post-processor for uncertainty evaluation of ensemble precipitation forecasts: An application to quantitative precipitation forecasts for civil protection purposes, Hydrology Research, nh20210452021, doi:10.2166/nh.2021.045, 2021.

  1. A. Tegos, W. Schlüter, N. Gibbons, Y. Katselis, and A. Efstratiadis, Assessment of environmental flows from complexity to parsimony - Lessons from Lesotho, Water, 10 (10), 1293, doi:10.3390/w10101293, 2018.

    Over the last decade, Environmental Flow Assessment (EFA) has focused scientific attention around heavily-modified hydrosystems, such as flow regulated releases downstream of dams. In this light, numerous approaches of varying complexity have been developed, the most holistic of which incorporate hydrological, hydraulic, biological and water quality inputs, as well as socioeconomic issues. Finding the optimal flow releases, informing policy and determining an operational framework are often the main focus. This work exhibits a simplification of the DRIFT framework, and is regarded as the first holistic EFA approach, consisting of three modules, namely hydrological, hydraulic and fish quality. A novel conceptual classification for fish quality is proposed, associating fish fauna requirements with hydraulic characteristics, exported by fish survey analyses. The new methodology was applied and validated successfully at three stream sites in Lesotho, where DRIFT was formerly employed.

    Full text: http://www.itia.ntua.gr/en/getfile/1878/1/documents/water-10-01293.pdf (2633 KB)

    See also: http://www.mdpi.com/2073-4441/10/10/1293/htm

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

    1. 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.
    2. 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.
    3. Sahoo, B. B., R. Jha, A. Singh, A. and D. Kumar, Long short-term memory (LSTM) recurrent neural network for low-flow hydrological time series forecasting, Acta Geophysica, 67, 1471-1481, doi:10.1007/s11600-019-00330-1, 2019.
    4. 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.
    5. 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.
    6. Jo, Y.-J., J.-H. Song, Y. Her, G. Provolo, J. Beom, M. Jeung, Y.-J. Kim, S.-H. Yoo, and K.-S. Yoon, Assessing the potential of agricultural reservoirs as the source of environmental flow, Water; 13(4), 508, doi:10.3390/w13040508, 2021.

  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. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A framework for dry period low flow forecasting in Mediterranean streams, Water Resources Management, 32 (15), 4911–1432, doi:10.1007/s11269-018-2060-z, 2018.

    The objective of this article is to provide a simple and effective tool for low flow forecasting up to six months ahead, with minimal data requirements, i.e. flow observations retrieved at the end of wet period (first half of April, for the Mediterranean region). The core of the methodological framework is the exponential decay function, while the typical split-sample approach for model calibration, which is known to suffer from the dependence on the selection of the calibration data set, is enhanced by introducing the so-called Randomly Selected Multiple Subsets (RSMS) calibration procedure. Moreover, we introduce and employ a modified efficiency metric, since in this modelling context the classical Nash-Sutcliffe efficiency yields unrealistically high performance. The proposed framework is evaluated at 25 Mediterranean rivers of different scales and flow dynamics, including streams with intermittent regime. Initially, signal processing and data smoothing techniques are applied to the raw hydrograph, in order to cut-off high flows that are due to flood events occurring in dry periods, and allow for keeping the decaying form of the baseflow component. We then employ the linear reservoir model to extract the annually varying recession coefficient, and, then, attempt to explain its median value (over a number of years) on the basis of typical hydrological indices and the catchment area. Next, we run the model in forecasting mode, by considering that the recession coefficient of each dry period ahead is a linear function of the observed flow at the end of the wet period. In most of the examined catchments, the model exhibits very satisfactory predictive capacity and is also robust, as indicated by the limited variability of the optimized model parameters across randomly selected calibration sets.

    Full text: http://www.itia.ntua.gr/en/getfile/1861/2/documents/Risva2018_Article_AFrameworkForDryPeriodLowFlowF.pdf (2268 KB)

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

    1. Tsihrintzis, V. A., and H. Vangelis, Water resources and environment, Water Resources Management, 32(15), 4813-4817, doi:10.1007/s11269-018-2164-5, 2018.
    2. Kapetas, L., N. Kazakis, K. Voudouris, and D. McNicholl, Water allocation and governance in multi-stakeholder environments: Insight from Axios Delta, Greece, Science of The Total Environment, 695, 133831, doi:10.1016/j.scitotenv.2019.133831, 2019.
    3. Azarnivand, A., M. Camporese, S. Alaghmand, and E. Dal, Simulated response of an intermittent stream to rainfall frequency patterns, Hydrological Processes, 34(3), 615-632, doi:10.1002/hyp.13610, 2020.
    4. Lee, D., H. Kim, I. Jung, and J. Yoon, Monthly reservoir inflow forecasting for dry period using teleconnection indices: A statistical ensemble approach, Applied Sciences, 10(10), 3470, doi:10.3390/app10103470, 2020.
    5. Nicolle, P., F. Besson, O. Delaigue, P. Etchevers, D. François, M. Le Lay, C. Perrin, F. Rousset, D. Thiéry, F. Tilmant, C. Magand, T. Leurent, and É. Jacob, PREMHYCE: An operational tool for low-flow forecasting, Proceedings of the International Association of Hydrological Sciences, 383, 381-389, doi:10.5194/piahs-383-381-2020, 2020.
    6. Tilmant, F., P. Nicolle, F. Bourgin, F. Besson, O. Delaigue, P. Etchevers, D. François, M. Le Lay, C. Perrin, F. Rousset, D. Thiéry, C. Magand, T. Leurent, et É. Jacob, PREMHYCE : un outil opérationnel pour la prévision des étiages, La Houille Blanche, 5, 37-44, doi:10.1051/lhb/2020043, 2020.

  1. I. Tsoukalas, S.M. Papalexiou, A. Efstratiadis, and C. Makropoulos, A cautionary note on the reproduction of dependencies through linear stochastic models with non-Gaussian white noise, Water, 10 (6), 771, doi:10.3390/w10060771, 2018.

    Since the prime days of stochastic hydrology back in 1960s, autoregressive (AR) and moving average (MA) models (as well as their extensions) have been widely used to simulate hydrometeorological processes. Initially, AR(1) or Markovian models with Gaussian noise prevailed due to their conceptual and mathematical simplicity. However, the ubiquitous skewed behavior of most hydrometeorological processes, particularly at fine time scales, necessitated the generation of synthetic time series to also reproduce higher-order moments. In this respect, the former schemes were enhanced to preserve skewness through the use of non-Gaussian white noise— a modification attributed to Thomas and Fiering (TF). Although preserving higher-order moments to approximate a distribution is a limited and potentially risky solution, the TF approach has become a common choice in operational practice. In this study, almost half a century after its introduction, we reveal an important flaw that spans over all popular linear stochastic models that employ non-Gaussian white noise. Focusing on the Markovian case, we prove mathematically that this generating scheme provides bounded dependence patterns, which are both unrealistic and inconsistent with the observed data. This so-called “envelope behavior” is amplified as the skewness and correlation increases, as demonstrated on the basis of real-world and hypothetical simulation examples.

    Full text: http://www.itia.ntua.gr/en/getfile/1848/1/documents/water-10-00771.pdf (14101 KB)

    See also: http://www.mdpi.com/2073-4441/10/6/771

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

    1. 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, 54(10), 7435-7458, doi:10.1029/2018WR022726, 2018.
    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. Marković, D., S. Ilić, D. Pavlović, J. Plavšić, and N. Ilich, Multivariate and multi-scale generator based on non-parametric stochastic algorithms, Journal of Hydroinformatics, 21(6), 1102–1117, doi:10.2166/hydro.2019.071, 2019.
    4. Nazemi, A., M. Zaerpour, and E. Hassanzadeh, Uncertainty in bottom-up vulnerability assessments of water supply systems due to regional streamflow generation under changing conditions, Journal of Water Resources Planning and Management, 146(2), doi:10.1061/(ASCE)WR.1943-5452.0001149, 2020.
    5. 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.
    6. Zounemat-Kermani, M., A. Mahdavi-Meymand, and A. Hinkelmann, A comprehensive survey on conventional and modern neural networks: application to river flow forecasting, Earth Science Informatics, doi:10.1007/s12145-021-00599-1, 2021.
    7. 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. G. Papaioannou, A. Efstratiadis, L. Vasiliades, A. Loukas, S.M. Papalexiou, A. Koukouvinos, I. Tsoukalas, and P. Kossieris, An operational method for Floods Directive implementation in ungauged urban areas, Hydrology, 5 (2), 24, doi:10.3390/hydrology5020024, 2018.

    An operational framework for flood risk assessment in ungauged urban areas is developed within the implementation of the EU Floods Directive in Greece, and demonstrated for Volos metropolitan area, central Greece, which is frequently affected by intense storms causing fluvial flash floods. A scenario-based approach is applied, accounting for uncertainties of key modeling aspects. This comprises extreme rainfall analysis, resulting to spatially-distributed Intensity-Duration-Frequency (IDF) relationships and their confidence intervals, and flood simulations, through the SCS-CN method and the unit hydrograph theory, producing design hydrographs at the sub-watershed scale, for several soil moisture conditions. The propagation of flood hydrographs and the mapping of inundated areas are employed by the HEC-RAS 2D model, with flexible mesh size, by representing the resistance caused by buildings through the local elevation rise method. For all hydrographs, upper and lower estimates on water depths, flow velocities and inundation areas are estimated, for varying roughness coefficient values. The methodology is validated against the flood event of the 9th October 2006, using observed flood inundation data. Our analyses indicate that although typical engineering practices for ungauged basins are subject to major uncertainties, the hydrological experience may counterbalance the missing information, thus ensuring quite realistic outcomes.

    Remarks:

    This article won the Hydrology Best Paper Award for 2020 (https://www.mdpi.com/journal/hydrology/awards/850)

    Full text: http://www.itia.ntua.gr/en/getfile/1829/1/documents/hydrology-05-00024_Idnk8fW.pdf (5243 KB)

    Additional material:

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

    1. 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.
    2. Manfreda, S., C. Samela, A. Refice, V. Tramutoli, and F. Nardi, Advances in large-scale flood monitoring and detection, Hydrology, 5(3), 49, doi:10.3390/hydrology5030049, 2018.
    3. Doroszkiewicz, J., R. J. Romanowicz, and A. Kiczko, The influence of flow projection errors on flood hazard estimates in future climate conditions, Water, 11(1), 49, doi:10.3390/w11010049, 2019.
    4. Enigl, K., C. Matulla, M. Schlögla, and F. Schmid, Derivation of canonical total-sequences triggering landslides and floodings in complex terrain, Advances in Water Resources, 129, 178-188, doi:10.1016/j.advwatres.2019.04.018, 2019.
    5. Chen, N., S. Yao, C. Wang, and W. Du, A method for urban flood risk assessment and zoning considering road environments and terrain, Sustainability, 11(10), 2734, doi:10.3390/su11102734, 2019.
    6. 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.
    7. Vojtek, M., A. Petroselli, J. Vojteková, and S. Asgharinia, Flood inundation mapping in small and ungauged basins: sensitivity analysis using the EBA4SUB and HEC-RAS modeling approach, Hydrology Research, 50(4), 1002-1019, doi:10.2166/nh.2019.163, 2019.
    8. Lorenzo-Lacruz, J., C. Garcia, E. Morán-Tejeda, A. Amengual, V. Homar, A. Maimó-Far, A. Hermoso, C. Ramis, and R. Romero, Hydro-meteorological reconstruction and geomorphological impact assessment of the October, 2018 catastrophic flash flood at Sant Llorenç, Mallorca (Spain), Natural Hazards and Earth System Sciences, 19(11), 2597-2617, doi:10.5194/nhess-19-2597-2019, 2019.
    9. Hamdan, A. N. A., A. A. Abbas, and A. T. Najm, Flood hazard analysis of proposed regulator on Shatt Al-Arab river, Hydrology, 6(3), 80, doi:0.3390/hydrology6030080, 2019.
    10. Deby, R., V. Dermawan, and D. Sisinggih, Analysis of Wanggu river flood inundation Kendari City Southeast Sulawesi province using HEC RAS 5.0.6, International Research Journal of Advanced Engineering and Science, 4(2), 270-275, 2019.
    11. Rauter, M., T. Thaler, M.-S. Attems, and S. Fuchs, Obligation or innovation: Can the EU Floods Directive Be seen as a tipping point towards more resilient flood risk management? A case study from Vorarlberg, Austria, Sustainability, 11, 5505, doi:10.3390/su11195505, 2019.
    12. 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.
    13. Rahmati, O., H. Darabi, A. T. Haghighi, S. Stefanidis, A. Kornejady, O. A. Nalivan, and D. T. Bui, Urban flood hazard modeling using self-organizing map neural network, Water, 11(11), 2370, doi:10.3390/w11112370, 2019.
    14. Dano, U. L., A.-L. Balogun, A.-N. Matori,K. Wan Yusouf, I. R. Abubakar, M. A. Said Mohamed, , Y.A. Aina, and B. Pradhan, Flood susceptibility mapping using an improved analytic network process with statistical models, Water, 11(3), 615, doi:10.3390/w11030615, 2019.
    15. Petroselli, A., S. Grimaldi, R. Piscopia, and F. Tauro, Design hydrograph estimation in small and ungauged basins: a comparative assessment of event based (EBA4SUB) and continuous (COSMO4SUB) modeling approaches, Acta Scientiarum Polonorum Formatio Circumiectus, 18(4), 113-124, doi:10.15576/ASP.FC/2019.18.4.113, 2019.
    16. Nguyen, V.-N., P. Yariyan, M. Amiri, A. Dang Tran, T.D. Pham, M.P. Do, P. T. Thi Ngo, V.-H. Nhu, N. Quoc Long, and D. Tien Bui, A new modeling approach for spatial prediction of flash flood with biogeography optimized CHAID tree ensemble and remote sensing data, Remote Sensing, 12(9), 1373, doi:10.3390/rs12091373, 2020.
    17. Kastridis, A., and D. Stathis, Evaluation of hydrological and hydraulic models applied in typical Mediterranean ungauged watersheds using post-flash-flood measurements, Hydrology, 7(1), 12, doi:10.3390/hydrology7010012, 2020.
    18. Stavropoulos, S., G. N. Zaimes, E. Filippidis, D. C. Diaconu, and D. Emmanouloudis, Mitigating flash floods with the use of new technologies: A multi-criteria decision analysis to map flood susceptibility for Zakynthos island, Greece, Journal of Urban & Regional Analysis, 12(2), 233-248, 2020.
    19. 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.
    20. Abdrabo, K. I., S. A. Kantoush, M. Saber, T. Sumi, O. M. Habiba, D. Elleithy, and B. Elboshy, Integrated methodology for urban flood risk mapping at the microscale in ungauged regions: A case study of Hurghada, Egypt, Remote Sensing, 12(21), 3548, doi:10.3390/rs12213548, 2020.
    21. Yariyan, P., M. Avand, R. A. Abbaspour, A. T. Haghighi, R. Costache, O. Ghorbanzadeh, S. Janizadeh, and T. Blaschke, Flood susceptibility mapping using an improved analytic network process with statistical models, Geomatics, Natural Hazards and Risk, 11(1), 2282-2314, doi:10.1080/19475705.2020.1836036, 2020.
    22. 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.
    23. Papaioannou, G., G. Varlas, A. Papadopoulos, A. Loukas, P. Katsafados, and E. Dimitriou, Investigating sea‐state effects on flash flood hydrograph and inundation forecasting, Hydrological Processes, 35(4), e14151, doi:10.1002/hyp.14151, 2021.
    24. Mahamat Nour, A., C. Vallet‐Coulomb, J. Gonçalves, F. Sylvestre, and P. Deschamps, Rainfall-discharge relationship and water balance over the past 60 years within the Chari-Logone sub-basins, Lake Chad basin, Journal of Hydrology: Regional Studies, 35, 100824, doi:10.1016/j.ejrh.2021.100824, 2021.
    25. Varlas, G., A. Papadopoulos, G. Papaioannou, and E. Dimitriou, Evaluating the forecast skill of a hydrometeorological modelling system in Greece, Atmosphere, 12(7), 902, doi:10.3390/atmos12070902, 2021.
    26. Khalaj, M. R., H. Noor, and A. Dastranj, Investigation and simulation of flood inundation hazard in urban areas in Iran, Geoenvironmental Disasters, 8, 18, doi:10.1186/s40677-021-00191-1, 2021.
    27. Hooke, J., J. Souza, and M. Marchamalo, Evaluation of connectivity indices applied to a Mediterranean agricultural catchment, Catena, 207, 105713, doi:10.1016/j.catena.2021.105713, 2021.
    28. Seleem, O., M. Heistermann, and A. Bronstert, Efficient hazard assessment for pluvial floods in urban environments: A benchmarking case study for the city of Berlin, Germany, Water, 13(18), 2476, doi:10.3390/w13182476, 2021.
    29. Cotugno, A., V. Smith, T. Baker, and R. Srinivasan, A framework for calculating peak discharge and flood inundation in ungauged urban watersheds using remotely sensed precipitation data: A case study in Freetown, Sierra Leone, Remote Sensing, 13(19), 3806, doi:10.3390/rs13193806, 2021.
    30. Berteni, F., A. Dada, and G. Grossi, Application of the MUSLE model and potential effects of climate change in a small Alpine catchment in Northern Italy, Water, 13(19), 2679, doi:10.3390/w13192679, 2021.

  1. E. Michailidi, S. Antoniadi, A. Koukouvinos, B. Bacchi, and A. Efstratiadis, Timing the time of concentration: shedding light on a paradox, Hydrological Sciences Journal, 63 (5), 721–740, doi:10.1080/02626667.2018.1450985, 2018.

    From the origins of hydrology, the time of concentration, tc, has been conventionally tackled as constant quantity. However, theoretical proof and empirical evidence imply that tc exhibits significant variability against rainfall, making its definition and estimation a hydrological paradox. Adopting the assumptions of the Rational method and the kinematic approach, an effective procedure in a GIS environment for estimating the travel time across a catchment’s longest flow path is provided. By applying it in 30 Mediterranean basins, it is illustrated that tc is a negative power function of excess rainfall intensity. Regional formulas are established to infer its multiplier (unit time of concentration) and exponent from abstract geomorphological information, which are validated against observed data and theoretical literature outcomes. Besides offering a fast and easy solution to the paradox, we highlight the necessity for implementing the varying tc concept within hydrological modelling, signalling a major shift from current engineering practices.

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

    1. Yazdia, M. N., D. J. Sample, D. Scott, J. Owen, M. Ketabchy, and N. Alamdari, Water quality characterization of storm and irrigation runoff from a container nursery, Science of the Total Environment, 667, 166-178, doi:10.1016/j.scitotenv.2019.02.326, 2019.
    2. 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.
    3. Harisuseno, D., D. N. Khaeruddin, and R. Haribowo, Time of concentration based infiltration under different soil density, water content, and slope during a steady rainfall, Journal of Water and Land Development, 41 (IV–VI), 61-68, doi:10.2478/jwld-2019-0028, 2019.
    4. Vojtek, M., A. Petroselli, J. Vojteková, and S. Asgharinia, Flood inundation mapping in small and ungauged basins: sensitivity analysis using the EBA4SUB and HEC-RAS modeling approach, Hydrology Research, 50(4), 1002-1019, doi:10.2166/nh.2019.163, 2019.
    5. Osuagwu, J., J. C. Agunwamba, and C. E. Nwabunor, Verification of time of concentration equation for improved drainage design, Environmental Management and Sustainable Development, 8(2), 151-161, doi:10.5296/emsd.v8i2.14902, 2019.
    6. Sandoval, S., and J.-L. Bertrand-Krajewski, From marginal to conditional probability functions of parameters in a conceptual rainfall-runoff model: an event-based approach, Hydrological Sciences Journal, 64(11), 1340-1350, doi:10.1080/02626667.2019.1635696, 2019.
    7. Masseroni, D., G. Ercolani, E. A. Chiaradia, and C. Gandolfi, A procedure for designing natural water retention measures in new development areas under hydraulic-hydrologic invariance constraints, Hydrology Research, 50(5), 1293-1308, doi:10.2166/nh.2019.018, 2019.
    8. Santos, S. M., J. C. N. Pscheidt, G. Tiago, S. Klein, N. B. Bonumá, P. L. B. Chaffe, and K. Masato, Time of concentration in an experimental basin: Methods for analysis, backwater effects and vegetation removal, Journal of Urban & Environmental Engineering, 13(1), 163-173, 2019.
    9. Beven, K. J., A history of the concept of time of concentration, Hydrology and Earth System Sciences, 24, 2655–2670, doi:10.5194/hess-24-2655-2020, 2020.
    10. Veeck, S., F. F. da Costa, D. L. C. Lima, A. Rolim da Paz, and D. G. A. Piccilli, Scale dynamics of the HIDROPIXEL high-resolution DEM-based distributed hydrologic modeling approach, Environmental Modelling & Software, 127, 104695, doi:10.1016/j.envsoft.2020.104695, 2020.
    11. Allnutt, C. E., O. J. Gericke, and J. P. J. Pietersen, Estimation of time parameter proportionality ratios in large catchments: Case study of the Modder‐Riet River Catchment, South Africa, Journal of Flood Risk Management, 13(3), e12628, doi:10.1111/jfr3.12628, 2020.
    12. González-Álvarez, Á., J. Molina-Pérez, B. Meza-Zúñiga, O. M. Viloria-Marimón, K. Tesfagiorgis, and J. A. Mouthón-Bello, Assessing the performance of different time of concentration equations in urban ungauged watersheds: Case study of Cartagena de Indias, Colombia, Hydrology, 7(3), 47, doi:10.3390/hydrology7030047, 2020.
    13. Dey, R., A. J. E. Gallant, and S. C. Lewis, Evidence of a continent-wide shift of episodic rainfall in Australia, Weather and Climate Extremes, 29, 100274, doi:10.1016/j.wace.2020.100274, 2020.
    14. 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.
    15. Ruman, S., R. Tichavský, K. Šilhán, K. and M. G. Grillakis, Palaeoflood discharge estimation using dendrogeomorphic methods, rainfall-runoff and hydraulic modelling—a case study from southern Crete, Natural Hazards, 105, 1721-1742, doi:10.1007/s11069-020-04373-2, 2021.
    16. Giani, G., M. A. Rico‐Ramirez, and R. A. Woods, A practical, objective and robust technique to directly estimate catchment response time, Water Resources Research, 57(2), e2020WR028201, doi:10.1029/2020WR028201, 2021.
    17. 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.
    18. Jato-Espino, D., and S. Pathak, Geographic location system for identifying urban road sections sensitive to runoff accumulation, Hydrology, 8(2), 72, doi:10.3390/hydrology8020072, 2021.
    19. Nash, D. M., A. J. Weatherley, P. J. A. Kleinman, and A. N. Sharpley, Estimating dissolved p losses from legacy sources in pastures - The limits of soil tests and small-scale rainfall simulators, Journal of Environmental Quality, doi:10.1002/jeq2.20265, 2021.
    20. Almedeij. J., Modified NRCS abstraction method for flood hydrograph generation, Journal of Irrigation and Drainage Engineering, 47(10), doi:10.1061/(ASCE)IR.1943-4774.0001609, 2021.
    21. Lapides, D. A., A. Sytsma, O. Crompton, and S. Thompson, Rational method time of concentration can underestimate peak discharge for hillslopes, Journal of Hydraulic Engineering, 147(10), doi:10.1061/(ASCE)HY.1943-7900.0001900, 2021.
    22. Lapides, D. A., A. Sytsma, and S. Thompson, Implications of distinct methodological interpretations and runoff coefficient usage for rational method predictions, Journal of the American Water Resources Association, doi:10.1111/1752-1688.12949, 2021.
    23. Fadhel, S., M. Al Aukidy, and M. S. Saleh, Uncertainty of intensity-duration-frequency curves due to adoption or otherwise of the temperature climate variable in rainfall disaggregation, Water, 13(17), 2337, doi:10.3390/w13172337, 2021.
    24. Tardif, F., F. St-Pierre, G. Pelletier, and M. J. Rodriguez, Comparison of methods to evaluate overland travel times for source water protection, Journal of Environmental Planning and Management, doi:10.1080/09640568.2021.1952858, 2021.

  1. E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, The curve number concept as a driver for delineating hydrological response units, Water, 10 (2), 194, doi:10.3390/w10020194, 2018.

    In this paper, a new methodology for delineating Hydrological Response Units (HRUs), based on the Curve Number (CN) concept, is presented. Initially, a semi-automatic procedure in a GIS environment is used to produce basin maps of distributed CN values as the product of the three classified layers, soil permeability, land use/land cover characteristics and drainage capacity. The map of CN values is used in the context of model parameterization, in order to identify the essential number and spatial extent of HRUs and, consequently, the number of control variables of the calibration problem. The new approach aims at reducing the subjectivity introduced by the definition of HRUs and providing parsimonious modelling schemes. In particular, the CN-based parameterization (1) allows the user to assign as many parameters as can be supported by the available hydrological information, (2) associates the model parameters with anticipated basin responses, as quantified in terms of CN classes across HRUs, and (3) reduces the effort for model calibration, simultaneously ensuring good predictive capacity. The advantages of the proposed approach are demonstrated in the hydrological simulation of the Nedontas River Basin, Greece, where parameterizations of different complexities are employed in a recently improved version of the HYDROGEIOS model. A modelling experiment with a varying number of HRUs, where the parameter estimation problem was handled through automatic optimization, showed that the parameterization with three HRUs, i.e., equal to the number of flow records, ensured the optimal performance. Similarly, tests with alternative HRU configurations confirmed that the optimal scores, both in calibration and validation, were achieved by the CN-based approach, also resulting in parameters values across the HRUs that were in agreement with their physical interpretation.

    Full text:

    See also: http://www.mdpi.com/2073-4441/10/2/194

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

    1. Aqnouy, M., J. E. S. El Messari, H. Ismail, A. Bouadila, J. G. M. Navarro, B. Loubna, and M. R. A. Mansour, Assessment of the SWAT model and the parameters affecting the flow simulation in the watershed of Oued Laou (Northern Morocco), Journal of Ecological Engineering, 20(4), 104-113, doi:10.12911/22998993/102794, 2019.
    2. Day, C., and G. Seay, Watershed surface characteristics and storm distribution impacts on low-order urban stream hydrology response, The Geographical Bulletin – Gamma Theta Upsilon, 60(2), 95-107, 2019.
    3. Rozos, E., A methodology for simple and fast streamflow modelling, Hydrological Sciences Journal, 65(7), 1084-1095, doi:10.1080/02626667.2020.1728475, 2020.
    4. Pobletei, D., J Arévaloi, O. Nicolis, and F. Figueroa, Optimization of the Hydrologic Response Units (HRU) using gridded meteorological data and spatially varying parameters, Earth and Space Science Open Archive, doi:10.1002/essoar.10502299.1, 2020.
    5. Weber, M., M. Feigl, K. Schulz, and M. Bernhardt, On the ability of LIDAR snow depth measurements to determine or evaluate the HRU discretization in a land surface model, Hydrology, 7(2), 20, doi:10.3390/hydrology7020020, 2020.
    6. Στεφανίδης, Σ. Ντάφης, και Χ. Γιάνναρος, Υδρολογική απόκριση της λεκάνης απορροής του χειμάρρου «Μπασδέκη» Ολυμπιάδας στην καταιγίδα της 25ης Νοεμβρίου 2019, Υδροτεχνικά (2019-2020), 29, 13-26, 2020.
    7. Soulis, K. X., E. Psomiadis, P. Londra, and D. Skuras, A new model-based approach for the evaluation of the net contribution of the European Union rural development program to the reduction of water abstractions in agriculture, Sustainability, 12(17), 7137, doi:10.3390/su12177137, 2020.
    8. Harisuseno, D., M. Bisri, and T.S. Haji, Inundation controlling practice in urban area: Case study in residential area of Malang, Indonesia, Journal of Water and Land Development, 46(VII–IX), 112–120, doi:10.24425/jwld.2020.134203, 2020.
    9. Nagel, G. W., F. Da Silva Terra, J. S. De Oliveira, I. Horák-Terra, and S. Beskow, Cálculo da curva número para bacia hidrográfica urbana utilizando diferentes abordagens de classificação para imagem orbital RapidEye: estudo de caso para o arroio Pepino (Pelotas, RS), Pesquisas em Geociências, 47(2), doi:10.22456/1807-9806.108583, 2020.
    10. Poblete, D., J. Arevalo, O. Nicolis, O., and F. Figueroa, Optimization of Hydrologic Response Units (HRUs) using gridded meteorological data and spatially varying parameters, Water, 12(12), 3558, doi:10.3390/w12123558, 2020.
    11. 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.
    12. Athira, P., and K. P. Sudheer, Calibration of distributed hydrological models considering the heterogeneity of the parameters across the basin: a case study of SWAT model, Environmental Earth Sciences, 80, 131, doi:10.1007/s12665-021-09434-8, 2021.
    13. Assaye, H., J. Nyssen, J. Poesen, H. Lemma, D. T. Meshesha, A. Wassie, E. Adgo, and A. Frank, Curve number calibration for measuring impacts of land management in sub-humid Ethiopia, Journal of Hydrology, 35, 100819, doi:10.1016/j.ejrh.2021.100819, 2021.
    14. Gunn, K. M., A. R. Buda, H. E. Gall, R. Cibin, C. D. Kennedy, and T. L. Veith, Integrating daily CO2 concentrations in SWAT-VSA to examine climate change impacts on hydrology in a karst watershed, Transactions of the ASABE, doi:10.13031/trans.13711, 2021.

  1. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Stochastic periodic autoregressive to anything (SPARTA): Modelling and simulation of cyclostationary processes with arbitrary marginal distributions, Water Resources Research, 54 (1), 161–185, WRCR23047, doi:10.1002/2017WR021394, 2018.

    Stochastic models in hydrology traditionally aim at reproducing the empirically derived statistical characteristics of the observed data rather than any specific distribution model that attempts to describe the usually non-Gaussian statistical behavior of the associated processes. SPARTA (Stochastic Periodic AutoRegressive To Anything) offers an alternative and novel approach which allows the explicit representation of each process of interest with any distribution model, while simultaneously establishes dependence patterns that cannot be fully captured by the typical linear stochastic schemes. Cornerstone of the proposed approach is the Nataf joint-distribution model, which is related with the Gaussian copula, combined with Gaussian periodic autoregressive processes. In order to obtain the target stochastic structure, we have also developed a computationally simple and efficient algorithm, based on a hybrid Monte-Carlo procedure that is used to approximate the required equivalent correlation coefficients. Theoretical and practical benefits of the proposed method, contrasted to outcomes from widely used stochastic models, are demonstrated by means of real-world as well as hypothetical monthly simulation examples involving both univariate and multivariate time series.

    Additional material:

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

    1. Papalexiou, S. M., Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency, Advances in Water Resources, 115, 234-252, doi:10.1016/j.advwatres.2018.02.013, 2018.
    2. 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.
    3. Marković, D., S. Ilić, D. Pavlović, J. Plavšić, and N. Ilich, Multivariate and multi-scale generator based on non-parametric stochastic algorithms, Journal of Hydroinformatics, 21(6), 1102-1117, doi:10.2166/hydro.2019.071, 2019.
    4. #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.
    5. Nazemi, A., M. Zaerpour, and E. Hassanzadeh, Uncertainty in bottom-up vulnerability assessments of water supply systems due to regional streamflow generation under changing conditions, Journal of Water Resources Planning and Management, 146(2), doi:10.1061/(ASCE)WR.1943-5452.0001149, 2020.
    6. Barber, C., J. R. Lamontagne, and R. M. Vogel, Improved estimators of correlation and R2 for skewed hydrologic data, Hydrological Sciences Journal, 65(1), 87-101, doi:10.1080/02626667.2019.1686639, 2020.
    7. Dutta, R., and R. Maity, Temporal networks based approach for non‐stationary hydroclimatic modelling and its demonstration with streamflow prediction, Water Resources Research, 56(8), e2020WR027086, doi:10.1029/2020WR027086, 2020.
    8. Demetriou, E., G. Mallouppas, and C.Hadjistassou, Embracing carbon neutral electricity and transportation sectors in Cyprus, Energy, doi:10.1016/j.energy.2021.120625, 2021.
    9. 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. 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. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, European Water, 57, 337–343, 2017.

    Low flows commonly occur in rivers during dry seasons within each year. They often concur with increased water demand which creates numerous water resources management problems. This paper seeks for simple yet efficient tools for low-flow forecasting, which are easy to implement, based on the adoption of an exponential decay model for the flow recession curve. A statistical attribute of flows preceding the start of the dry period is used as the starting flow. On the other hand, the decay rate (recession parameter) is assumed as a linear function of the starting flow. The two parameters of that function are time-invariant, and they are optimized over a reference time series representing the low flow component of the observed hydrographs. The methodology is tested in the basins of Achelous, Greece, Xeros and Peristerona, Cyprus, and Salso, Italy. Raw data are filtered by signal processing techniques which remove the effect of flood events occurring in dry periods, thus allow-ing the preservation of the decaying form of the flow recession curve. Results indicate that satisfac-tory low flow forecasts are possible for Mediterranean basins of different hydrological behaviour.

    Remarks:

    Conference paper published in Special Issue of European Water: "10th Word Congress on Water Resources and Environment".

    Full text: http://www.itia.ntua.gr/en/getfile/1753/1/documents/EW_2017_57_47.pdf (859 KB)

    See also: http://www.ewra.net/ew/pdf/EW_2017_57_47.pdf

  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. 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:

    • [97] 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. 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.
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    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.
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  1. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.

    In water resources optimization problems, the objective function usually presumes to first run a simulation model and then evaluate its outputs. However, long simulation times may pose significant barriers to the procedure. Often, to obtain a solution within a reasonable time, the user has to substantially restrict the allowable number of function evaluations, thus terminating the search much earlier than required. A promising strategy to address these shortcomings is the use of surrogate modeling techniques. Here we introduce the Surrogate-Enhanced Evolutionary Annealing-Simplex (SEEAS) algorithm that couples the strengths of surrogate modeling with the effectiveness and efficiency of the evolutionary annealing-simplex method. SEEAS combines three different optimization approaches (evolutionary search, simulated annealing, downhill simplex). Its performance is benchmarked against other surrogate-assisted algorithms in several test functions and two water resources applications (model calibration, reservoir management). Results reveal the significant potential of using SEEAS in challenging optimization problems on a budget.

    Related works:

    • [110] Early presentation if EGU conference

    Full text: http://www.itia.ntua.gr/en/getfile/1587/2/documents/SEEAS_paper.pdf (4310 KB)

    Additional material:

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

    1. Dariane , A. B., and M. M. Javadianzadeh, Towards an efficient rainfall–runoff model through partitioning scheme, Water, 8, 63, doi:10.3390/w8020063, 2016.
    2. Yaseen, Z. M., O. Jaafar, R. C. Deo, O. Kisi, J. Adamowski, J. Quilty, and A. El-Shafie, Boost stream-flow forecasting model with extreme learning machine data-driven: A case study in a semi-arid region in Iraq, Journal of Hydrology, 542, 603-614, doi:10.1016/j.jhydrol.2016.09.035, 2016.
    3. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
    4. #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.
    5. Salazar, J. Z., P. M. Reed, J. D. Quinn, M. Giuliani, and A. Castelletti, Balancing exploration, uncertainty and computational demands in many objective reservoir optimization, Advances in Water Resources, 109, 196-210, doi:10.1016/j.advwatres.2017.09.014, 2017.
    6. Christelis, V., and A. Mantoglou, Physics-based and data-driven surrogate models for pumping optimization of coastal aquifers, European Water, 57, 481–488, 2017.
    7. #Thandayutham, K., E. Avital, N. Venkatesan, and A. Samad, Design and analysis of a marine current turbine, Proceedings of ASME 2017 Gas Turbine India Conference and Exhibition, GTINDIA2017-4912, V001T02A014, Bangalore, India, doi:10.1115/GTINDIA2017-4912, 2017.
    8. Christelis, V., R. G. Regis, and A. Mantoglou, Surrogate-based pumping optimization of coastal aquifers under limited computational budgets, Journal of Hydroinformatics, 20(1), 164-176, doi:10.2166/hydro.2017.063, 2018.
    9. Christelis, V., and A. G. Hughes, Metamodel-assisted analysis of an integrated model composition: an example using linked surface water – groundwater models, Environmental Modelling and Software, 107, 298-306, doi:10.1016/j.envsoft.2018.05.004, 2018.
    10. Zischg, A. P., G. Felder, M. Mosimann, V. Röthlisberger, and R. Weingartner, Extending coupled hydrological-hydraulic model chains with a surrogate model for the estimation of flood losses, Environmental Modelling and Software, 108, 174-185, doi:10.1016/j.envsoft.2018.08.009, 2018.
    11. Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers using seawater intrusion models of variable-fidelity and evolutionary algorithms, Water Resources Management, 33(2), 555-558, doi:10.1007/s11269-018-2116-0, 2019.
    12. Thandayutham, K., L. K. Mishra, and A. Samad, Optimal design of a marine current turbine using CFD and FEA, Proceedings of the Fourth International Conference in Ocean Engineering (ICOE2018), K. Murali, V. Sriram, A. Samad, N. Saha (editors), Lecture Notes in Civil Engineering, 23, 675-690, doi:10.1007/978-981-13-3134-3, 2019.
    13. Christelis, V., G. Kopsiaftis, and A. Mantoglou, Performance comparison of multiple and single surrogate models for pumping optimization of coastal aquifers, Hydrological Sciences Journal, 64(3), 336-349, doi:10.1080/02626667.2019.1584400, 2019.
    14. Cai, X., L. Gao, X. Li, and H-. Qiu, Surrogate-guided differential evolution algorithm for high dimensional expensive problems, Swarm and Evolutionary Computation, 48, 288-311, doi:10.1016/j.swevo.2019.04.009, 2019.
    15. Huot, P.-L., A. Poulin, C. Audet, and S. Alarie, A hybrid optimization approach for efficient calibration of computationally intensive hydrological models, Hydrological Sciences Journal, 64(9), 1204-1222, doi:10.1080/02626667.2019.1624922, 2019.
    16. Jahandideh-Tehrani, M., O. Bozorg-Haddad, and H. A. Loáiciga, Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview, Environmental Monitoring and Assessment, 191:439, doi:10.1007/s10661-019-7581-2, 2019.
    17. Sandoval, S., and J.-L. Bertrand-Krajewski, From marginal to conditional probability functions of parameters in a conceptual rainfall-runoff model: an event-based approach, Hydrological Sciences Journal, 64(11), 1340-1350, doi:10.1080/02626667.2019.1635696, 2019.
    18. Zhao, C. S., T. L. Pan, J. Xi, S. T. Yang, J. Zhao, X. J. Gan, L. P. Hou, and S. Y. Ding, Streamflow calculation for medium-to-small rivers in data scarce inland areas, Science of The Total Environment, 693, 133571, doi:10.1016/j.scitotenv.2019.07.377, 2019.
    19. Monteil, C., F. Zaoui, N. Le Moine, and F. Hendrickx, Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm, Hydrology and Earth System Sciences, 24, 3189-3209, 10.5194/hess-24-3189-2020, 2020.
    20. Muhammed, K. A., and R. Farmani, Energy optimization using a pump scheduling tool in water distribution systems, ARO – The Scientific Journal of Koya University, 8(1), 112-123, doi:10.14500/aro.10635, 2020.
    21. #Castro-Gama M., C. Agudelo-Vera, and D. Bouziotas, A bird’s-eye view of data validation in the drinking water industry of the Netherlands, The Handbook of Environmental Chemistry, Springer, Berlin, Heidelberg, doi:10.1007/698_2020_609, 2020.
    22. Xai, W., C. Shoemaker, T. Akhtar, and M.-T. Nguyen, Efficient parallel surrogate optimization algorithm and framework with application to parameter calibration of computationally expensive three-dimensional hydrodynamic lake PDE models, Environmental Modelling and Software, 135, 104910, doi:10.1016/j.envsoft.2020.104910, 2021.
    23. Saadatpour, M., S. Javaheri, A. Afshar, and S. S. Solis, Optimization of selective withdrawal systems in hydropower reservoir considering water quality and quantity aspects, Expert Systems with Applications, 184, 115474, doi:10.1016/j.eswa.2021.115474, 2021.
    24. Zhao, T., and B. Minsker, Efficient metamodel approach to handling constraints in nonlinear optimization for drought management, Journal of Water Resources Planning and Management, 147(12), doi:10.1061/(ASCE)WR.1943-5452.0001476, 2021.
    25. Anahideh, H., J. Rosenberger, and V. Chen, High-dimensional black-box optimization under uncertainty, Computers & Operations Research, 137, 105444, doi:10.1016/j.cor.2021.105444, 2022.

  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. 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. 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.
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  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/

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  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

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  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

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    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. J. A. P. Pollacco, B. P. Mohanty, and A. Efstratiadis, Weighted objective function selector algorithm for parameter estimation of SVAT models with remote sensing data, Water Resources Research, 49 (10), 6959–6978, doi:10.1002/wrcr.20554, 2013.

    The objective function of the inverse problem in Soil Vegetation Atmosphere Transfer (SVAT) models can be expressed as the aggregation of two criteria, accounting for the uncertainties of surface soil moisture (θ) and evapotranspiration (ET), retrieved from remote sensing (RS). In this context, we formulate a Weighted Objective Function (WOF) with respect to model effective soil hydraulic parameters, comprising of two components for θ and ET, respectively, and a dimensionless coefficient w. Given that the sensitivity of θ is increased by omitting the periods when soil moisture decoupling occurs, we also introduce within the WOF a threshold, θd, which outlines the decoupling of the surface and root-zone moisture. The optimal values of w and θd are determined by using a novel framework, Weighted Objective Function Selector Algorithm (WOFSA). This performs numerical experiments, assuming known reference conditions. In particular, it solves the inverse problem for different sets of θ and ET, considering the uncertainties of retrieving them from RS, and then runs the hydrological model to obtain the simulated water fluxes and their residuals, ΔWF, against the reference responses. It estimates the two unknown variables, w and θd, by maximizing the linear correlation between the WOF and maximum ΔWF. The framework is tested using a modified Soil-Water-Atmosphere-Plant (SWAP) model, under 22 contrasting hydroclimatic scenarios. It is shown that for each texture class, w can be expressed as function of the average θ and ET-fraction, while that for all scenarios θd can be modeled as function of the average θ, average ET and standard deviation of ET. Based on the outcomes of this study, we also provide recommendations on the most suitable time period for soil moisture measurements for capturing its dynamics and thresholds. Finally, we propose the implementation of WOFSA within multiobjective calibration, as a generalized tool for recognizing robust solutions from the Pareto front.

    Full text: http://www.itia.ntua.gr/en/getfile/1383/2/documents/WRR_paper.pdf (2717 KB)

    Additional material:

    See also: http://dx.doi.org/10.1002/wrcr.20554

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

    1. Mohanty, B. P., Soil hydraulic property estimation using remote sensing: a review, Vadose Zone Journal, 12(4), 2013.
    2. Wöhling, T., S. Gayler, E. Priesack, J. Ingwersen, H.-D. Wizemann, P. Högy, M. Cuntz, S. Attinger, V. Wulfmeyer, and T. Streck, Multiresponse, multiobjective calibration as a diagnostic tool to compare accuracy and structural limitations of five coupled soil-plant models and CLM3.5, Water Resources Research, 49(12), 8200–8221, 2013.
    3. #Gupta, M., N. K. Garg, P. K Srivastava, and T. Islam, Integration of TRMM rainfall in numerical model for pesticide prediction in subtropical climate, Proceedings of 11th International Conference on Hydroinformatics (HIC 2014), New York City, 2014.
    4. Gong, W., Q. Duan, J. Li, C. Wang, Z. Di, Y. Dai, A. Ye, and C. Miao, Multi-objective parameter optimization of common land model using adaptive surrogate modelling, Hydrology and Earth System Sciences, 19, 2409–2425, doi:10.5194/hess-19-2409-2015, 2015.
    5. Garg, N. K., and M. Gupta, Assessment of improved soil hydraulic parameters for soil water content simulation and irrigation scheduling, Irrigation Science, 33(4), 247-264, doi:10.1007/s00271-015-0463-7, 2015.
    6. Larsen, M. A. D., J. C. Refsgaard, K. H. Jensen, M. B. Butts, S. Stisen, and M. Mollerup, Calibration of a distributed hydrology and land surface model using energy flux measurements, Agricultural and Forest Meteorology, 217, 74–88, doi:10.1016/j.agrformet.2015.11.012, 2016.
    7. #Gupta, M., P. K Srivastava, and T. Islam, Integrative use of near-surface satellite soil moisture and precipitation for estimation of improved irrigation scheduling parameters, Satellite Soil Moisture Retrieval: Techniques and Applications , P. K. Srivastava, G. Petropoulos, and Y. H. Kerr (editors), 271-288, doi:10.1016/B978-0-12-803388-3.00014-0, 2016.
    8. Maurya, S., P. K. Srivastava, M. Gupta, T. Islam, and D. Han, Integrating soil hydraulic parameter and microwave precipitation with morphometric analysis for watershed prioritization, Water Resources Management, 30(14), 5385–5405, doi:10.1007/s11269-016-1494-4, 2016.
    9. Fernández-Gálvez, J., J. A. P. Pollacco, L. Lilburne, S. McNeill, S. Carrick, L. Lassabatere, and R. Angulo-Jaramillo, Deriving physical and unique bimodal soil Kosugi hydraulic parameters from inverse modelling, Advances in Water Resources, 103933, doi:10.1016/j.advwatres.2021.103933, 2021.
    10. Bonneau, J., G. L. Kouyi, L. Lassabatere, and T. D. Fletcher, Field validation of a physically-based model for bioretention systems, Journal of Cleaner Production, 312, 127636, doi:10.1016/j.jclepro.2021.127636, 2021.

  1. N. Mamassis, A. Efstratiadis, and E. Apostolidou, Topography-adjusted solar radiation indices and their importance in hydrology, Hydrological Sciences Journal, 57 (4), 756–775, doi:10.1080/02626667.2012.670703, 2012.

    Solar radiation, direct and diffuse, is affected by surface characteristics, such as slope, aspect, altitude and shading. The paper examines the effects of topography on radiation, at multiple spatiotemporal scales, using suitable geometrical methods for the direct and diffuse components. Two indices are introduced for comparing the direct radiation received by areas at the same and different latitudes, respectively. To investigate the profile of direct radiation through the Greek territory, these are evaluated from hourly to annual basis, via GIS techniques. Moreover, different approaches are examined for estimating the actual global radiation at operational spatial scales (sub-basin and terrain), according to the available meteorological data. The study indicates that the errors of typical hydrometeorological modelling formulas, ignoring the topographic effects and the seasonal allocation of direct and diffuse radiation, depend on the spatial scale and they are non-uniformly distributed in time. In all cases, the estimations are improved by applying the proposed adjusting approaches. In particular, the adjustment of the measured global radiation ensures up to 10% increase of efficiency, while the modified Angström formula achieves slight (i.e. 2-4%) increase of efficiency and notable reduction of bias.

    See also: http://dx.doi.org/10.1080/02626667.2012.670703

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

    1. Kunkel, V., T. Wells, and G. R. Hancock, Soil temperature dynamics at the catchment scale, Geoderma, 273, 32–44, doi:10.1016/j.geoderma.2016.03.011, 2016.
    2. Felicísimo Pérez, Á. M., and M.Á. Martín-Tardío, A method of downscaling temperature maps based on analytical hillshading for use in species distribution modelling, Cartography and Geographic Information Science, 45(4), 329-338, doi:10.1080/15230406.2017.1338620, 2018.
    3. Frey, J., K. Kovach, S. Stemmler, and B. Koch, UAV photogrammetry of forests as a vulnerable process. A sensitivity analysis for a structure from motion RGB-image pipeline, Remote Sensing, 16(2), 912, doi:10.3390/rs10060912, 2018.
    4. Aguilar, C., R. Pimentel, and M. J. Polo, Two decades of distributed global radiation time series across a mountainous semiarid area (Sierra Nevada, Spain), Earth System Science Data, 13, 1335-1359, doi:10.5194/essd-13-1335-2021, 2021.
    5. Nepali, B. R., J. Skartveit, and C. B. Baniya, Impacts of slope aspects on altitudinal species richness and species composition of Narapani-Masina landscape, Arghakhanchi, West Nepal, Journal of Asia-Pacific Biodiversity, 14(3), 415-424, doi:10.1016/j.japb.2021.04.005, 2021.

  1. A. Efstratiadis, and K. Hadjibiros, Can an environment-friendly management policy improve the overall performance of an artificial lake? Analysis of a multipurpose dam in Greece, Environmental Science and Policy, 14 (8), 1151–1162, doi:10.1016/j.envsci.2011.06.001, 2011.

    Taking as example a multipurpose dam in Greece, we wish to show that by following a rational operation policy, where the improvement of the broader environmental system becomes a high-priority target, it is possible to achieve a much more efficient allocation of its “traditional” water uses. In this context, we review the 50-year history of the Plastiras reservoir in central Greece, to highlight the multiple negative impacts from a non-systematic, abstraction-oriented, operation policy. This kind of management is contrasted to a hypothetical one, obtained through a multidisciplinary methodological framework that has been developed ten years ago, which aimed to compromise a number of conflicting water uses. This required establishing a minimum allowable level for agricultural abstractions and stabilising the annual releases for irrigation and drinking water supply. The criteria under study are, directly or indirectly, related to the water storage in the lake. Therefore, the key idea is to investigate the performance of each criterion with regard to the variability of the level, by examining alternative level vs. abstraction control rules. Thus, the quantity of water that would be yearly available is a function of the minimum level allowed and the desirable reliability. In fact, objective analysis indicates that the maintenance of the reservoir level as high as possible is necessary for the conservation of the quality of the lake’s landscape, for the development of tourist activity and also for providing drinking water of good quality. The advantages of the proposed framework are then exhibited through a back-analysis that focuses to the recent period. The implementation of this management policy not only would improve the water and landscape quality as well as the tourist perspectives, but also allow for a much more efficient planning of the agricultural and, under some premises, hydroelectric energy needs. Thus, the adoption of a constant annual release, irrespective of the recent sequence of inflows, may be beneficial for the long-term interests of all social groups and, therefore, conflicts among drinking water supply, tourism, landscape quality, irrigation and hydroelectric production would become less intense. Yet, the practice showed that a consensus between scientists, authorities and stakeholders for establishing the suggested policy is a considerably difficult task.

    See also: http://dx.doi.org/10.1016/j.envsci.2011.06.001

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

    1. Tajziehchi, S., S. M. Monavari, and A. Karbassi, An effective participatory-based method for dam social impact assessment, Polish Journal of Environmental Studies, 21(6), 1841-1848, 2012.
    2. #Makrogianni, S., and K. Hadjibiros, Interdisciplinarity in environmental research: an analysis based on scientific publications, Proceedings of the 13th International Conference on Environmental Science and Technology, CEST2013_0681, Athens, 2013.
    3. #Shukla, P., Performance Evaluation of Conservation Programmes for Lakes of the Nainital Region, Research paper, 14 p., GRIN Verlag GmbH, 2014.#Shukla, P., Performance Evaluation of Conservation Programmes for Lakes of the Nainital Region, Research paper, 14 p., GRIN Verlag GmbH, 2014.
    4. #Patsialis, T., I. Kougias, J. Ganoulis, and N. Theodossiou, Irrigation dams for renewable energy production, Economics of Water Management in Agriculture, Bournaris, T., J. Berbel, B. Manos, and D. Viaggi (editors), CRC Press, 2014.
    5. Dias-Sardinha, I., and D. Ross, Perceived impact of the Alqueva dam on regional tourism development, Tourism Planning and Development, 12(3), 362-375, doi:10.1080/21568316.2014.988880, 2015.
    6. Martin-Utrillas, M., F. Juan-Garcia, J. Canto-Perello, and Jorge Curiel-Esparza, Optimal infrastructure selection to boost regional sustainable economy, International Journal of Sustainable Development & World Ecology, 22(1), 30-38, doi:10.1080/13504509.2014.954023, 2015.
    7. Khorasani, H., R. Kerachian, and S. Malakpour-Estalaki, Developing a comprehensive framework for eutrophication management in off-stream artificial lakes, Journal of Hydrology, 562, 103-124, doi:10.1016/j.jhydrol.2018.04.052, 2018.
    8. Rodrigues, C., and T. Fidélis, The integration of land use in public water reservoirs plans – A critical analysis of the regulatory approaches used for the protection of banks, Land Use Policy, 81, 762-775, doi:10.1016/j.landusepol.2018.10.047, 2019.
    9. 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, jwc2020202, doi:10.2166/wcc.2020.202, 2020.

  1. 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.

    Remarks:

    The full text is available at the journal's web site: http://dx.doi.org/10.1080/02626667.2011.610759

    Huard's Discussion can be accessed again from the journal's web site: http://dx.doi.org/10.1080/02626667.2011.610758

    Weblog discussions can be seen in Climate Science, ABC News Watch, Fabius Maximus, Itia.

    Related works:

    • [32] A comparison of local and aggregated climate model outputs with observed data

    Full text: http://www.itia.ntua.gr/en/getfile/1140/1/documents/2011HSJ_OpeningClosedEyes.pdf (88 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. Jiang, P., M. R. Gautam, J. Zhu and Z. Yu, How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?, Journal of Hydrology, 479, 75-85, 2013.
    2. Chun, K. P., H. S. Wheater, and C. Onof, Comparison of drought projections using two UK weather generators, Hydrological Sciences Journal, 58(2), 1–15, 2013.
    3. #Ranzi, R., Influence of climate and anthropogenic feedbacks on the hydrological cycle, water management and engineering, Proceedings of 2013 IAHR World Congress, 2013.
    4. 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, 59(1), 1-28, doi:10.1080/02626667.2013.857411, 2014.
    5. #Jiménez Cisneros, B.E., T. Oki, N.W. Arnell, G. Benito, J.G. Cogley, P. Döll, T. Jiang, and S.S. Mwakalila, Freshwater resources. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 229-269, 2014.
    6. Hesse, C., V. Krysanova, A. Stefanova, M. Bielecka, and D. A. Domnin, Assessment of climate change impacts on water quantity and quality of the multi-river Vistula Lagoon catchment, Hydrological Sciences Journal, 60(5), 890-911, doi:10.1080/02626667.2014.967247, 2015.
    7. Nayak, P. C., R. Wardlaw, and A. K. Kharya, Water balance approach to study the effect of climate change on groundwater storage for Sirhind command area in India, International Journal of River Basin Management, 13(2), 243-261, doi:10.1080/15715124.2015.1012206, 2015.
    8. Frank, P., Negligence, non-science, and consensus climatology, Energy and Environment, 26(3), doi:10.1260/0958-305X.26.3.391, 2015.
    9. Kara, F., I. Yucel, and Z. Akyurek, Climate change impacts on extreme precipitation of water supply area in Istanbul: Use of ensemble climate modelling and geo-statistical downscaling, Hydrological Sciences Journal, 61(14), 2481-2495, doi:10.1080/02626667.2015.1133911, 2016.
    10. Refsgaard, J. C., T. O. Sonnenborg, M. B. Butts, J. H. Christensen, S. Christensen, M. Drews, K. H. Jensen, F. Jørgensen, L. F. Jørgensen, M. A. D. Larsen, S. H. Rasmussen, L. P. Seaby, D. Seifert, and T. N. Vilhelmsen, Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?, Hydrological Sciences Journal, 61(13), 2312-2324, doi:10.1080/02626667.2015.1131899, 2016.
    11. 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, 62(1), 1-14, doi:10.1080/02626667.2016.1241398, 2017.
    12. Connolly, R., M. Connolly, W. Soon, D. R. Legates, R. G. Cionco, and V. M. Velasco Herrera, Northern hemisphere snow-cover trends (1967–2018): A comparison between climate models and observations, Geosciences, 9(3), 135, doi:10.3390/geosciences9030135, 2019.
    13. Kron, W., J. Eichner, and Z. W. Kundzewicz, Reduction of flood risk in Europe – Reflections from a reinsurance perspective, Journal of Hydrology, doi:10.1016/j.jhydrol.2019.06.050, 2019.

  1. 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.

    The modelling of human-modified basins that are inadequately measured constitutes a challenge for hydrological science. Often, models for such systems are detailed and hydraulics-based for only one part of the system while for other parts oversimplified models or rough assumptions are used. This is typically a bottom-up approach, which seeks to exploit knowledge of hydrological processes at the micro-scale at some components of the system. Also, it is a monomeric approach in two ways: first, essential interactions among system components may be poorly represented or even omitted; second, differences in the level of detail of process representation can lead to uncontrolled errors. Additionally, the calibration procedure merely accounts for the reproduction of the observed responses using typical fitting criteria. The paper aims to raise some critical issues, regarding the entire modelling approach for such hydrosystems. For this, two alternative modelling strategies are examined that reflect two modelling approaches or philosophies: a dominant bottom-up approach, which is also monomeric and, very often, based on output information, and a top-down and holistic approach based on generalized information. Critical options are examined, which codify the differences between the two strategies: the representation of surface, groundwater and water management processes, the schematization and parameterization concepts and the parameter estimation methodology. The first strategy is based on stand-alone models for surface and groundwater processes and for water management, which are employed sequentially. For each model, a different (detailed or coarse) parameterization is used, which is dictated by the hydrosystem schematization. The second strategy involves model integration for all processes, parsimonious parameterization and hybrid manual-automatic parameter optimization based on multiple objectives. A test case is examined in a hydrosystem in Greece with high complexities, such as extended surface-groundwater interactions, ill-defined boundaries, sinks to the sea and anthropogenic intervention with unmeasured abstractions both from surface water and aquifers. Criteria for comparison are the physical consistency of parameters, the reproduction of runoff hydrographs at multiple sites within the studied basin, the likelihood of uncontrolled model outputs, the required amount of computational effort and the performance within a stochastic simulation setting. Our work allows for investigating the deterioration of model performance in cases where no balanced attention is paid to all components of human-modified hydrosystems and the related information. Also, sources of errors are identified and their combined effect are evaluated.

    Full text: http://www.itia.ntua.gr/en/getfile/1055/11/documents/hess-15-743-2011.pdf (1733 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-15-743-2011

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

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

    1. Gharari, S., M. Hrachowitz, F. Fenicia, and H. H. G. Savenije, Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment, Hydrology and Earth System Sciences, 15, 3275-3291, doi:10.5194/hess-15-3275-2011, doi:10.5194/hess-15-3275-2011, 2011.
    2. #Gharari, S., M. Hrachowitz, F. Fenicia, and H. H. G Savenije, Moving beyond traditional model calibration or how to better identify realistic model parameters: sub-period calibration, Hydrology and Earth System Science Discussions,, 9, 1885-1918, doi:10.5194/hessd-9-1885-2012, 2012.
    3. Flipo, N., C. Monteil, M. Poulin, C. de Fouquet, and M. Krimissa, Hybrid fitting of a hydrosystem model: Long term insight into the Beauce aquifer functioning (France), Water Recourses Research, 48, W05509, doi:10.1029/2011WR011092, 2012.
    4. Wang, X., T. Liu and W. Yang, Development of a robust runoff-prediction model by fusing the rational equation and a modified SCS-CN method, Hydrological Sciences Journal, 57(6), 1118-1140, doi:10.1080/02626667.2012.701305, 2012.
    5. Maneta, M. P., and W. W. Wallender, Pilot-point based multi-objective calibration in a surface–subsurface distributed hydrological model, Hydrological Sciences Journal, 58(2), 390-407, doi:10.1080/02626667.2012.754987, 2013.
    6. 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), 1198-1255, 2013.
    7. #Loukas, A., and L. Vasiliades, Review of applied methods for flood-frequency analysis in a changing environment in Greece, In: A review of applied methods in Europe for flood-frequency analysis in a changing environment, Floodfreq COST action ES0901: European procedures for flood frequency estimation (ed. by H. Madsen et al.), Centre for Ecology & Hydrology, Wallingford, UK, 2013.
    8. Flipo, N., A. Mouhri, B. Labarthe, S. Biancamaria, A. Rivière and P. Weill, Continental hydrosystem modelling: the concept of nested stream–aquifer interfaces, Hydrology and Earth System Sciences, 18, 3121-3149, doi:10.5194/hess-18-3121-2014, 2014.
    9. Ivkovic, K. M., B. F. W. Croke and R. A.Kelly, Overcoming the challenges of using a rainfall-runoff model to estimate the impacts of groundwater extraction on low flows in an ephemeral stream, Hydrology Research, 45(1), 58-72, doi:10.2166/nh.2013.204, 2014.
    10. Mateo, C. M., N. Hanasaki, D. Komori, K. Tanaka, M. Kiguchi, A. Champathong, T. Sukhapunnaphan, D.Yamazaki, and T. Oki, Assessing the impacts of reservoir operation to floodplain inundation by combining hydrological, reservoir management, and hydrodynamic models, Water Resources Research, 50(9), 7245–7266, doi:10.1002/2013WR014845, 2014.
    11. Gharari, S., M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije, Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrology and Earth System Sciences, 18, 4839-4859, doi:10.5194/hess-18-4839-2014, 2015.
    12. 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, 60(7-8), 1184-1199, doi:10.1080/02626667.2014.9672482014, 2015.
    13. Pryet, A., B. Labarthe, F. Saleh, M. Akopian and N. Flipo, Reporting of stream-aquifer flow distribution at the regional scale with a distributed process-based model, Water Resources Management, 10.1007/s11269-014-0832-7, 29(1), 139-159, 2015.
    14. Donnelly, C., J. C. M. Andersson, and B. Arheimer, Using flow signatures and catchment similarities to evaluate the E-HYPE multi-basin model across Europe, Hydrological Sciences Journal, 61(2), 255-273, doi:10.1080/02626667.2015.1027710, 2016.
    15. Bellin, A., B. Majone, O. Cainelli, D. Alberici, and F. Villa, A continuous coupled hydrological and water resources management model, Environmental Modelling and Software, 75, 176–192, doi:10.1016/j.envsoft.2015.10.013, 2016.
    16. Ajmal, M., J.-H. Ahn, and , T.-W. Kim, Excess stormwater quantification in ungauged watersheds using an event-based modified NRCS model, Water Resources Management, 30(4), 1433-1448, doi:10.1007/s11269-016-1231-z, 2016.
    17. Ma, L., C. He, H. Bian, and L. Sheng, MIKE SHE modeling of ecohydrological processes: Merits, applications, and challenges, Ecological Engineering, 96, 137–149, doi:10.1016/j.ecoleng.2016.01.008, 2016.
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  1. 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.

    We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe. We spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections do not correspond to reality any better.

    Remarks:

    The paper has been discussed in weblogs and forums.

    Weblogs and forums that discussed this article during 2010:

    1. Very Important New Paper “A Comparison Of Local And Aggregated Climate Model Outputs With Observed Data” By Anagnostopoulos Et Al 2010 (Climate Science: Roger Pielke Sr.)
    2. New peer reviewed paper shows just how bad the climate models really are (Watts Up With That?)
    3. Missing News: No skill in climate modelling (ABC News Watch)
    4. Missing News: Climate models disputed (ABC News Watch)
    5. New peer reviewed paper shows just how bad the climate models really are (repost 1) (Countdown to critical mass)
    6. New peer reviewed paper shows just how bad the climate models really are (repost2 ) (Climate Observer)
    7. New Major Peer-Reviewed Study: Climate Models' Predictions Found To Be Shitty (C3)
    8. New peer reviewed paper shows just how bad the climate models really are - A response to the Climate Change Misinformation at wattsupwiththat.com (Wott's Up With That?)
    9. Climate model abuse (Niche Modeling)
    10. Very Important New Paper on models versus reality (Greenie Watch)
    11. New paper shows that there is no means of reliably predicting climate variables (Greenie Watch 2)
    12. A comparison of local and aggregated climate model outputs with observed data (Fire And Ice)
    13. Peer Reviewed Study States The Obvious (US Message Board)
    14. Climate models don’t work, in hindsight (Herald Sun Andrew Bolt Blog)
    15. Climate models don’t work, in hindsight (repost) (The Daily Telegraph)
    16. No abuse hides the fact:  warmist models cannot even predict our past (Herald Sun Andrew Bolt Blog 2)
    17. No abuse hides the fact: the warmist models cannot even predict our past (PA Pundits – International)
    18. Aussie rains – IPCC models are bunkum, Energy tsunami, CCNet updates, Exit EU petition (clothcap)
    19. Aussie rains – IPCC models are bunkum, Energy tsunami, CCNet updates, Exit EU petition (repost) (My Telegraph)
    20. Science not politics (ecomyths)
    21. More evidence that Global Climate computer models are worthless (Tucano's Perch)
    22. Model skill? (Retread Resources Blog)
    23. Estudo sobre modelos climáticos (MeteoPT.com - Fórum de Meteorologia)
    24. Strategie di verifica delle prestazioni dei GCM, i risultati degli idrologi dell’università di Atene (Climate Monitor)
    25. Strategie di verifica delle prestazioni dei GCM, i risultati degli idrologi dell’università di Atene (repost) (Blog All Over The World)
    26. Klima - spådommer og målinger (ABC News)
    27. "Scam for the Ages" Makes Madoff Look Like Small Change (Al Fin)
    28. Teoria do AGA: um passado duvidoso, um presente mal contado e um futuro pior ainda. (Sou Engenheiro)

    Other reactions in weblogs, forums and Internet resources during 2010:

    Climate Etc. * Climate Etc. (2) * Climate Etc. (3) * YouTube * Science Forum * Google Groups * Google Groups 2 * Errors in IPCC climate science * Errors in IPCC climate science (2) * Just Grounds Community * A Few Things Ill Considered * Popular Technology.net * The Climate Scam * JunkScience * The Chronicle of Higher Education * The Little Skeptic * Jennifer Marohasy * Dot Earth Blog - NYTimes.com * ICECAP * Watching the Deniers * DVD Talk * Pure Poison * Peak Oil News and Message Boards * Bishop Hill * San Diego News * Sheffield Forum * Herald Sun Andrew Bolt Blog 3 * BBC - Richard Black's Earth Watch * Liberation * Pistonheads * ABC.net.au * Climate Conversation Group * Sydsvenskan - Nyheter dygnet runt * Telepolis * Keskisuomalainen * Keskisuomalainen 2

    Related works:

    • [142] Credibility of climate predictions revisited (predecessor presentation)
    • [35] On the credibility of climate predictions (previous related publication)

    Full text: http://www.itia.ntua.gr/en/getfile/978/1/documents/928051726__.pdf (1309 KB)

    Additional material:

    See also: http://dx.doi.org/10.1080/02626667.2010.513518

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

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

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  1. 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.

    One decade after the first publications on multiobjective hydrological calibration, we summarize the experience gained so far, by underlining the key perspectives offered by such approaches to improve parameter identifiability. After reviewing the fundamentals of vector optimization theory and the algorithmic issues, we link the multicriteria calibration approach with the concepts of uncertainty and equifinality. Specifically, the multicriteria framework enables recognizing and handling errors and uncertainties, and detecting prominent behavioural solutions with acceptable trade-offs. Particularly in models of complex parameterization, a multiobjective approach becomes essential for improving the identifiability of parameters and augmenting the information contained in calibration, by means of both multiresponse measurements and empirical metrics (“soft” data), which account for the hydrological expertise. Based on the literature review, we also provide alternative techniques to treat with conflicting and non-commeasurable criteria, and hybrid strategies to utilize the information gained towards identifying promising compromise solutions that ensure consistent and reliable calibrations.

    Full text: http://www.itia.ntua.gr/en/getfile/924/2/documents/919806565_.pdf (290 KB)

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  1. 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.

    Since 1990 extensive funds have been spent on research in climate change. Although Earth Sciences, including climatology and hydrology, have benefited significantly, progress has proved incommensurate with the effort and funds, perhaps because these disciplines were perceived as “tools” subservient to the needs of the climate change enterprise rather than autonomous sciences. At the same time, research was misleadingly focused more on the “symptom”, i.e. the emission of greenhouse gases, than on the “illness”, i.e. the unsustainability of fossil fuel-based energy production. Unless energy saving and use of renewable resources become the norm, there is a real risk of severe socioeconomic crisis in the not-too-distant future. A framework for drastic paradigm change is needed, in which water plays a central role, due to its unique link to all forms of renewable energy, from production (hydro and wave power) to storage (for time-varying wind and solar sources), to biofuel production (irrigation). The extended role of water should be considered in parallel to its other uses, domestic, agricultural and industrial. Hydrology, the science of water on Earth, must move towards this new paradigm by radically rethinking its fundamentals, which are unjustifiably trapped in the 19th-century myths of deterministic theories and the zeal to eliminate uncertainty. Guidance is offered by modern statistical and quantum physics, which reveal the intrinsic character of uncertainty/entropy in nature, thus advancing towards a new understanding and modelling of physical processes, which is central to the effective use of renewable energy and water resources.

    Remarks:

    Blogs and forums that have discussed this article: Climate science; Vertical news; Outside the cube.

    Update 2011-09-26: The removed video of the panel discussion of Nobelists entitled “Climate Changes and Energy Challenges” (held in the framework of the 2008 Meeting of Nobel Laureates at Lindau on Physics) which is referenced in footnote 1 of the paper, still cannot be located online. However, Larry Gould has an audio file of the discussion here.

    Full text: http://www.itia.ntua.gr/en/getfile/878/17/documents/hess-13-247-2009.pdf (1476 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-13-247-2009

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

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

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  1. 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.

    Geographically distributed predictions of future climate, obtained through climate models, are widely used in hydrology and many other disciplines, typically without assessing their reliability. Here we compare the output of various models to temperature and precipitation observations from eight stations with long (over 100 years) records from around the globe. The results show that models perform poorly, even at a climatic (30-year) scale. Thus local model projections cannot be credible, whereas a common argument that models can perform better at larger spatial scales is unsupported.

    Remarks:

    The paper has been widely discussed in weblogs and forums.

    Weblogs and forums that discussed this article during 2008:

    1. Koutsoyiannis et al 2008: On the credibility of climate predictions (Climate Audit by Steve McIntyre) Reaction by first author * * * Additional reactions: 2 * 3 * 4 * 5 * 6 * more
    2. On the credibility of climate predictions by Koutsoyiannis et al. 2008 (Climate Science by Roger Pielke Sr. 1)
    3. Comments on a New Report on Climate Change in Colorado… (Climate Science by Roger Pielke Sr. 2)
    4. New Paper On Dynamic Downscaling Of Climate Models By Rockel Et. Al. Published (Climate Science by Roger Pielke Sr. 3)
    5. Hypothesis testing and long range memory (Real Climate by Gavin A. Schmidt) Reaction by 1st author; * * * Additional reaction
    6. Koutsoyiannis vs RealClimate.ORG (The Reference Frame by Luboš Motl) Reaction by 1rst author
    7. Modellen en vroegere werkelijkheid: een test (Klimaat by Marcel Severijnen 1)
    8. Nog eens: Modellen en vroegere werkelijkheid (Klimaat by Marcel Severijnen 2)
    9. Far from model predictions. As for the CSIRO’s… (Andrew Bolt Blog 1)
    10. Dud studies behind Rudd’s freakish claims (Andrew Bolt Blog 2)
    11. Rudd’s dud study (Andrew Bolt Blog 3)
    12. November snows all over the CSIRO (Andrew Bolt Blog 4)
    13. New paper demonstrates lack of credibility for climate model predictions (Jennifer Marohasy Blog 1)
    14. Ten of the Best Climate Research Papers (Nine Peer-Reviewed): A Note from Cohenite (Jennifer Marohasy Blog 2)
    15. Ten Worst Man-Made Disasters (Jennifer Marohasy Blog 3)
    16. Climate models struggling for credibility (Al Fin)
    17. Climate models fuzz (European Tribune)
    18. If it wasn't so serious then it'd be funny (Kerplunk - Common sense from Down Under)
    19. Laying the boot into climate models (The Tizona Group)
    20. More model mania (Planet Gore)
    21. New research on the credibility of climate predictions (SciForums)
    22. New paper demonstrates lack of credibility for climate model predictions 2 (Blogotariat)
    23. New study: climate models fail again (MSNBC Boards 1)
    24. Global Climate Models Fail (Again) (MSNBC Boards 2)
    25. On the credibility of climate predictions (Chronos)
    26. Sane skepticism, part 2 (Helicity)
    27. Science. On the credibility of climate predictions (Greenhouse Bullcrap)
    28. Testing global warming models (Assorted Meanderings)
    29. Climate cuttings 21 (Bishop Hill blog)
    30. Models, Climate Change and Credibility... (21st Century Schizoid Man)
    31. Two valuable perspectives on global warming (Fabius Maximus)
    32. Unreliability of climate models? (Climate Change)
    33. Crumbling Consensus: Global Climate Models Fail (Stubborn Facts)
    34. The Australian government's climate castle is built on sand (Greenie Watch)
    35. Koutsoyiannis et al 2008 (Detached Ideas)
    36. Credibility of Climate Predictions Paper (TWO community)
    37. "Climate consensus" continues to unravel (Solomonia)
    38. Climate models have no predictive value (Acadie 1755)
    39. Global Warming Summary series, Part 5: The Earth’s Greenhouse Gas – CO2 and IPCC Climate Modeling (Global Warming Science)
    40. Reducing Vulnerability to Climate-Sensitive Risks is the Best Insurance Policy (Cato Unbound)
    41. Global Warming News of the Week (No Oil for Pacifists)
    42. A few more cooling blasts at hot air balloons (Clothcap2 : My Telegraph)
    43. IPCC-Klimamodell unbrauchbar (jetzt Sueddeutsche)
    44. Uups II: IPCC-Klimamodelle fantasieren (Die Achse des Guten)
    45. Griechische Unsicherheiten (Climate Review)
    46. El fracaso de los modelos (Valdeperrillos)
    47. Klimamodeller er usikre (Debattcentralen - Aftenposten.no)
    48. Studie: Klimatmodellernas trovärdighet låg (Klimatsvammel)
    49. Credibilidad de las predicciones climáticas (FAEC Mitos y Fraudes)

    Other reactions in weblogs, forums and Internet resources during 2008:

    Climate Audit 2 * Climate Audit 3 * Real Climate 2 * Junk Science * Wikipedia * Wikipedia Talk 1 * Wikipedia Talk 2 * Wikipedia Talk 3 * Global Warming Clearinghouse 1 * Global Warming Clearinghouse 2 * Global Warming Clearinghouse 3 * ICECAP * Climate Feedback (Nature) * Google Groups - alt.global-warming 1 * Google Groups - alt.global-warming 2 * Google Groups - alt.politics.usa * Google Groups - sci.environment * Google Groups - sci.physics * Yahoo Tech Groups * Yahoo Message Boards * Andrew Bolt Blog 5 * Andrew Bolt Blog 6 * Andrew Bolt Blog 7 * Andrew Bolt Blog 8 * Andrew Bolt Blog 9 * Andrew Bolt Blog 10 * Andrew Bolt Blog 11 * Andrew Bolt Blog 12 * Andrew Bolt Blog 13 * Jennifer Marohasy Blog 4 * Jennifer Marohasy Blog 5 * Jennifer Marohasy Blog 6 * Jennifer Marohasy Blog 7 * Jennifer Marohasy Blog 8 * Jennifer Marohasy Blog 9 * Jennifer Marohasy Blog 10 * Jennifer Marohasy Blog 11 * Jennifer Marohasy Blog 12 * Jennifer Marohasy Blog 13 * Jennifer Marohasy Blog 14 * The Blackboard 1 * The Blackboard 2 * The Motley Fool Discussion Boards 1 * The Motley Fool Discussion Boards 2 * The Daily Bayonet * FinanMart * JREF Forum 1 * JREF Forum 2 * JREF Forum 3 * AccuWeather * Climate Change Fraud 1 * Climate Change Fraud 2 * Climate Change Fraud 4 * Climate Change Fraud 5 * Watts Up With That? 1 * Watts Up With That? 2 * Watts Up With That? 3 * Watts Up With That? 4 * Watts Up With That? 5 * City-Data Forum * Climate Brains * Dvorak Uncensored * Newspoll * The Australian 1 * The Australian 2 * ABC Unleashed 1 * ABC Unleashed 2 * ABC Unleashed 3 * ABC Unleashed 4 * ABC Science Online Forum * Global Warming Skeptics * Niche Modeling * Dot Earth - The New York Times 1 * Dot Earth - The New York Times 2 * Dot Earth - The New York Times 3 * Dot Earth - The New York Times 4 * Dot Earth - The New York Times 5 * Dot Earth - The New York Times 6 * Bart Verheggen * WE Blog * Globe and Mail 1 * Globe and Mail 2 * Small Dead Animals * forums.ski.com.au * ABC Message Board * Sydney Morning Herald 1 (also published in the print version of the newspaper) * Sydney Morning Herald 2 * Sydney Morning Herald 3 * PistonHeads * Clipmarks * British Blogs * The Devil's Kitchen * Peak Oil Journal * The Volokh Conspiracy * Weather Underground * Capitol Grilling * Science & Environmental Policy Project * SookNET Technology * Climate Review 2 * Social Science News Central * Urban75 Forums * Wolf Howling * Launch Magazine Online * Popular Technology * The Environment Site Forums * CNC zone * Solar Cycle 24 Forums * Wired Science * Climate 411 * Daimnation * The Forum * Global Warming Information * Christian Forums 1 * Christian Forums 2 * CommonDreams.org 1 * CommonDreams.org 2 * Greenhouse Bullcrap 2 * Derkeiler Newsgroup * YouTube * Fresh Video * Topix * WeerOnline * The Air Vent * Greenfyre’s * Crikey * ChangeBringer * Scotsman.com News * Climate Change Controversies - David Pratt * Skeptical Science * Block’s Indicator of Sustainable Growth * Digg * Millard Fillmore’s Bathtub * News Busters * AgoraVox * Notre Planete * France 5 * Wissen - Sueddeutsche * Telepolis-Blogforen 1 * Telepolis-Blogforen 2 * Telepolis-Blogforen 3 * WirtschaftsWoche * Antizyklisches Forum * Oekologismus.de * Público.es * Uppsalainitiativet * Tiede.fi 1 * Tiede.fi 2 * Tiede.fi 3 * kolumbus.fi/ * De Rerum Natura * Ilmastonmuutos - totta vai tarua * Politics.be * Keisarin uudet vaatteet * Keskustelut * Que Treta * Svensson * Punditokraterne * StumbleUpon * Scribd

    Related works:

    • [143] Assessment of the reliability of climate predictions based on comparisons with historical time series (predecessor presentation)
    • [32] A comparison of local and aggregated climate model outputs with observed data (follow up study)

    Full text: http://www.itia.ntua.gr/en/getfile/864/1/documents/2008HSJClimPredictions.pdf (997 KB)

    Additional material:

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

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

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    22. Kawasaki, A., M. Takamatsu, J. He, P. Rogers, and S. Herath, An integrated approach to evaluate potential impact of precipitation and land-use change on streamflow in Srepok River Basin, Theory and Applications of GIS, 2010.
    23. Vastila, K., M. Kummu, C. Sangmanee, and S. Chinvanno, Modelling climate change impacts on the flood pulse in the Lower Mekong floodplains, Journal of Water and Climate Change, 01.1, 67-86, 2010.
    24. Kundzewicz, Z. W., and E. Z. Stakhiv, Are climate models “ready for prime time” in water resources management applications, or is more research needed? Hydrological Sciences Journal, 55(7), 1085–1089, 2010.
    25. Zhang, S.-F., Y. Gu, and J. Lin, Uncertainty analysis in the application of climate models, Shuikexue Jinzhan/Advances in Water Science, 21(4), 504-511, 2010.
    26. Wu, S.-Y., Potential impact of climate change on flooding in the Upper Great Miami River Watershed, Ohio, USA: a simulation-based approach, Hydrological Sciences Journal, 55(8), 1251-1263, 2010.
    27. Soon, W., and D. R. Legates, Avoiding carbon myopia: three considerations for policy makers concerning manmade carbon dioxide, Ecology Law Currents, 37(1), 2010.
    28. #Liebscher, H.-J., and H. G. Mendel, Vom empirischen Modellansatz zum komplexen hydrologischen Flussgebietsmodell – Rückblick und Perspektiven, 132 p., Koblenz, Bundesanstalt für Gewässerkunde, 2010.
    29. #Maletta, H. E., and E. Maletta, Climate Change, Agriculture and Food Security in Latin America and the Caribbean, 319 p., 2010.
    30. Stockwell, D. R. B., Critique of drought models in the Australian Drought Exceptional Circumstances Report (DECR), Energy and Environment, 21(5), 425-436, 2010.
    31. Kigobe, M., N. McIntyre, H. Wheater and R. Chandler, Multi-site stochastic modelling of daily rainfall in Uganda, Hydrological Sciences Journal, 56(1), 17–33, 2011.
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  1. 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.

    The HYDROGEIOS modelling framework represents the main processes of the hydrological cycle in heavily modified catchments, with decision-depended abstractions and interactions between surface and groundwater flows. A semi-distributed approach and a monthly simulation time step are adopted, which are sufficient for water resources management studies. The modelling philosophy aims to ensure consistency with the physical characteristics of the system, while keeping the number of parameters as low as possible. Therefore, multiple levels of schematisation and parameterisation are adopted, by combining multiple levels of geographical data. To optimally allocate human abstractions from the hydrosystem during a planning horizon or even to mimic the allocation occurred in a past period (e.g. the calibration period), in the absence of measured data, a linear programming problem is formulated and solved within each time step. With this technique the fluxes across the hydrosystem are estimated, and the satisfaction of physical and operational constraints is ensured. The model framework includes a parameter estimation module that involves various goodness-of-fit measures and state-of-the-art evolutionary algorithms for global and multiobjective optimisation. By means of a challenging case study, the paper discusses appropriate modelling strategies which take advantage of the above framework, with the purpose to ensure a robust calibration and reproduce natural and human induced processes in the catchment as faithfully as possible.

    Remarks:

    Permission is granted to reproduce and modify this paper under the terms of the Creative Commons NonCommercial ShareAlike 2.5 license. The discussion paper and its reviews are shown in the HESSD site.

    Full text: http://www.itia.ntua.gr/en/getfile/787/1/documents/hess-12-989-2008.pdf (3843 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-12-989-2008

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

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    10. #Loukas, A., and L. Vasiliades, Review of applied methods for flood-frequency analysis in a changing environment in Greece, In: A review of applied methods in Europe for flood-frequency analysis in a changing environment, Floodfreq COST action ES0901: European procedures for flood frequency estimation (ed. by H. Madsen et al.), Centre for Ecology & Hydrology, Wallingford, UK, 2013.
    11. Varni, M., R. Comas, P. Weinzettel and S. Dietrich, Application of the water table fluctuation method to characterize groundwater recharge in the Pampa plain, Argentina, Hydrological Sciences Journal, 58 (7), 1445-1455, 2013.
    12. Han, J.-C., G.-H. Huang, H. Zhang, Z. Li, and Y.-P Li, Effects of watershed subdivision level on semi-distributed hydrological simulations: case study of the SLURP model applied to the Xiangxi River watershed, China, Hydrological Sciences Journal, 59(1), 108-125, 2014.
    13. Gharari, S., M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije, Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrology and Earth System Sciences, 18, 4839-4859, doi:10.5194/hessd-10-14801-2013, 2013.
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    15. Wi, S., Y.C.E. Yang, S. Steinschneider, A. Khalil, and C.M. Brown, Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change, Hydrology and Earth System Sciences, 19, 857-876, doi:10.5194/hess-19-857-2015, 2015.
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    22. Soulis, K. X., D. Manolakos, J. Anagnostopoulos, and D. Papantonis, Development of a geo-information system embedding a spatially distributed hydrological model for the preliminary assessment of the hydropower potential of historical hydro sites in poorly gauged areas, Renewable Energy, 92, 222-232, doi:10.1016/j.renene.2016.02.013, 2016.
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  1. 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.

    During the last decade, numerous studies have been carried out to predict future climate based on climatic models run on the global scale and fed by plausible scenarios about anthropogenic forcing to climate. Based on climatic model output, hydrologic models attempt then to predict future hydrologic regimes at regional scales. Much less systematic work has been done to estimate climatic uncertainty and to assess the climatic and hydrologic model outputs within an uncertainty perspective. In this study, a stochastic framework for future climatic uncertainty is proposed, based on the following lines: (1) climate is not constant but rather varying in time and expressed by the long-term (e.g. 30-year) time average of a natural process, defined on a fine scale; (2) the evolution of climate is represented as a stochastic process; (3) the distributional parameters of a process, marginal and dependence, are estimated from an available sample by statistical methods; (4) the climatic uncertainty is the result of at least two factors, the climatic variability and the uncertainty of parameter estimation; (5) a climatic process exhibits a scaling behavior, also known as long-range dependence or the Hurst phenomenon; (6) because of this dependence, the uncertainty limits of the future are affected by the available observations of the past. The last two lines differ from classical statistical considerations and produce uncertainty limits that eventually are much wider than those of classical statistics. A combination of analytical and Monte Carlo methods is developed to determine uncertainty limits for the nontrivial scaling case. The framework developed is applied with temperature, rainfall and runoff data from a catchment in Greece, for which data exist for about a century. The uncertainty limits are then superimposed onto deterministic projections up to 2050, obtained for several scenarios and climatic models combined with a hydrologic model. These projections indicate a significant increase of temperature in the future, beyond uncertainty bands, and no significant change of rainfall and runoff as they lie well within uncertainty limits.

    Remarks:

    Erratum in equation (A3) in the final paper; see the correct version in preprint.

    Additional material:

    See also: http://dx.doi.org/10.1175/JHM576.1

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

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  1. 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.

    The Plastiras dam was constructed in the late 1950s mainly for electric power production, but it has also partially covered irrigation needs and water supply of the plain of Thessaly. Later, the site has been designated as an environment conservation zone because of ecological and landscape values, while tourist activities have been developed around the reservoir. Irrigation of agricultural land, hydroelectric production, drinking water supply, tourism, ecosystem water quality and scenery conservation have evidently been conflicting targets for many years. Good management would require a multi-criteria decision making. Historical data show that the irregular water release has resulted in a great annual fluctuation of the reservoir water level. This situation could be improved by a rational management of abstractions. Apparently, higher release leads simultaneously to more power production and to irrigation of a larger agricultural land. Moreover, demands for electricity and for irrigation are partially competing to each other, due to different optimal time schedules of releases. On the other hand, higher water release leads to lower water level in the reservoir and, therefore, it decreases the beauty of the scenery and deteriorates the trophic state of the lake. Such degradation affects the tourist potential as well as the quality of drinking water supplied by the reservoir. A multi-criteria approach uses different scenarios for the minimum permissible water level of the reservoir, if a constant annual release is applied. The minimum level concept is a simple and functional tool, because it is understood by people, easily certified and incorporated into regulations. The quantity of water that would be yearly available is a function of the minimum level allowed. The water quality depends upon the trophic state of the lake, mainly the concentration of chlorophyll-a, which determines the state of eutrophication and is estimated by water quality simulation models, taking into account pollutant loads such as nitrogen and phosphorus. The value of the landscape is much depending on the water level of the lake, because for lower levels a dead-zone appears between the surface of the water and the surrounding vegetation. When this dead zone is large, it seems lifeless and the lake appears partially empty. Quantification of this visual effect is not easy, but it is possible to establish a correspondence between the aesthetic assessment of the scenery and the minimum allowed reservoir level. Using results from hydrological analysis, water quality models and landscape evaluation, it seems possible to construct a multi-criteria table with different criteria described against alternatives and with a plot of three relative indices against the minimum level allowed. However, decision making has to take into account the fact that comparison or merging of indices corresponding to different criteria analysis encompasses a degree of arbitrariness. More objective decisions would be possible if different benefits and costs were measured in a common unit. Moreover, management will be sensitive to different social pressures.

    Related works:

    • [39] Publication focused on the logic of multicriteria decisions.

    Full text: http://www.itia.ntua.gr/en/getfile/704/1/documents/2006GnestPlastiras.pdf (114 KB)

    Additional material:

    See also: http://www.gnest.org/Journal/Vol7_No3.htm

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

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

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  1. 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.

    The possible water management of the Plastiras Lake, an artificial reservoir in central Greece, is examined. The lake and surrounding landscape are aesthetically degraded when the water level drops, and the requirement of maintaining a high quality of the scenery constitutes one of the several conflicting water uses, the other ones being irrigation, water supply, and power production. This environmental water use, and, to a lesser extent, the requirement for adequate water quality, results in constraining the annual release. Thus, the allowed fluctuation of reservoir stage is not defined by the physical and technical characteristics of the reservoir, but by a multi-criteria decision, the three criteria being maximising water release, ensuring adequate water quality, and maintaining a high quality of the natural landscape. Each of these criteria is analyzed separately. The results are then put together in a multicriterion tableau, which helps understand the implications of the possible alternative decisions. Several conflict resolution methods are overviewed, namely willingness to pay, hedonic prices, and multi-criteria decision analysis. All these methods attempt to quantify non-quantifiable qualities, and it is concluded that they don't necessarily offer any advantage over merely making a choice based on understanding.

    Remarks:

    Permission is granted to reproduce and modify this paper under the terms of the Creative Commons NonCommercial ShareAlike 2.5 license.

    Full text: http://www.itia.ntua.gr/en/getfile/683/1/documents/2005HESSPlastiras.pdf (404 KB)

    Additional material:

    See also: http://dx.doi.org/10.5194/hess-9-507-2005

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

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

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    4. #Sargentis G. F., V. Symeonidis, and N. Symeonidis, Rules and methods for the development of a prototype landscape (Almyro) in north Evia by the creation of a thematic park, Proceedings of the 12th International Conference on Environmental Science and Technology (CEST2011), Rhodes, Greece, 2011.
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    7. Zhang, T., W. H. Zeng, S. R. Wang, and Z. K. Ni, Temporal and spatial changes of water quality and management strategies of Dianchi Lake in southwest China, Hydrology and Earth System Sciences, 18, 1493-1502, doi:10.5194/hess-18-1493-2014, 2014.
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    9. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.

  1. 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.

    A hydrological simulation model was developed for conjunctive representation of surface and groundwater processes. It comprises a conceptual soil moisture accounting module, based on an enhanced version of the Thornthwaite model for the soil moisture reservoir, a Darcian multi-cell groundwater flow module and a module for partitioning water abstractions among water resources. The resulting integrated scheme is highly flexible in the choice of time (i.e. monthly to daily) and space scales (catchment scale, aquifer scale). Model calibration involved successive phases of manual and automatic sessions. For the latter, an innovative optimization method called evolutionary annealing-simplex algorithm is devised. The objective function involves weighted goodness-of-fit criteria for multiple variables with different observation periods, as well as penalty terms for restricting unrealistic water storage trends and deviations from observed intermittency of spring flows. Checks of the unmeasured catchment responses through manually changing parameter bounds guided choosing final parameter sets. The model is applied to the particularly complex Boeoticos Kephisos basin, Greece, where it accurately reproduced the main basin response, i.e. the runoff at its outlet, and also other important components. Emphasis is put on the principle of parsimony which resulted in a computationally effective modelling. This is crucial since the model is to be integrated within a stochastic simulation framework.

    Full text: http://www.itia.ntua.gr/en/getfile/630/1/documents/2004HSJCalibrSemiDistrModel.pdf (445 KB)

    Additional material:

    See also: http://dx.doi.org/10.1623/hysj.49.5.819.55130

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

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

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  1. 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.

    The minimisation of the water cost is examined in the framework of an integrated water resources planning and management model, implemented within the decision support system for the management of the Athens water supply system. The mathematical framework employs a simulation-optimisation scheme, where simulation is applied to faithfully represent the system operation, whereas optimisation is applied to derive the optimal management policy, which simultaneously minimises the risk and cost of decision-making. Real economic criteria in addition with virtual costs are appropriately assigned to preserve the physical constraints and water use priorities, ensuring also the lowest-cost transportation of water from the sources to the consumption. The proposed model is tested in the hydrosystem of Athens, in order to minimise the expected operational cost for several system configurations.

    Additional material:

    See also: http://dx.doi.org/10.1080/15730620410001732099

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

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

    1. #SIRRIMED (Sustainable use of irrigation water in the Mediterranean Region), D4.2 and D5.2 Report on Models to be Implemented in the District Information Systems (DIS) and Watershed Information Systems (WIS), 95 pp., Universidad Politécnica de Cartagena, 2011.
    2. Lerma, N., J. Paredes-Arquiola, J. Andreu, and A. Solera, Development of operating rules for a complex multi-reservoir system by coupling genetic algorithms and network optimization, Hydrological Sciences Journal, 58 (4), 797-812, 2013.
    3. Newman, J. P., G. C. Dandy, and H. R. Maier, Multiobjective optimization of cluster-scale urban water systems investigating alternative water sources and level of decentralization, Water Resources Research, doi:10.1002/2013WR015233, 2014.
    4. Salazar, J. Z., P. M. Reed, J. D. Herman, M. Giuliani, and A. Castelletti, A diagnostic assessment of evolutionary algorithms for multi-objective surface water reservoir control, Advances in Water Resources, 92, 172-185, doi:10.1016/j.advwatres.2016.04.006, 2016.
    5. Stamou, A. T., and P. Rutschmann, Pareto optimization of water resources using the nexus approach, Water Resources Management, 32(15), 5053-5065, doi:10.1007/s11269-018-2127-x, 2018.
    6. Stamou, A.-T., and P. Rutschmann, Optimization of water use based on the water-energy-food nexus concept: Application to the long-term development scenario of the Upper Blue Nile River, Water Utility Journal, 25, 1-13, 2020.

  1. 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.

    The main components of a decision support system (DSS) developed to support the management of the water resource system of Athens are presented. The DSS includes information systems that perform data acquisition, management and visualisation, and models that perform simulation and optimisation of the hydrosystem. The models, which are the focus of the present work, are organised into two main modules. The first one is a stochastic hydrological simulator, which, based on the analysis of historical hydrological data, generates simulations and forecasts of the hydrosystem inputs. The second one allows the detailed study of the hydrosystem under alternative management policies implementing the parameterisation-simulation-optimisation methodology. The mathematical framework of this new methodology performs the allocation of the water resources to the different system components, keeping the number of control variables small and thus reducing the computational effort, even for a complex hydrosystem like the one under study. Multiple, competitive targets and constraints with different priorities can be set, which are concerned among others, with the system reliability and risk, the overall average operational cost and the overall guaranteed yield of the system. The DSS is in the final stage of its development and its results, some of which are summarised in the paper, have been utilised to support the new masterplan of the hydrosystem management.

    Additional material:

    See also: http://dx.doi.org/10.1016/S1474-7065(03)00106-2

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

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

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    26. Nouiri, I., F. Chemak, D. Mansour, H. Bellali, J. Ghrab, J. Baaboub, and M. K. Chahed, Impacts of irrigation water management on consumption indicators and exposure to the vector of Zoonotic Cutaneous Leishmaniasis (ZCL) in Sidi Bouzid, Tunisia, International Journal of Agricultural Policy and Research, 3(2), 93-103, doi:10.15739/IJAPR.031, 2015.
    27. Nouiri , I., M. Yitayew, J. Maßmann, and J. Tarhouni, Multi-objective optimization tool for integrated groundwater management, Water Resources Management, 29(14), 5353-5375, doi:10.1007/s11269-015-1122-8, 2015.
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  1. 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.

    A decision support tool is developed for the management of water resources, focusing on multipurpose reservoir systems. This software tool has been designed in such a way that it can be suitable to hydrosystems with multiple water uses and operating goals, calculating complex multi-reservoir systems as a whole. The mathematical framework is based on the parameterization-simulation-optimization scheme. The main idea consists of a parametric formulation of the operating rules for reservoirs and other projects (i.e. hydropower plants). This methodology enables the radical decrease of the number of decision variables, making feasible the location of the optimal management policy, which maximizes the system yield and the overall operational benefit and minimizes the risk for the management decisions. The program was developed using advanced software engineering techniques. It is adaptable in a wide range of water resources systems and its purpose is to support water and power supply companies and related authorities. It was already applied to two of the most complicated hydrosystems of Greece, the first time as a planning tool and the second time as a management tool.

    Additional material:

    See also: http://dx.doi.org/10.1111/j.1752-1688.2002.tb05536.x

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

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

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    6. #McCartney, M.P. and S. Awulachew, Improving dam planning and operation in the Nile Basin through the use of decision support systems, Proceedings of the Nile Basin Development Forum, 2006.
    7. #McCartney, M.P., Decision Support Systems for Large Dam Planning and Operation in Africa, IWMI Working Paper 119, 47 pp. International Water Management Institute, Colombo, Sri Lanka, 2006.
    8. #Bravo, J.M., W. Collischonn, J.V. Pilar, and C.E.M. Tucci, Otimização de regras de operação de reservatórios utilizando um algoritmo evolutivo, Anais do I Simpósio de Recursos Hídricos do Sul-Sudeste, ABRH, 2006.
    9. #Bravo, J. M., W. Collischonn, and J. V. Pilar, Optimización de la operación de una represa con múltiples usos utilizando un algoritmo evolutivo, Anales del IV Congreso argentino de presas y aprovechamientos hidroeléctricos, CADP, 2006.
    10. #Bravo, J. M., W. Collischonn, C. E. M. Tucci, and B. C. da Silva, Avaliação dos benefícios da previsão meteorológica na operação de reservatórios com usos múltiplos, Concurso I Prêmio INMET de Estudos sobre os Benefícios da Meteorologia para o Brasil, 2006.
    11. #Bravo, J. M., W. Collischonn, J. V. Pilar, B. C. da Silva, and C. E. M. Tucci, Evaluación de los beneficios de la previsión de caudal en la Operación de una represa, Anales del XXI congreso Nacional del Agua, 2007.
    12. #Bravo, J. M., W. Collischonn, J. V. Pilar, and C. E. M. Tucci, Influência da capacidade de regularização de reservatórios nos benefícios da previsão de vazão de longo prazo, Anais do XVII Simpósio Brasileiro de Recursos Hídricos, ABRH, 2007.
    13. Bravo, J. M., W. Collischonn, J. V. Pilar, and C. E. M. Tucci, Otimização de regras de operação de reservatórios com incorporação da previsão de vazão, Revista Brasileira de Recursos Hídricos, 13(1), 181-196, 2008.
    14. Celeste, A. B, and Billib, M., Evaluation of stochastic reservoir operation optimization models, Advances in Water Resources, 32(9), 1429-1443, 2009.
    15. Alemu, E. T., R. N. Palmer, A. Polebitski, and B. Meaker, Decision support system for optimizing reservoir operations using ensemble streamflow predictions, Journal of Water Recourses Planning and Management, 137(1), 72-82, 2011.
    16. Obolewskia, K., E. SkorbiŁowiczb, M. SkorbiŁowiczb, K. Glińska-Lewczukc, A. M. Asteld, and A. Strzelczake, The effect of metals accumulated in reed (Phragmites australis) on the structure of periphyton, Ecotoxicology and Environmental Safety, 74(4), 558-568, 2011.
    17. Kinyanjui, B. K., A. N. Gitau, and M. K. Mang’oli, Power development planning models in East Africa, Strategic Planning for Energy and the Environment, 31(1), 43-55, 2011.
    18. #McCartney, M., and G. Lacombe, Review of water resource and reservoir planning models for use in the Mekong, Mekong MK1 project on optimizing reservoir management for livelihoods, 24 pp., CGIAR Challenge Program on Water and Food, 2011.
    19. Ortega-Gaucin, D., Reglas de operación para el sistema de presas del Distrito de Riego 005 Delicias, Chihuahua, México, Ingeniería Agrícola y Biosistemas, 4(1), 31-39, 2012.
    20. Bianucci, P., A. Sordo-Ward, J. I. Pérez, J. García-Palacios, L. Mediero and L. Garrote, Risk-based methodology for parameter calibration of a reservoir flood control model, Natural Hazards and Earth System Sciences, 13, 965-981, 2013.
    21. Cavallo, A., A. Di Nardo, G. De Maria and M. Di Natale, Automated fuzzy decision and control system for reservoir management, Journal of Water Supply: Research and Technology – AQUA, 62(4), 189-204, 2013.
    22. Donia, N., Aswan High Dam reservoir management system, Journal of Hydroinformatics, 15(4), 1491-1510, 2013.
    23. Arunkumar, R., and V. Jothiprakash, Evaluation of a multi-reservoir hydropower system using a simulation model, ISH Journal of Hydraulic Engineering, 20 (2), 177-187, 2014.
    24. Latorre, J., S. Cerisola, A. Ramos, A. Perea, and R. Bellido, Coordinated hydropower plant simulation for multireservoir systems, Journal of Water Resources Planning and Management, 140(2), 216–227, 2014.
    25. Asadzadeh, M., S. Razavi, B. A. Tolson, and D. Fay, Pre-emption strategies for efficient multi-objective optimization: Application to the development of Lake Superior regulation plan, Environmental Modelling and Software, 54, 128-141, 2014.
    26. #Meseguer, J., G. Cembrano, J. M. Mirats, and E. Bonada, Optimizing operating rules of multiple source water supply systems in terms of system reliability and resulting operating costs: survey of simulation-optimization modeling approaches based on general purpose tools, 11th International Conference on Hydroinformatics, New York City, USA, 2014.
    27. Da Hora, M. A. G. M., and L. F. L. Legey, Water resource conflict in the Amazon Region: The case of hydropower generation and multiple water uses in the Tocantins and Araguaia river basins, The Global Journal of Researches in Engineering, 15(2), 2015.
    28. Oliveira, I. A., and A. B. Celeste, Operação de reservatório sergipano via curvas-guia parametrizadas por modelo de simulação-otimização, Scientia cum Industria, 4(3), doi:10.18226/23185279.v4iss3p154, 2016.
    29. Müller, R., and N. Schütze, Multi-objective optimization of multi-purpose multi-reservoir systems under high reliability constraints, Environmental Earth Sciences, 75:1278, doi:10.1007/s12665-016-6076-5, 2016.
    30. Celeste, A. B., and L. A. Ventura, Simple simulation–optimisation vs SDP for reservoir operation, Proceedings of the Institution of Civil Engineers – Water Management, 170(3), 128–138, doi:10.1680/jwama.15.00018, 2017.
    31. #Venkatesh, J., G. Chandrasekhar, I. V. Muralikrishna, and R. S. Dwivedi, Decision support system for optimization of multi-purpose reservoir system operations: a review, 17th ESRI India User Conference 2017, Delhi, 2017.
    32. Arunkumar, R., and V. Jothiprakash, Evaluating a multi-reservoir system for sustainable integrated operation using a simulation model, Sustainable Water Resources Management, 4, 981-990, doi:10.1007/s40899-017-0201-9, 2018.
    33. Stamou, A. T., and P. Rutschmann, Pareto optimization of water resources using the nexus approach, Water Resources Management, 32(15), 5053-5065, doi:10.1007/s11269-018-2127-x, 2018.
    34. Lei, X., Q. Tan, X. Wang, H. Wang, X. Wen, C. Wang, and Z.-W. Zhang, Stochastic optimal operation of reservoirs based on copula functions, Journal of Hydrology, 557, 265-275, doi:10.1016/j.jhydrol.2017.12.038, 2018.
    35. Rozos, E., An assessment of the operational freeware management tools for multi-reservoir systems, Water Science and Technology: Water Supply, 19(4), 995-1007, doi:10.2166/ws.2018.169, 2019.
    36. Stamou, A.-T., and P. Rutschmann, Optimization of water use based on the water-energy-food nexus concept: Application to the long-term development scenario of the Upper Blue Nile River, Water Utility Journal, 25, 1-13, 2020.
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Book chapters and fully evaluated conference publications

  1. 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.

    The fundamental concepts in the field of water-energy systems and their historical evolution with emphasis on recent developments are reviewed. Initially, a brief history of the relation of water and energy is presented, and the concept of the water-energy nexus in the 21th century is introduced. The investigation of the relationship between water and energy shows that this relationship comprises both conflicting and synergistic elements. Hydropower is identified as the major industry of the sector and its role in addressing modern energy challenges by means of integrated water-energy management is highlighted. Thus, the modelling steps of designing and operating a hydropower system are reviewed, followed by an analysis of theory and physics behind energy hydraulics. The key concept of uncertainty, which characterises all types of renewable energy, is also presented in the context of the design and management of water-energy systems. Subsequently, environmental considerations and impacts of using water for energy generation are discussed, followed by a summary of the developments in the emerging field of maritime energy. Finally, present challenges and possible future directions are presented.

  1. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Development of a distributed hydrological software application employing novel velocity-based techniques, 11th World Congress on Water Resources and Environment “Managing Water Resources for a Sustainable Future”, Madrid, European Water Resources Association, 2019.

    The aim of this study is the development of an event-based distributed hydrological model, incorporating novel methodologies for estimating the effective rainfall and flow routing across the terrain and the hydrographic network (Risva 2018). We present two modelling configurations of the model, one for extracting the flood hydrograph (separating interflow) and one for the full hydrograph, at the basin outlet.

    Full text:

  1. C. Rebolho, V. Andréassian, I. Tsoukalas, et A. Efstratiadis, La crue du Loing de Juin 2016 était-elle exceptionnelle?, De la prévision des crues à la gestion de crise, Avignon, Société Hydrotechnique de France, 2018.

    A heavy rainfall event affected the northern center part of France from May 30 to June 6, 2016, leading to a general overflowing of rivers in the Seine and Loire catchments. The resulting inundations exceeded the previous records on some catchments, such as the River Loing where the water height of January 1910 was outreached for the first time. This event results from the combination of an extremely wet month of May and a rainfall accumulation of 130 mm in one week which led to a daily peak flow of 450 m3/s on this catchment. The main goal of this study is to show the limitations of standard methods for the estimation of return periods of extreme events. Usually, statistic laws such as Gumbel of GEV are used to calculate such return periods. However, various fitting methods exist and can be used to assess the parameters of the theoretical laws. In this study, we found that depending on the methodology, the return period varies from 260 to 2 400 years when using the observed discharges. To address this issue we simulated a long series of streamflows by coupling a rainfall generator and the conceptual hydrological model GR4J. The empirical return period given by the models is 1 000 years. But in this case, we also have the uncertainties of the two models, particularly the hydrological model which struggles reproducing the non-linearities of the catchment behaviour especially when modelling extreme events. This is why it is difficult to assign a single value to the return period of extreme events when only a range is available.

    Full text: http://www.itia.ntua.gr/en/getfile/1918/1/documents/REBOLHO_ARTICLE_SHF_PREVISION.pdf (467 KB)

    See also: http://www.shf-hydro.org/223-1-events-16.html

  1. 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.

    In this study, a holistic approach for the optimal management of two large, multi-reservoir hydrosystems in Greece is analysed, applied in cases of multiple and conflicting water uses, such as hydroelectric production and the coverage of irrigation and drinking water demands. In general, the optimal management of such hydrosystems presents a strong challenge for engineers, due to the stochasticity of inflows and the non-linear nature of hydroelectric production. To manage the strong variability of renewable energy production, the use of the two studied cases of Acheloos-Thessaly and Aliakmonas as pump-storage systems is proposed. To explore the optimal management policies, the methodological framework of “Parameterisation-Simulation-Optimisation” (PSO) is applied, employed through the use of Hydronomeas software and its hydroelectric production optimization module. The goal of the analysis is the estimation of the capacity to generate firm energy with a preset high reliability level in both systems, as well as the assessment of the consequent economic benefit obtained with the optimal policies found through Hydronomeas. Moreover, the benefits of employing pump-storage schemes in order to provide a buffer for other renewable energy sources with strong variability, such as wind energy, is explored.

    Full text: http://www.itia.ntua.gr/en/getfile/1747/1/documents/fragmata2017.pdf (1070 KB)

    Additional material:

  1. I. Tsoukalas, C. Makropoulos, and A. Efstratiadis, Stochastic simulation of periodic processes with arbitrary marginal distributions, 15th International Conference on Environmental Science and Technology (CEST2017), Rhodes, Global Network on Environmental Science and Technology, 2017.

    Stochastic simulation of hydrological processes has a key role in water resources planning and management due to its ability to incorporate hydrological uncertainty within decision-making. Due to seasonality, the statistical characteristics of such processes are considered periodic functions, thus implying the use of cyclostationary stochastic models, typically using a common statistical distribution. Yet, this may not be representative of the statistical structure of such processes across all seasons. In this context, we introduce a novel model suitable for the simulation of periodic processes with arbitrary marginal distributions, called Stochastic Periodic AutoRegressive To Anything (SPARTA). Apart from capturing the periodic correlation structure of the underlying processes, its major advantages are a) the accurate preservation of seasonally-varying marginal distributions; b) the explicit generation of non-negative values; and c) the parsimonious model structure. Finally, the performance of the model is demonstrated through a theoretical (artificial) case study.

    Full text: http://www.itia.ntua.gr/en/getfile/1731/1/documents/cest2017_00797_oral_paper_V2.pdf (655 KB)

    Additional material:

    See also: http://cest.gnest.org/sites/default/files/presentation_file_list/cest2017_00797_oral_paper.pdf

  1. G. Papaioannou, L. Vasiliades, A. Loukas, A. Efstratiadis, S.M. Papalexiou, Y. Markonis, and A. Koukouvinos, A methodological approach for flood risk management in urban areas: The Volos city paradigm, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

    A methodological approach based on the implementation of the EU Floods Directive in Greece is developed and presented for flood risk management of urban areas. The flood risk assessment procedure is demonstrated for Volos city of Thessaly, Greece, where frequent flood episodes are observed due to intense storms. A unified deterministic extreme event-based methodology is applied for hydrologic and hydraulic modelling of floods. The hydrologic part is based on semi-distributed application of the HEC-HMS rainfall-runoff model with spatially-distributed design hyetographs. The SCS-CN method is used to estimate effective rainfall and the SCS synthetic unit hydrograph to produce extreme flood hydrographs at subwatershed scale. The hydraulic modelling is based on the propagation of flood hydrographs across the river network and the mapping of inundated areas using the HEC-RAS 2D model with flexible mesh size. Representation of the resistance caused by buildings have been simulated with the local elevation rise method using transformation of the Digital Terrain Model to a Digital Elevation Model. For the adopted design hyetographs upper and lower estimates on water depths, flow velocities and flood inundation areas are estimated taking into account structural and parameter uncertainty of the hydrologic and hydraulic models by varying antecedent soil moisture conditions and roughness coefficient values. The results indicate the uncertainty introduced on flood risk management in urban areas using typical engineering practices.

    Related works:

    • [11] Full research article published in Hydrology.

    Full text: http://www.itia.ntua.gr/en/getfile/1707/1/documents/EWRA2017_A_103184_UTH_NTUA.pdf (3124 KB)

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

    1. #Ruchinskaya, T., and K. Lalenis, Building urban resilience of public places in Volos, Greece. Perspectives and possibilities of related contribution of blockchain technology, Proceedings of IFoU 2018: Reframing Urban Resilience Implementation: Aligning Sustainability and Resilience, Barcelona, doi:10.3390/IFOU2018-05931, 2018.
    2. #Ruchinskaya, T., and K. Lalenis, The effect of public places on community resilience. A case study of the role of social and digital tools in the City of Volos (Greece), in: Smaniotto Costa, C. et al. (eds.): C3Places, Culture & Territory 04, 201-214, doi:10.24140/2020-sct-vol.4-2.3, 2020.

  1. 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.

    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.

    Additional material:

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

    1. da Silva Júnior, J. C. , V. Medeiros, C. Garrozi, A. Montenegro, and G. E. Gonçalves, Random forest techniques for spatial interpolation of evapotranspiration data from Brazilian’s Northeast, Computers and Electronics in Agriculture, 166, 105017, doi:10.1016/j.compag.2019.105017, 2019.

  1. K. Risva, D. Nikolopoulos, A. Efstratiadis, and I. Nalbantis, A simple model for low flow forecasting in Mediterranean streams, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

    Low flows commonly occur in rivers during dry seasons within each year. They often concur with increased water demand which creates numerous water resources management problems. This paper seeks for simple yet efficient tools for low-flow forecasting, which are easy to implement, based on the adoption of an exponential decay model for the flow recession curve. A statistical attribute of flows preceding the start of the dry period is used as the starting flow, as for example the minimum flow of early April. On the other hand, the decay rate (recession parameter) is assumed as a linear function of the starting flow. The two parameters of that function are time-invariant, and they are optimised over a reference time series representing the low flow component of the observed hydrographs. The methodology is tested in the basins of Achelous, Greece, Xeros and Peristerona, Cyprus, and Salso, Italy. Raw data are filtered by simple signal processing techniques which remove the effect of flood events occurring in dry periods, thus allowing the preservation of the decaying form of the flow recession curve. Results indicate that satisfactory low flow forecasts are possible for Mediterranean basins of different hydrological behaviour.

    Additional material:

  1. T. Vergou, A. Efstratiadis, and D. Dermatas, Water balance model for evaluation of landfill malfunction due to leakage, Proceedings of ISWA 2016 World Congress, Novi Sad, Ιnternational Solid Waste Association, 2016.

    We present a conceptual model that aims to represent the main hydrological processes in a landfill, taking into account its dynamic evolution. The model is employed in a real-world case study, involving the operation of the landfill of Mavrorachi, Northern Greece, for a one-year period. The landfill exhibits several environmental problems due to significant leakage production, which often exceeds the capacity of treatment works, as well as lateral outflows. By simulating the entire water cycle over the landfill basin, we attempt to recognize the major sources of failure and propose management measures to mitigate the current environmental impacts.

  1. S. Mihas, A. Efstratiadis, K. Nikolaou, and N. Mamassis, Drought and water scarcity management plan for the Peloponnese river basin districts, 12th International Conference “Protection & Restoration of the Environment”, Skiathos, Dept. of Civil Engineering and Dept. of Planning & Regional Development, Univ. Thessaly, Stevens Instute of Technology, 2014.

    The drought and water scarcity management plan was drafted for the Peloponnese River Basin Districts as outlined by the implementation of the Water Framework Directive 2000/60/EC in Greece by the Special Secretariat of Water (Ministry of Environment Energy & Climate Change). The evaluation of hydrological droughts was mainly based on precipitation data, which was used to evaluate the SPI index at several time scales (from 3-month to 5-year). Moreover, the drought hazard was evaluated, taking into consideration the demands and the water resources availability, at various spatial scales. For this aim, we developed an innovative methodology, based on the estimation of a temporally varying water exploitation index, as generalization of the typical WEI. The possibilities of predicting drought events, by using simple statistical models and evaluating the probabilities of transition from the current carrying water condition to the next are also examined. Additionally, an operational plan for drought prediction is elaborated, on the basis of representative hydrologic data that is retrieved twice a year i.e. at the end of the first trimester and semester of the hydrological year. Finally, we provide guidance for the operational implementation of the above methodology by the competent authorities and its link to specific management measures depending on the classification of each drought event, at the alert scale.

    Full text: http://www.itia.ntua.gr/en/getfile/1458/1/documents/A216_paper_hSRt2DZ.pdf (1188 KB)

    Additional material:

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

    1. Apostolaki, S., E. Akinsete, S. Tsani, P. Koundouri, N. Pittis, and E. Levantis, Assessing the effectiveness of the WFD as a tool to address different levels of water scarcity based on two case studies of the Mediterranean region, Water, 11, 840, doi:10.3390/w11040840, 2019.

  1. 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.

    The drawbacks of conventional energy sources including their negative environmental impacts emphasize the need to integrate renewable energy sources into the energy balance. However, the renewable sources strongly depend on time varying and uncertain hydrometeorological processes, including wind speed, sunshine duration and solar radiation. To study the design and management of hybrid energy systems we investigate the stochastic properties of these natural processes, including possible long-term persistence. We use wind speed and sunshine duration time series retrieved from a European database of daily records and we estimate representative values of the Hurst coefficient for both variables. We conduct simultaneous generation of synthetic time series of wind speed and sunshine duration, on yearly, monthly and daily scale. To this we use the Castalia software system which performs multivariate stochastic simulation. Using these time series as input, we perform stochastic simulation of an autonomous hypothetical hybrid renewable energy system and optimize its performance using genetic algorithms. For the system design we optimize the sizing of the system in order to satisfy the energy demand with high reliability also minimizing the cost. While the simulation scale is the daily, a simple method allows utilizing the sub-daily distribution of the produced wind power. Various scenarios are assumed in order to examine the influence of input parameters, such as the Hurst coefficient, and design parameters such as the photovoltaic panel angle.

    Full text: http://www.itia.ntua.gr/en/getfile/1408/1/documents/2013Fragmata_Hybrid.pdf (549 KB)

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.1.3787.0327

    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, 21(4), 495- 504, doi:10.30955/gnj.002978, 2019.

  1. 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.

    We describe a holistic approach for the management of complex hydrosystems whose primary aim is hydropower production. This is based on the parameterisation-simulation-optimization methodological framework, which is implemented within the Decision Support System “Hydronomeas”. After the analysis of the developed methodology and simulation and optimization tools, a number of applications in the Acheloos-Thessaly hydrosystem are shown. The results include the assessment of the hydropower potential of the system as well as its corresponding benefit, thus being of particular interest to long-term energy planning.

    Full text: http://www.itia.ntua.gr/en/getfile/1407/2/documents/2013Fragmata_Acheloos.pdf (1801 KB)

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.1.1952.0244

  1. 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.

    Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk –a key issue of the 2007/60/EC Directive– it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its functionality has been implemented as open-source software for use in a wide range of applications in the field of water resources monitoring and management, such as the demonstration case study outlined in this work.

    Additional material:

    See also: http://dx.doi.org/10.1117/12.2028621

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

    1. Damte, F., B. G. Mariam, M. Teshome, T. K. Lohani, G. Dhiman, and M. Shabaz, Computing the sediment and ensuing its erosive activities using HEC-RAS to surmise the flooding in Kulfo River in Southern Ethiopia, World Journal of Engineering, doi:10.1108/WJE-01-2021-0002, 2021.

  1. 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.

    The article, apart from the introduction (section 1), is organized as follows: In section 2, we review the Penman-Monteith method and its simplifications, which estimate evapotranspiration on the basis of temperature and radiation data. In section 3 we present the new parametric model, which compromises the requirements for parsimony and consistency. In section 4, we calibrate the model at the point scale, using historical meteorological data, and evaluate it against other empirical approaches. In addition, we investigate the geographical distribution of its parameters over Greece. Finally, in section 5 we summarize the outcomes of our research and discuss next research steps.

    Full text: http://www.itia.ntua.gr/en/getfile/1284/1/documents/2013InTech_ParametricModelPET.pdf (819 KB)

    See also: http://dx.doi.org/10.5772/52927

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

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

    1. Samaras, D. A., A. Reif, and K. Theodoropoulos, Evaluation of radiation-based reference evapotranspiration models under different Mediterranean climates in Central Greece, Water Resources Management, 28 (1), 207-225, 2014.
    2. Tabari, H., P. H. Talaee, P. Willems, and C. Martinez, Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations, Hydrological Sciences Journal, 61(3), 610-619, doi:10.1080/02626667.2014.947293, 2016.
    3. Jaber, H. S., S. Mansor, B. Pradhan, and N. Ahmad, Evaluation of SEBAL model for evapotranspiration mapping in Iraq using remote sensing and GIS, International Journal of Applied Engineering Research, 11(6), 3950-3955, 2016.
    4. Kumar, D., J. Adamowski, R. Suresh, and B. Ozga-Zielinski, Estimating evapotranspiration using an extreme learning machine model: case study in North Bihar, India, Journal of Irrigation and Drainage Engineering, 04016032, doi:10.1061/(ASCE)IR.1943-4774.0001044, 2016.
    5. Djaman, K., D. Rudnick, V. C. Mel, and D. Mutiibwa, Evaluation of Valiantzas’ simplified forms of the FAO-56 Penman-Monteith reference evapotranspiration model in a humid climate, Journal of Irrigation and Drainage Engineering, doi:10.1061/(ASCE)IR.1943-4774.0001191, 2017.
    6. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.
    7. Norström, E., C. Katrantsiotis, R. H. Smittenberg, and K. Kouli, Chemotaxonomy in some Mediterranean plants and implications for fossil biomarker records, Geochimica et Cosmochimica Acta, 219, 96-110, doi:10.1016/j.gca.2017.09.029, 2017.
    8. 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, doi:10.1007/s40030-017-0241-z, 2017.
    9. Mentzafou, A., S. Wagner, and E. Dimitriou, Historical trends and the long-term changes of the hydrological cycle components in a Mediterranean river basin, Science of The Total Environment, 636, 558-568, doi:10.1016/j.scitotenv.2018.04.298, 2018.
    10. Norström, E., C. Katrantsiotis, M. Finné, J. Risberg, R. H. Smittenberg, S. Bjursäter, Biomarker hydrogen isotope composition (δD) as proxy for Holocene hydroclimatic change and seismic activity in SW Peloponnese, Greece, Journal of Quaternary Science, 33(5), 563-574, doi:10.1002/jqs.3036, 2018.
    11. Mengistu, B., and G. Amente, Three methods of estimating the power of maximum temperature in TM–ET estimation equation, SN Applied Sciences, 1:1403, doi:10.1007/s42452-019-1461-9, 2019.
    12. Mengistu, B., and G. Amente, Reformulating and testing Temesgen-Melesse's temperature-based evapotranspiration estimation method, Heliyon, 6(1), e02954, doi:10.1016/j.heliyon.2019.e02954, 2020.
    13. Středová, H., J. Klimešová, T. Středa, and P. Fukalová, Could the directly measured data of transpiration be replaced by model outputs?, Contributions to Geophysics and Geodesy, 50(1), 33-47, doi:10.31577/congeo.2020.50.1.2, 2020.
    14. Jaiswal, S., and M. S. Ballal, Fuzzy inference based irrigation controller for agricultural demand side management, Computers and Electronics in Agriculture, 175, 105537, doi:10.1016/j.compag.2020.105537, 2020.
    15. Rezaei, M., H. Ghasemieh, and K. Abdollahi, Simplified version of the METRIC model for estimation of actual evapotranspiration, International Journal of Remote Sensing, 42(14), 5568-5599, doi:10.1080/01431161.2021.1925991, 2021.
    16. 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.

  1. 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.

    The flood regime in Greece is investigated, from the early past to modern years. Large-scale floods, mainly due to deglaciation processes (also known as palaeofloods), together with earthquakes and volcanoes, are the major mechanisms that formed the current diverse Greek terrain. The influence of these impressive phenomena is reflected in some ancient myths, also reflecting earlier efforts of flood control and management. The struggle of humans against the destructive power of floods is further testified by several structures revealed by archaeological research. In modern times, the dramatic change of the demographic and socio-economic conditions made imperative the construction of large-scale water projects, which in turn resulted in large-scale environmental changes. The consequences of these practices, both positive and negative, are discussed, with regard to the problem of floods in Greece.

    Additional material:

    See also: http://www.routledge.com/books/details/9780203098097/

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

    1. #Kundzewicz, Z. W., Introduction, Changes of Flood Risk in Europe, IAHS-AISH Publication, (SPEC. ISS. 10), (ed. Z. W. Kundzewicz), 1-7, 2012.
    2. Mentzafou, A. and Dimitriou, E.: Flood risk assessment for a heavily modified urban stream, Proc. IAHS, 366, 147-148, 10.5194/piahs-366-147-2015, 2015.
    3. Karagiorgos, K., M. Heiser, T. Thaler, J. Hübl, and S. Fuchs, Micro-sized enterprises: vulnerability to flash floods, Natural Hazards, 84(2), 1091–1107, doi:10.1007/s11069-016-2476-9, 2016.
    4. #Sevastas, S., I. Siarkos, N. Theodossiou, I. Ifadis, and K. Kaffas, Comparing hydrological models built upon open access and/or measured data in a GIS environment, Proceedings of the Sixth International Conference on Environmental Management, Engineering, Planning & Economics, 377-386, Thessaloniki, 2017.
    5. Veal, R. J., The politics and economics of ancient forests: Timber and fuel as levers of Greco-Roman control, Economie et inégalité: Ressources, échanges et pouvoir dans l'Antiquité classique, 63(8), 317-367, doi :10.17863/CAM.13218, 2017.
    6. Diakakis, M., G. Deligiannakis, K. Katsetsiadou, Z. Antoniadis, and M. Melaki, Mapping and classification of direct flood impacts in the complex conditions of an urban environment: The case study of the 2014 flood in Athens, Greece, Urban Water Journal, 14(10), 1065-1074, doi:10.1080/1573062X.2017.1363247, 2017.
    7. #Karatzas, S., D. Chondrogiani, and P. Saranti, Intelligent sustainable urban drainage systems (I-SUDS): A framework for flood mitigation and rainwater reuse, Fifth International Conference on Small and Descentralised Water and Wastewater Treatment Plants, Thessaloniki, 2018.
    8. #Angelakis, A. N., G. Antoniou, K. Voudouris, N. Kazakis, and N. Dalezios, History of floods in Greece: Causes and measures for protection, 5th IWA International Symposium on Water and Wastewater Technologies in Ancient Civilizations: Evolution of Technologies from Prehistory to Modern Times, Dead Sea, Jordan, 2019.
    9. 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, 101, 833–852, doi:10.1007/s11069-020-03898-w, 2020.
    10. Koukouvelas, I. K., D. J. W. Piper, D. Katsonopoulou, N. Kontopoulos, S. Verroios, K. Nikolakopoulos, and V. Zygouri, Earthquake-triggered landslides and mudflows: Was this the wave that engulfed Ancient Helike? The Holocene, 30(12), 1653-1668, doi:10.1177/0959683620950389, 2020.
    11. Mazza, A., Waterscape and floods management of Greek Selinus: The Cottone River Valley, Open Archaeology, 7(1), 1066-1090, doi:10.1515/opar-2020-0172, 2021.

  1. C. Makropoulos, E. Safiolea, A. Efstratiadis, E. Oikonomidou, V. Kaffes, C. Papathanasiou, and M. Mimikou, Multi-reservoir management with Open-MI, Proceedings of the 11th International Conference on Environmental Science and Technology, Chania, A, 788–795, Department of Environmental Studies, University of the Aegean, 2009.

    The paper applies advanced integrated modeling techniques supported by the Open Modeling Interface (OpenMI) standard to optimize water resources allocation for a rapidly growing rural area in Greece. Water uses in a rural basin are significantly affected by urban growth, changes in agricultural practices and industrial needs. This results in a complex water system, whose optimal configuration requires the combination of structural and non-structural approaches. Furthermore, the reliable operation of the water system may be placed under significant stress due to increasing trends of extreme events associated with potential climatic changes which affect freshwater availability. To evaluate and improve the system’s operation, a series of specialized models need to be linked and exchange data at runtime. The approach presented in this paper, used OpenMI (an open source, royalty free standard) to facilitate the direct, timestep-by-timestep, communication of models from different providers, written in different coding languages, with different spatial and temporal resolutions. The models were “migrated” to OpenMI and were run simultaneously, linked (exchanging data) at nodes specified by the modeler. The resulting integrated modeling system is tested in the Thessaly Water District, Greece, where growing water demand has often become an issue of conflict between stakeholders. As an example of the type of problems typically faced in the region, a system of two reservoirs receiving flows from different subbassins is designed to satisfy the water demand of the study area. The principal reservoir, the Smokovo reservoir, is a real reservoir, currently in operation, situated on the confluence of two streams, tributaries of the Pinios river. Downstream of Smokovo reservoir, the river flow has to satisfy a series of needs such as ecological flows, increasing irrigation needs, increasing potable water demand of the local municipalities, and production of electricity. The second reservoir introduced in this study is the potential rehabilitation of the Lake Xyniada, as a means to improve the overall resilience of the water system to extreme events and possibly decrease the costs (ecological-economic) of water consumption in the area. The integrated modeling system comprises of three OpenMI-compliant model components: a reservoir model (RMM), a hydraulic model with supporting rainfall-runoff modules (MIKE-11) and a multi-reservoir operational rule component. The models were set-up, calibrated, and linked to exchange data at runtime using data provided by the Public Power Corporation and the Ministry of Environment. The modeling system was run under different operating rules to assess the reliability of the combined reservoir system and compare it with the one-reservoir existing solution against different stakeholder objectives. The paper suggests indicative solutions from the preliminary analysis and concludes with the identification of key future challenges and ideas for further development.

    Full text: http://www.itia.ntua.gr/en/getfile/932/1/documents/openMI_chania.pdf (451 KB)

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

    1. Fotopoulos, F., C. Makropoulos C., and M.A Mimikou, Flood forecasting in transboundary catchments using the Open Modeling Interface, Environmental Modelling and Software, 25(12), 1640-1649, 2010.
    2. #Moe, S. J., L. J. Barkved, M. Blind, C.. Makropoulos, M. Vurro, S. Ekstrand, J. Rocha, M. Mimikou, and M. J. Ulstein, How can climate change be incorporated in river basin management plans under the WFD? Report from the EurAqua Conference 2008, 27 p., Norwegian Institute for Water Research, 2010.

  1. 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.

    Most complex hydrological modelling schemes, when calibrated on a single observed response (e.g. river flow at a point), provide poor predictive capability, due to the fact that the rest of variables of basin response remain practically uncontrolled. Current advances in modelling point out that it is essential to take into account multiple fitting criteria, which correspond to different observed responses or to different aspects of the same response. This can be achieved through multiobjective calibration tools, thus providing a set of solutions rather than a single global optimum. Besides, actual multiobjective optimization methods are rather inefficient, when real-world problems with many criteria and many control variables are involved. In hydrological applications there are some additional issues, due to uncertainties related to the representation of complex processes and the observation errors. The multiobjective evolutionary annealing-simplex (MEAS) method implements an innovative scheme, particularly developed for the optimization of such problems. Its features and capabilities are illustrated by solving a challenging parameter estimation problem, dealing with hydrological modelling and water resources management in a karstic basin in Greece.

    See also: http://dx.doi.org/10.1007/978-3-540-79881-1_19

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

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

    1. #Solomatine, D. L.M. See and R.J. Abrahart, Data-driven modelling: concepts, approaches and experiences, Practical hydroinformatics , ed. by R.J. Abrahart, L. M. See, and D. P. Solomatine, 33-47, Springer, doi:10.1007/978-3-540-79881-1_2, 2008.
    2. Pollacco, J. A. P., and B. P. Mohanty, Uncertainties of water fluxes in SVAT models: inverting surface soil moisture and evapotranspiration retrieved from remote sensing, Vadose Zone Journal, 11(3), vzj2011.0167, 2012.
    3. Dumedah, G., Formulation of the evolutionary-based data assimilation and its implementation in hydrological forecasting, Water Resources Management, 26(13), 3853-3870, 2012.
    4. Dumedah, G., and P. Coulibaly, Evaluating forecasting performance for data assimilation methods: the Ensemble Kalman Filter, the Particle Filter, and the Evolutionary-based assimilation, Advances in Water Resources, 60, 47-63, 2013.
    5. Gharari, S., M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije, Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrology and Earth System Sciences, 18, 4839-4859, doi:10.5194/hess-18-4839-2014, 2014.
    6. Ho, V. H., I. Kougias, and J. H. Kim, Reservoir operation using hybrid optimization algorithms, Global Nest Journal, 17(1), 103-117, 2015.
    7. Tigkas, D., V. Christelis, and G. Tsakiris, Comparative study of evolutionary algorithms for the automatic calibration of the Medbasin-D conceptual hydrological model, Environmental Processes, 3(3), 629–644, doi:10.1007/s40710-016-0147-1, 2016.
    8. Laura, R., L. L. Matthieu, G. Federico, L. M. Nicolas, H. Frédéric, M. Céline, and R. Pierre, Impact of mesoscale spatial variability of climatic inputs and parameters on the hydrological response, Journal of Hydrology, 553, 13-25, doi:10.1016/j.jhydrol.2017.07.037, 2017.
    9. Naik, P., S. Aramideh, and A. M. Ardekani, History matching of surfactant-polymer flooding using polynomial chaos expansion, Journal of Petroleum Science and Engineering, 173, 1438-1452, doi:10.1016/j.petrol.2018.09.089, 2019.
    10. Kwakye, S. O., and A. Bárdossy, Hydrological modelling in data-scarce catchments: Black Volta basin in West Africa, SN Applied Sciences, 2, 628, doi:10.1007/s42452-020-2454-4, 2020.
    11. Sun, R., F. Hernández, X. Liang, and H. Yuan, A calibration framework for high-resolution hydrological models using a multiresolution and heterogeneous strategy, 2020.
    12. Monteil, C., F. Zaoui, N. Le Moine, and F. Hendrickx, Multi-objective calibration by combination of stochastic and gradient-like parameter generation rules – the caRamel algorithm, Hydrology and Earth System Sciences, 24, 3189-3209, 10.5194/hess-24-3189-2020, 2020.
    13. Dubois, E., M. Larocque, S. Gagné, and G. Meyzonnat, Simulation of long-term spatiotemporal variations in regional-scale groundwater recharge: Contributions of a water budget approach in southern Quebec, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2021-71, 2021.
    14. #Dubois, E., M. Larocque, S. Gagné, and G. Meyzonnat, Hydrobudget User Guide – Version 1.0, Université du Québec à Montréal, Montréal, Québec, Canada, 2021.

  1. 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.

    The Plastiras dam was constructed in the late 1950s mainly for electric power production, but it has also partially covered irrigation needs and water supply of the plain of Thessaly. Later, the site has been designated as an environment conservation zone because of ecological and landscape values, while tourist activities have been developed around the reservoir. Irrigation of agricultural land, hydroelectric production, drinkable water supply, tourism, lake water quality and scenery conservation have evidently been conflicting targets for many years. Good management would require a multi-criteria decision making. Historical data show that the irregular water release has resulted in a great annual fluctuation of the reservoir water level. This situation could be improved by a rational management of abstractions. Apparently, higher release leads simultaneously to more power production and to irrigation of a larger agricultural land. Moreover, demands for electricity and for irrigation are partially competing to each other, due to different optimal time schedules of releases. On the other hand, higher water release leads to lower water level in the reservoir and, therefore, it decreases the beauty of the scenery and deteriorates the trophic state of the lake. Such degradation affects the tourist potential as well as the quality of drinking water supplied by the reservoir. A multi-criteria approach uses different scenarios for the minimum permissible water level of the reservoir, if a constant annual release is applied. The minimum level concept is a simple and functional tool, because it is easily understood by people, certified and incorporated into regulations. The quantity of water that would be yearly available is a function of the minimum level allowed. The water quality depends upon the trophic state of the lake, mainly the concentration of chlorophyll-a, which determines the state of eutrophication and is estimated by water quality simulation models, taking into account pollutant loads such as nitrogen and phosphorus. The value of the landscape is much depending on the water level of the lake, because for lower levels a dead-zone appears between the surface of the water and the surrounding vegetation. When this dead zone is large, it seems lifeless and the lake appears partially empty. Quantification of this visual effect is not easy, but it is possible to establish a correspondence between the aesthetic assessment of the scenery and the minimum allowed reservoir level. Using results from hydrological analysis, water quality models and landscape evaluation, it seems possible to construct a multi-criterion table with different criteria described against alternatives and with a plot of three relative indices against the minimum level allowed. However, decision making has to take into account the fact that comparison or merging of indices corresponding to different criteria analysis encompasses a degree of arbitrariness. More objective decisions would be possible if different benefits and costs were measured in a common unit. Moreover, management will be sensitive to different social pressures.

    Related works:

    • [38] Posterior more complete version.

    Full text: http://www.itia.ntua.gr/en/getfile/682/1/documents/2005CestRhodesPlastiras.pdf (141 KB)

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

    1. Stamou, A.I., K. Hadjibiros, A. Andreadakis and A. Katsiri, Establishing minimum water level for Plastiras reservoir (Greece) combining water quality modelling with landscape aesthetics, Environmental Modeling and Assessment, 12(3), 157-170, 2007.
    2. #Sargentis G. F., V. Symeonidis, and N. Symeonidis, Rules and methods for the development of a prototype landscape (Almyro) in north Evia by the creation of a thematic park, Proceedings of the 12th International Conference on Environmental Science and Technology (CEST2011), Rhodes, Greece, 2011.

  1. 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.

    Decision support systems (DSS), in combination with human judgment and experience, may guide to rational decisions in a variety of ill-structured technological problems. Optimal management of water recourse systems constitutes a typical field for application of DSS. The complexity of the water resource management raises the need for a holistic approach, based on systems theory and making use of advanced mathematical techniques. The paper presents the experience gained in developing of DSS for the management of large-scale hydrosystems in Greece. Specifically, it describes the route to an integrated methodological framework, comprising innovative models for stochastic analysis, simulation and optimisation. This framework, which is progressively improved and evolved, has been recently implemented operationally for the support of the supervision and management of the exceptionally complex water supply system of Athens. In the near future, the generalisation and enhancement of the mathematical models and computer tools is scheduled, in order to make a comprehensive tool for the sustainable management of hydrosystems of a wide range of scales.

    Full text:

  1. 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.

    An attempt is made to integrate groundwater models within a decision support system (DSS) called Hydronomeas, which is designed to assist large multi-reservoir system (MRS) management. This will help managing conjunctive use schemes. The DSS is currently used for the water supply of Athens, Greece. The simulated system is the Boeoticos Kephisos River Basin and its underlying karst. The karst supplies irrigation water locally as well as drinking water to Athens. Furthermore, the basin's surface outflows account for most of the inflow into Lake Yliki, one of the three main reservoirs of the Athens MRS. Three models of different levels of complexity are tested. The first model is a multi-cell model that simulates surface flows within the basin coupled to subsurface flows. The second model is a conceptually-based lumped model while the third model is a pre-existing distributed groundwater model based on the MODFLOW package. Tests with various management scenarios allow drawing conclusions regarding model efficiency and suitability for use within a DSS.

    Remarks:

    Full text:

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

    1. #Dentinho, T.P., R. Minciardi, M. Robba, R. Sacile & V. Silva, Impacts of agriculture and dairy farming on groundwater quality: an optimization problem. In: Voinov, A. et al. (eds.), Proceedings of the iEMSs 3rd Biennial Meeting, Burlington, USA, 2006.
    2. #Giupponi, C., Sustainable Management of Water Resources: An Integrated Approach, 361 pages, Edward Elgar Publishing (ISBN 1845427459), 2006.
    3. #Barlebo, H.C. (ed.), State-of-the-art report with users’ requirements for new IWRM tools, NeWater, www.newater.info, 2006.
    4. #Dentinho, T. et al, The architecture of a decision support system (DSS) for groundwater quality preservation in Terceira Island (Azores), Integrated Water Management: Practical Experiences and Case Studies, P. Meire et al. (eds.), Springer, 2007.
    5. #Lowry, T. S., S. A. Pierce, V. C. Tidwell, and W. O. Cain, Merging spatially variant physical process models under an optimized systems dynamics framework, Technical Report, Sandia National Laboratories, 67 p., 2007.
    6. Bandani, E. and M. A. Moghadam, Application of groundwater mathematical model for assessing the effects of Galoogah dam on the Shooro aquifer, Iran, European Journal of Scientific Research, 54 (4), 499-511, 2011.
    7. Golchin, I., M. A. Moghaddam and N. Asadi, Numerical study of groundwater flow in Iranshahr plain aquifer, Iran, Middle-East Journal of Scientific Research, 8 (5), 975-983, 2011.
    8. #Minciardi, R., M. Robba, and R. Sacile, Environmental Decision Support Systems for soil pollution control and prevention, Soil Remediation, L. Aachen and P. Eichmann (eds.), Chapter 2, 45-85, Nova Science Publishers, 2011.
    9. #Pierce, S. a., J. M. Sharp Jr, and D. J. Eaton, Decision support systems and processes for groundwater, Integrated Groundwater Management: Concepts, Approaches and Challenges, A. J. Jakeman, O. Barreteau, R. J. Hunt, J.-D. Rinaudo, A. Ross (editors), 639-665, Springer, doi:10.1007/978-3-319-23576-9_25, 2016.

  1. 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.

    The problems associated with establishing a "safe" minimum level for a reservoir serving multiple and conflicting purposes (hydroelectric power generation, water supply, irrigation and recreation) are discussed. A comprehensive approach of the problem considers three different criteria. The first criterion is water quantity. Available long-term reservoir inflow data are analyzed to establish 'sustainable" water inputs in relation to demands that have to be satisfied. The second criterion is ecology and landscape and considers how fluctuations of the reservoir level affect the lake banks vegetation. It discusses the implications to aesthetic, touristic and beneficial uses. The third criterion is water quality and considers how the fluctuations in lake volume affect the chemical and biological status of the lake. For this purpose a one-dimensional eutrophication model was used. The minimum water level is established from the synthesis of the above, using a multi-criteria analysis.

    Remarks:

    Full text: http://www.itia.ntua.gr/en/getfile/546/1/documents/2002TsehiaPlastiras.pdf (241 KB)

    See also: http://dx.doi.org/10.13140/RG.2.1.4872.4723

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

    1. #Spanoudaki, K., and A. Stamou, The prospects of developing integrated ecological models for the needs of the WFD 2000/60, Proceedings of the International Conference for the Restoration and Protection of the Environment V, Mykonos, 2004.
    2. #Stamou, A. I., K. Nanou-Giannarou, and K. Spanoudaki, Best modeling practices in the application of the Directive 2000/60 in Greece, Proc. 3rd IASME/WSEAS Int. Conf. on Energy, Environment, Ecosystems and Sustainable Development, 388-397, 2007.
    3. Stamou, A.I., K. Hadjibiros, A. Andreadakis, and A. Katsiri, Establishing minimum water level for Plastiras reservoir (Greece) combining water quality modelling with landscape aesthetics, Environmental Modeling and Assessment, 12(3), 157-170, 2007.

  1. 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.

    The evolutionary annealing-simplex algorithm is a probabilistic heuristic global optimisation technique that joins ideas from different methodological approaches, enhancing them with some original elements. The main concept is based on a controlled random search scheme, where a generalised downhill simplex methodology is coupled with a simulated annealing procedure. The algorithm combines the robustness of simulated annealing in rugged problems, with the efficiency of hill-climbing methods in simple search spaces. The following-up procedure is based on a simplex-searching scheme. The simplex is reformulated at each generation going either downhill or uphill, according to a probabilistic criterion. In the first case, it moves towards the direction of a candidate local minimum via a generalised Nelder-Mead strategy. In the second case, it expands itself along the uphill direction, in order to escape from the current local minimum. In all possible movements, a combination of deterministic as well as stochastic transition rules is applied. The evolutionary annealing-simplex algorithm was first examined in a variety of typical benchmark functions and then it was applied in two global optimisation problems taken from water resources engineering, the calibration of a hydrological model and the optimisation of a multiple reservoir systems' operation. The algorithm has been proved very reliable in locating the global optimum, requiring reasonable computational effort.

    Remarks:

    Web page of optimization algorithms: http://itia.ntua.gr/en/softinfo/29/

    Related works:

    • [225] Development of the method within the master thesis of the first author.
    • [224] Improved version for single- and multiobjective optimization problems within the PhD thesis of the first author.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.1.1038.6162

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

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

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    7. Martins, J., P. Tomás, and L. Sousa, Neural code metrics: Analysis and application to the assessment of neural models, Neurocomputing, 72(10-12), 2337-2350, 2009.
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    16. Kourakos, G., and A. Mantoglou, Development of a multi-objective optimization algorithm using surrogate models for coastal aquifer management, Journal of Hydrology, 479, 13-23, 2013.
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    20. Tigkas, D., V. Christelis, and G. Tsakiris, Comparative study of evolutionary algorithms for the automatic calibration of the Medbasin-D conceptual hydrological model, Environmental Processes, doi:10.1007/s40710-016-0147-1, 2016.
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  1. 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.

    The development process of scenarios used within a decision support system for water resources management is discussed, based on the case of the Athens water resource system. In particular, the schematisation process of the real world hydrosystem into a model representation is analysed, as well as further information consisting a scenario, including hydrological and water demand conditions, operational constraints, targets and their priorities, management objectives, and methodological assumptions used in decision making, is discussed

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.1.3135.7684

  1. 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.

    A decision support tool is developed for the management of water resources, focusing on multipurpose reservoir systems. This software tool has been designed in such a way that it can be suitable to hydrosystems with multiple and very often contradictory water uses and operating goals, calculating complex multi-reservoir systems as a whole. The mathematical framework is based on the original scheme parameterization-simulation-optimization. The main idea consists of a parametric formulation of the operating rules for reservoirs and other projects (i.e. hydropower plants). This methodology enables the decrease of the decision variables, making feasible the location of the optimal management policy, which maximizes the system yield and the overall operational benefit and minimizes the risk for the management decisions. The program was developed using advanced software engineering techniques. As proved two detailed case studies, it is flexible enough and thus suitable for use to a wide range of applications, so it can be helpful to water and power supply companies and related authorities.

    Related works:

    • [43] Posterior more complete version.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.1.3528.9848

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

    1. #Xenos, D., C. Karopoulos and E. Parlis, Modern confrontation of the management of Athens' water supply system, Proc. 7th Conference on Environmental Science and Technology, Syros, Greece, 952-958, 2001.
    2. #Zeitoun, D. G., and A. J. Mellout, Decision support systems based on automatic water balance computation for groundwater management planning – The case of Israel’s coastal aquifer, Geoinformatics for Natural Resource Management, Joshi, P. K., P. Pani, S. N. Mohapartra, and T. P. Singh (eds.), Ch. 7, 634 pp., Nova Science Publishers Inc., New York, 2009.
    3. Stamou, A.-T., and P. Rutschmann, Towards the optimization of water resource use in the Upper Blue Nile river basin, European Water, 60, 61-66, 2017.

  1. 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.

    Optimisation of a multiple-reservoir system becomes increasingly complex when conflicting water uses exist, such as water supply, irrigation, hydroelectric power generation etc. Hydronomeas is a software tool, suitable for simulating and conducting a search for the optimum water resources management policy of a multi-purpose hydrosystem. The mathematical model is based on recent introduction and theoretical development of parametric rules for operation of multiple-reservoir systems. Software implementation was such performed that the model can be easily applied to a wide range of hydrosystems and that representation will be as realistic as possible, incorporating all natural, operational, environmental and other restrictions. Hydronomeas consists of several subsystems, including operational simulation, optimisation and visualisation. The first two cope with goals concerning both consumptive and energy-oriented water uses. Hydronomeas has been applied on the hydrosystem comprising all existing and under construction projects of the Acheloos river, its planned diversion and the related projects in Thessalia.

    Related works:

    • [67] Μεταγενέστερη και πληρέστερη εργασία που αναφέρεται στην έκδοση 2 του λογισμικού, η οποία βασίζεται σε πιο προχωρημένη μεθοδολογία βελτιστοποίησης.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.1.4053.2724

Conference publications and presentations with evaluation of abstract

  1. K.-K. Drakaki, G.-K. Sakki, I. Tsoukalas, P. Kossieris, and A. Efstratiadis, Setting the problem of energy production forecasting for small hydropower plants in the Target Model era, EGU General Assembly 2021, online, EGU21-3168, doi:10.5194/egusphere-egu21-3168, European Geosciences Union, 2021.

    The highly-competitive electricity market over EU and the challenges induced by the so-called “Target Model”, introduce significant uncertainties to day-ahead trades involving renewable energy, since most of these sources are driven by non-controllable weather processes (wind, solar, hydro). Here, we explore the case of small hydropower plants that have negligible storage capacity, and thus their production is just a nonlinear transformation of inflows. We discuss different forecasting approaches, which take advantage of alternative sources of information, depending on data availability. Among others, we investigate whether is it preferable to employ day-ahead predictions based on past energy production data per se, or use these data in order to retrieve past inflows, which allows for introducing hydrological knowledge within predictions. Overall objective is to move beyond the standard, yet risky, point forecasting methods, providing a single expected value of hydropower production, thus quantifying the overall uncertainty of each forecasting method. Power forecasts are evaluated in terms of economic efficiency, accounting for the impacts of over- and under-estimations in the real-world electricity market.

    Full text:

  1. V. Kourakos, A. Efstratiadis, and I. Tsoukalas, Can hydrological model identifiability be improved? Stress-testing the concept of stochastic calibration, EGU General Assembly 2021, online, EGU21-11704, doi:10.5194/egusphere-egu21-11704, European Geosciences Union, 2021.

    Hydrological calibrations with historical data are often deemed insufficient for deducing safe estimations about a model structure that imitates, as closely as possible, the anticipated catchment behaviour. Ιn order to address this issue, we investigate a promising strategy, using as drivers synthetic time series, which preserve the probabilistic properties and dependence structure of the observed data. The key idea is calibrating a model on the basis of synthetic rainfall-runoff data, and validating against the full observed data sample. To this aim, we employed a proof of concept on few representative catchments, by testing several lumped conceptual hydrological models with alternative parameterizations and across two time-scales, monthly and daily. Next, we attempted to reinforce the validity of the recommended methodology by employing monthly stochastic calibrations in 100 MOPEX catchments. As before, a number of different hydrological models were used, for the purpose of proving that calibration with stochastic inputs is independent of the chosen model. The results highlight that in most cases the new approach leads to stronger parameter identifiability and stable predictive capacity across different temporal windows, since the model is trained over much extended hydroclimatic conditions.

    Full text:

  1. K. Risva, G.-K. Sakki, A. Efstratiadis, and N. Mamassis, Hydropower potential assessment made easy via the unit geo-hydro-energy index, EGU General Assembly 2021, online, EGU21-4462, doi:10.5194/egusphere-egu21-4462, European Geosciences Union, 2021.

    The design of hydropower works typically follows a top-down approach, starting from a macroscopic screening of the broader region of interest, to select promising clusters for hydroelectric exploitation, based on easily retrievable information. Manual approaches are very laborious and may fail to detect sites of significant hydropower potential. In order to facilitate this kind of studies, we provide a novel geomorphological approach to assess the hydropower potential across river networks. The method is based on the discretization of the stream network into segments of equal length, thus providing a background layer of head differences between potential abstraction and power production sites. Next, at each abstraction point, we estimate the so-called unit geo-hydro-energy index (UGHE), which is a key concept of our approach. UGHE is defined as the ratio of annual potential energy divided by the upstream catchment area, the head difference, and the unit annual runoff of the catchment, which is set equal to 1000 mm. The method is further expanded, to estimate the actual hydropotential, if spatially distributed runoff data are available. All analyses are automatized by taking advantage of the high-level interpreted programming language Python and the open-source QGIS tool. The proposed framework is demonstrated at the regional scale, involving the siting of run-of-river hydroelectric works in the Peneios river basin.

    Full text:

  1. G.-K. Sakki, I. Tsoukalas, P. Kossieris, and A. Efstratiadis, A dilemma of small hydropower plants: Design with uncertainty or uncertainty within design?, EGU General Assembly 2021, online, EGU21-2398, doi:10.5194/egusphere-egu21-2398, European Geosciences Union, 2021.

    Small hydropower plants (SHPPs) are subject to multiple uncertainties and complexities, despite their limited scale. These uncertainties are often ignored in the typical engineering practice, which results in risky design. As this type of renewable energy rapidly penetrates the electricity mix, the impacts of their uncertainties, exogenous and endogenous, become critical. In this vein, we develop a stochastic simulation-optimization framework tailored for small hydropower plants. First, we investigate the underlying multicriteria design problem and its peculiarities, in order to determine a best-compromise performance metric that ensures efficient and effective optimizations. Next, we adjust to the optimal design problem a modular uncertainty assessment procedure. This combines statistical and stochastic approaches to quantify the uncertainty of the inflow process per se, the associated input data, the initial selection of efficiency curves for the turbine mixing in the design phase, as well as the drop of efficiency due to aging effects. Overall, we propose a holistic framework for the optimal design of SHPPs, highlighting the added value of considering the stochasticity of input processes and parameters. The novelty of this approach is the transition from the conventional to the uncertainty-aware design; from the unique value to Pareto-optimality, and finally to the reliability of the expected performance, in terms of investment costs, hydropower production, and associated revenues.

    Full text:

  1. 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.

    The storage-reliability-yield (SRY) relationship is a well-established tool for preliminary design of reservoirs fulfilling consumptive water uses, yet rarely employed within hydropower planning studies. Here, we discuss the theoretical basis for representing the trade-offs between reservoir size and expected revenues from hydropower production, under uncertain inflows, by taking advantage of the stochastic simulation-optimization approach. We also demonstrate that under some assumptions, the complex and site-specific problem, mainly induced by the nonlinearity of storage-head-energy conversion, can be significantly simplified and generalized as well. The methodology is tested across varying runoff regimes and under a wide range of potential reservoir geometries, expressed in terms of a generic shape parameter of the head-storage relationship. Based on the outcomes of these analyses we derive empirical expressions that link reliable energy with summary inflow statistics, reservoir capacity and geometry.

    Full text:

  1. M. Nezi, C. Ntigkakis, I. Tsoukalas, and A. Efstratiadis, Multidimensional context for extreme analysis of daily streamflow, rainfall and accumulated rainfall across USA, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-19674, doi:egusphere-egu2020-19674, 2020.

    Statistical analysis of rainfall and runoff extremes plays a crucial role in hydrological design and flood risk management. Usually this analysis is performed separately for the two processes of interest, thus ignoring their dependencies, which appear at multiple temporal scales. Actually, the generation of a flood strongly depends on soil moisture conditions, which in turn depends on past rainfall. Using daily rainfall and runoff data from about 400 catchments in USA, retrieved from the MOPEX repository, we investigate the statistical behavior of the corresponding annual rainfall and streamflow maxima, also accounting for the influence of antecedent soil moisture conditions. The latter are quantified by means of accumulated daily rainfall at various aggregation scales (i.e., from 5 up to 30 days) before each extreme rainfall and streamflow event. Analysis of maxima is employed by fitting the Generalized Extreme Value (GEV) distribution, using the L-moments method for extracting the associated parameters (shape, scale, location). Significant attention is paid for ensuring statistically consistent estimations of the shape parameter, which is empirically adjusted in order to minimize the influence of sample uncertainty. Finally, we seek for the possible correlations among the derived parameter values and hydroclimatic characteristics of the studied basins, and also depict their spatial distribution across USA.

    Full text: http://www.itia.ntua.gr/en/getfile/2029/1/documents/EGU2020-19674-print.pdf (291 KB)

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-19674.html

  1. C. Ntigkakis, M. Nezi, and A. Efstratiadis, Post-extraction of flood hydrographs under limited and heterogeneous information: Case study of Western Attica event, November 2017, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-18262, doi:egusphere-egu2020-18262, 2020.

    In November 2017, a storm event of substantial but unknown local intensity caused a flash flood in Western Attica, Greece, which was responsible for 24 human fatalities and large-scale economical losses. Our focus is to the neighbouring catchment of Sarantapotamos, which has been equipped with an automatic stage recorder that was destroyed during the rising of the flood. Our overall objective is the estimation of the rainfall over the broader area of interest, through a reverse rainfall-runoff modelling approach at this specific catchment. Several sources of information are accounted for in order to reproduce the “observed” flood hydrograph, including photos and videos. We then employ Monte Carlo simulations to evaluate the uncertainty induced from limited and even missing data. Utilising the outcome of these analyses, we provide probabilistic estimations of the modelled rainfall, as well as risk evaluations, by estimating the maximum intensities and associated return periods of the storm event across multiple time scales.

    Full text:

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-18262.html

  1. A. G. Pettas, P. Mavritsakis, I. Tsoukalas, N. Mamassis, and A. Efstratiadis, Empirical metric for uncertainty assessment of wind forecasting models in terms of power production and economic efficiency, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-8018, doi:10.5194/egusphere-egu2020-8018, 2020.

    As made for most of renewable energy sources, wind energy is driven by highly uncertain and thus unpredictable meteorological processes. In the context of wind power scheduling and control, reliable wind predictions across scales is a challenging problem. However, since the generation of wind energy is, in fact, a nonlinear transformation of wind velocity through the power curve of each specific turbine, the errors in meteorological predictions have different impacts on wind power forecasts. It is well-known that for quite a large range of wind velocity values, the wind power production is either zero or constant, thus independent of the individual wind velocity value. This interesting feature allows for ensuring better predictions of the output, i.e. the energy production, with respect to input, i.e. wind velocity. Taking advantage of this, we present a hybrid stochastic framework for multi-step ahead wind velocity predictions and their evaluation by means of power production and economic efficiency. The methodology is tested for different wind regimes and different layouts of wind turbine systems, emphasizing to mixing of different turbine types, which allows for minimizing uncertainties. Finally, we investigate the use of this index in the technical and operational optimization of wind energy systems.

    Full text:

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-8018.html

  1. K. Risva, D. Nikolopoulos, and A. Efstratiadis, Distributed hydrological modelling using spatiotemporally varying velocities, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-13402, doi:10.5194/egusphere-egu2020-13402, 2020.

    We present a distributed hydrological model with minimal calibration requirements, which represents the rainfall-runoff transformation and the flow routing processes. The generation of surface runoff is based on a modified NRCS-CN scheme. Key novelty is the use of representative CN values, which are initially assigned to model cells on the basis of slope, land cover and permeability maps, and adjusted to antecedent soil moisture conditions. For the propagation of runoff to the basin outlet two flow types are considered, i.e. overland flow across the terrain and channel flow along the river network. These are synthesized by employing a novel velocity-based approach, where the assignment of velocities along the river network is based on macroscopic hydraulic information. It also uses the concept of varying time of concentration, which is considered function of the average runoff intensity across the catchment. This configuration is suitable for event-based flood simulation and requires the specification of only two lumped inputs, which are either manually estimated or inferred through calibration. The model can also run in continuous mode, by employing a soil moisture accounting scheme that produces both the surface (overland) runoff and the interflow through the unsaturated zone. The two model configurations are demonstrated in the representation of observed flows across Nedontas river basin at South Peloponnese, Greece.

    Full text: http://www.itia.ntua.gr/en/getfile/2026/1/documents/EGU2020-13402-print.pdf (290 KB)

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-13402.html

  1. E. Manta, R. Ioannidis, G.-F. Sargentis, and A. Efstratiadis, Aesthetic evaluation of wind turbines in stochastic setting: Case study of Tinos island, Greece, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-5484, doi:10.5194/egusphere-egu2020-5484, 2020.

    Wind turbines are large-scale engineering infrastructures that may cause significant social reactions, due to the anticipated aesthetic nuisance. On the other hand, aesthetics is a highly subjective issue, thus any attempt towards its quantification requires accounting for the uncertainty induced from subjectivity. In this work, taking as example the Aegean island of Tinos, Cyclades, Greece, we present a stochastic-based methodology for evalu