Panayiotis Dimitriadis

Civil Engineer, MSc., Dr. Engineer
pandim@itia.ntua.gr
+30-2107722860

Participation in research projects

Participation as Researcher

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

Participation in engineering studies

  1. Study of the management of Kephisos

Published work

Publications in scientific journals

  1. P. Dimitriadis, T. Iliopoulou, G.-F. Sargentis, and D. Koutsoyiannis, Spatial Hurst–Kolmogorov Clustering, Encyclopedia, 1 (4), 1010–1025, doi:10.3390/encyclopedia1040077, 2021.
  2. D. Koutsoyiannis, and P. Dimitriadis, Towards generic simulation for demanding stochastic processes, Sci, 3, 34, doi:10.3390/sci3030034, 2021.
  3. S. Vavoulogiannis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Multiscale temporal irreversibility of streamflow and its stochastic modelling, Hydrology, 8 (2), 63, doi:10.3390/hydrology8020063, 2021.
  4. L. Katikas, P. Dimitriadis, D. Koutsoyiannis, T. Kontos, and P. Kyriakidis, A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series, Applied Energy, 295, 116873, doi:10.1016/j.apenergy.2021.116873, 2021.
  5. P. Dimitriadis, D. Koutsoyiannis, T. Iliopoulou, and P. Papanicolaou, A global-scale investigation of stochastic similarities in marginal distribution and dependence structure of key hydrological-cycle processes, Hydrology, 8 (2), 59, doi:10.3390/hydrology8020059, 2021.
  6. G.-F. Sargentis, T. Iliopoulou, P. Dimitriadis, N. Mamassis, and D. Koutsoyiannis, Stratification: An entropic view of society's structure, World, 2, 153–174, doi:10.3390/world2020011, 2021.
  7. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, A stochastic view of varying styles in art paintings, Heritage, 4, 21, doi:10.3390/heritage4010021, 2021.
  8. G.-F. Sargentis, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Landscape planning of infrastructure through focus points’ clustering analysis. Case study: Plastiras artificial lake (Greece), Infrastructures, 6 (1), 12, doi:10.3390/infrastructures6010012, 2021.
  9. K. Glynis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of daily air temperature extremes from a global ground station network, Stochastic Environmental Research & Risk Assessment, doi:10.1007/s00477-021-02002-3, 2021.
  10. G.-F. Sargentis, T. Iliopoulou, S. Sigourou, P. Dimitriadis, and D. Koutsoyiannis, Evolution of clustering quantified by a stochastic method — Case studies on natural and human social structures, Sustainability, 12 (19), 7972, doi:10.3390/su12197972, 2020.
  11. G.-F. Sargentis, P. Dimitriadis, R. Ioannidis, T. Iliopoulou, E. Frangedaki, and D. Koutsoyiannis, Optimal utilization of water resources for local communities in mainland Greece (case study of Karyes, Peloponnese), Procedia Manufacturing, 44, 253–260, doi:10.1016/j.promfg.2020.02.229, 2020.
  12. G.-F. Sargentis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues of Leonardo Da Vinci’s and Pablo Picasso’s paintings with stochastic evaluation, Heritage, 3 (2), 283–305, doi:10.3390/heritage3020017, 2020.
  13. R. Ioannidis, T. Iliopoulou, C. Iliopoulou, L. Katikas, A. Petsou, M.-E. Merakou, M.-E. Asimomiti, N. Pelekanos, G. Koudouris, P. Dimitriadis, C. Plati, E. Vlahogianni, K. Kepaptsoglou, N. Mamassis, and D. Koutsoyiannis, Solar-powered bus route: introducing renewable energy into a university campus transport system, Advances in Geosciences, 49, doi:10.5194/adgeo-49-215-2019, 2019.
  14. P. Dimitriadis, and D. Koutsoyiannis, The mode of the climacogram estimator for a Gaussian Hurst-Kolmogorov process, Journal of Hydroinformatics, doi:10.2166/hydro.2019.038, 2019.
  15. G.-F. Sargentis, P. Dimitriadis, R. Ioannidis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic evaluation of landscapes transformed by renewable energy installations and civil works, Energies, 12 (4), 2817, doi:10.3390/en12142817, 2019.
  16. A. Koskinas, A. Tegos, P. Tsira, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and Τ. Williamson, Insights into the Oroville Dam 2017 spillway incident, Geosciences, 9 (37), doi:10.3390/geosciences9010037, 2019.
  17. P. Dimitriadis, K. Tzouka, D. Koutsoyiannis, H. Tyralis, A. Kalamioti, E. Lerias, and P. Voudouris, Stochastic investigation of long-term persistence in two-dimensional images of rocks, Spatial Statistics, 29, 177–191, doi:10.1016/j.spasta.2018.11.002, 2019.
  18. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, A stochastic model for the hourly solar radiation process for application in renewable resources management, Advances in Geosciences, 45, 139–145, doi:10.5194/adgeo-45-139-2018, 2018.
  19. 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.
  20. Y. Markonis, Y. Moustakis, C. Nasika, P. Sychova, P. Dimitriadis, M. Hanel, P. Máca, and S.M. Papalexiou, Global estimation of long-term persistence in annual river runoff, Advances in Water Resources, 113, 1–12, doi:10.1016/j.advwatres.2018.01.003, 2018.
  21. H. Tyralis, P. Dimitriadis, D. Koutsoyiannis, P.E. O’Connell, K. Tzouka, and T. Iliopoulou, On the long-range dependence properties of annual precipitation using a global network of instrumental measurements, Advances in Water Resources, 111, 301–318, doi:10.1016/j.advwatres.2017.11.010, 2018.
  22. P. Dimitriadis, and D. Koutsoyiannis, Stochastic synthesis approximating any process dependence and distribution, Stochastic Environmental Research & Risk Assessment, 32 (6), 1493–1515, doi:10.1007/s00477-018-1540-2, 2018.
  23. E. Moschos, G. Manou, P. Dimitriadis, V. Afendoulis, D. Koutsoyiannis, and V. Tsoukala, Harnessing wind and wave resources for a Hybrid Renewable Energy System in remote islands: a combined stochastic and deterministic approach, Energy Procedia, 125, 415–424, doi:10.1016/j.egypro.2017.08.084, 2017.
  24. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, Investigation on the stochastic nature of the solar radiation process, Energy Procedia, 125, 398–404, 2017.
  25. K. Mavroyeoryos, I. Engonopoulos, H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system, Energy Procedia, 125, 435–442, doi:10.1016/j.egypro.2017.08.095, 2017.
  26. G. Karakatsanis, D. Roussis, Y. Moustakis, N. Gournari, I. Parara, P. Dimitriadis, and D. Koutsoyiannis, Energy, variability and weather finance engineering, Energy Procedia, 125, 389–397, doi:10.1016/j.egypro.2017.08.073, 2017.
  27. M. Chalakatevaki, P. Stamou, S. Karali, V. Daniil, P. Dimitriadis, K. Tzouka, T. Iliopoulou, D. Koutsoyiannis, P. Papanicolaou, and N. Mamassis, Creating the electric energy mix in a non-connected island, Energy Procedia, 125, 425–434, doi:10.1016/j.egypro.2017.08.089, 2017.
  28. 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.
  29. I. Deligiannis, P. Dimitriadis, Ο. Daskalou, Y. Dimakos, and D. Koutsoyiannis, Global investigation of double periodicity οf hourly wind speed for stochastic simulation; application in Greece, Energy Procedia, 97, 278–285, doi:10.1016/j.egypro.2016.10.001, 2016.
  30. 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.
  31. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of turbulence and hydrometeorological processes, Hydrological Sciences Journal, 61 (9), 1623–1640, doi:10.1080/02626667.2015.1085988, 2016.
  32. P. Dimitriadis, D. Koutsoyiannis, and K. Tzouka, Predictability in dice motion: how does it differ from hydrometeorological processes?, Hydrological Sciences Journal, 61 (9), 1611–1622, doi:10.1080/02626667.2015.1034128, 2016.
  33. P. Dimitriadis, and D. Koutsoyiannis, Application of stochastic methods to double cyclostationary processes for hourly wind speed simulation, Energy Procedia, 76, 406–411, doi:10.1016/j.egypro.2015.07.851, 2015.
  34. P. Dimitriadis, and D. Koutsoyiannis, Climacogram versus autocovariance and power spectrum in stochastic modelling for Markovian and Hurst–Kolmogorov processes, Stochastic Environmental Research & Risk Assessment, 29 (6), 1649–1669, doi:10.1007/s00477-015-1023-7, 2015.

Book chapters and fully evaluated conference publications

  1. G.-F. Sargentis, R. Ioannidis, M. Chiotinis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues with stochastic evaluation, Data Analytics for Cultural Heritage, edited by A. Belhi, A. Bouras, A.K. Al-Ali, and A.H. Sadka, doi:10.1007/978-3-030-66777-1_8, Springer, 2021.
  2. 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.
  3. D. Koutsoyiannis, P. Dimitriadis, F. Lombardo, and S. Stevens, From fractals to stochastics: Seeking theoretical consistency in analysis of geophysical data, Advances in Nonlinear Geosciences, edited by A.A. Tsonis, 237–278, doi:10.1007/978-3-319-58895-7_14, Springer, 2018.
  4. P. Dimitriadis, A. Tegos, A. Petsiou, V. Pagana, I. Apostolopoulos, E. Vassilopoulos, M. Gini, A. D. Koussis, N. Mamassis, D. Koutsoyiannis, and P. Papanicolaou, Flood Directive implementation in Greece: Experiences and future improvements, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

Conference publications and presentations with evaluation of abstract

  1. A. Lagos, S. Sigourou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Land Cover Change: Does it affect temperature variability?, EGU General Assembly 2021, online, EGU21-9000, doi:10.5194/egusphere-egu21-9000, European Geosciences Union, 2021.
  2. G. Vagenas, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic analysis of time-series related to ocean acidification, EGU General Assembly 2021, online, EGU21-2637, doi:10.5194/egusphere-egu21-2637, European Geosciences Union, 2021.
  3. Ο. Akoumianaki, T. Iliopoulou, P. Dimitriadis, E. Varouchakis, and D. Koutsoyiannis, Stochastic analysis of the spatial stochastic structure of precipitation in the island of Crete, Greece, EGU General Assembly 2021, online, EGU21-4640, doi:10.5194/egusphere-egu21-4640, European Geosciences Union, 2021.
  4. K. Papoulakos, T. Iliopoulou, P. Dimitriadis, D. Tsaknias, and D. Koutsoyiannis, Investigating the impacts of clustering of floods on insurance practices; a spatiotemporal analysis in the USA, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-8667, doi:10.5194/egusphere-egu2020-8667, 2020.
  5. G.T. Manolis, K. Papoulakos, T. Iliopoulou, P. Dimitriadis, D. Tsaknias, and D. Koutsoyiannis, Clustering mechanisms of flood occurrence; modelling and relevance to insurance practices, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-9357, doi:10.5194/egusphere-egu2020-9357, 2020.
  6. C. Farmakis, P. Dimitriadis, V. Bellos, P. Papanicolaou, and D. Koutsoyiannis, Investigation of the uncertainty of spatial flood inundation among widely used 1D/2D hydrodynamic models, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15629, European Geosciences Union, 2019.
  7. K. Kardakaris, M. Kalli, T. Agoris, P. Dimitriadis, N. Mamassis, and D. Koutsoyiannis, Investigation of the stochastic structure of wind waves for energy production, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-13188, European Geosciences Union, 2019.
  8. S. Vavoulogiannis, N. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of rainfall and runoff series from a large hydrometeorological dataset, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, European Geosciences Union, 2019.
  9. T. Goulianou, K. Papoulakos, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic characteristics of flood impacts for agricultural insurance practices, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-5891, European Geosciences Union, 2019.
  10. D. Galanis, T. Andrikopoulou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Investigation and stochastic simulation of the music of wind and precipitation, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-13332, European Geosciences Union, 2019.
  11. M. Karataraki, A. Thanasko, K. Printziou, G. Koudouris, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, C. Plati, and D. Koutsoyiannis, Campus solar roads: a feasibility analysis, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15648-2, European Geosciences Union, 2019.
  12. M.-E. Asimomiti, N. Pelekanos, P. Dimitriadis, T. Iliopoulou, E. Vlahogianni, and D. Koutsoyiannis, Campus solar roads: Stochastic modeling of passenger demand, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10585, European Geosciences Union, 2019.
  13. A. Petsou, M.-E. Merakou, T. Iliopoulou, C. Iliopoulou, P. Dimitriadis, R. Ioannidis, K. Kepaptsoglou, and D. Koutsoyiannis, Campus solar roads: Optimization of solar panel and electric charging station location for university bus route, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10832, European Geosciences Union, 2019.
  14. M. Megagianni, E.-M. Barka, P. Dimitriadis, K. Noutsopoulos, and S. Malamis, Investigation of stochastic similarities among influent and treated effluent variables of spatially distributed wastewater treatment plants in Greece;I: Statistical analysis of influent variables in terms of the marginal distribution, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15596-1, European Geosciences Union, 2019.
  15. E.-M. Barka, M. Megagianni, P. Dimitriadis, S. Malamis, and K. Noutsopoulos, Investigation of stochastic similarities among influent and treated effluent variables of spatially distributed wastewater treatment plants in Greece; II: Statistical analysis of treated effluent variables in terms of the marginal distribution, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15574, European Geosciences Union, 2019.
  16. G.-F. Sargentis, E. Frangedaki, P. Dimitriadis, and D. Koutsoyiannis, Development of a web platform of knowledge exchange for optimal selection of building materials based on ecological criteria, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10395, European Geosciences Union, 2019.
  17. R. Ioannidis, P. Dimitriadis, G.-F. Sargentis, E. Frangedaki, T. Iliopoulou, and D. Koutsoyiannis, Stochastic similarities between hydrometeorogical and art processes for optimizing architecture and landscape aesthetic parameters, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-11403, European Geosciences Union, 2019.
  18. A. Zoukos, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Global investigation of the multi-scale probabilistic behaviour of dry spells from rainfall records, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17966-1, doi:10.13140/RG.2.2.13555.78886, European Geosciences Union, 2018.
  19. V. Skoura, P. Dimitriadis, T. Iliopoulou, M. Crok, and D. Koutsoyiannis, A trendy analysis for the identification of extremal changes and trends in hydroclimatic processes; application to global precipitation, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17889-1, European Geosciences Union, 2018.
  20. E. Chardavellas, P. Dimitriadis, I. Papakonstantis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of vertical thermal jet and macroscale hydrometeorological processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17803-1, European Geosciences Union, 2018.
  21. P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Simulating precipitation at a fine time scale using a single continuous-state distribution, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18614, European Geosciences Union, 2018.
  22. P. Dimitriadis, and D. Koutsoyiannis, An innovative stochastic process and simulation algorithm for approximating any dependence structure and marginal distribution, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18710, European Geosciences Union, 2018.
  23. K. Sakellari, P. Dimitriadis, and D. Koutsoyiannis, A global stochastic analysis for the temperature and dew-point processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17941-1, European Geosciences Union, 2018.
  24. M. Chalakatevaki, E. Klousakou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of the uncertainty of hydrometeorological processes by means of the climacogram, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17714-1, European Geosciences Union, 2018.
  25. G. Karakatsanis, E. Kontarakis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Hydroclimate and agricultural output in developing countries, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-13059-1, European Geosciences Union, 2018.
  26. A. Tegos, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure and probability distribution of the global potential evapotranspiration, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17849-3, European Geosciences Union, 2018.
  27. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, and D. Koutsoyiannis, Stochastic investigation of the Hurst-Kolmogorov behaviour in arts, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17740-1, European Geosciences Union, 2018.
  28. S. Sigourou, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, A. Skopeliti, K. Sakellari, G. Karakatsanis, L. Tsoulos, and D. Koutsoyiannis, Comparison of climate change vs. urbanization, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18598-2, European Geosciences Union, 2018.
  29. S. Sigourou, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, A. Skopeliti, K. Sakellari, G. Karakatsanis, L. Tsoulos, and D. Koutsoyiannis, Statistical and stochastic comparison of climate change vs. urbanization, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18608-2, European Geosciences Union, 2018.
  30. P. Dimitriadis, H. Tyralis, T. Iliopoulou, K. Tzouka, Y. Markonis, N. Mamassis, and D. Koutsoyiannis, A climacogram estimator adjusted for timeseries length; application to key hydrometeorological processes by the Köppen-Geiger classification, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17832, European Geosciences Union, 2018.
  31. Y. Markonis, Y. Moustakis, C. Nasika, P. Sychova, P. Dimitriadis, M. Hanel, P. Máca, and S.M. Papalexiou, Investigation of the factors that affect the auto-correlation structure of annual river runoff, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-7324, European Geosciences Union, 2018.
  32. A. Pizarro, P. Dimitriadis, C. Samela, D. Koutsoyiannis, O. Link, and S. Manfreda, Discharge uncertainty on bridge scour process, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-8045, European Geosciences Union, 2018.
  33. A. Pizarro, P. Dimitriadis, M. Chalakatevaki, C. Samela, S. Manfreda, and D. Koutsoyiannis, An integrated stochastic model of the river discharge process with emphasis on floods and bridge scour, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-8271, European Geosciences Union, 2018.
  34. A. Gkolemis, P. Dimitriadis, G. Karakatsanis, T. Iliopoulou, and D. Koutsoyiannis, A stochastic investigation of the intermittent behaviour of wind; application to renewable energy resources management, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-15979-3, European Geosciences Union, 2018.
  35. Y. Kalogeris, P. Dimitriadis, T. Iliopoulou, V. Papadopoulos, and D. Koutsoyiannis, Investigation of the correlation structure behaviour through intermediate storage retention, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17247-1, European Geosciences Union, 2018.
  36. K. Tzouka, P. Dimitriadis, E. Varouchakis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure of two-dimensional images of rocks from small to large scales, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17306-1, European Geosciences Union, 2018.
  37. P. Dimitriadis, E. Varouchakis, T. Iliopoulou, G. Karatzas, and D. Koutsoyiannis, Stochastic investigation of the spatial variability of precipitation over Crete, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17155-1, European Geosciences Union, 2018.
  38. M. Nezi, P. Dimitriadis, A. Pizarro, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of the streamflow process adjusted for human impact, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17473-1, European Geosciences Union, 2018.
  39. G. Koudouris, P. Dimitriadis, T. Iliopoulou, G. Karakatsanis, and D. Koutsoyiannis, A stochastic model for hourly solar radiation process applied in renewable resources management, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-16275-2, European Geosciences Union, 2018.
  40. 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.
  41. 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.
  42. 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.
  43. 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.
  44. 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.
  45. 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.
  46. P. Dimitriadis, K. Tzouka, H. Tyralis, and D. Koutsoyiannis, Stochastic investigation of rock anisotropy based on the climacogram, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10632-1, European Geosciences Union, 2017.
  47. P. Dimitriadis, T. Iliopoulou, H. Tyralis, and D. Koutsoyiannis, Identifying the dependence structure of a process through pooled timeseries analysis, IAHS Scientific Assembly 2017, Port Elizabeth, South Africa, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2017.
  48. H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, An extensive review and comparison of R Packages on the long-range dependence estimators, Asia Oceania Geosciences Society (AOGS) 14th Annual Meeting, Singapore, HS06-A003, doi:10.13140/RG.2.2.18837.22249, Asia Oceania Geosciences Society, 2017.
  49. H. Tyralis, P. Dimitriadis, T. Iliopoulou, K. Tzouka, and D. Koutsoyiannis, Dependence of long-term persistence properties of precipitation on spatial and regional characteristics, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-3711, doi:10.13140/RG.2.2.13252.83840/1, European Geosciences Union, 2017.
  50. 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.
  51. P. Stamou, S. Karali, M. Chalakatevaki, V. Daniil, K. Tzouka, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and N. Mamassis, Creating the electric energy mix of a non-connected Aegean island, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10130-10, doi:10.13140/RG.2.2.36537.77927, European Geosciences Union, 2017.
  52. E. Hadjimitsis, E. Demetriou, K. Sakellari, H. Tyralis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Investigation of the stochastic nature of temperature and humidity for energy management, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10164-5, European Geosciences Union, 2017.
  53. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, Investigation of the stochastic nature of solar radiation for renewable resources management, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10189-4, doi:10.13140/RG.2.2.16215.06564, European Geosciences Union, 2017.
  54. E. Moschos, G. Manou, C. Georganta, P. Dimitriadis, T. Iliopoulou, H. Tyralis, D. Koutsoyiannis, and V. Tsoukala, Investigation of the stochastic nature of wave processes for renewable resources management: a pilot application in a remote island in the Aegean sea, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10225-3, doi:10.13140/RG.2.2.30226.66245, European Geosciences Union, 2017.
  55. A. Koskinas, E. Zacharopoulou, G. Pouliasis, I. Engonopoulos, K. Mavroyeoryos, I. Deligiannis, G. Karakatsanis, P. Dimitriadis, T. Iliopoulou, D. Koutsoyiannis, and H. Tyralis, Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10495-4, doi:10.13140/RG.2.2.10529.81767, European Geosciences Union, 2017.
  56. D. Roussis, I. Parara, N. Gournari, Y. Moustakis, P. Dimitriadis, T. Iliopoulou, D. Koutsoyiannis, and G. Karakatsanis, Energy, variability and weather finance engineering, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-16919, European Geosciences Union, 2017.
  57. 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.
  58. P. Dimitriadis, Y. Markonis, T. Iliopoulou, E. Feloni, N. Gournari, I. Deligiannis, P. Kastis, C. Nasika, E. Lerias, Y. Moustakis, A. Petsiou, A. Sotiriadou, A. Markopoulos, V. Tyrogiannis, and D. Koutsoyiannis, Stochastic similarities between hydroclimatic processes for variability characterization, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, European Geosciences Union, 2016.
  59. I. Deligiannis, P. Dimitriadis, and D. Koutsoyiannis, Hourly temporal distribution of wind, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, 18, EGU2016-13138-4, doi:10.13140/RG.2.2.25967.53928, European Geosciences Union, 2016.
  60. E. Lerias, A. Kalamioti, P. Dimitriadis, Y. Markonis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of temperature process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14828-3, European Geosciences Union, 2016.
  61. I. Deligiannis, V. Tyrogiannis, Ο. Daskalou, P. Dimitriadis, Y. Markonis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of wind process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14946-6, doi:10.13140/RG.2.2.26681.36969, European Geosciences Union, 2016.
  62. A. Sotiriadou, A. Petsiou, E. Feloni, P. Kastis, T. Iliopoulou, Y. Markonis, H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of precipitation process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-15137-5, doi:10.13140/RG.2.2.28955.46881, European Geosciences Union, 2016.
  63. P. Dimitriadis, N. Gournari, and D. Koutsoyiannis, Markov vs. Hurst-Kolmogorov behaviour identification in hydroclimatic processes, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14577-4, doi:10.13140/RG.2.2.21019.05927, European Geosciences Union, 2016.
  64. Y. Markonis, C. Nasika, Y. Moustakis, A. Markopoulos, P. Dimitriadis, and D. Koutsoyiannis, Global investigation of Hurst-Kolmogorov behaviour in river runoff, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-17491, doi:10.13140/RG.2.2.16331.59684, European Geosciences Union, 2016.
  65. D. Koutsoyiannis, F. Lombardo, P. Dimitriadis, Y. Markonis, and S. Stevens, From fractals to stochastics: seeking theoretical consistency in analysis of geophysical data, 30 Years of Nonlinear Dynamics in Geosciences, Rhodes, Greece, doi:10.13140/RG.2.2.34215.55209, 2016.
  66. D. Koutsoyiannis, and P. Dimitriadis, From time series to stochastics: A theoretical framework with applications on time scales spanning from microseconds to megayears, Orlob Second International Symposium on Theoretical Hydrology, Davis, California, USA, doi:10.13140/RG.2.2.14082.89284, University California Davis, 2016.
  67. 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.
  68. P. Dimitriadis, L. Lappas, Ο. Daskalou, A. M. Filippidou, M. Giannakou, Ε. Gkova, R. Ioannidis, Α. Polydera, Ε. Polymerou, Ε. Psarrou, A. Vyrini, S.M. Papalexiou, and D. Koutsoyiannis, Application of stochastic methods for wind speed forecasting and wind turbines design at the area of Thessaly, Greece, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-13810, doi:10.13140/RG.2.2.25355.08486, European Geosciences Union, 2015.
  69. 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.
  70. 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.
  71. P. Dimitriadis, and D. Koutsoyiannis, Using multiple stochastic tools in identification of scaling in hydrometeorology, AGU 2014 Fall Meeting, San Francisco, USA, American Geophysical Union, 2014.
  72. I. Pappa, Y. Dimakos, P. Dimas, P. Kossieris, P. Dimitriadis, and D. Koutsoyiannis, Spatial and temporal variability of wind speed and energy over Greece, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-13591, doi:10.13140/RG.2.2.11238.63048, European Geosciences Union, 2014.
  73. P. Dimitriadis, D. Koutsoyiannis, and C. Onof, N-Dimensional generalized Hurst-Kolmogorov process and its application to wind fields, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.15642.64963, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  74. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Climacogram-based modelling of isotropic turbulence, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  75. P. Dimitriadis, K. Tzouka, and D. Koutsoyiannis, Windows of predictability in dice motion, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.19417.52322, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.
  76. 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.
  77. V. Pagana, A. Tegos, P. Dimitriadis, A. Koukouvinos, P. Panagopoulos, and N. Mamassis, Alternative methods in floodplain hydraulic simulation - Experiences and perspectives, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10283-2, European Geosciences Union, 2013.
  78. A. Oikonomou, P. Dimitriadis, A. Koukouvinos, A. Tegos, V. Pagana, P. Panagopoulos, N. Mamassis, and D. Koutsoyiannis, Floodplain mapping via 1D and quasi-2D numerical models in the valley of Thessaly, Greece, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10366, doi:10.13140/RG.2.2.25165.03040, European Geosciences Union, 2013.
  79. P. Dimitriadis, D. Koutsoyiannis, and Y. Markonis, Spectrum vs Climacogram, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-993, doi:10.13140/RG.2.2.27838.89920, European Geosciences Union, 2012.
  80. P. Dimitriadis, M. Liveri-Dalaveri, A. Kaldis, C. Kotsalos, G. Papacharalampous, and P. Papanicolaou, Zone of flow establishment in turbulent jets, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-12716, European Geosciences Union, 2012.
  81. P. Dimitriadis, and P. Papanicolaou, Statistical analysis of turbulent positively buoyant jets, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-12672, European Geosciences Union, 2012.
  82. S. Giannoulis, C. Ioannou, E. Karantinos, L. Malatesta, G. Theodoropoulos, G. Tsekouras, A. Venediki, P. Dimitriadis, S.M. Papalexiou, and D. Koutsoyiannis, Long term properties of monthly atmospheric pressure fields, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 4680, doi:10.13140/RG.2.2.36017.79201, European Geosciences Union, 2012.
  83. P. Dimitriadis, P. Papanicolaou, and D. Koutsoyiannis, Hurst-Kolmogorov dynamics applied to temperature fields for small turbulence scales, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-772, doi:10.13140/RG.2.2.22137.26724, European Geosciences Union, 2011.
  84. P. Dimitriadis, D. Koutsoyiannis, C. Onof, and K. Tzouka, Multidimensional Hurst-Kolmogorov process for modelling temperature and rainfall fields, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-739, doi:10.13140/RG.2.2.12070.93761, European Geosciences Union, 2011.
  85. P. Dimitriadis, D. Koutsoyiannis, and A. Paschalis, Three dimensional Hurst-Kolmogorov process for modelling rainfall fields, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-979-1, doi:10.13140/RG.2.2.29844.30088, European Geosciences Union, 2010.

Academic works

  1. P. Dimitriadis, Hurst-Kolmogorov dynamics in hydroclimatic processes and in the microscale of turbulence, PhD thesis, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2017.

Research reports

  1. D. Koutsoyiannis, S.M. Papalexiou, Y. Markonis, P. Dimitriadis, and P. Kossieris, Stochastic framework for uncertainty assessment of hydrometeorological procesess, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 231 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, January 2015.
  2. 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.
  3. 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.

Engineering reports

  1. D. Koutsoyiannis, Y. Markonis, A. Koukouvinos, S.M. Papalexiou, N. Mamassis, and P. Dimitriadis, Hydrological study of severe rainfall in the Kephisos basin, Greece, Study of the management of Kephisos , Commissioner: General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: Exarhou Nikolopoulos Bensasson, Denco, G. Karavokiris, et al., 154 pages, Athens, 2010.

Details on research projects

Participation as Researcher

  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

Details on engineering studies

  1. Study of the management of Kephisos

    Duration: June 2009–April 2010

    Commissioned by: General Secretariat of Public Works

    Contractors:

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

Published work in detail

Publications in scientific journals

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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  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/

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  1. Y. Markonis, Y. Moustakis, C. Nasika, P. Sychova, P. Dimitriadis, M. Hanel, P. Máca, and S.M. Papalexiou, Global estimation of long-term persistence in annual river runoff, Advances in Water Resources, 113, 1–12, doi:10.1016/j.advwatres.2018.01.003, 2018.

    Long-term persistence (LTP) of annual river runoff is a topic of ongoing hydrological research, due to its implications to water resources management. Here, we estimate its strength, measured by the Hurst coefficient H, in 696 annual, globally distributed, streamflow records with at least 80 years of data. We use three estimation methods (maximum likelihood estimator, Whittle estimator and least squares variance) resulting in similar mean values of H close to 0.65. Subsequently, we explore potential factors influencing H by two linear (Spearman's rank correlation, multiple linear regression) and two non-linear (self-organizing maps, random forests) techniques. Catchment area is found to be crucial for medium to larger watersheds, while climatic controls, such as aridity index, have higher impact to smaller ones. Our findings indicate that long-term persistence is weaker than found in other studies, suggesting that enhanced LTP is encountered in large-catchment rivers, were the effect of spatial aggregation is more intense. However, we also show that the estimated values of H can be reproduced by a short-term persistence stochastic model such as an auto-regressive AR(1) process. A direct consequence is that some of the most common methods for the estimation of H coefficient, might not be suitable for discriminating short- and long-term persistence even in long observational records.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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    • [89] Initial presentation in EGU conference

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

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    1. Bakanos, P. I., and K. L. Katsifarakis, Optimizing operation of a large-scale pumped storage hydropower system coordinated with wind farm by means of genetic algorithm, Global Nest Journal, 2019.
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  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.

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

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

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

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  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.

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    98. Urzică, A., A. Mihu-Pintilie, C. C. Stoleriu, C. I. Cîmpianu, E. Huţanu, C. I. Pricop, and A. Grozavu, Using 2D HEC-RAS modeling and embankment dam break scenario for assessing the flood control capacity of a multi-reservoir system (NE Romania), Water, 13(1), 57, doi:10.3390/w13010057, 2021.
    99. Elhag, M., and N. Yilmaz, Insights of remote sensing data to surmount rainfall/runoff data limitations of the downstream catchment of Pineios River, Greece, Environmental Earth Sciences, 80, 35, doi:10.1007/s12665-020-09289-5, 2021.
    100. Hdeib, R., R. Moussa, F. Colin, and C. Abdallah, A new cost-performance grid to compare different flood modelling approaches, Hydrological Sciences Journal, 66(3), 434-449, doi:10.1080/02626667.2021.1873346, 2021.
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    102. Santos, E. D. S., H. S. K. Pinheiro, and H. G. Junior, Height above the nearest drainage to predict flooding areas in São Luiz do Paraitinga, São Paulo, Floresta e Ambiente, 28(2), doi:10.1590/2179-8087-floram-2020-0070, 2021.
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  1. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of turbulence and hydrometeorological processes, Hydrological Sciences Journal, 61 (9), 1623–1640, doi:10.1080/02626667.2015.1085988, 2016.

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

    Additional material:

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

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

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

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

    Additional material:

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

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

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

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

    Remarks:

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

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

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

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

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

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

    Additional material:

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

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

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

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

Book chapters and fully evaluated conference publications

  1. G.-F. Sargentis, R. Ioannidis, M. Chiotinis, P. Dimitriadis, and D. Koutsoyiannis, Aesthetical issues with stochastic evaluation, Data Analytics for Cultural Heritage, edited by A. Belhi, A. Bouras, A.K. Al-Ali, and A.H. Sadka, doi:10.1007/978-3-030-66777-1_8, Springer, 2021.

    Throughout human history, the quantification of aesthetics has intrigued philosophers, artists, and mathematicians alike. In this chapter, a methodology based on stochastic mathematics is applied for the quantification of aesthetic attributes of paintings and landscapes. The paintings analyzed include Da Vinci, Pablo Picasso, and various other celebrated paintings from 1250 AD to modern times. In regard to landscapes, the analysis focuses on the aesthetic transformations imposed to landscapes from wind energy projects. The methodology used is called stochastic 2D-C analysis and is based on a stochastic computational tool that analyzes brightness fluctuation in images. The 2D-C tool is used to measure the degree of variability and in particular the change in variability vs. scale. The application of the tool provides (a) input on the qualitative efficiency of mainstream methods used in landscape-impact analysis, (b) insights into the expression forms of the examined artists and historical periods, and finally (c) evidence that can be used in the search of the originality of an artwork of disputed authorship.

  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. D. Koutsoyiannis, P. Dimitriadis, F. Lombardo, and S. Stevens, From fractals to stochastics: Seeking theoretical consistency in analysis of geophysical data, Advances in Nonlinear Geosciences, edited by A.A. Tsonis, 237–278, doi:10.1007/978-3-319-58895-7_14, Springer, 2018.

    Fractal-based techniques have opened new avenues in the analysis of geophysical data. On the other hand, there is often a lack of appreciation of both the statistical uncertainty in the results, and the theoretical properties of the stochastic concepts associated with these techniques. Several examples are presented which illustrate suspect results of fractal techniques. It is proposed that concepts used in fractal analyses are stochastic concepts and the fractal techniques can readily be incorporated into the theory of stochastic processes. This would be beneficial in studying biases and uncertainties of results in a theoretically consistent framework, and in avoiding unfounded conclusions. In this respect, a general methodology for theoretically justified stochastic processes, which evolve in continuous time and stem from maximum entropy production considerations, is proposed. Some important modelling issues are discussed with focus on model identification and fitting, often made using inappropriate methods. The theoretical framework is applied to several processes, including turbulent velocities measured every several microseconds, and wind and temperature measurements. The applications shows that several peculiar behaviours observed in these processes are easily explained and reproduced by stochastic techniques.

    Additional material:

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

  1. P. Dimitriadis, A. Tegos, A. Petsiou, V. Pagana, I. Apostolopoulos, E. Vassilopoulos, M. Gini, A. D. Koussis, N. Mamassis, D. Koutsoyiannis, and P. Papanicolaou, Flood Directive implementation in Greece: Experiences and future improvements, 10th World Congress on Water Resources and Environment "Panta Rhei", Athens, European Water Resources Association, 2017.

    The implementation of the European Directive 2007/60 is a crucial step towards the development of a sophisticated flood management plan for the main River Basin Districts by including any necessary structural measures. For this reason, extensive hydrological and hydraulic analysis is needed under the ubiquitous uncertainty which cannot be eliminated by numerical models. In this study, we present our experience from the directive implementation and we discuss structural components of uncertainty in the flood modelling practice mostly related to the river network. We propose and review some of the most efficient engineering practices by examining issues like: (a) the consistency and accuracy of the required input data of the topography such as the Digital Elevation Model, cross-sectional measurements of the river and maps of land use; (b) the uncertainty components related to the hydrological SCS-CN framework and other hydrological methods for the determination of the input hydrograph; (c) the theoretical framework of each hydraulic model such as the scheme dimension (1d, 2d or coupled 1d/2d), the type of solution of the numerical scheme (explicit or implicit), the boundary conditions and the type of discretization (grid or sectionbased); (d) the uncertainty components related to the flood inundation modelling, such as the roughness coefficient at the river and floodplain; (e) the necessity of validation data such as the flow discharge, the flood inundation area, and the velocity measurements.

Conference publications and presentations with evaluation of abstract

  1. A. Lagos, S. Sigourou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Land Cover Change: Does it affect temperature variability?, EGU General Assembly 2021, online, EGU21-9000, doi:10.5194/egusphere-egu21-9000, European Geosciences Union, 2021.

    Changes in the land cover occur all the time at the surface of the Earth both naturally and anthropogenically. In the last decades, certain types of land cover change, including urbanization, have been correlated to local temperature increase, but the general dynamics of this relationship are still not well understood. This work examines whether land cover is a parameter affecting temperature increase by employing global datasets of land cover change, i.e. the Historical Land-Cover Change Global Dataset, and daily temperature from the NOAA database. We thoroughly investigate the temperature variability and its possible correlation to the different types of land-cover changes. A comparison is specifically made between the rate of temperature increase measured in urban areas, and the same rate measured in nearby non-urban areas.

    Full text: http://www.itia.ntua.gr/en/getfile/2112/2/documents/EGU21-9000_presentation.pdf (3350 KB)

    Additional material:

  1. G. Vagenas, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic analysis of time-series related to ocean acidification, EGU General Assembly 2021, online, EGU21-2637, doi:10.5194/egusphere-egu21-2637, European Geosciences Union, 2021.

    Since the pre-industrial era at the end of the 18th century, the atmospheric carbon dioxide concentration (CO2) has increased by 47.46% from the level of 280 ppmv (parts per million volume) to 412.89 ppmv (Mauna Loa – NOAA Station, November 2020). These increased concentrations caused by natural & anthropogenic activities, interact with the aquatic environment which acts as a safety valve. Nevertheless, the absorbed CO2 amounts undergo chemical transformations, resulting in increasing ionized concentrations that can significantly reduce the water’s pH, a process described as ocean acidification. Here, we use the HOT (Hawaii-Ocean-Time series) to perform time series analysis for temperature, carbon dioxide partial pressure and pH. More specifically, we analyze their temporal changes in month and annual time lag. Then, we proceed in comparisons with relevant studies on atmospheric data to evaluate the produced results. Finally, we make an effort to disentangle the results with simplified assumptions connected with the observed impact of ocean acidification on the aquatic ecosystems.

    Full text: http://www.itia.ntua.gr/en/getfile/2110/2/documents/EGU21-2637_presentation.pdf (5539 KB)

    Additional material:

  1. Ο. Akoumianaki, T. Iliopoulou, P. Dimitriadis, E. Varouchakis, and D. Koutsoyiannis, Stochastic analysis of the spatial stochastic structure of precipitation in the island of Crete, Greece, EGU General Assembly 2021, online, EGU21-4640, doi:10.5194/egusphere-egu21-4640, European Geosciences Union, 2021.

    In the last few years, the island of Crete (Greece - Eastern Mediterranean) has been affected by extreme events. In recent decades, hydrometeorological processes in the island of Crete are monitored by an extensive network of meteorological stations. Here we stochastically analyze the spatial stochastic structure of precipitation in the island by employing sophisticated statistical tools, as well as by analyzing a large database of daily precipitation records. We investigate fifty-eight rainfall stations scattered in the four prefectures of Crete, for the years 1974-2020. Descriptive statistical analysis of precipitation examines several temporal properties in the data, while correlation analysis of precipitation variability provides relations between stations and regions for spatial patterns identification. This work also investigates the precipitation variability by employing statistical tools such as the autocorrelation, autoregressive (seasonal) analysis, probability distribution function fitting, and climacogram calculation, i.e. variance of the averaged process vs. spatial and temporal scales, to identify statistical properties, temporal dependencies, potential similarities in the dependence structure and marginal probability distribution.

    Full text: http://www.itia.ntua.gr/en/getfile/2109/2/documents/EGU21-4640_presentation.pdf (1504 KB)

    Additional material:

  1. K. Papoulakos, T. Iliopoulou, P. Dimitriadis, D. Tsaknias, and D. Koutsoyiannis, Investigating the impacts of clustering of floods on insurance practices; a spatiotemporal analysis in the USA, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-8667, doi:10.5194/egusphere-egu2020-8667, 2020.

    Recent research has revealed the significance of Hurst-Kolmogorov dynamics and inherent uncertainties in flood inundation and flood mapping. However, classic risk estimation for flood insurance practices is formulated under the assumption of independence between the frequency and the severity of extreme flood events, which is unlikely to be tenable in real-world hydrometeorological processes exhibiting long range dependence. Furthermore, insurable flood losses are considered as ideally independent and non-catastrophic due to the widely spread perception of limited risk regarding catastrophically large flood losses. As the accurate risk assessment is a fundamental process on flood insurance and reinsurance practices, this study investigates the effects of lack of fulfillment of these assumptions, paving the way for a deeper understanding of the underlying clustering mechanisms of stream flow extremes. For this purpose, we present a spatiotemporal analysis of the daily stream flow series from the US-CAMELS dataset, comprising the impacts of clustering mechanisms on return intervals, duration and severity of the over-threshold events which are treated as proxies for collective risk. Moreover, an exploratory analysis is introduced regarding the stochastic aspects of the correlation between the properties of the extreme events and the actual claim records of the FEMA National Flood Insurance Program which are recently published.

    Full text: http://www.itia.ntua.gr/en/getfile/2133/1/documents/papoulakos_2020.pdf (3143 KB)

  1. G.T. Manolis, K. Papoulakos, T. Iliopoulou, P. Dimitriadis, D. Tsaknias, and D. Koutsoyiannis, Clustering mechanisms of flood occurrence; modelling and relevance to insurance practices, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-9357, doi:10.5194/egusphere-egu2020-9357, 2020.

    Population growth, economic development and risk-blind urbanization often increase exposure to risk, including that due to floods. While rural flooding may affect much larger areas of land, urban floods are more challenging to manage, since the higher population and asset density in the urban environment increase the environmental and social impacts of floods and make the potential flood damages more costly. Therefore, the need for integrated flood insurance policy and products on extended parts of the world is pronounced in order to reduce the financial consequences of extreme flood events, which endanger in many cases the environmental, social and economic stability. As the assessment of the so-called collective risk is a typical issue faced in insurance and reinsurance practices, in this study we investigate the stochastic dynamics of daily stream flow series with particular interest to the existence of clustering mechanisms in floods, which is known to increase the potential risk. We analyse collective risk on the US-CAMELS dataset, treating the streamflow exceedances over given thresholds as proxies for insurance claim amounts. Moreover, we develop modelling and simulation approaches of extreme flows as a step towards the deeper understanding of the relationship between the stochastic patterns of flood occurrence and proxies of insurance claims, paving the way for a more efficient use of the available streamflow records.

    Full text: http://www.itia.ntua.gr/en/getfile/2132/1/documents/manolis_egu20.pdf (1660 KB)

  1. C. Farmakis, P. Dimitriadis, V. Bellos, P. Papanicolaou, and D. Koutsoyiannis, Investigation of the uncertainty of spatial flood inundation among widely used 1D/2D hydrodynamic models, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15629, European Geosciences Union, 2019.

    On several occasions, hydrodynamic models are applied in order to establish flood risk and flood hazard maps and evaluate the impacts of floods. More often these models are treated as deterministic tools and, as a result,the uncertainties stemmed from the modelling simplifications and assumptions are ignored. Specifically, when the spatial propagation of a flood wave is of interest the highest uncertainties emerge at the boundary conditions, at the model input parameters and even at the model structure. The aim of this research is to examine the aforementioned sources of uncertainty in benchmark scenarios. Three models are tested (i.e. the one-dimensional HEC-RAS, the quasi-two-dimensional LISFLOOD-FP, and a two-dimensional scheme of the OpenFOAM) on steady hydraulic conditions and uniform channel geometry. In each model a sensitivity analysis is performed by varying the grid resolution, the input discharge, the roughness coefficient in the channel and floodplain, and the channel longitudinal and lateral gradient. After statistically analyzing the fluctuation of the output parameters (i.e. the mean water velocity at the inflow and outflow cross section, and the water volume), the uncertainty in the different model configurations is quantified and compared.

    Full text: http://www.itia.ntua.gr/en/getfile/1994/1/documents/Chrysanthos_Farmakis_poster1.pdf (2072 KB)

  1. K. Kardakaris, M. Kalli, T. Agoris, P. Dimitriadis, N. Mamassis, and D. Koutsoyiannis, Investigation of the stochastic structure of wind waves for energy production, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-13188, European Geosciences Union, 2019.

    Ocean energy is considered a promising renewable energy resource mainly due to its massive energy potential.State of the art technologies that can harness the ocean dynamics are discussed in terms of their efficiency and cost of energy production. The ocean related process with the highest potential, but also the highest uncertainty, is the wave process generated by wind. We analyze several wind-wave timeseries mostly close to shore but also one of the largest available timeseries located in the Northern Adriatic Sea with almost 40 years of 3 hours resolution of recorded wave heights and periods. We estimate marginal seasonal properties as well as second-order depen-dence structures in terms of the climacogram (i.e. variance of the averaged process vs. scale) that is shown to be advantageous as compared to more traditional stochastic tools such as the autocovariance and the power spectrum.Finally, we propose a stochastic model that can adequately simulate the observed variability of timeseries in state and scale.

    Full text: http://www.itia.ntua.gr/en/getfile/1968/1/documents/Poster_HCQaTsC.pdf (1450 KB)

  1. S. Vavoulogiannis, N. Ioannidis, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of rainfall and runoff series from a large hydrometeorological dataset, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, European Geosciences Union, 2019.

    We investigate the recently published CAMELS dataset, which is one of the most comprehensive large-scale datasets in terms of river flow timeseries and attributes of catchments minimally impacted by human activities. We examine the stochastic properties of daily river flow and rainfall series and investigate the links between the two at various lags, through climacogram-based stochastics tools (i.e. the climacogram and cross-climacogram) examining the variance versus spatio-temporal scale. We also explore the impact of various climatic and geophysical catchment attributes such as seasonality and timing of precipitation, aridity, mean catchment slope and soil conductivity, on the identified rainfall-runoff stochastic relationships.

    Full text: http://www.itia.ntua.gr/en/getfile/1966/1/documents/egu_teliko_powerpoint.pdf (1006 KB)

  1. T. Goulianou, K. Papoulakos, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Stochastic characteristics of flood impacts for agricultural insurance practices, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-5891, European Geosciences Union, 2019.

    During the last decades, the rising demand for crops for human consumption and industrial processes has led to a growth of investments and search for innovative solutions across the field of agriculture. However, one major risk that both investors and low-income farmers encounter worldwide is the impact of extreme weather events on their crop yield. The risk caused by extreme weather is an inhibitor of growth of agriculture and, apparently, agricultural insurance is strategically important for dealing with that risk. In particular, crop-yield insurance is purchased by agricultural producers, and in many cases is subsidized by governments, to protect them against the loss of their crops due to natural disasters, such as extreme flood events. In this context, the main subject of this research is to apply a stochastic approach of extremes for evaluating the impact of flood risk on agricultural insurance practices.We investigate stochastic aspects of extreme flows such as the right tail of the distribution of extremes and the existence of clustering mechanisms. For this purpose, we analyze daily flow series from the CAMELS dataset.Furthermore, we review current insurance practices in the agriculture domain in Greece and inspect the underlying stochastic assumptions, while evaluating changes in the estimated flood risk in the case that these assumptions are not valid.

    Full text: http://www.itia.ntua.gr/en/getfile/1961/1/documents/2019_EGU_Flood__Insurance_Poster_FINAL.pdf (2183 KB)

  1. D. Galanis, T. Andrikopoulou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Investigation and stochastic simulation of the music of wind and precipitation, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-13332, European Geosciences Union, 2019.

    Sound can be used as a means to detect and measure hydrometeorological variables that can generate sound.Thereby rain and wind over the sea surface can be estimated by the sound they produce if the ocean ambient noise is removed. A loud and distinctive sound is produced when the raindrops hit the ocean surface but waves also generate sound when they break. While rain and wind are difficult to measure over the ocean as gauges have to be mounted on surface buoys or ships, acoustic gauges placed beneath the ocean surface have been used as an alternative of measurement. The data that are collected from these gauges are then analysed using empirical models.In order for the sound data to be converted to wind speed and rainfall intensity, climacogram-based stochastic tools are used instead of the more traditional power spectrum ones. Furthermore, an application of this stochastic method is presented on the first ever recorded sound of wind on planet Mars, a mission executed by NASA’s In Sight lander.The study concludes with a discussion on possible similarities between the sound produced by the above variables and music (e.g. digital music for entertainment).

    Full text: http://www.itia.ntua.gr/en/getfile/1960/1/documents/EGU_Poster_.pdf (3194 KB)

  1. M. Karataraki, A. Thanasko, K. Printziou, G. Koudouris, R. Ioannidis, T. Iliopoulou, P. Dimitriadis, C. Plati, and D. Koutsoyiannis, Campus solar roads: a feasibility analysis, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15648-2, European Geosciences Union, 2019.

    We study the possibility of replacing conventional roads and buses with solar powered panel roads and electric buses fueled by solar energy within a closed system at a university campus. We also examine an alternative option of using solar buses equipped with panels on the rooftop. We review the recent advances in the technology of solar roads and buses and examine the modeling challenges and uncertainties of a transportation system powered by solar energy. We evaluate the economic aspects as well as the advantages and limitations of the proposed systems.The feasibility of this project is examined in terms of its application in the NTUA campus and possible directions for further research are identified.

    Full text: http://www.itia.ntua.gr/en/getfile/1959/1/documents/Teliko_poster_egu_1_selida.pdf (1985 KB)

  1. M.-E. Asimomiti, N. Pelekanos, P. Dimitriadis, T. Iliopoulou, E. Vlahogianni, and D. Koutsoyiannis, Campus solar roads: Stochastic modeling of passenger demand, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10585, European Geosciences Union, 2019.

    In the era of rapid technological advancements, innovations have started to reshape the field of transportation and energy management. University Campuses are considered as the ideal venue for implementing and testing innovative transportation services, as they usually encompass a closed form small-scale transportation infrastructure, and mainly involve users highly receptive to emerging technologies, due to their academic background. Nevertheless,the assessment of such services is a complex task, which should take into consideration issues related to energy sufficiency, passengers’ demand estimation and routing specifications. The present paper addresses the problem of stochastic passenger demand estimation under the uncertainties introduced by the implementation of a novel university bus service operated by hybrid vehicles under the concept of “opportunity charging” and solar powered buses. Aspects such as the relationship between the passengers’ need to move around the campus and parameters,such as time schedules, waiting time and alternative means of transportation are addressed. The passenger demand series generated by the models are linked to bus dwell times, which in turn determine the available charging time at each bus stop.

    Full text: http://www.itia.ntua.gr/en/getfile/1958/1/documents/solar_roads.pdf (2434 KB)

  1. A. Petsou, M.-E. Merakou, T. Iliopoulou, C. Iliopoulou, P. Dimitriadis, R. Ioannidis, K. Kepaptsoglou, and D. Koutsoyiannis, Campus solar roads: Optimization of solar panel and electric charging station location for university bus route, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10832, European Geosciences Union, 2019.

    We explore the prospect of replacing conventional university campus buses powered by fossil fuels with ones using solar energy. The proposed research investigates the emerging technology of solar powered road panels within a stochastic framework in order to optimally determine the corresponding infrastructure requirements for a university circulator line. More specifically, an optimization model is developed in order to determine the optimal locations for solar-powered roadway segments and electric charging stations for the existing university campus bus route. Since the availability of solar energy is linked to sunshine levels, we explore the possibility of using hybrid buses, powered by electricity and storing the energy to batteries in order to allow operation in days with no sunshine. As an alternative we study the use of solar buses equipped with panels on the rooftop. In order to account for the uncertainty associated with the system inputs, the transportation demand for the campus route and the availability of solar energy over the campus area are simulated using stochastic methods. The capital cost and energy consumption of the selected buses, charging stations and solar panels are also investigated in a case study for the NTUA campus.

    Full text: http://www.itia.ntua.gr/en/getfile/1957/1/documents/EGU-Solar-Roads-FINAL.pdf (1082 KB)

  1. M. Megagianni, E.-M. Barka, P. Dimitriadis, K. Noutsopoulos, and S. Malamis, Investigation of stochastic similarities among influent and treated effluent variables of spatially distributed wastewater treatment plants in Greece;I: Statistical analysis of influent variables in terms of the marginal distribution, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15596-1, European Geosciences Union, 2019.

    The aim of this research is to identify any statistical similarities among influent variables of spatially distributed wastewater treatment plants. The data is downloaded from the Greek national database of wastewater treatment plants (http://astikalimata.ypeka.gr), where spatial information (location, treated population) is uniformly distributed over Greece. For each plant several influent parameters (i.e. BOD5, COD, SS, T-N, NH4-N, NO3-N,T-P) are analyzed in terms of their marginal distributions. Specifically, for each variable we estimate its marginal statistics for each season and overall, e.g. probability distribution function and first four classical and L-moments,and we perform statistical methods (e.g. square error and maximum-likelihood) to identify the most appropriate distribution that can adequately simulate the observed variability. Finally, we discuss the spatial distribution of the marginal estimates of the selected variables and whether they exhibit any statistical similarities.

    Full text: http://www.itia.ntua.gr/en/getfile/1956/1/documents/teliki_parousiasi_megagianni-converted.pdf (600 KB)

  1. E.-M. Barka, M. Megagianni, P. Dimitriadis, S. Malamis, and K. Noutsopoulos, Investigation of stochastic similarities among influent and treated effluent variables of spatially distributed wastewater treatment plants in Greece; II: Statistical analysis of treated effluent variables in terms of the marginal distribution, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-15574, European Geosciences Union, 2019.

    The aim of this research is to identify any statistical similarities among treated effluent variables of spatially distributed wastewater treatment plants. The data is downloaded from the Greek national database of waste water treatment plants (http://astikalimata.ypeka.gr) uniformly distributed over Greece. For each plant several treate deffluent parameters (i.e. BOD5, COD, SS, T-N, NH4-N, NO3-N, T-P) are analyzed in terms of their marginal distributions. Specifically, for each variable we estimate its marginal statistics for each season and overall, e.g.probability distribution function and first four classical and L-moments, and we perform statistical methods (e.g.square error and maximum-likelihood) to identify the most appropriate distribution that can adequately simulate the observed variability. We discuss over the spatial distribution of the marginal estimates of the selected variables and whether they exhibit any statistical similarities among them, and among the marginal estimates of the influent variables. Finally, we further discuss how the production of sludge can be used for energy production, based also on the available spatial information (type of treatment, location etc.) of each plan.

    Full text: http://www.itia.ntua.gr/en/getfile/1955/1/documents/egu_evridiki_-_final_1.pdf (2845 KB)

  1. G.-F. Sargentis, E. Frangedaki, P. Dimitriadis, and D. Koutsoyiannis, Development of a web platform of knowledge exchange for optimal selection of building materials based on ecological criteria, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-10395, European Geosciences Union, 2019.

    Decisions on technical issues must simultaneously satisfy several conflicting objectives. Several methods have been developed to help identify the "optimal" decision. Such decisions are made by politicians but experts, constructors and the society must have the ability to overview and influence these decisions. The interaction of the different groups can be implemented using a web platform. The criteria to optimize this platform and its architecture are analysed. The aim is to give to non-expert users a general view of the problem and the solutions suggested, and help them form an informed opinion on a technical problem. At the same time it would help politicians and experts to take into account the public opinions in decision making.

    Remarks:

    This research has been supported by the OptArch project: "Optimization Driven Architectural Design of Structures" (No: 689983) belonging to the Marie Skłodowska-Curie Actions (MSCA) Research and Innovation Staff Exchange (RISE) H2020-MSCA-RISE-2015.

    Full text:

  1. R. Ioannidis, P. Dimitriadis, G.-F. Sargentis, E. Frangedaki, T. Iliopoulou, and D. Koutsoyiannis, Stochastic similarities between hydrometeorogical and art processes for optimizing architecture and landscape aesthetic parameters, European Geosciences Union General Assembly 2019, Geophysical Research Abstracts, Vol. 21, Vienna, EGU2019-11403, European Geosciences Union, 2019.

    Stochastics help develop a unified perception for natural phenomena and expel dichotomies like random vs. deterministic, as both randomness and predictability coexist and are intrinsic to natural systems which can be deterministic and random at the same time, depending on the prediction horizon and the time scale. The high complexity and uncertainty of natural processes has been long identified through observations as well as extended analyses of hydrometeorological processes such as temperature, humidity, surface wind, precipitation, atmospheric pressure, river discharges etc. All these processes seem to exhibit high unpredictability due to the clustering of events. Art is a mix of determinism (e.g., certain rules have to be followed) and stochasticity (e.g., creativity and inspiration). However, in this analysis we analyse each artistic work in a stochastic approach, and attempt to identify their degree of intrinsic uncertainty. The stochastic analysis includes the investigation of possible Hurst-Kolmogorov behaviour in the art of different periods (visual arts, music, poetry) and of relationships with natural processes. Based on the stochastic analysis of different artworks, we make an image analysis of architectural elements in the landscape in order to formulate an indicator that can be used in engineering.

    Remarks:

    This research has been supported by the OptArch project: "Optimization Driven Architectural Design of Structures" (No: 689983) belonging to the Marie Skłodowska-Curie Actions (MSCA) Research and Innovation Staff Exchange (RISE) H2020-MSCA-RISE-2015.

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  1. A. Zoukos, T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis, Global investigation of the multi-scale probabilistic behaviour of dry spells from rainfall records, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17966-1, doi:10.13140/RG.2.2.13555.78886, European Geosciences Union, 2018.

    Understanding and modelling the rainfall process at fine timescales has been a classic endeavor of hydrology, particularly because of its importance in everyday life, hydrological design and water resources management. At fine timescales, the rainfall process alternates between wet and dry states exhibiting pronounced clustering behavior. Herein, we employ a probabilistic characterization of rainfall intermittency as a two-state process and estimate the probability-dry across a range of timescales from minutes to months. To model the resulting multi-scale behavior, we employ a stochastic model derived from an entropy maximization framework at a multi-scale setting, which was previously found to successfully describe sub-daily rainfall in single case studies. We investigate whether the proposed model is able to capture the wide range of rainfall regimes observed worldwide and discuss its potential generality. Furthermore, we show how such a modelling approach of rainfall intermittency can prove valuable for practical purposes, such as the derivation of ombrian (intensity-duration-frequency) curves.

    Full text: http://www.itia.ntua.gr/en/getfile/1824/2/documents/2018EGU_DrySpells.pdf (2215 KB)

    Additional material:

  1. V. Skoura, P. Dimitriadis, T. Iliopoulou, M. Crok, and D. Koutsoyiannis, A trendy analysis for the identification of extremal changes and trends in hydroclimatic processes; application to global precipitation, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17889-1, European Geosciences Union, 2018.

    During the last decades it has been trendy to identify trends in extreme phenomena and attribute them to anthropogenic climate change. Although the majority of analyses tend to identify increasing (and sometimes decreasing) trends in hydrometeorological extremes, there are a few works that show no significant change in the distribution tail of the processes. A few analyses have shown that changes in the extremes can be adequately explained by the Hurst-Kolmogorov (HK) behaviour. In this work, we test the tail behaviour of several well-known distributions when combined to an HK model. Finally, we provide illustrative examples on whether or not the observed variability in precipitation extremes could be explained by the HK behaviour.

    Full text: http://www.itia.ntua.gr/en/getfile/1823/1/documents/EGU2018-17889-1.pdf (32 KB)

  1. E. Chardavellas, P. Dimitriadis, I. Papakonstantis, D. Koutsoyiannis, and P. Papanicolaou, Stochastic similarities between the microscale of vertical thermal jet and macroscale hydrometeorological processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17803-1, European Geosciences Union, 2018.

    Most hydrometeorological processes (such as temperature, wind etc.) are governed by turbulent state. In this study, we seek for stochastic similarities between the correlation structure of hydrometeorological processes (as has been already derived from global analyses of surface stations) and experimental vertical thermal jet at different states. It is well established experimentally that a jet flow close to the nozzle (at the zone of the core) is laminar and far from the nozzle (at the zone of established flow) fully turbulent. We apply several stochastic tools (autocorrelation, power spectrum, climacogram etc.) at the two aforementioned zones as well as at the intermediate zone of flow establishment (5 to 15 diameters away from the nozzle) in an attempt to identify any stochastic similarities and differences between the three zones, and thus, between the laminar and turbulent flow state transition. For this, spatio-temporal temperature records are obtained on the plane of symmetry of heated vertical round jets (for a laboratory turbulent scale at the order of mm) using tracer concentration measurements via a planar laser induced fluorescence technique (PLIF). Finally, a characterization of jet thermal turbulent state is proposed based on the Hurst parameter that is used for the identification of the long-term persistent behavior (or else called Hurst-Kolmogorov behaviour) of a process.

    Full text: http://www.itia.ntua.gr/en/getfile/1822/1/documents/EGU2018-17803-1.pdf (32 KB)

  1. P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Simulating precipitation at a fine time scale using a single continuous-state distribution, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18614, European Geosciences Union, 2018.

    Some hydrometeorological processes such as precipitation are usually modelled as two-state processes distinguishing the wet and dry state and simulating each of the two in different ways. It can be noted that the assignment of either of the two states in observation records involves some difficulties, as the accuracy of measurements in the area of low values is problematic. This is even more perplexed by the fact that the low values are the most frequent as in most rainfall records, measured at a fine temporal scale, the mode of the continuous part of the distribution is zero. However, the separation in two states may not be necessary. Here we apply a modelling framework of geophysical processes, such as precipitation, without treating them as two-state processes but with a single continuous-type distribution, which has very high densities at values close to zero. This requires the simulation of arbitrary marginal distributions, with very high skewness and kurtosis, as well as ability to preserve any dependence structure. These requirements can be satisfied in a rather simple manner using a recent simulation framework (Dimitriadis and Koutsoyiannis, 2017), which is here tested with fine time scale precipitation.

    Full text: http://www.itia.ntua.gr/en/getfile/1821/1/documents/EGU2018-18614.pdf (32 KB)

  1. P. Dimitriadis, and D. Koutsoyiannis, An innovative stochastic process and simulation algorithm for approximating any dependence structure and marginal distribution, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18710, European Geosciences Union, 2018.

    We present an innovative stochastic framework for the approximation of any dependence structure and marginal distribution. This framework is based on the concepts of ergodicity, stationarity and homogenization and can adequately simulate (through implicit and explicit methods) the correlation structure (from small to large scales), marginal distribution (with focus on the extreme left and right tails), internal periodicities (such as diurnal and seasonal) as well as certain aspects of the intermittent behaviour. We further introduce a flexible stochastic process and we apply it (following the suggested framework) to an abundant number of geophysical processes (such as temperature, dew-point, relative humidity, wind, streamflow, precipitation, atmospheric pressure and several turbulent microscale processes) and we seek for stochastic similarities in between them. Interestingly, all the examined processes exhibit fractal behaviour (at the small scales) and Hurst-Kolmogorov behaviour (at the large scales).

    Full text: http://www.itia.ntua.gr/en/getfile/1820/1/documents/EGU2018-18710.pdf (30 KB)

  1. K. Sakellari, P. Dimitriadis, and D. Koutsoyiannis, A global stochastic analysis for the temperature and dew-point processes, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17941-1, European Geosciences Union, 2018.

    Temperature and dew-point (or equivalently relative humidity) are considered as the most characteristic atmospheric process related to climate dynamics. In this study, we present an integrated stochastic framework, which can describe and simulate both the second-order dependence structure and the marginal distribution simultaneously. We use a large dataset comprising hourly temperature and dew point records around the globe to identify stochastic similarities and patterns. Based on these results we construct a parsimonious stochastic model that is based on entropy maximization and that can adequately simulate the correlation structure, extreme (left and right) tails, intermittent effects and internal double (diurnal and seasonal) periodicities.

    Full text: http://www.itia.ntua.gr/en/getfile/1819/1/documents/EGU2018-17941-1.pdf (31 KB)

  1. M. Chalakatevaki, E. Klousakou, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of the uncertainty of hydrometeorological processes by means of the climacogram, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17714-1, European Geosciences Union, 2018.

    An important characteristic of the atmospheric processes is their inherent uncertainty. As randomness and predictability coexist and are intrinsic to natural systems, these systems can be treated as deterministic and random at the same time, depending on the prediction horizon and the time scale. Specifically, the more complex a process is, the larger the Hurst parameter, which quantifies a natural behaviour (called Hurst-Kolmogorov HK), identified in numerous geophysical processes. Although several methods can be used to estimate the Hurst parameter, the climacogram (i.e. variance of the averaged process vs. scale; Koutsoyiannis, 2003) is one of the most powerful ones, with a lower statistical estimation uncertainty compared to the autocovariance and power spectrum. We apply the climacogram to real-world timeseries from various atmospheric processes in order to infer their dependence structure, characterize them and compare their degree of uncertainty across different timescales.

    Full text: http://www.itia.ntua.gr/en/getfile/1818/1/documents/EGU2018-17714-1.pdf (31 KB)

  1. G. Karakatsanis, E. Kontarakis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Hydroclimate and agricultural output in developing countries, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-13059-1, European Geosciences Union, 2018.

    According to international data on developing countries we observe a strong correlation of their Gross Domestic Product (GDP) to their agricultural output, suggesting that a large fraction of total income in the developing world derives from domestic agricultural value added. In addition, the significant lack of irrigation infrastructure (e.g. reservoirs and irrigation networks) forces these countries’ income into strong dependence from local hydroclimatological conditions; as the majority of crop output is -in turn- based on rain-fed agriculture. In our work we examine -via annual time-series analysis- the temporal dynamics between hydroclimate data (mainly precipitation), GDP, agricultural value added and the international prices of agricultural commodities, for developing countries, in order to study how these variables are mutually entwined in time. Furthermore, we perform various econometric tests on their correlation validity. An important aspect of our work concerns the detection of change in the composition of the economies of developing countries. Specifically, as developing countries acquire infrastructure it is highly probable to expect a gradual decoupling of the climate-agricultural output-GDP relationship.

    Full text: http://www.itia.ntua.gr/en/getfile/1817/1/documents/EGU2018-13059-1.pdf (33 KB)

  1. A. Tegos, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure and probability distribution of the global potential evapotranspiration, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17849-3, European Geosciences Union, 2018.

    We investigate the second-order dependence structure and marginal probability distribution of the potential evapotranspiration (PET) determined by a recently proposed parametric model at several locations worldwide. The dependence structure is estimated through the climacogram (i.e. variance of the averaged process vs. scale of averaging), which has some advantages over other stochastic metrics (such as autocovariance and power-spectrum). Furthermore, we discuss stochastic similarities and cross-correlations of the PET with the corresponding temperature, dew-point and wind.

    Full text: http://www.itia.ntua.gr/en/getfile/1815/1/documents/EGU2018-17849-3.pdf (30 KB)

  1. G.-F. Sargentis, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, and D. Koutsoyiannis, Stochastic investigation of the Hurst-Kolmogorov behaviour in arts, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17740-1, European Geosciences Union, 2018.

    The Hurst-Kolmogorov (HK) behaviour (i.e. power-law decrease of the process variance vs. scale of averaging) has been already identified in numerous geophysical processes highlighting the large uncertainty of Nature in all time scales. In this study, we investigate through the climacogram whether or not some art works (such as paintings, music pieces and poems) also exhibit this behaviour and try to interpret the results in terms of (un)predictability in works of art.

    Full text:

  1. S. Sigourou, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, A. Skopeliti, K. Sakellari, G. Karakatsanis, L. Tsoulos, and D. Koutsoyiannis, Comparison of climate change vs. urbanization, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18598-2, European Geosciences Union, 2018.

    Urbanization has long been identified as one of the major human impacts on the micro-climate of urban areas and has been linked to large (and often disastrous) changes into several hydroclimatic processes such as temperature, humidity and precipitation. However, climate change studies have rarely separated the urban local-scale influence from the global one. In this study, we thoroughly investigate and compare the changes in the variability of the above hydroclimatic processes in urban regions and in the ones with small or negligible human impact. The analysis includes global historical databases of the above processes as well as of the urbanization impact through land-use change.

    Full text: http://www.itia.ntua.gr/en/getfile/1810/1/documents/EGU2018-18598-2.pdf (31 KB)

  1. S. Sigourou, P. Dimitriadis, T. Iliopoulou, R. Ioannidis, A. Skopeliti, K. Sakellari, G. Karakatsanis, L. Tsoulos, and D. Koutsoyiannis, Statistical and stochastic comparison of climate change vs. urbanization, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-18608-2, European Geosciences Union, 2018.

    Urbanization has long been identified as one of the major human impacts on the micro-climate of urban areas and has been linked to large (and often disastrous) changes into several hydroclimatic processes such as temperature, humidity and precipitation. However, climate change studies have rarely separated the urban local-scale influence from the global one. In this study, we thoroughly investigate and compare the changes in the variability of the above hydroclimatic processes in urban regions and in the ones with small or negligible human impact. The analysis includes Monte-Carlo experiments to assess how the aforementioned variability can be simulated through a stochastic model.

    Full text: http://www.itia.ntua.gr/en/getfile/1809/1/documents/EGU2018-18608-2.pdf (31 KB)

  1. P. Dimitriadis, H. Tyralis, T. Iliopoulou, K. Tzouka, Y. Markonis, N. Mamassis, and D. Koutsoyiannis, A climacogram estimator adjusted for timeseries length; application to key hydrometeorological processes by the Köppen-Geiger classification, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17832, European Geosciences Union, 2018.

    We present a climacogram estimator (variance of the scaled process vs. scale) that employs all the available information through a pooled time series estimation approach. This method does not discard time-series of short length or of high percentage of missing values; a common practice in hydrometeorology. Furthermore, we estimate and compare the second-order dependence structure (overall and classified by the Köppen-Geiger system) over the last two climatic periods (60 years) for several processes (temperature, dew-point, wind, precipitation, river discharge and atmospheric pressure) using worldwide surface stations. This analysis is performed based on the standardized climacogram, which shows numerous benefits compared to the autocorrelation and standardized power-spectrum.

    Full text: http://www.itia.ntua.gr/en/getfile/1800/1/documents/EGU2018-17832.pdf (34 KB)

  1. Y. Markonis, Y. Moustakis, C. Nasika, P. Sychova, P. Dimitriadis, M. Hanel, P. Máca, and S.M. Papalexiou, Investigation of the factors that affect the auto-correlation structure of annual river runoff, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-7324, European Geosciences Union, 2018.

    The auto-correlation structure of annual river runoff is a topic of ongoing hydrological research, due to its implications to water resources management. Most studies have concluded that there is medium to strong long-term persistence (LTP), measured by the Hurst coefficient H. Here, we determine H by three different estimation methods (maximum likelihood estimator, Whittle estimator and least squares variance), in 696 annual, globally distributed, streamflow records with at least 80 years of data. Subsequently, we explore potential factors influencing H by two linear (Spearman’s rank correlation, multiple linear regression) and two non-linear (self-organizing maps, random forests) techniques. Catchment area is found to be crucial for medium to larger watersheds, while climatic controls, such as aridity index, have higher impact to smaller ones. Our findings indicate that long-term persistence is weaker (H = 0.65) than found in other studies, suggesting that enhanced LTP is encountered in large-catchment rivers, were the effect of spatial aggregation is more intense. However, we also show that the estimated values of H can be reproduced by a short-term persistence stochastic model such as an auto-regressive AR(1) process. A direct consequence is that some of the most common methods for the estimation of H coefficient, might not be suitable for discriminating short- and long-term persistence even in long observational records.

    Full text: http://www.itia.ntua.gr/en/getfile/1798/1/documents/EGU2018-7324.pdf (32 KB)

  1. A. Pizarro, P. Dimitriadis, C. Samela, D. Koutsoyiannis, O. Link, and S. Manfreda, Discharge uncertainty on bridge scour process, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-8045, European Geosciences Union, 2018.

    Floods are one of the most important factors on the bridge scour process. However, the uncertainty related to discharge is high due to the presence of clustering effects, the use of outdated rating curves, and the practical issue of measuring at extreme conditions. In this context, employing the best scour model with an uncertain discharge input leads to unreliable scour estimations. The goal of this research seeks to quantify the scour uncertainty due to the discharge uncertainty using stochastic tools and the BRISENT model [Pizarro et al., 2017] for discharge and scour analysis, respectively. To this aim, we examine several stations covering small and large temporal scales of the river discharge. These stations are selected under the criterion of ensuring low human influence on the natural process. The stochastic structure of discharge is modeled fitting the Hurst-Kolmogorov (HK) behavior in terms of the climacogram and a discharge generator was constructed based on the assumptions of homogeneity, stationarity, and ergodicity. Monte Carlo simulations of flood events coupled with the BRISENT model allow computing both the maximum scour depth for a fixed time interval (for instance, the bridge life) and the scour depth evolution over time. Results show that assuming a bridge life of 100 years and sufficient number of discharge simulations leads to a fixed non-exceedance scour probability distribution. Finally, the scour expected value is compared with two widely used in practice equilibrium scour predictive methods, i.e. (1) HEC-18 [Richardson and Davis, 2001], and (2) Chinese equation [Gao et al., 1993].

    Full text: http://www.itia.ntua.gr/en/getfile/1797/1/documents/EGU2018-8045.pdf (34 KB)

  1. A. Pizarro, P. Dimitriadis, M. Chalakatevaki, C. Samela, S. Manfreda, and D. Koutsoyiannis, An integrated stochastic model of the river discharge process with emphasis on floods and bridge scour, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-8271, European Geosciences Union, 2018.

    Floods have an important influence on society, being able to affect human life, human properties and also cultural heritage. Nevertheless, the dynamics of floods and their interaction with infrastructure over time is still unexplored. Therefore, there is a significant need for the development of new hydrologic and hydraulic modeling techniques able to represent the process in a realistic way. With this aim, the stochastic structure of the discharge has been modeled by a generalized Hurst-Kolmogorov (HK) process in terms of dependence structure (from long to short term) and marginal distribution (from left to right distribution tail). Several long length discharge time series have been filtered with the aim to ensure a minimum human influence on the discharge regime. Time series were analyzed using the climacogram stochastic tool for the analysis because of its good properties, such as small statistical errors, a priori known bias and a mean close to its mode. Finally, a general and parsimonious discharge model, with emphasis on floods, is coupled with a hydraulic model for long run numerical simulations. The authors are seeking to apply these ideas to evaluate the hydraulic infrastructure risk due to the discharge uncertainty and, in particular, to assess the bridge scour risk.

    Full text: http://www.itia.ntua.gr/en/getfile/1796/1/documents/EGU2018-8271.pdf (33 KB)

  1. A. Gkolemis, P. Dimitriadis, G. Karakatsanis, T. Iliopoulou, and D. Koutsoyiannis, A stochastic investigation of the intermittent behaviour of wind; application to renewable energy resources management, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-15979-3, European Geosciences Union, 2018.

    A challenging characteristic of renewable energy systems is intermittence of the related natural processes (such as wind), whose management imposes an additional cost. This also implies the need to immediate back up the extra supply (introduced by the resource’s physical bursts) to other units (e.g. in a hybrid pumped storage hydropower system). The complexity of this issue does not just rely on the need for optimizing the hybrid system but rather on the requirement for simulating these bursts. In this study, we introduce and test an innovative model for the wind process by simultaneously preserving not only the marginal distribution (including extreme events), correlation structure (from small to large scales) and internal double (diurnal and seasonal) periodicities but also its intermittent behaviour. Furthermore, we present a pilot application including a pumped storage hydropower system and we show how the additional cost imposed by the intermittent behaviour of wind can be estimated.

    Full text: http://www.itia.ntua.gr/en/getfile/1795/1/documents/EGU2018-15979-3.pdf (33 KB)

  1. Y. Kalogeris, P. Dimitriadis, T. Iliopoulou, V. Papadopoulos, and D. Koutsoyiannis, Investigation of the correlation structure behaviour through intermediate storage retention, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17247-1, European Geosciences Union, 2018.

    A typical problem in stochastic dynamics is the change of variability of a process through intermediate storage retention. In this study, we perform exhaustive Monte-Carlo experiments as to quantify this change through the estimation of the autovariance function, power-spectrum and climacogram (i.e. variance of scaled process vs. scale) and with focus in short-term (e.g. Markov or powered-exponential) and long-term (such as Hurst-Kolmogorov) processes. Also, we show how the simulation methods and results from this analysis can be used to perform a sensitivity analysis to real case applications of seismic activity through geological formations as well as of rainfall-runoff cross-correlations through soil.

    Full text: http://www.itia.ntua.gr/en/getfile/1794/1/documents/EGU2018-17247-1.pdf (29 KB)

  1. K. Tzouka, P. Dimitriadis, E. Varouchakis, and D. Koutsoyiannis, Stochastic investigation of the correlation structure of two-dimensional images of rocks from small to large scales, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17306-1, European Geosciences Union, 2018.

    We investigate the drop of variance vs. scale for geostatistical processes through the use of the climacogram-based variogram (CBV) and climacogram-based power-spectrum (CBS), where climacogram is the (plot of) variance of the space-averaged process vs. the spatial scale. Focus is given to the small and medium scale properties of the rocks and an attempt is made to link the CBV and CBS with these and provide certain stochastic characteristics based on their composition and resolution. The analysis is based both on microscale and macroscale data, as extracted from grayscale images of rocks. Also, comparisons are made, through Monte-Carlo experiments, to the autocovariance-based metrics (such as variogram and power-spectrum) for a variety of common (white noise, Markov and Hurst-Kolmogorov) processes. Finally, a parsimonious model is proposed that can adequately describe the second-order dependence structure of rocks for a large variety of scales.

    Full text: http://www.itia.ntua.gr/en/getfile/1793/1/documents/EGU2018-17306-1.pdf (31 KB)

  1. P. Dimitriadis, E. Varouchakis, T. Iliopoulou, G. Karatzas, and D. Koutsoyiannis, Stochastic investigation of the spatial variability of precipitation over Crete, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17155-1, European Geosciences Union, 2018.

    The island of Crete is located at the Eastern Mediterranean and is expected to be significantly affected by future climatic variations. The island is monitored from 82 rainfall stations that cover the whole area of the island. Information is available at monthly and annual basis since 1981. This work examines potential spatial and temporal rainfall variability by employing statistical tools (such as the climacogram, i.e. variance of the scaled process vs. scale) to identify potential similarities in the dependence structure and marginal probability distribution. Finally, the spatial analysis involves the application of novel spatial dependence functions as well as a common expression for the correlation structure and marginal density distribution.

    Full text: http://www.itia.ntua.gr/en/getfile/1792/1/documents/EGU2018-17155-1.pdf (30 KB)

  1. M. Nezi, P. Dimitriadis, A. Pizarro, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of the streamflow process adjusted for human impact, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-17473-1, European Geosciences Union, 2018.

    The streamflow process is important in water resources management and although it has been thoroughly examined in a stochastic framework, still an integrated model that takes into account the human impact has not yet been thoroughly studied. Here we examine several datasets, in numerous locations under different climatic regimes, with long time series comprising streamflow measurements from small and large catchments in order to identify patterns induced by human impact and in particular streamflow regulation by upstream reservoirs. Based on the above results and on the concepts of ergodicity, stationarity and homogeneity, we try to identify stochastic similarities in regulated flow regimes in different catchments.

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  1. G. Koudouris, P. Dimitriadis, T. Iliopoulou, G. Karakatsanis, and D. Koutsoyiannis, A stochastic model for hourly solar radiation process applied in renewable resources management, European Geosciences Union General Assembly 2018, Geophysical Research Abstracts, Vol. 20, Vienna, EGU2018-16275-2, European Geosciences Union, 2018.

    Since the beginning of the 21st century, the scientific community has made huge leaps to exploit renewable energy sources, with solar radiation being one of the most important. However, the variability of solar radiation has a significant impact on solar energy conversion systems, such as in photovoltaic systems, characterized by a fast and non-linear response to incident solar radiation. The performance prediction of these systems is typically based on hourly or daily data because those are usually available at these time scales. The aim of this work is to investigate the stochastic nature and time evolution of the solar radiation process in a daily and hourly step on a monthly basis scale, with the ultimate goal of creating a stochastic model capable of generating hourly solar radiation. For this purpose, an analysis was initially made at stations in Greece and then on a global scale. We propose a distribution that can adequately describe daily solar radiation and a new distribution consisting of the sum of two known distribution functions that is capable of capturing all aspects of the hourly solar radiation. Also, we exploit the clear sky index coefficient (T) for the double periodicity of the process, so as to achieve an integrated framework for the description of the solar radiation at all scales. Also, we use statistical tests and selection criteria, in order to verify the goodness of fit of the selected distribution. Then, we propose a cyclostationary model that can handle long-term persistence and reproduce the clear sky index coefficient (KT). The model can preserve the probability density function and also the dependence structure. Finally, we apply the proposed stochastic model to a theoretical case of renewable energy management, with an ultimate goal to maximize the financial profit of the production system.

    Full text: http://www.itia.ntua.gr/en/getfile/1790/1/documents/EGU2018-16275-2.pdf (32 KB)

  1. 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.

    Renewable energy resources, e.g., wind and solar energy, are characterized by great degree of uncertainty and in general, limited predictability, because of the irregular variability of the related geophysical processes. A simple and robust measure of the inherent uncertainty of a process is the Hurst parameter. Specifically, the more complex a process is, the larger the introduced uncertainty (unpredictability) and the larger the Hurst parameter. This behaviour (called Hurst-Kolmogorov, HK) has been identified in numerous geophysical processes. Although there are several methods for estimating the Hurst parameter, the climacogram (i.e. variance of the averaged process vs. scale of averaging) is one of the most powerful ones, with a lower statistical estimation uncertainty compared to the autocovariance and power spectrum. We apply the climacogram method to timeseries from processes related to renewable energy systems (wind, solar, ocean etc.) with the aim to characterize their degree of uncertainty and predictability across different timescales. We compare results among the different processes and we provide real-world examples of renewable energy systems management to illustrate the technical relevance of our findings.

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  1. 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.

    A plant-wide mathematical model has been developed in order to simulate the operation of urban wastewater treatment plants. The model consists of several sub-models, one for each treatment unit. The model is able to assess the effluent quality, the energy and chemicals consumption and the greenhouse gas emissions (GHG). The biological process model is based on a modification of the activated sludge model no.1 (ASM1) including all the biological processes related to N2O and CO2 production pathways. To simulate settling processes, a one-dimensional model was used which is based on the general flux theory for zone settling, while an anaerobic digestion sub-model based on a modification of activated digestion model no.1 (ADM1) was developed. Finally simulation of the other treatment units (pretreatment, primary treatment, gravity and mechanical thickening and dewatering) is based on mass balances based on the efficiency of each unit. It is well known that there is a high level of uncertainty when determining the appropriate values of the stoichiometric and kinetic parameters employed in the model’s kinetic equations. Most of these values are derived through experimental procedures conducted under different conditions thus presenting high variability. A Monte Carlo based approach was used to provide for the identification of the most important model’s stoichiometric and kinetic parameters that affects model’s results. The mathematical model takes into account the random fluctuation of these parameters by creating a range of possible values for each one of them and a corresponding probability distribution. Thus values selection is taking place in a pseudo-random way through a specific probability distribution (normal, lognormal, uniform, etc.). Based on the results prioritization of uncertainty sources was implemented.

    Full text: http://www.itia.ntua.gr/en/getfile/1788/1/documents/EGU2018-18719-1.pdf (34 KB)

  1. 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.

    A common issue in the river analysis is that most discharges measurements are taken from stage measurements and then an empirical expression is applied often called rating curves. There are several empirical relationships to determine the rating curves in order to estimate the river discharge when the water-surface is known and vice versa. Here, we investigate the stochastic uncertainty induced in empirical expressions of common rating curves. For this, we perform exhaustive Monte-Carlo experiments by assuming a theoretical stochastic structure (with or without fixed trends) for the river stage and we estimate the change in the dependence structure and marginal distribution of the river discharge. We further perform a sensitivity analysis on the input parameters of the common stage-discharge expressions in order to identify and estimate the overall induced uncertainty. Finally, we discuss on the results and we derive some preliminary conclusions on whether a stochastic structure (including trends) empirically estimated in terms of stage can be arbitrarily translated into discharge.

    Full text: http://www.itia.ntua.gr/en/getfile/1787/1/documents/EGU2018-18947-2.pdf (31 KB)

  1. 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.

    A recent flash flood event in the Mandra region west of Athens, Greece, turned urban roads into fast-flowing rivers, and caused many fatalities and economic damages. After this incident a great dispute arose whether the devastating results were due to the extreme nature of the storm event or to the poor flood protection works. In this study, we present a preliminary analysis of the urban flood inundation at the wider area by taking into account the uncertainty introduced by the input discharge, topography and hydraulic characteristics. Finally, we discuss how hydraulic works could reduce the severity of the event.

    Full text:

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

    1. Diakakis, M., N. Boufidis, J. M. Salanova Grau, E. Andreadakis, and I. Stamos, A systematic assessment of the effects of extreme flash floods on transportation infrastructure and circulation: The example of the 2017 Mandra flood, International Journal of Disaster Risk Reduction, 47, 101542, doi:10.1016/j.ijdrr.2020.101542, 2020.
    2. Kanellopoulos, T. D., A. P. Karageorgis, A. Kikaki, S. Chourdaki, I. Hatzianestis, I. Vakalas, and G.-A. Hatiris, The impact of flash-floods on the adjacent marine environment: the case of Mandra and Nea Peramos (November 2017), Greece, Journal of Coastal Conservation, 24, 56, doi:10.1007/s11852-020-00772-6, 2020.
    3. Diakakis, Μ., G. Deligiannakis, Z. Antoniadis, M. Melaki, N. K. Katsetsiadou, E. Andreadakis, N. I. Spyrou, and M. Gogou, Proposal of a flash flood impact severity scale for the classification and mapping of flash flood impacts, Journal of Hydrology, 590, 125452, doi:10.1016/j.jhydrol.2020.125452, 2020.

  1. 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.

    A recent storm event, of substantial yet unknown local intensity, in Western Attica (west of Athens, Greece) has caused a flash flood with many fatalities in the city of Mandra as well as material damages. After this incident a debate started on whether the devastating results were due to the extreme nature of the rainfall event or to the poor flood protection works. In this study, we present information gathered from several sources (including hydrometric data from a neighboring catchment, point rainfall data from the broader area of interest, satellite observations and audiovisual material) in an attempt to represent the rainfall-runoff event. We further analyze the available data to approximately estimate the return period of the storm event. Finally, we discuss on the feasibility of the prediction of this storm.

    Full text:

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

    1. Kanellopoulos, T. D., A. P. Karageorgis, A. Kikaki, S. Chourdaki, I. Hatzianestis, I. Vakalas, and G.-A. Hatiris, The impact of flash-floods on the adjacent marine environment: the case of Mandra and Nea Peramos (November 2017), Greece, Journal of Coastal Conservation, 24, 56, doi:10.1007/s11852-020-00772-6, 2020.

  1. 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.

    We investigate the computational challenges of a model for the integrated simulation – optimization of water and renewable energy fluxes, based on an example (hypothetical) hybrid water – energy system at a small non-connected island (Astypalaia, Greece). The system consists of a hydroelectric reservoir with pumped storage facilities, connected with system of wind and solar power plants. The model runs on hourly time step, using as inputs rainfall and temperature data, data for the water supply, irrigation and electric energy demands, as well as energy production data from wind and solar resources. The reservoir system attempts to fulfill the two water demands and regulate the energy excesses and deficits. Due to the fine time step of calculations and the use of synthetic time series of long horizon, the computational burden of simulation runs in an optimization framework is significant. In an attempt to minimize the computational load, particularly in optimizations, we investigate the use of surrogate approaches, through black-box sub-models (e.g., neural networks) that represent autonomous parts of the whole simulation procedure. The outcomes of surrogate models are compared with the corresponding outputs of the original model.

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  1. P. Dimitriadis, K. Tzouka, H. Tyralis, and D. Koutsoyiannis, Stochastic investigation of rock anisotropy based on the climacogram, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10632-1, European Geosciences Union, 2017.

    Anisotropy plays an important role on rock properties and entails valuable information for many fields of applied geology and engineering. Many methods are developed in order to detect transitions from isotropy to anisotropy but as a scale–depended effect, anisotropy also needs to be determined in multiple scales. We investigate the application of a stochastic tool, the climacogram (i.e. variance of the averaged process vs. scale) to characterize anisotropy in rocks at different length scales through image processing. The data are pictures from laboratory, specifically thin sections, and pictures of rock samples and rock formations in the field in order to examine anisotropy in nano, micro and macroscale.

    Additional material:

  1. P. Dimitriadis, T. Iliopoulou, H. Tyralis, and D. Koutsoyiannis, Identifying the dependence structure of a process through pooled timeseries analysis, IAHS Scientific Assembly 2017, Port Elizabeth, South Africa, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2017.

    Geophysical processes are known to exhibit significant departures from time-independence, ranging from short-range Markovian structure to Hurst-Kolmogorov behavior with large Hurst parameters. However, the identification of the dependence structure of a process is subject to many uncertainties, namely model uncertainty and estimation uncertainty particularly arising from the short length of available timeseries. Here we apply the climacogram (i.e. plot of the variance of the averaged process vs. scale) estimation method which has been shown to be the more robust and less uncertain among various stochastic metrics for the characterization of time-dependence. We further investigate the possibility of eliminating the sampling uncertainty by adequately employing all the available information through a pooled timeseries estimation approach, instead of discarding time-series of short length or of high percentage of missing values as typically performed in such tasks. We compare the merits and demerits of each approach as related to the strength of the dependence structure, the number and sample size of the available timeseries.

    Full text: http://www.itia.ntua.gr/en/getfile/1770/1/documents/IAHS2017-182-1.pdf (196 KB)

  1. H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, An extensive review and comparison of R Packages on the long-range dependence estimators, Asia Oceania Geosciences Society (AOGS) 14th Annual Meeting, Singapore, HS06-A003, doi:10.13140/RG.2.2.18837.22249, Asia Oceania Geosciences Society, 2017.

    The long-range dependence (LRD) is a well-established property of climatic variables such as temperature and precipitation. A long list of estimators of the LRD parameters exist while a few comparison studies of their properties have been published. The emergence of R as one of the favourite programming languages among the hydrological community and its increasing number of packages enable the fast implementation of statistical methods in hydrological studies. Many R packages include functions for the estimation of the parameter, which characterizes the LRD, e.g. the Hurst parameter of the Hurst-Kolmogorov behaviour or the d parameter of the ARFIMA model. Here we present an extensive review of all R packages containing functions used to estimate the LRD parameter. Furthermore, we examine the properties of the implemented estimators and we perform an extended simulation experiment to compare them.

    Full text: http://www.itia.ntua.gr/en/getfile/1721/1/documents/AOGS-HS06-A003presentation.pdf (1829 KB)

    Additional material:

  1. H. Tyralis, P. Dimitriadis, T. Iliopoulou, K. Tzouka, and D. Koutsoyiannis, Dependence of long-term persistence properties of precipitation on spatial and regional characteristics, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-3711, doi:10.13140/RG.2.2.13252.83840/1, European Geosciences Union, 2017.

    The long-term persistence (LTP), else known in hydrological science as the Hurst phenomenon, is a behaviour observed in geophysical processes in which wet years or dry years are clustered to respective long time periods. A common practice for evaluating the presence of the LTP is to model the geophysical time series with the Hurst-Kolmogorov process (HKp) and estimate its Hurst parameter H where high values of H indicate strong LTP. We estimate H of the mean annual precipitation using instrumental data from approximately 1 500 stations which cover a big area of the earth’s surface and span from 1916 to 2015. We regress the H estimates of all stations on their spatial and regional characteristics (i.e. their location, elevation and Köppen-Geiger climate class) using a random forest algorithm. Furthermore, we apply the Mann-Kendall test under the LTP assumption (MKt-LTP) to all time series to assess the significance of observed trends of the mean annual precipitation. To summarize the results, the LTP seems to depend mostly on the location of the stations, while the predictive value of the fitted regression model is good. Thus when investigating for LTP properties we recommend that the local characteristics should be considered. Additionally, the application of the MKt-LTP suggests that no significant monotonic trend can characterize the global precipitation. Dominant positive significant trends are observed mostly in main climate type D (snow), while in the other climate types the percentage of stations with positive significant trends was approximately equal to that of negative significant trends. Furthermore, 50% of all stations do not exhibit significant trends at all.

    Full text: http://www.itia.ntua.gr/en/getfile/1695/1/documents/EGU2017-3711presentation_.pdf (1608 KB)

    Additional material:

  1. 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.

    Non-connected islands to the electric gird are often depending on oil-fueled power plants with high unit cost. A hybrid energy system with renewable resources such as wind and solar plants could reduce this cost and also offer more environmental friendly solutions. However, atmospheric processes are characterized by high uncertainty that does not permit harvesting and utilizing full of their potential. Therefore, a more sophisticated framework that somehow incorporates this uncertainty could improve the performance of the system. In this context, we describe several stochastic and financial aspects of this framework. Particularly, we investigate the cross-correlation between several atmospheric processes and the energy demand, the possibility of mixing renewable resources with the conventional ones and in what degree of reliability, and critical financial subsystems such as weather derivatives. A pilot application of the above framework is also presented for a remote island in the Aegean Sea.

    Full text: http://www.itia.ntua.gr/en/getfile/1689/1/documents/EGU2017oral_16781_final.pdf (3038 KB)

    Additional material:

  1. P. Stamou, S. Karali, M. Chalakatevaki, V. Daniil, K. Tzouka, P. Dimitriadis, T. Iliopoulou, P. Papanicolaou, D. Koutsoyiannis, and N. Mamassis, Creating the electric energy mix of a non-connected Aegean island, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10130-10, doi:10.13140/RG.2.2.36537.77927, European Geosciences Union, 2017.

    As the electric energy in the non-connected islands is mainly produced by oil-fueled power plants, the unit cost is extremely high. Here the various energy sources are examined in order to create the appropriate electric energy mix for a non-connected Aegean island. All energy sources (renewable and fossil fuels) are examined and each one is evaluated using technical, environmental and economic criteria. Finally the most appropriate energy sources are simulated considering the corresponding energy works. Special emphasis is given to the use of biomass and the possibility of replacing (even partially) the existing oil-fueled power plant. Finally, a synthesis of various energy sources is presented that satisfies the electric energy demand taking into account the base and peak electric loads of the island.

    Full text: http://www.itia.ntua.gr/en/getfile/1688/2/documents/posterEGU.pdf (2687 KB)

    Additional material:

  1. E. Hadjimitsis, E. Demetriou, K. Sakellari, H. Tyralis, P. Dimitriadis, T. Iliopoulou, and D. Koutsoyiannis, Investigation of the stochastic nature of temperature and humidity for energy management, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10164-5, European Geosciences Union, 2017.

    Atmospheric temperature and dew point, in addition to their role in atmospheric processes, influence the management of energy systems since they highly affect the energy demand and production. Both temperature and humidity depend on the climate conditions and geographical location. In this context, we analyze numerous of observations around the globe and we investigate the long-term behaviour and periodicities of the temperature and humidity processes. Also, we present and apply a parsimonious stochastic double-cyclostationary model for these processes to an island in the Aegean Sea and investigate their link to energy management.

    Additional material:

  1. G. Koudouris, P. Dimitriadis, T. Iliopoulou, N. Mamassis, and D. Koutsoyiannis, Investigation of the stochastic nature of solar radiation for renewable resources management, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10189-4, doi:10.13140/RG.2.2.16215.06564, European Geosciences Union, 2017.

    A detailed investigation of the variability of solar radiation can be proven useful towards more efficient and sustainable design of renewable resources systems. This variability is mainly caused from the regular seasonal and diurnal variation, as well as its stochastic nature of the atmospheric processes, i.e. sunshine duration. In this context, we analyze numerous observations in Greece (Hellenic National Meteorological Service; http://www.hnms.gr/) and around the globe (NASA SSE - Surface meteorology and Solar Energy; http://www.soda-pro.com/webservices/radiation/nasa-sse) and we investigate the long-term behaviour and double periodicity of the solar radiation process. Also, we apply a parsimonious double-cyclostationary stochastic model to a theoretical scenario of solar energy production for an island in the Aegean Sea.

    Full text: http://www.itia.ntua.gr/en/getfile/1686/1/documents/SGU2017_solar_pres.pdf (1812 KB)

    Additional material:

  1. E. Moschos, G. Manou, C. Georganta, P. Dimitriadis, T. Iliopoulou, H. Tyralis, D. Koutsoyiannis, and V. Tsoukala, Investigation of the stochastic nature of wave processes for renewable resources management: a pilot application in a remote island in the Aegean sea, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, EGU2017-10225-3, doi:10.13140/RG.2.2.30226.66245, European Geosciences Union, 2017.

    The large energy potential of ocean dynamics is not yet being efficiently harvested mostly due to several technological and financial drawbacks. Nevertheless, modern renewable energy systems include wave and tidal energy in cases of nearshore locations. Although the variability of tidal waves can be adequately predictable, wind-generated waves entail a much larger uncertainty due to their dependence to the wind process. Recent research has shown, through estimation of the wave energy potential in coastal areas of the Aegean Sea, that installation of wave energy converters in nearshore locations could be an applicable scenario, assisting the electrical network of Greek islands. In this context, we analyze numerous of observations and we investigate the long-term behaviour of wave height and wave period processes. Additionally, we examine the case of a remote island in the Aegean sea, by estimating the local wave climate through past analysis data and numerical methods, and subsequently applying a parsimonious stochastic model to a theoretical scenario of wave energy production.

    Full text: http://www.itia.ntua.gr/en/getfile/1685/1/documents/EGU2017-10225-3_poster.pdf (3588 KB)

    Additional material:

  1. A. Koskinas, E. Zacharopoulou, G. Pouliasis, I. Engonopoulos, K. Mavroyeoryos, I. Deligiannis, G. Karakatsanis, P. Dimitriadis, T. Iliopoulou, D. Koutsoyiannis, and H. Tyralis, Simulation of electricity demand in a remote island for optimal planning of a hybrid renewable energy system, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10495-4, doi:10.13140/RG.2.2.10529.81767, European Geosciences Union, 2017.

    We simulate the electrical energy demand in the remote island of Astypalaia. To this end we first obtain information regarding the local socioeconomic conditions and energy demand. Secondly, the available hourly demand data are analysed at various time scales (hourly, weekly, daily, seasonal). The cross-correlations between the electrical energy demand and the mean daily temperature as well as other climatic variables for the same time period are computed. Also, we investigate the cross-correlation between those climatic variables and other variables related to renewable energy resources from numerous observations around the globe in order to assess the impact of each one to a hybrid renewable energy system. An exploratory data analysis including all variables is performed with the purpose to find hidden relationships. Finally, the demand is simulated considering all the periodicities found in the analysis. The simulation time series will be used in the development of a framework for planning of a hybrid renewable energy system in Astypalaia.

    Full text: http://www.itia.ntua.gr/en/getfile/1684/2/documents/EGU2017_CrossCorr-EnergyDemand.pdf (2668 KB)

    Additional material:

  1. D. Roussis, I. Parara, N. Gournari, Y. Moustakis, P. Dimitriadis, T. Iliopoulou, D. Koutsoyiannis, and G. Karakatsanis, Energy, variability and weather finance engineering, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-16919, European Geosciences Union, 2017.

    Most types of renewable energies are characterized by intense intermittency, causing significant instabilities to the grid; further requiring additional infrastructure (e.g. pumped-storage) for buffering hydrometeorological uncertainties, as well as complex operational rules for load balancing. In addition, most intermittent renewable units are subsidized, creating significant market inefficiencies.Weather derivatives comprise mature financial tools for integrating successfully the intermittent-load and base-load components into a unified hybrid energy system and establish their operation within a generalized uncertainty management market. With a growing global market share and 46% utilization of this financial tool by the energy industry and 12% by agriculture (that partially concerns biofuel resources), weather derivatives are projected to constitute a critical subsystem of many grids for buffering frequent hydrometeorological risks of low and medium impacts –which are not covered by standard insurance contracts that aim exclusively at extreme events and high financial damages. In this context, we study the attributes of hydrometeorological time series in a remote and small island in Greece, powered by an autonomous hybrid energy system. Upon the results we choose the optimal underlying index and we further compose and engineer a weather derivative with features of a typical option contract –which we consider most flexible and appropriate for the case– to test our assumptions on its beneficiary effects for both the budget of private energy producers and the island’s public administration.

    Additional material:

  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, European Geosciences Union General Assembly 2017, Geophysical Research Abstracts, Vol. 19, Vienna, 19, EGU2017-10334-4, European Geosciences Union, 2017.

    Small islands are regarded as promising areas for developing hybrid water-energy systems that combine multiple sources of renewable energy with pumped-storage facilities. Essential element of such systems is the water storage component (reservoir), which implements both flow and energy regulations. Apparently, the representation of the overall water-energy management problem requires the simulation of the operation of the reservoir system, which in turn requires a faithful estimation of water inflows and demands of water and energy. Yet, in small-scale reservoir systems, this task in far from straightforward, since both the availability and accuracy of associated information is generally very poor. For, in contrast to large-scale reservoir systems, for which it is quite easy to find systematic and reliable hydrological data, in the case of small systems such data may be minor or even totally missing. The stochastic approach is the unique means to account for input data uncertainties within the combined water-energy management problem. Using as example the Livadi reservoir, which is the pumped storage component of the small Aegean island of Astypalaia, Greece, we provide a simulation framework, comprising: (a) a stochastic model for generating synthetic rainfall and temperature time series; (b) a stochastic rainfall-runoff model, whose parameters cannot be inferred through calibration and, thus, they are represented as correlated random variables; (c) a stochastic model for estimating water supply and irrigation demands, based on simulated temperature and soil moisture, and (d) a daily operation model of the reservoir system, providing stochastic forecasts of water and energy outflows.

    Related works:

    • [28] Associated paper in Energy Procedia

    Full text: http://www.itia.ntua.gr/en/getfile/1682/2/documents/2017_EGU_RRproject_final.pdf (2019 KB)

    Additional material:

  1. P. Dimitriadis, Y. Markonis, T. Iliopoulou, E. Feloni, N. Gournari, I. Deligiannis, P. Kastis, C. Nasika, E. Lerias, Y. Moustakis, A. Petsiou, A. Sotiriadou, A. Markopoulos, V. Tyrogiannis, and D. Koutsoyiannis, Stochastic similarities between hydroclimatic processes for variability characterization, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, European Geosciences Union, 2016.

    The most important hydroclimatic processes such as temperature, dew point, wind, precipitation and river discharges are investigated for their stochastic behaviour on annual scale through several historical records. We investigate the stochastic similarities between them in terms of long-term persistence and we comment on their statistical variability giving emphasis on the last period. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

    Full text: http://www.itia.ntua.gr/en/getfile/1954/1/documents/StochSimilHydroClim2016.pdf (2569 KB)

  1. I. Deligiannis, P. Dimitriadis, and D. Koutsoyiannis, Hourly temporal distribution of wind, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, 18, EGU2016-13138-4, doi:10.13140/RG.2.2.25967.53928, European Geosciences Union, 2016.

    The wind process is essential for hydrometeorology and additionally, is one of the basic renewable energy resources. Most stochastic forecast models are limited up to daily scales disregarding the hourly scale which is significant for renewable energy management. Here, we analyze hourly wind timeseries giving emphasis on the temporal distribution of wind within the day. We finally present a periodic model based on statistical as well as hydrometeorological reasoning that shows good agreement with data.

    Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

    Full text: http://www.itia.ntua.gr/en/getfile/1769/1/documents/2016EGU_DELIGIANNIS_Wind.pdf (2997 KB)

    Additional material:

  1. E. Lerias, A. Kalamioti, P. Dimitriadis, Y. Markonis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of temperature process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14828-3, European Geosciences Union, 2016.

    The temperature process is considered as the most characteristic hydrometeorological process and has been thoroughly examined in the climate-change framework. We use a dataset comprising hourly temperature and dew point records to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e. mean process variance vs. scale) for various time periods.

    Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly

    Full text: http://www.itia.ntua.gr/en/getfile/1660/1/documents/TempDewP.pdf (2727 KB)

    Additional material:

  1. I. Deligiannis, V. Tyrogiannis, Ο. Daskalou, P. Dimitriadis, Y. Markonis, T. Iliopoulou, and D. Koutsoyiannis, Stochastic investigation of wind process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14946-6, doi:10.13140/RG.2.2.26681.36969, European Geosciences Union, 2016.

    The wind process is considered one of the hydrometeorological processes that generates and drives the climate dynamics. We use a dataset comprising hourly wind records to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e. mean process variance vs. scale) for various time periods.

    Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

    Full text:

    Additional material:

  1. A. Sotiriadou, A. Petsiou, E. Feloni, P. Kastis, T. Iliopoulou, Y. Markonis, H. Tyralis, P. Dimitriadis, and D. Koutsoyiannis, Stochastic investigation of precipitation process for climatic variability identification, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-15137-5, doi:10.13140/RG.2.2.28955.46881, European Geosciences Union, 2016.

    The precipitation process is important not only to hydrometeorology but also to renewable energy resources management. We use a dataset consisting of daily and hourly records around the globe to identify statistical variability with emphasis on the last period. Specifically, we investigate the occurrence of mean, maximum and minimum values and we estimate statistical properties such as marginal probability distribution function and the type of decay of the climacogram (i.e. mean process variance vs. scale).

    Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.

    Full text: http://www.itia.ntua.gr/en/getfile/1658/1/documents/RainP.pdf (3820 KB)

    Additional material:

  1. P. Dimitriadis, N. Gournari, and D. Koutsoyiannis, Markov vs. Hurst-Kolmogorov behaviour identification in hydroclimatic processes, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-14577-4, doi:10.13140/RG.2.2.21019.05927, European Geosciences Union, 2016.

    Hydroclimatic processes are usually modelled either by exponential decay of the autocovariance function, i.e. Markovian behaviour, or power type decay, i.e. long-term persistence (or else Hurst-Kolmogorov behaviour). For the identification and quantification of such behaviours several graphical stochastic tools can be used such as the climacogram (i.e. plot of the variance of the averaged process vs. scale), autocovariance, variogram, power spectrum etc. with the former usually exhibiting smaller statistical uncertainty as compared to the others. However, most methodologies including these tools are based on the expected value of the process. In this analysis, we explore a methodology that combines both the practical use of a graphical representation of the internal structure of the process as well as the statistical robustness of the maximum-likelihood estimation. For validation and illustration purposes, we apply this methodology to fundamental stochastic processes, such as Markov and Hurst-Kolmogorov type ones.

    Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly

    Full text: http://www.itia.ntua.gr/en/getfile/1657/1/documents/MvHP.pdf (777 KB)

    Additional material:

  1. Y. Markonis, C. Nasika, Y. Moustakis, A. Markopoulos, P. Dimitriadis, and D. Koutsoyiannis, Global investigation of Hurst-Kolmogorov behaviour in river runoff, European Geosciences Union General Assembly 2016, Geophysical Research Abstracts, Vol. 18, Vienna, EGU2016-17491, doi:10.13140/RG.2.2.16331.59684, European Geosciences Union, 2016.

    Long-term persistence or Hurst-Kolmogorov behaviour is a well-studied property of river discharge. Here, we use a large dataset (GRDC international archive), which counts over 2100 records above 60 years, 450 of which are also above 100 years, to examine the dependence structure of the monthly mean, and annual maxima and minima. We estimate the Hurst coefficient H, using Maximum Likelihood and Climacogram-based estimation methods for record lengths between 60 and 208 years, and investigate the sample size effect on the estimation (in subsets of 60-80, 80-100, 100-120 and above 120 years). We further extend our investigation by exploring the roles of catchment size, runoff mean values, altitude of gauge, location (zonal: tropical, mid-latitude, high-latitude), climatic type (Koppen classification) to H estimates. Finally, we investigate whether or not there are any links ˝ between H and the statistical properties of regional precipitation and temperature (including mean, coefficient of variation, auto-correlation and H coefficient of the latter processes).

    Full text: http://www.itia.ntua.gr/en/getfile/1652/1/documents/EGU2016HK_Rivers.pdf (1636 KB)

    Additional material:

  1. D. Koutsoyiannis, F. Lombardo, P. Dimitriadis, Y. Markonis, and S. Stevens, From fractals to stochastics: seeking theoretical consistency in analysis of geophysical data, 30 Years of Nonlinear Dynamics in Geosciences, Rhodes, Greece, doi:10.13140/RG.2.2.34215.55209, 2016.

    Fractal-based techniques have opened new avenues in the analysis of geophysical data. On the other hand, there is often a lack of appreciation of both the statistical uncertainty in the results, and the theoretical properties of the stochastic concepts associated with these techniques. Several examples are presented which illustrate suspect results of fractal techniques. It is proposed that concepts used in fractal analyses are stochastic concepts and the fractal techniques can readily be incorporated into the theory of stochastic processes. This would be beneficial in studying biases and uncertainties of results in a theoretically consistent framework, and in avoiding unfounded conclusions. In this respect, a general methodology for theoretically justified stochastic processes, which evolve in continuous time and stem from maximum entropy production considerations, is proposed. Some important modelling issues are discussed with focus on model identification and fitting, which are often made using inappropriate methods. The theoretical framework is applied to several processes, including turbulent velocities measured every several microseconds and hydroclimatic processes, whose proxy reconstructions can provide information for time scales up to millions of years.

    Full text: http://www.itia.ntua.gr/en/getfile/1627/1/documents/2016RhodesStochastics__.pdf (3402 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.34215.55209

  1. D. Koutsoyiannis, and P. Dimitriadis, From time series to stochastics: A theoretical framework with applications on time scales spanning from microseconds to megayears, Orlob Second International Symposium on Theoretical Hydrology, Davis, California, USA, doi:10.13140/RG.2.2.14082.89284, University California Davis, 2016.

    “Time series” has been an ambiguous term, sometimes referring to a series of measurements and other times used as synonymous to a stochastic process in discrete time. This ambiguity has been harmful to several scientific disciplines, theoretical and applied including hydrology, as it has hampered the understanding of the difference between a number and the abstract object called a random variable. Furthermore, what has been known as “time series models”, such as ARMA models have been equally misleading, as they are often non-parsimonious or overfitted, unnatural or artificial, theoretically unjustified and, eventually, unnecessary.

    We present a general methodology for more theoretically justified stochastic processes, which evolve in continuous time and stem from maximum entropy production considerations, thereby enabling parsimonious modelling. The discrete-time properties of the processes are theoretically derived from the continuous-time ones and a general simulation methodology in discrete time is built, which explicitly handles the effects of discretization and truncation. Some additional modelling issues are discussed with focus on model identification and fitting, which are often made using inappropriate methods.

    We apply the theoretical framework for several processes, including turbulent velocities measured every several microseconds and hydroclimatic processes, whose proxy reconstructions can provide information for time scales up to millions of years.

    Full text: http://www.itia.ntua.gr/en/getfile/1618/1/documents/2016OrlobDavisStochastics3.pdf (3441 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.14082.89284

  1. 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.

    Following the legislative EU targets and taking advantage of its high renewable energy potential, Greece can obtain significant benefits from developing its water, solar and wind energy resources. In this context we present a GIS-based methodology for the optimal sizing and siting of solar and wind energy systems at the regional scale, which is tested in the Prefecture of Thessaly. First, we assess the wind and solar potential, taking into account the stochastic nature of the associated meteorological processes (i.e. wind speed and solar radiation, respectively), which is essential component for both planning (i.e. type selection and sizing of photovoltaic panels and wind turbines) and management purposes (i.e. real-time operation of the system). For the optimal siting, we assess the efficiency and economic performance of the energy system, also accounting for a number of constraints, associated with topographic limitations (e.g., terrain slope, proximity to road and electricity grid network, etc.), the environmental legislation and other land use constraints. Based on this analysis, we investigate favorable alternatives using technical, environmental as well as financial criteria. The final outcome is GIS maps that depict the available energy potential and the optimal layout for photovoltaic panels and wind turbines over the study area. We also consider a hypothetical scenario of future development of the study area, in which we assume the combined operation of the above renewables with major hydroelectric dams and pumped-storage facilities, thus providing a unique hybrid renewable system, extended at the regional scale.

    Full text: http://www.itia.ntua.gr/en/getfile/1609/2/documents/2016EGU_RenewablesOptLocation.pdf (1719 KB)

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.19535.48803

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

    1. Wu, Y., T. Zhang, C. Xu, B. Zhang, L. Li, Y. Ke, Y. Yan, and R. Xu, Optimal location selection for offshore wind-PV-seawater pumped storage power plant using a hybrid MCDM approach: A two-stage framework, Energy Conversion and Management, 199, doi:10.1016/j.enconman.2019.112066, 2019.

  1. P. Dimitriadis, L. Lappas, Ο. Daskalou, A. M. Filippidou, M. Giannakou, Ε. Gkova, R. Ioannidis, Α. Polydera, Ε. Polymerou, Ε. Psarrou, A. Vyrini, S.M. Papalexiou, and D. Koutsoyiannis, Application of stochastic methods for wind speed forecasting and wind turbines design at the area of Thessaly, Greece, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-13810, doi:10.13140/RG.2.2.25355.08486, European Geosciences Union, 2015.

    Several methods exist for estimating the statistical properties of wind speed, most of them being deterministic or probabilistic, disregarding though its long-term behaviour. Here, we focus on the stochastic nature of wind. After analyzing several historical timeseries at the area of interest (AoI) in Thessaly (Greece), we show that a Hurst-Kolmogorov (HK) behaviour is apparent. Thus, disregarding the latter could lead to unrealistic predictions and wind load situations, causing some impact on the energy production and management. Moreover, we construct a stochastic model capable of preserving the HK behaviour and we produce synthetic timeseries using a Monte-Carlo approach to estimate the future wind loads in the AoI. Finally, we identify the appropriate types of wind turbines for the AoI (based on the IEC 61400 standards) and propose several industrial solutions.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.25355.08486

  1. 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.

    Within the ongoing research project “Combined Renewable Systems for Sustainable Energy Development” (CRESSENDO), we have developed a novel stochastic simulation framework for optimal planning and management of large-scale hybrid renewable energy systems, in which hydropower plays the dominant role. The methodology and associated computer tools are tested in two major adjacent river basins in Greece (Acheloos, Peneios) extending over 15 500 km2 (12% of Greek territory). River Acheloos is characterized by very high runoff and holds ~40% of the installed hydropower capacity of Greece. On the other hand, the Thessaly plain drained by Peneios – a key agricultural region for the national economy – usually suffers from water scarcity and systematic environmental degradation. The two basins are interconnected through diversion projects, existing and planned, thus formulating a unique large-scale hydrosystem whose future has been the subject of a great controversy. The study area is viewed as a hypothetically closed, energy-autonomous, system, in order to evaluate the perspectives for sustainable development of its water and energy resources. In this context we seek an efficient configuration of the necessary hydraulic and renewable energy projects through integrated modelling of the water and energy balance. We investigate several scenarios of energy demand for domestic, industrial and agricultural use, assuming that part of the demand is fulfilled via wind and solar energy, while the excess or deficit of energy is regulated through large hydroelectric works that are equipped with pumping storage facilities. The overall goal is to examine under which conditions a fully renewable energy system can be technically and economically viable for such large spatial scale.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.17726.69440

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

    1. Stamou, A. T., and P. Rutschmann, Pareto optimization of water resources using the nexus approach, Water Resources Management, 32, 5053-5065, doi:10.1007/s11269-018-2127-x, 2018.
    2. 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. 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.

    We present a multi-criteria simulation-optimization framework for the optimal design and setting of flood protection structures along river banks. The methodology is tested in the lower course of the Arachthos River (Epirus, Greece), downstream of the hydroelectric dam of Pournari. The entire study area is very sensitive, particularly because the river crosses the urban area of Arta, which is located just after the dam. Moreover, extended agricultural areas that are crucial for the local economy are prone to floods. In the proposed methodology we investigate two conflicting criteria, i.e. the minimization of flood hazards (due to damages to urban infrastructures, crops, etc.) and the minimization of construction costs of the essential hydraulic structures (e.g. dikes). For the hydraulic simulation we examine two flood routing models, named 1D HEC-RAS and quasi-2D LISFLOOD, whereas the optimization is carried out through the Surrogate-Enhanced Evolutionary Annealing-Simplex (SE-EAS) algorithm that couples the strengths of surrogate modeling with the effectiveness and efficiency of the EAS method.

    Full text:

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

    1. Xu, Z., P. Plink-Björklund, S. Wu, Z. Liu, W. Feng, K. Zhang, Z. Yang, and Y. Zhong, Sinuous bar fingers of digitate shallow‐water deltas: Insights into their formative processes and deposits from integrating morphological and sedimentological studies with mathematical modelling, Sedimentology, doi:10.1111/sed.12923, 2021.

  1. P. Dimitriadis, and D. Koutsoyiannis, Using multiple stochastic tools in identification of scaling in hydrometeorology, AGU 2014 Fall Meeting, San Francisco, USA, American Geophysical Union, 2014.

    The identification and quantification of stochastic scaling laws has been an important task in modelling of hydrometeorological processes. Stochastic tools such as the power spectrum, autocovariance function, structure and climacogram have been among the most powerful. However, the common practice of using solely one of them may lead to process misinterpretation. We introduce a methodology that compares these stochastic tools and seeks the optimal one for different scales in terms of minimizing fitting errors. For validation and illustration purposes, we apply this methodology to various fundamental stochastic processes, such as Markovian, Hurst-Kolmogorov (HK) and Cauchy type ones. For each one, we produce Gaussian synthetic time series, we estimate the uncertainty of their expected values and finally, we conclude upon the ones with the smallest uncertainty. Furthermore, we apply this method to a real case time-series of high resolution turbulent flow velocities.

    Full text: http://www.itia.ntua.gr/en/getfile/1952/1/documents/MultipleStochasticTools2014.pdf (1791 KB)

  1. I. Pappa, Y. Dimakos, P. Dimas, P. Kossieris, P. Dimitriadis, and D. Koutsoyiannis, Spatial and temporal variability of wind speed and energy over Greece, European Geosciences Union General Assembly 2014, Geophysical Research Abstracts, Vol. 16, Vienna, EGU2014-13591, doi:10.13140/RG.2.2.11238.63048, European Geosciences Union, 2014.

    To appraise the wind potential over Greece we analyse the main statistical properties of wind speed through time. To this end, we use 66 time series from 1932 to 2013 on daily and monthly time scale and examine the spatial variability of wind speed over Greece. To depict the main statistical behavior and potential of the wind over Greece, maps have been created illustrating the basic statistical characteristics of wind speed on monthly to annual time scale. We also examine time series of energy production from the currently developed system of key wind parks and we compare the theoretical potential with the actually produced energy. Finally, we explore a methodology to simulate wind energy production in a stochastic framework. In that context we generate hourly wind speed synthetic data using a modified Bartlett-Lewis model implemented in Hyetos. The results of our analysis offer an improved overall picture of wind speed variability over Greece and help us clarify to which extent Hyetos is applicable in the stochastic generation of wind speed time series.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.11238.63048

  1. P. Dimitriadis, D. Koutsoyiannis, and C. Onof, N-Dimensional generalized Hurst-Kolmogorov process and its application to wind fields, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.15642.64963, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.

    An N-dimensional generalized Hurst-Kolmogorov stochastic model is presented that can simulate time-varying spatial geophysical fields, consistent with the observed long-term spatial and temporal persistence. The model is tested through some applications based on time-varying wind velocity field.

    Full text: http://www.itia.ntua.gr/en/getfile/1411/1/documents/2013Kos_ND_Hurst.pdf (7096 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.15642.64963

  1. P. Dimitriadis, D. Koutsoyiannis, and P. Papanicolaou, Climacogram-based modelling of isotropic turbulence, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.

    The stochastic structure of isotropic and homogeneous turbulence is studied in terms of its climacogram. A stochastic model is presented and tested over observational data of different scales and isotropy ratios. Observational data include solar wind, atmospheric wind velocities, laboratory scale wind velocities and turbulent buoyant jet concentrations. Theoretical expressions of the spectrum, structural and autocorrelation functions produced directly from the model show good agreement with data and differences from the existing models of turbulence.

  1. P. Dimitriadis, K. Tzouka, and D. Koutsoyiannis, Windows of predictability in dice motion, Facets of Uncertainty: 5th EGU Leonardo Conference – Hydrofractals 2013 – STAHY 2013, Kos Island, Greece, doi:10.13140/RG.2.2.19417.52322, European Geosciences Union, International Association of Hydrological Sciences, International Union of Geodesy and Geophysics, 2013.

    Dice throw experiments are performed based on visualization techniques. Video frames taken with frequency of 120 Hz are retrieved making it possible to monitor the dice trajectories in time and space. A statistical analysis is performed on the observations and a model is built to predict the state of the die a few frames later. The time window for which the prediction has some skill is then studied. The results show that even in dice throws, which are commonly used to symbolize randomness, there is some predictability for short horizons.

    Full text: http://www.itia.ntua.gr/en/getfile/1394/1/documents/2013Kos_DiceGame_1.pdf (1945 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.19417.52322

  1. 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.

    Flood engineering is typically tackled as a sequential application of formulas and models, with specific assumptions and parameter values, thus providing fully deterministic outputs. In this procedure, the unique probabilistic concept is the return period of rainfall, which is set a priori, to represent the acceptable risk of all design variables of interest (peak flows, flood hydrographs, flow depths and velocities, inundated areas, etc.). Yet, a more consistent approach would require estimating the risks by integrating the uncertainties of all individual variables. This option can be offered by stochastic simulation, which is the most effective and powerful technique for analysing systems of high complexity and uncertainty. This presupposes to recognize which of the modelling components represent time-varying processes and which ones represent unknown, thus uncertain, parameters. In the proposed framework both should be handled as random variables. The following computational steps are envisaged: (a) generation of synthetic time series of areal rainfall, through multivariate stochastic disaggregation models; (b) generation of random sets of initial soil moisture conditions; (c) run of hydrological and hydraulic simulation models with random sets of parameter values, picked from suitable distributions; (d) statistical analysis of the model outputs and determination of empirical pdfs; and (e) selection of the design value, which corresponds to the acceptable risk. This approach allows for estimating the full probability distribution of the output variables, instead of a unique value, as resulted by the deterministic procedure. In this context, stochastic simulation also offers the means to introduce the missing culture of uncertainty appreciation in flood engineering.

    Full text: http://www.itia.ntua.gr/en/getfile/1384/1/documents/KosFloodStochSim.pdf (1860 KB)

    See also: http://dx.doi.org/10.13140/RG.2.2.16848.51201

  1. V. Pagana, A. Tegos, P. Dimitriadis, A. Koukouvinos, P. Panagopoulos, and N. Mamassis, Alternative methods in floodplain hydraulic simulation - Experiences and perspectives, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10283-2, European Geosciences Union, 2013.

    Floods can simply be defined as the physical phenomena, during which an initially dry land area is covered by water. Floods are normally caused by extreme weather conditions, while their evolution depends mainly on geomorphologic factors, such as soil stability, vegetation cover, as well as the geometrical characteristics of the river basin. To prevent floods’ consequences, we have to study the hydraulic behavior of all the basins. Here, the study is focused on the upstream part of the Rafina basin, located in the east of Athens (Greece). Particularly, a hydraulic simulation is accomplished via the one-dimensional HEC-RAS and the quasi-two-dimensional LISFLOOD-FP and FLO-2D models. Additionally, a sensitivity analysis is carried out to investigate the effects of the floodplain and river roughness coefficients on the flood inundation in conjunction with a modern probabilistic view. Finally, a comparison between the three models is made regarding the simulated maximum water depth and maximum flow velocity.

    Full text:

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

    1. #Μίχας, Σ. Ν., Κ. Ι. Νικολάου, Σ. Λ. Λαζαρίδου, και Μ. Ν. Πικούνης, Σύγκριση μαθηματικών ομοιωμάτων διόδευσης πλημμυρικού κύματος από υποθετική θραύσης φράγματος Αγιόκαμπου, Πρακτικά 2ου Πανελλήνιου Συνεδρίου Φραγμάτων και Ταμιευτήρων, Αθήνα, Αίγλη Ζαππείου, Ελληνική Επιτροπή Μεγάλων Φραγμάτων, 2013.

  1. A. Oikonomou, P. Dimitriadis, A. Koukouvinos, A. Tegos, V. Pagana, P. Panagopoulos, N. Mamassis, and D. Koutsoyiannis, Floodplain mapping via 1D and quasi-2D numerical models in the valley of Thessaly, Greece, European Geosciences Union General Assembly 2013, Geophysical Research Abstracts, Vol. 15, Vienna, EGU2013-10366, doi:10.13140/RG.2.2.25165.03040, European Geosciences Union, 2013.

    The European Union Floods Directive defines a flood as ‘a covering by water of land not normally covered by water’. Human activities, such as agriculture, urban development, industry and tourism, contribute to an increase in the likelihood and adverse impacts of flood events. The study of the hydraulic behaviour of a river is important in flood risk management. Here, we investigate the behaviour of three hydraulic models, with different theoretical frameworks, in a real case scenario. The area is located in the Penios river basin, in the plain of Thessaly (Greece). The three models used are the one-dimensional HEC-RAS and the quasi two-dimensional LISFLOOD-FP and FLO-2D which are compared to each other, in terms of simulated maximum water depth as well as maximum flow velocity, and to a real flood event. Moreover, a sensitivity analysis is performed to determine how each simulation is affected by the river and floodplain roughness coefficient, in terms of flood inundation.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.25165.03040

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

    1. #Μίχας, Σ. Ν., Κ. Ι. Νικολάου, Σ. Λ. Λαζαρίδου, και Μ. Ν. Πικούνης, Σύγκριση μαθηματικών ομοιωμάτων διόδευσης πλημμυρικού κύματος από υποθετική θραύσης φράγματος Αγιόκαμπου, Πρακτικά 2ου Πανελλήνιου Συνεδρίου Φραγμάτων και Ταμιευτήρων, Αθήνα, Αίγλη Ζαππείου, Ελληνική Επιτροπή Μεγάλων Φραγμάτων, 2013.

  1. P. Dimitriadis, D. Koutsoyiannis, and Y. Markonis, Spectrum vs Climacogram, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-993, doi:10.13140/RG.2.2.27838.89920, European Geosciences Union, 2012.

    Two common stochastic tools, the spectrum and the climacogram are compared. Using time series from (a) a couple of simple harmonic functions, (b) synthetic data generated using a complex stochastic model, (c) a large-scale paleoclimatic reconstructions and (d) laboratory-scale measurements of turbulent velocity, we estimate the spectra (using fast Fourier transform) and climacograms. Both original and smooth versions of the spectra are used. The spectrum and the climacogram tools are compared to each other giving emphasis to each advantages and disadvantages and also, some questions regarding the interpretation and inference from the above methods, are discussed.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.27838.89920

  1. P. Dimitriadis, M. Liveri-Dalaveri, A. Kaldis, C. Kotsalos, G. Papacharalampous, and P. Papanicolaou, Zone of flow establishment in turbulent jets, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-12716, European Geosciences Union, 2012.

    It is well established experimentally that as the Reynolds number increases the core of the jet diminishes and has smaller effects on the jet’s mean profiles (e.g. concentration, temperature, velocity). The scope of this project is to examine this relationship based on dimensional analysis and experimental data. For that, spatio-temporal temperature records are obtained on the plane of symmetry of heated vertical round jets (for a laboratory turbulent scale at the order of mm) using tracer concentration measurements via a planar laser induced fluorescence technique (PLIF). The investigation area is set close to the nozzle of the jets (5-6 diameters away), at the zone of flow establishment (ZFE), so as to determine the geometric characteristics (dimensions and shape) of the core as a function of the initial velocity and nozzle diameter. The ZFE is estimated through the absence of turbulent intensity fluctuations (assuming a 1% of the maximum intensity as a threshold value).

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  1. P. Dimitriadis, and P. Papanicolaou, Statistical analysis of turbulent positively buoyant jets, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, EGU2012-12672, European Geosciences Union, 2012.

    The future aim of this work is to create a statistical model for turbulent positively buoyant jets. For this, a statistical analysis is presented here, for a two-dimensional (2D) spatio-temporal temperature records obtained from tracer concentration measurements on the plane of symmetry of vertical heated jet. Some of the statistical tools used in this analysis are the probability and probability density distributions, energy spectrum, climacogram and Hurst coefficient distribution, autocorrelation and structural functions. Moreover, the above measurements are compared with existing ones from the literature.

    Full text:

  1. S. Giannoulis, C. Ioannou, E. Karantinos, L. Malatesta, G. Theodoropoulos, G. Tsekouras, A. Venediki, P. Dimitriadis, S.M. Papalexiou, and D. Koutsoyiannis, Long term properties of monthly atmospheric pressure fields, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 4680, doi:10.13140/RG.2.2.36017.79201, European Geosciences Union, 2012.

    We assess the statistical properties of atmospheric pressure time series retrieved from a large database of monthly records. We analyze the short and long term properties of the time series including possible trends, persistence and antipersistence. We also analyze times series of climatic indices which are based on the atmospheric pressure fields, such as the North Atlantic oscillation index and the El Niño-Southern Oscillation index.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.36017.79201

  1. P. Dimitriadis, P. Papanicolaou, and D. Koutsoyiannis, Hurst-Kolmogorov dynamics applied to temperature fields for small turbulence scales, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-772, doi:10.13140/RG.2.2.22137.26724, European Geosciences Union, 2011.

    Two-dimensional (2D) spatio-temporal temperature records obtained from tracer concentration measurements on the plane of symmetry of heated jets (small turbulence scale) are statistically analyzed and the presence of Hurst-Kolmogorov (HK) dynamics is detected. The 2D HK process is then fitted to the data and synthetic time-varying and/or spatial fields are generated for temperature, which are consistent with the observed. Moreover, the 2D HK process is formulated assuming anisotropy, so as to take into account possibly different autocorrelation decay rates (Hurst coefficients) in each dimension of the field. In addition, the results are also investigated in comparison with Kolmogorov’s power spectrum model K41.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.22137.26724

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

    1. #Deskos, G. B., P. G. Dimitriadis and P. N. Papanicolaou, Density stratification in the mixed regime of a buoyant jet in confined ambient, Proceedings of the 2nd Joint Conference of EYE-EEDYP "Integrated Water Resources Management for Sustainable Development" (Ed.: P. Giannopoulos and A. Dimas), 200-211, Patras, Greece, 2012.

  1. P. Dimitriadis, D. Koutsoyiannis, C. Onof, and K. Tzouka, Multidimensional Hurst-Kolmogorov process for modelling temperature and rainfall fields, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-739, doi:10.13140/RG.2.2.12070.93761, European Geosciences Union, 2011.

    A multidimensional (MD) stochastic simulation model is presented, which is a direct extension of the 1D simple scaling process, known as Hurst-Kolmogorov (HK) process following the analysis of the 2D extension of Koutsoyiannis et al. (2011). The MD HK process can generate time-varying spatial geophysical fields (such as rainfall and temperature), consistent with the observed long-term spatiotemporal persistence (slowly decaying autocorrelation over spatial or temporal displacement). The MD HK process is formulated assuming anisotropy, so as to take into account possibly different autocorrelation decay rates (Hurst coefficients) in each dimension of the field. The MD HK process is also investigated through some applications based on observed temperature and rainfall fields.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.12070.93761

  1. P. Dimitriadis, D. Koutsoyiannis, and A. Paschalis, Three dimensional Hurst-Kolmogorov process for modelling rainfall fields, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, EGU2010-979-1, doi:10.13140/RG.2.2.29844.30088, European Geosciences Union, 2010.

    A three-dimensional (3D) stochastic simulation model is presented, which is a direct extension of the 1D simple scaling process (fractional Gaussian noise). The 3D process can generate time-varying 2D rainfall fields through a rather simple procedure, as well as other time-varying 2D spatial geophysical fields, consistent with the observed 2D long-term spatial persistence over time (3D slowly decaying autocorrelation over scale). Moreover, the differences between 1D (generating rainfall time series at a point), 2D (generating rainfall fields for specific time steps) and 3D (generating spatio-temporal rainfall fields) scaling processes are also being investigated through some applications based on observed rainfall fields.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.29844.30088

Academic works

  1. P. Dimitriadis, Hurst-Kolmogorov dynamics in hydroclimatic processes and in the microscale of turbulence, PhD thesis, Department of Water Resources and Environmental Engineering – National Technical University of Athens, 2017.

    The high complexity and uncertainty of atmospheric dynamics has been long identified through the observation and analysis of hydroclimatic processes such as temperature, dew-point, humidity, atmospheric wind, precipitation, atmospheric pressure, river discharge and stage etc. Particularly, all these processes seem to exhibit high unpredictability due to the clustering of events, a behaviour first identified in Nature by H.E. Hurst in 1951 while working at the River Nile, although its mathematical description is attributed to A. N. Kolmogorov who developed it while studying turbulence in 1940. To give credits to both scientists this behaviour and dynamics is called Hurst-Kolmogorov (HK). In order to properly study the clustering of events as well as the stochastic behaviour of hydroclimatic processes in general we would require numerous of measurements in annual scale. Unfortunately, large lengths of high quality annual data are hardly available in observations of hydroclimatic processes. However, the microscopic processes driving and generating the hydroclimatic ones are governed by turbulent state. By studying turbulent phenomena in situ we may be able to understand certain aspects of the related macroscopic processes in field. Certain strong advantages of studying microscopic turbulent processes in situ is the recording of very long time series, the high resolution of records and the controlled environment of the laboratory. The analysis of these time series offers the opportunity of better comprehending, control and comparison of the two scientific methods through the deterministic and stochastic approach. In this thesis, we explore and further advance the second-order stochastic framework for the empirical as well as theoretical estimation of the marginal characteristic and dependence structure of a process (from small to extreme behaviour in time and state). Also, we develop and apply explicit and implicit algorithms for stochastic synthesis of mathematical processes as well as stochastic prediction of physical processes. Moreover, we analyze several turbulent processes and we estimate the Hurst parameter (H >> 0.5 for all cases) and the drop of variance with scale based on experiments in turbulent jets held at the laboratory. Additionally, we propose a stochastic model for the behaviour of a process from the micro to the macro scale that results from the maximization of entropy for both the marginal distribution and the dependence structure. Finally, we apply this model to microscale turbulent processes, as well as hydroclimatic ones extracted from thousands of stations around the globe including countless of data. The most important innovation of this thesis is that, to the Author’s knowledge, a unique framework (through modelling of common expression of both the marginal density distribution function and the second-order dependence structure) is presented that can include the simulation of the discretization effect, the statistical bias, certain aspects of the turbulent intermittent (or else fractal) behaviour (at the microscale of the dependence structure) and the long-term behaviour (at the macroscale of the dependence structure), the extreme events (at the left and right tail of the marginal distribution), as well as applications to 13 turbulent and hydroclimatic processes including experimentation and global analyses of surface stations (overall, several billions of observations). A summary of the major innovations of the thesis are: (a) the further development, and extensive application to numerous processes, of the classical second-order stochastic framework including innovative approaches to account for intermittency, discretization effects and statistical bias; (b) the further development of stochastic generation schemes such as the Sum of Autoregressive (SAR) models, e.g. AR(1) or ARMA(1,1), the Symmetric-Moving-Average (SMA) scheme in many dimensions (that can generate any process second-order dependence structure, approximate any marginal distribution to the desired level of accuracy and simulate certain aspects of the intermittent behaviour) and an explicit and implicit (pseudo) cyclo-stationary (pCSAR and pCSMA) schemes for simulating the deterministic periodicities of a process such as seasonal and diurnal; and (c) the introduction and application of an extended stochastic model (with an innovative identical expression of a four-parameter marginal distribution density function and correlation structure, i.e. g(x;C)=λ/[(1+|x/a+b|^c )]^d, with C=[λ,a,b,c,d]), that encloses a large variety of distributions (ranging from Gaussian to powered-exponential and Pareto) as well as dependence structures (such as white noise, Markov and HK), and is in agreement (in this form or through more simplified versions) with an interestingly large variety of turbulent (such as horizontal and vertical thermal jet of positively buoyancy processes using laser-induced-fluorescence techniques as well as grid-turbulence generated within a wind-tunnel), geostatistical (such as 2d rock formations), and hydroclimatic processes (such as temperature, atmospheric wind, dew-point and thus, humidity, precipitation, atmospheric pressure, river discharges and solar radiation, in a global scale, as well as a very long time series of river stage, and wave height and period). Amazingly, all examined physical processes (overall 13) exhibited long-range dependence and in particular, most (if treated properly within a robust physical and statistical framework, e.g. by adjusting the process for sampling errors as well as discretization and bias effects) with a mean long-term persistence parameter equal to H ≈ 5/6 (as in the case of isotropic grid-turbulence), and (for the processes examined in the microscale such atmospheric wind, surface temperature and dew-point, in a global scale, and a long duration discharge time series and storm event in terms of precipitation and wind) a powered-exponential behaviour with a fractal parameter close to M ≈ 1/3 (as in the case of isotropic grid-turbulence).

    Full text: http://www.itia.ntua.gr/en/getfile/1767/1/documents/PhD_Panayiotis_Dimitriadis_NTUA.pdf (37297 KB)

Research reports

  1. D. Koutsoyiannis, S.M. Papalexiou, Y. Markonis, P. Dimitriadis, and P. Kossieris, Stochastic framework for uncertainty assessment of hydrometeorological procesess, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 231 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, January 2015.

    Related project: Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO)

    Full text: http://www.itia.ntua.gr/en/getfile/1589/1/documents/Report_EE1.pdf (14753 KB)

  1. 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.

    We present the theoretical documentation of the hydrological-hydraulic simulation model that has been developed within the new version of computer system Hydrogeios. The model has been enhanced in order to represent the hydrological processes at the hourly time scale, which allows to be used for both hydrological design and flood forecasting. In the report are described in detail the whole theoretical background, based on the integration of simulation models for surface- and groundwater processes, water resources management models, and alternative numerical schemes for flow routing along the river network. Moreover, we explain the procedure for preparation of input data and construction of all essential thematic layers, as well as the procedure for estimating model parameters through advanced calibration tools.

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

    Full text: http://www.itia.ntua.gr/en/getfile/1491/1/documents/Report_3_5.pdf (3568 KB)

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

    1. 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.

  1. 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.

    The objective of the research report is the literature review of the theoretical framework of flood hydrology, which is branch of engineering hydrology. The research aims to a critical review of the world experience (in terms of methodologies as well as computer tools), and the practices that are employed within flood hydrology studies in Greece. The topics that are examined are: (a) fundamental concepts of flood hydrology are related processes; (b) characteristic hydrological magnitudes of river basins (physiographic properties, runoff coefficient, time of concentrations, curve number, unit hydrograph, time-area curves); (c) probabilistic assessment of extreme hydrological events; (d) methods for estimating design flows; (e) methods for estimating design hydrographs; (f) flood routing models; (g) computer packages; (h) Greek standards and practices.

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

    Full text: http://www.itia.ntua.gr/en/getfile/1215/1/documents/Report_WP3_1_1.pdf (3203 KB)

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

    1. 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.

Engineering reports

  1. D. Koutsoyiannis, Y. Markonis, A. Koukouvinos, S.M. Papalexiou, N. Mamassis, and P. Dimitriadis, Hydrological study of severe rainfall in the Kephisos basin, Greece, Study of the management of Kephisos , Commissioner: General Secretariat of Public Works – Ministry of Environment, Planning and Public Works, Contractors: Exarhou Nikolopoulos Bensasson, Denco, G. Karavokiris, et al., 154 pages, Athens, 2010.

    Related project: Study of the management of Kephisos

    Full text: http://www.itia.ntua.gr/en/getfile/970/1/documents/2010AthensOmbrian__.pdf (6638 KB)