Antonis Christofides

Civil Engineer, MSc Computer Science, PhD candidate
anthony@itia.ntua.gr
https://antonischristofides.com/

Participation in research projects

Participation as Researcher

  1. DEUCALION – Assessment of flood flows in Greece under conditions of hydroclimatic variability: Development of physically-established conceptual-probabilistic framework and computational tools
  2. Maintenance, upgrading and extension of the Decision Support System for the management of the Athens water resource system
  3. Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information"
  4. Development of a Geographical Information System and an Internet application for the supervision of Kephisos protected areas
  5. Support on the compilation of the national programme for water resources management and preservation
  6. Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)
  7. Classification of quantitative and qualitative parameters of the water resources of Greece - Phases 1 and 2
  8. Investigation of scenarios for the management and protection of the quality of the Plastiras Lake
  9. Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems
  10. Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information

Published work

Publications in scientific journals

  1. D. Koutsoyiannis, C. Onof, Z. W. Kundzewicz, and A. Christofides, On hens, eggs, temperatures and CO₂: Causal links in Earth’s atmosphere, Sci, 5 (3), 35, doi:10.3390/sci5030035, 2023.
  2. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 2. Applications, Proceedings of The Royal Society A, 478 (2261), 20210836, doi:10.1098/rspa.2021.0836, 2022.
  3. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 1.Theory, Proceedings of The Royal Society A, 478 (2261), 20210835, doi:10.1098/rspa.2021.0835, 2022.
  4. N. Mamassis, K. Mazi, E. Dimitriou, D. Kalogeras, N. Malamos, S. Lykoudis, A. Koukouvinos, I. L. Tsirogiannis, I. Papageorgaki, A. Papadopoulos, Y. Panagopoulos, D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. Vitantzakis, N. Kappos, D. Katsanos, B. Psiloglou, E. Rozos, T. Kopania, I. Koletsis, and A. D. Koussis, OpenHi.net: A synergistically built, national-scale infrastructure for monitoring the surface waters of Greece, Water, 13 (19), 2779, doi:10.3390/w13192779, 2021.
  5. D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. G. Anagnostopoulos, and N. Mamassis, Scientific dialogue on climate: is it giving black eyes or opening closed eyes? Reply to “A black eye for the Hydrological Sciences Journal” by D. Huard, Hydrological Sciences Journal, 56 (7), 1334–1339, doi:10.1080/02626667.2011.610759, 2011.
  6. G. G. Anagnostopoulos, D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, A comparison of local and aggregated climate model outputs with observed data, Hydrological Sciences Journal, 55 (7), 1094–1110, doi:10.1080/02626667.2010.513518, 2010.
  7. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.
  8. D. Koutsoyiannis, A. Efstratiadis, N. Mamassis, and A. Christofides, On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671–684, doi:10.1623/hysj.53.4.671, 2008.
  9. K. Hadjibiros, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, A. Stamou, A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Multi-criteria reservoir water management, Global Network for Environmental Science and Technology, 7 (3), 386–394, doi:10.30955/gnj.000394, 2005.
  10. A. Christofides, A. Efstratiadis, D. Koutsoyiannis, G.-F. Sargentis, and K. Hadjibiros, Resolving conflicting objectives in the management of the Plastiras Lake: can we quantify beauty?, Hydrology and Earth System Sciences, 9 (5), 507–515, doi:10.5194/hess-9-507-2005, 2005.
  11. D. Koutsoyiannis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, and A. Christofides, A decision support system for the management of the water resource system of Athens, Physics and Chemistry of the Earth, 28 (14-15), 599–609, doi:10.1016/S1474-7065(03)00106-2, 2003.

Book chapters and fully evaluated conference publications

  1. A. Efstratiadis, A. D. Koussis, S. Lykoudis, A. Koukouvinos, A. Christofides, G. Karavokiros, N. Kappos, N. Mamassis, and D. Koutsoyiannis, Hydrometeorological network for flood monitoring and modeling, Proceedings of First International Conference on Remote Sensing and Geoinformation of Environment, Paphos, Cyprus, 8795, 10-1–10-10, doi:10.1117/12.2028621, Society of Photo-Optical Instrumentation Engineers (SPIE), 2013.
  2. S. Kozanis, A. Christofides, N. Mamassis, and D. Koutsoyiannis, openmeteo.org: a web service for the dissemination of free meteorological data, Advances in Meteorology, Climatology and Atmospheric Physics, edited by C.G. Helmis and P. Nastos, Athens, 203–208, doi:10.1007/978-3-642-29172-2_29, Springer, Athens, 2012.
  3. G.-F. Sargentis, K. Hadjibiros, and A. Christofides, Plastiras lake: the impact of water level on the aesthetic value of landscape, Proceedings of the 9th International Conference on Environmental Science and Technology (9CEST), Rhodes, B, 817–824, Department of Environmental Studies, University of the Aegean, 2005.
  4. K. Hadjibiros, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, A. Stamou, A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Multi-criteria reservoir water management, Proceedings of the 9th International Conference on Environmental Science and Technology (9CEST), Rhodes, A, 535–543, Department of Environmental Studies, University of the Aegean, 2005.
  5. N. Mamassis, A. Christofides, and D. Koutsoyiannis, Hydrometeorological data acquisition, management and analysis for the Athens water supply system, BALWOIS Conference on Water Observation and Information System for Decision Support, Ochrid, FYROM, doi:10.13140/RG.2.1.1845.5284, Ministry of Environment and Physical Planning FYROM, Skopie, 2004.
  6. K. Hadjibiros, D. Koutsoyiannis, A. Katsiri, A. Stamou, A. Andreadakis, G.-F. Sargentis, A. Christofides, A. Efstratiadis, and A. Valassopoulos, Management of water quality of the Plastiras reservoir, 4th International Conference on Reservoir Limnology and Water Quality, Ceske Budejovice, Czech Republic, doi:10.13140/RG.2.1.4872.4723, 2002.
  7. D. Koutsoyiannis, N. Mamassis, and A. Christofides, Experience from the operation of the automatic telemetric meteorological station in the National Technical University, Proceedings of the 8th National Congress of the Greek Hydrotechnical Association, edited by G. Christodoulou, A. Stamou, and A. Nanou, Athens, 301–308, doi:10.13140/RG.2.1.4577.5603, Greek Hydrotechnical Association, 2000.

Conference publications and presentations with evaluation of abstract

  1. D. Koutsoyiannis, C. Onof, Z. W. Kundzewicz, and A. Christofides, A stochastic approach to causality (Invited talk), AGU 2022 Fall Meeting, doi:10.13140/RG.2.2.25180.87681, American Geophysical Union, 2022.
  2. A. Efstratiadis, N. Mamassis, A. Koukouvinos, D. Koutsoyiannis, K. Mazi, A. D. Koussis, S. Lykoudis, E. Demetriou, N. Malamos, A. Christofides, and D. Kalogeras, Open Hydrosystem Information Network: Greece’s new research infrastructure for water, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-4164, doi:10.5194/egusphere-egu2020-4164, 2020.
  3. N. Malamos, A. Tegos, I. L. Tsirogiannis, A. Christofides, and D. Koutsoyiannis, Implementation of a regional parametric model for potential evapotranspiration assessment, IrriMed 2015 – Modern technologies, strategies and tools for sustainable irrigation management and governance in Mediterranean agriculture, Bari, doi:10.13140/RG.2.1.3992.0725, 2015.
  4. 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.
  5. A. Efstratiadis, I. Tsoukalas, P. Kossieris, G. Karavokiros, A. Christofides, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Computational issues in complex water-energy optimization problems: Time scales, parameterizations, objectives and algorithms, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5121, doi:10.13140/RG.2.2.11015.80802, European Geosciences Union, 2015.
  6. S. Kozanis, A. Christofides, A. Efstratiadis, A. Koukouvinos, G. Karavokiros, N. Mamassis, D. Koutsoyiannis, and D. Nikolopoulos, Using open source software for the supervision and management of the water resources system of Athens, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 7158, doi:10.13140/RG.2.2.28468.04482, European Geosciences Union, 2012.
  7. A. Christofides, S. Kozanis, G. Karavokiros, and A. Koukouvinos, Enhydris, Filotis & openmeteo.org: Free software for environmental management, FLOSS Conference 2011, Athens, http://conferences.ellak.gr/2011/, 2011.
  8. D. Tsaknias, D. Bouziotas, A. Christofides, A. Efstratiadis, and D. Koutsoyiannis, Statistical comparison of observed temperature and rainfall extremes with climate model outputs, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-3454, doi:10.13140/RG.2.2.15321.52322, European Geosciences Union, 2011.
  9. A. Christofides, and D. Koutsoyiannis, Causality in climate and hydrology, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-7440, doi:10.13140/RG.2.2.33776.46082, European Geosciences Union, 2011.
  10. A. Christofides, S. Kozanis, G. Karavokiros, Y. Markonis, and A. Efstratiadis, Enhydris: A free database system for the storage and management of hydrological and meteorological data, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, 8760, European Geosciences Union, 2011.
  11. S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon – open source software for the analysis of hydrological data, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12419, doi:10.13140/RG.2.2.21350.83527, European Geosciences Union, 2010.
  12. G. G. Anagnostopoulos, D. Koutsoyiannis, A. Efstratiadis, A. Christofides, and N. Mamassis, Credibility of climate predictions revisited, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 611, doi:10.13140/RG.2.2.15898.24009, European Geosciences Union, 2009.
  13. D. Koutsoyiannis, N. Mamassis, A. Christofides, A. Efstratiadis, and S.M. Papalexiou, Assessment of the reliability of climate predictions based on comparisons with historical time series, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 09074, doi:10.13140/RG.2.2.16658.45768, European Geosciences Union, 2008.
  14. A. Efstratiadis, G. Karavokiros, S. Kozanis, A. Christofides, A. Koukouvinos, E. Rozos, N. Mamassis, I. Nalbantis, K. Noutsopoulos, E. Romas, L. Kaliakatsos, A. Andreadakis, and D. Koutsoyiannis, The ODYSSEUS project: Developing an advanced software system for the analysis and management of water resource systems, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 03910, doi:10.13140/RG.2.2.24942.20805, European Geosciences Union, 2006.
  15. S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon - A hydrological data management and processing software tool, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04644, doi:10.13140/RG.2.2.34222.10561, European Geosciences Union, 2005.
  16. A. Efstratiadis, D. Koutsoyiannis, K. Hadjibiros, A. Andreadakis, A. Stamou, A. Katsiri, G.-F. Sargentis, and A. Christofides, A multicriteria approach for the sustainable management of the Plastiras reservoir, Greece, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.23631.48801, European Geophysical Society, 2003.

Presentations and publications in workshops

  1. A. Christofides, Language and Large Language Models, Stuff we don't mention in the normal course of studies, Rovies, National Technical University of Athens (NTUA), 2023.
  2. A. Christofides, and D. Koutsoyiannis, God and the arrogant species: Contrasting nature's intrinsic uncertainty with our climate simulating supercomputers, 104th Annual Conference & Exhibition, Orlando, Florida, Air & Waste Management Association, 2011.
  3. N. Mamassis, E. Tiligadas, D. Koutsoyiannis, M. Salahoris, G. Karavokiros, S. Mihas, K. Noutsopoulos, A. Christofides, S. Kozanis, A. Efstratiadis, E. Rozos, and L. Bensasson, HYDROSCOPE: National Databank for Hydrological, Meteorological and Geographical Information, Towards a rational handling of current water resource problems: Utilizing Data and Informatics for Information, Hilton Hotel, Athens, 2010.
  4. D. Koutsoyiannis, G. Tsakalias, A. Christofides, A. Manetas, A. Sakellariou, R. Mavrodimou, N. Papakostas, N. Mamassis, I. Nalbantis, and Th. Xanthopoulos, HYDROSCOPE: Creation of a national data bank of hydrological and meteorological information, Research and Technology Days '95, National Technical University of Athens, 1995.
  5. A. Christofides, How much time does it take to write tests? A case study, EuroPython, Dublin, July 2022.
  6. A. Tsitouras, A. Christofides, T. Smirnis, A. Peppas, R. Limnaiou, E. Evangelou, M. Tziouvalekas, Ch. Petsoulas, G. Karavokiros, and Ch. Tsantilas, ChemicalSE: Internet application for the managment of a large volume of geographical invormation using exclusively free sofware, 4th Congress of Geographical Information Systems and Spatial Analysis in Agriculture and Environment, Agricultural University of Athens, May 2022.
  7. I. L. Tsirogiannis, N. Malamos, P. Barouchas, P. Baltzoi, K. Fotia, G. Tenedios, D. Giotis, D. Kateris, E. Tsoumani, S. Chiras, and A. Christofides, Evaluation of the application of the IRMA_SYS irrigation DSS on kiwi crop, 28th Conference of the Hellenic Horticulture Science Company, Thessaloniki, 465–468, October 2017.

Various publications

  1. A. Christofides, D. Koutsoyiannis, C. Onof, and Z. W. Kundzewicz, Causality, Climate, Etc., doi:10.13140/RG.2.2.21608.44803, Climate Etc. (Judith Curry's blog), 2023.
  2. A. Christofides, Why Andreas writes suboptimal code and why this hinders scientific research, 3 pages, 11 May 2014.
  3. S. Kozanis, and A. Christofides, A webservice API to access free data from hydroscope and openmeteo.org projects, Athens Green Hackathon, Athens, http://athens.greenhackathon.com/, 2012.
  4. A. Christofides, and G. Milonaki, What problems are hidden in the agreement between the State and Microsoft, Newspaper Eleftherotipia, 63, 13 March 2006.

Educational notes

  1. A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Presentation of the research project "Investigation of scenarios for the management and protection of the quality of the Plastiras Lake", 79 pages, 1 April 2003.

Academic works

  1. A. Christofides, Summary of "Associates systems for decision support" by A. P. Sage, Course work, 3 pages, Department of Computer Science – University of Manchester, Manchester, 7 March 2000.
  2. A. Christofides, Short Term Rain Prediction with Artificial Neural Networks, MSc thesis, 46 pages, Manchester, October 2000.
  3. A. Christofides, Infilling of missing values of hydrometeorological time series in distributed relational databases, Diploma thesis, 75 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 1994.

Research reports

  1. A. Siskos, G. Karavokiros, A. Christofides, and A. Efstratiadis, Development of decision support system for renewable energy managment, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 103 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2015.
  2. S. Kozanis, A. Christofides, and A. Efstratiadis, Scientific documentation of the Hydrognomon software (version 4 ), Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information" , Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 173 pages, Athens, June 2010.
  3. D. Koutsoyiannis, A. Andreadakis, R. Mavrodimou, A. Christofides, N. Mamassis, A. Efstratiadis, A. Koukouvinos, G. Karavokiros, S. Kozanis, D. Mamais, and K. Noutsopoulos, National Programme for the Management and Protection of Water Resources, Support on the compilation of the national programme for water resources management and preservation, 748 pages, doi:10.13140/RG.2.2.25384.62727, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, February 2008.
  4. A. Christofides, and G. Karavokiros, Database design, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 1, 144 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2007.
  5. S. Kozanis, A. Christofides, and A. Efstratiadis, Description of the data management and processing system "Hydrognomon", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 2, 141 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2005.
  6. A. Christofides, and S. Kozanis, Hydrognomon (version 1.0) - Software for data management, Modernisation of the supervision and management of the water resource system of Athens, Report 22, 90 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  7. D. Koutsoyiannis, I. Nalbantis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, A. Christofides, E. Rozos, A. Economou, and G. M. T. Tentes, Methodology and theoretical background, Modernisation of the supervision and management of the water resource system of Athens, Report 15, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.
  8. Ministry of Development, NTUA, Institute of Geological and Mining Research, and Centre for Research and Planning, Master plan for water resource management of the country, Completion of the classification of quantitative and qualitative parameters of water resources in water districts of Greece, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 549 pages, Ministry of Development, Athens, January 2003.
  9. K. Hadjibiros, D. Koutsoyiannis, A. Andreadakis, A. Katsiri, A. Stamou, A. Valassopoulos, A. Efstratiadis, I. Katsiris, M. Kapetanaki, A. Koukouvinos, N. Mamassis, K. Noutsopoulos, G.-F. Sargentis, and A. Christofides, Overview report, Investigation of scenarios for the management and protection of the quality of the Plastiras Lake, Report 1, 23 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2002.
  10. G.-F. Sargentis, and A. Christofides, The landscape, Investigation of scenarios for the management and protection of the quality of the Plastiras Lake, Report 4, 73 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2002.
  11. A. Koukouvinos, and A. Christofides, Development of a geographic information system for hydrology, water use and related works, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3, Report 38, 50 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 1999.
  12. Team of the YBET96 project, Master plan for the country's water resource management, Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 339 pages, Ministry of Development, Athens, November 1996.
  13. A. Christofides, and N. Mamassis, Hydrometeorological data processing, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 18, 268 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 1995.
  14. N. Papakostas, G. Tsakalias, and A. Christofides, Instructions manual, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, 50 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 1994.
  15. NTUA Hydroscope Team, HYDROSCOPE, User manual for the database and applications for hydrology and meteorology, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 180 pages, National Technical University of Athens, Athens, December 1994.

Miscellaneous works

  1. A. Christofides, and N. Mamassis, Comments on the proposal for a law on the renewable energy sources, 4 pages, 15 January 2010.
  2. A. Christofides, Openmeteo database description, 8 pages, 2005.
  3. A. Christofides, and D. Koutsoyiannis, Hydrognomon: A database for hydrological and meteorological time series and a processing system of time series, 16 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 2002.
  4. A. Christofides, Software for the management of measuring stations and time series, 12 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 2001.
  5. A. Christofides, The meteorological station of NTUA, 50 pages, June 1999.

Details on research projects

Participation as Researcher

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

    Duration: March 2011–March 2014

    Budget: €145 000

    Commissioned by: General Secretariat of Research and Technology

    Contractors:

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

    Project director: D. Koutsoyiannis

    Principal investigator: N. Mamassis

    Programme: ΕΣΠΑ "Συνεργασία"

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

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

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

    Duration: October 2008–November 2011

    Budget: €72 000

    Project director: N. Mamassis

    Principal investigator: D. Koutsoyiannis

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

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

    Duration: December 2009–May 2011

    Budget: €140 000

    Commissioned by: Hydroscope Systems Consortium

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: N. Mamassis

    Principal investigator: N. Mamassis

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

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

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

    Duration: April 2008–March 2009

    Budget: €30 000

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: N. Mamassis

    Principal investigator: N. Mamassis

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

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

    Duration: February 2007–May 2007

    Budget: €45 000

    Commissioned by: Ministry of Environment, Planning and Public Works

    Contractor: Department of Water Resources and Environmental Engineering

    Project director: D. Koutsoyiannis

    Principal investigator: A. Andreadakis

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

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

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

    Duration: July 2003–June 2006

    Budget: €779 656

    Commissioned by: General Secretariat of Research and Technology

    Contractor: NAMA

    Collaborators:

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

    Project director: D. Koutsoyiannis

    Principal investigator: A. Andreadakis

    Programme: ΕΠΑΝ, Φυσικό Περιβάλλον και Βιώσιμη Ανάπτυξη

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

  1. Classification of quantitative and qualitative parameters of the water resources of Greece - Phases 1 and 2

    Duration: February 1996–April 2003

    Budget: €216 000

    Commissioned by: Directorate of Water and Natural Resources

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: D. Koutsoyiannis

    Principal investigators: A. Andreadakis, D. Mamais

    The scope of the project is the classification of the existing information related to water quantity and quality in the water districts of Greece, using geographical information systems. The project part related to water quantity aims at the development of a methodology for establishing a water balance between supply and demand and extracting the most important summary characteristics that are then entered into a geographical information system. The methodology is applied at a water district scale, using information based on existing studies. The project part related to water quality aims at the characterisation of the rivers, lakes and aquifers based on the water quality characteristics, and the water uses and requirements. The characterisation is based on the classification of critical quantity parameters that have been measured and includes the use of a geographical information system. The project was elaborated in two phases. The first phase was implemented in 1996, and its objective was the development of methodologies, the analysis of the 10 water districts and their relationships and the creation of maps. In collaboration with other authorities (Ministry of Development, Institute of Geology and Mineral Exploitation, Centre for Research and Planning), the institutional and administrative status, the international environment and the water policies, were investigated. Finally a first approach towards the integrated management of the water resources of the country was attempted. The second phase was implemented in 2002-2003, and aims at the completion of the study, by incorporating the 4 remaining water districts, a more analytical approach regarding the water management at a country scale and the update of results of the first phase.

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

    Duration: May 2001–January 2002

    Commissioned by:

    1. Prefectural Government of Karditsa
    2. Municipality of Karditsa

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Project director: K. Hadjibiros

    Principal investigator: D. Koutsoyiannis

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

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

    Duration: February 1996–September 1996

    Commissioned by: Directorate of Water and Natural Resources

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

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

    Project director: D. Koutsoyiannis

    Principal investigator: A. Andreadakis

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

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

    Duration: January 1992–December 1993

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

    Commissioned by:

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

    Contractor: Department of Water Resources, Hydraulic and Maritime Engineering

    Collaborators:

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

    Project director: D. Koutsoyiannis

    Principal investigators: M. Aftias, D. Koutsoyiannis

    Programme: STRIDE

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

Published work in detail

Publications in scientific journals

  1. D. Koutsoyiannis, C. Onof, Z. W. Kundzewicz, and A. Christofides, On hens, eggs, temperatures and CO₂: Causal links in Earth’s atmosphere, Sci, 5 (3), 35, doi:10.3390/sci5030035, 2023.

    The scientific and wider interest in the relationship between atmospheric temperature (T) and concentration of carbon dioxide ([CO₂]) has been enormous. According to the commonly assumed causality link, increased [CO₂] causes a rise in T. However, recent developments cast doubts on this assumption by showing that this relationship is of the hen-or-egg type, or even unidirectional but opposite in direction to the commonly assumed one. These developments include an advanced theoretical framework for testing causality based on the stochastic evaluation of a potentially causal link between two processes via the notion of the impulse response function. Using, on the one hand, this framework and further expanding it and, on the other hand, the longest available modern time series of globally averaged T and [CO₂], we shed light on the potential causality between these two processes. All evidence resulting from the analyses suggests a unidirectional, potentially causal link with T as the cause and [CO₂] as the effect. That link is not represented in climate models, whose outputs are also examined using the same framework, resulting in a link opposite the one found when the real measurements are used.

    https://www.itia.ntua.gr/en/getfile/2342/4/documents/GraphicalAbstract1.jpg

    Full text: http://www.itia.ntua.gr/en/getfile/2342/1/documents/sci-05-00035-v2.pdf (7279 KB)

    Additional material:

  1. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 2. Applications, Proceedings of The Royal Society A, 478 (2261), 20210836, doi:10.1098/rspa.2021.0836, 2022.

    In a companion paper, we develop the theoretical background of a stochastic approach to causality with the objective of formulating necessary conditions that are operationally useful in identifying or falsifying causality claims. Starting from the idea of stochastic causal systems, the approach extends it to the more general concept of hen-or-egg causality, which includes as special cases the classic causal, and the potentially causal and anti-causal systems. The framework developed is applicable to large-scale open systems, which are neither controllable nor repeatable. In this paper, we illustrate and showcase the proposed framework in a number of case studies. Some of them are controlled synthetic examples and are conducted as a proof of applicability of the theoretical concept, to test the methodology with a priori known system properties. Others are real-world studies on interesting scientific problems in geophysics, and in particular hydrology and climatology.

    Additional material:

  1. D. Koutsoyiannis, C. Onof, A. Christofides, and Z. W. Kundzewicz, Revisiting causality using stochastics: 1.Theory, Proceedings of The Royal Society A, 478 (2261), 20210835, doi:10.1098/rspa.2021.0835, 2022.

    Causality is a central concept in science, in philosophy and in life. However, reviewing various approaches to it over the entire knowledge tree, from philosophy to science and to scientific and technological applications, we locate several problems, which prevent these approaches from defining sufficient conditions for the existence of causal links. We thus choose to determine necessary conditions that are operationally useful in identifying or falsifying causality claims. Our proposed approach is based on stochastics, in which events are replaced by processes. Starting from the idea of stochastic causal systems, we extend it to the more general concept of hen-or-egg causality, which includes as special cases the classic causal, and the potentially causal and anti-causal systems. Theoretical considerations allow the development of an effective algorithm, applicable to large-scale open systems, which are neither controllable nor repeatable. The derivation and details of the algorithm are described in this paper, while in a companion paper we illustrate and showcase the proposed framework with a number of case studies, some of which are controlled synthetic examples and others real-world ones arising from interesting scientific problems.

    Additional material:

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

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

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

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

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

    1. Spyrou, C., M. Loupis, N. Charizopoulos, P. Arvanitis, A. Mentzafou, E. Dimitriou, S. E. Debele, J. Sahani, and P. Kumar, Evaluating nature-based solution for flood reduction in Spercheios river basin Part 2: Early experimental evidence, Sustainability, 14(6), 10345, doi:10.3390/su141610345, 2022.
    2. #Chrysanthopoulos, E., C. Pouliaris, I. Tsiroggianis, K. Markantonis, P. Kofakis, and A. Kallioras, Evaluating the efficiency of numerical and data driven modeling in forecasting soil water content, Proceedings of the 3rd IAHR Young Professionals Congress, 64-65, 2022.
    3. #Samih, I., and D. Loudyi, Short-term urban water demand forecasting using Theta Models in Casablanca city, Morocco, Proceedings of the 3rd IAHR Young Professionals Congress, International Association for Hydro-Environment Engineering and Research, 2022.
    4. Mazi, K., A. D. Koussis, S. Lykoudis, B. E. Psiloglou, G. Vitantzakis, N. Kappos, D. Katsanos, E. Rozos, I. Koletsis, and T. Kopania, Establishing and operating (pilot phase) a telemetric streamflow monitoring network in Greece, Hydrology, 10(1), 19, doi:10.3390/hydrology10010019, 2023.
    5. Koltsida, E., N. Mamassis, and A. Kallioras, Hydrological modeling using the Soil and Water Assessment Tool in urban and peri-urban environments: the case of Kifisos experimental subbasin (Athens, Greece), Hydrology and Earth System Sciences, 27, 917-931, doi:10.5194/hess-27-917-2023, 2023.
    6. Tsirogiannis, I. L., N. Malamos, and P. Baltzoi, Application of a generic participatory decision support system for irrigation management for the case of a wine grapevine at Epirus, Northwest Greece, Horticulturae, 9(2), 267, doi:10.3390/horticulturae9020267, 2023.
    7. Yeşilköy, S., Ö. Baydaroğlu, N. Singh, Y. Sermet, and I. Demir, A contemporary systematic review of cyberinfrastructure systems and applications for flood and drought data analytics and communication, EarthArXiv, doi:10.31223/X5937W, 2023.
    8. Fotia, K., and I. Tsirogiannis, Water footprint score: A practical method for wider communication and assessment of water footprint performance, Environmental Sciences Proceedings, 25(1), 71, doi:10.3390/ECWS-7-14311, 2023.
    9. Bloutsos, A. A., V. I. Syngouna, I. D. Manariotis, and P. C. Yannopoulos, Seasonal and long-term water quality of Alfeios River Basin in Greece, Water, Air and Soil Pollution, 235, 215, doi:10.1007/s11270-024-06981-1, 2024.

  1. D. Koutsoyiannis, A. Christofides, A. Efstratiadis, G. G. Anagnostopoulos, and N. Mamassis, Scientific dialogue on climate: is it giving black eyes or opening closed eyes? Reply to “A black eye for the Hydrological Sciences Journal” by D. Huard, Hydrological Sciences Journal, 56 (7), 1334–1339, doi:10.1080/02626667.2011.610759, 2011.

    Remarks:

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

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

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

    Related works:

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

    Full text: http://www.itia.ntua.gr/en/getfile/1140/1/documents/2011HSJ_OpeningClosedEyes.pdf (88 KB)

    Additional material:

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

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

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

  1. G. G. Anagnostopoulos, D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, A comparison of local and aggregated climate model outputs with observed data, Hydrological Sciences Journal, 55 (7), 1094–1110, doi:10.1080/02626667.2010.513518, 2010.

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

    Remarks:

    The paper has been discussed in weblogs and forums.

    Weblogs and forums that discussed this article during 2010:

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

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

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

    Related works:

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

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

    Additional material:

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

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

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

    1. Kundzewicz, Z. W., and E. Z. Stakhiv, Are climate models “ready for prime time” in water resources management applications, or is more research needed? Hydrological Sciences Journal, 55(7), 1085–1089, 2010.
    2. #Liebscher, H.-J., and H. G. Mendel, Vom empirischen Modellansatz zum komplexen hydrologischen Flussgebietsmodell – Rückblick und Perspektiven, 132 p., Koblenz, Bundesanstalt für Gewässerkunde, 2010.
    3. Stockwell, D. R. B., Critique of drought models in the Australian Drought Exceptional Circumstances Report (DECR), Energy and Environment, 21(5), 425-436, 2010.
    4. Di Baldassarre, G., M. Elshamy, A. van Griensven, E. Soliman, M. Kigobe, P. Ndomba, J. Mutemi, F. Mutua, S. Moges, J.-Q. Xuan, D. Solomatine, and S. Uhlenbrook, Future hydrology and climate in the River Nile basin: a review, Hydrological Sciences Journal, 56(2), 199-211, 2011.
    5. Carlin, A., A multidisciplinary, science-based approach to the economics of climate change, International Journal of Environmental Research and Public Health, 8(4), 985-1031, 2011.
    6. Fildes, R., and N. Kourentzes, Validation and forecasting accuracy in models of climate change, International Journal of Forecasting, 27(4), 968-995, 2011.
    7. Kundzewicz, Z. W., Nonstationarity in water resources – Central European perspective, Journal of the American Water Resources Association, 47(3), 550-562, 2011.
    8. Sivakumar, B., Water crisis: From conflict to cooperation – an overview, Hydrological Sciences Journal, 56(4), 531-552, 2011.
    9. Loehle, C., Criteria for assessing climate change impacts on ecosystems, Ecology and Evolution, 1 (1), 63–72, 2011.
    10. Ward, J. D., A. D. Werner, W. P. Nel, and S. Beecham, The influence of constrained fossil fuel emissions scenarios on climate and water resource projections, Hydrology and Earth System Sciences, 15, 1879-1893, 2011.
    11. #Idso, C., R. M. Carter, and S. F. Singer, Climate models and their limitations, Climate Change Reconsidered: 2011 Interim Report of the Nongovernmental International Panel on Climate Change (NIPCC), Chapter 1, 32 pp., 2011.
    12. #Huard, D., The challenges of climate change interpretation, Ouranos Newsletter, Montreal, Quebec, 3 pp., 21 September 2011.
    13. Stakhiv, E. Z., Pragmatic approaches for water management under climate change uncertainty, JAWRA Journal of the American Water Resources Association, 47(6), 1183-1196, 2011.
    14. Huard, D., A black eye for the Hydrological Sciences Journal, Discussion of “A comparison of local and aggregated climate model outputs with observed data”, by G. G. Anagnostopoulos et al. (2010, Hydrol. Sci. J. 55 (7), 1094–1110), Hydrological Sciences Journal, 56(7), 1330–1333, 2011.
    15. #Martin, T. E., Mine waste management in wet, mountainous terrain: Some British Columbia perspectives, Part II – Creating, managing and judging our legacy, Proceedings Tailings and Mine Waste 2011, Vancouver, BC, Canada, 2011.
    16. #Kundzewicz, Z. W., Comparative assessment: fact or fiction? Paper presented at the Workshop Including long-term climate change in hydrologic design, World Bank, Washington, D.C., USA, November 21, 2011.
    17. Okruszko, T., H. Duel, M. Acreman, M. Grygoruk, M. Flörke, and C. Schneider, Broad-scale ecosystem services of European wetlands — overview of the current situation and future perspectives under different climate and water management scenarios, Hydrological Sciences Journal, 56(8), 1501–1517, 2011.
    18. Stanislawska, K., K Krawiec, and Z. W. Kundzewicz, Modeling global temperature changes with genetic programming, Computers and Mathematics with Applications, 64(12), 3717-3728, 2012.
    19. Petheram, C., P. Rustomji, T. R. McVicar, W. Cai, F. H. S. Chiew, J. Vleeshouwer, T. G. Van Niel, L.-T. Li, R. G. Cresswell, R. J. Donohue, J. Teng, and J.-M. Perraud, Estimating the impact of projected climate change on runoff across the tropical savannas and semi-arid rangelands of northern Australia, Journal of Hydrometeorology, 13 (2), 483-503, 2012.
    20. #Fekete, B. M., and E. Stakhiv, Water management preparation strategies for adaptation to changing climate, Climatic Change and Global Warming of Inland Waters: Impacts and Mitigation for Ecosystems and Societies, C. R. Goldman, M. Kumagai, and R. D. Robarts (eds.), 413-427, 2012.
    21. #Asian Development Bank, Guidelines for climate proofing investment in agriculture, rural development and food security, 101 pp., Mandaluyong City, Philippines, ISBN 978-92-9092-900-0, 2012.
    22. Hromadka, T. V., M. Jaye, M. Phillips, T. Hromadka, and D. Phillips, A mathematical model of cryospheric response to climate changes, Journal of Cold Regions Engineering, 27 (2), 67-93, 2013.
    23. Serrat-Capdevila, A., J. B. Valdes, F. Dominguez, and S. Rajagopal, Characterizing the water extremes of the new century in the US South-west: a comprehensive assessment from state-of-the-art climate model projections, International Journal of Water Resources Development, 29 (2), 152-171, 2013.
    24. Nastos, P. T., N. Politi, and J. Kapsomenakis, Spatial and temporal variability of the aridity index in Greece, Atmospheric Research, 19, 140-152, 2013.
    25. Jiang, P., M. R. Gautam, J. Zhu, and Z. Yu, How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?, Journal of Hydrology, 479, 13-23, 2013.
    26. Nazemi, A., H. S. Wheater, K. P. Chun, and A. Elshorbagy, A stochastic reconstruction framework for analysis of water resource system vulnerability to climate-induced changes in river flow regime, Water Resources Research, 49(1), 291-305, doi:10.1029/2012WR012755, 2013.
    27. Chun, K. P., H. S. Wheater, and C. Onof, Comparison of drought projections using two UK weather generators, Hydrological Sciences Journal, 58(2), 1–15, 2013.
    28. Pielke, Sr. R.A., Comment on “The North American Regional Climate Change Assessment Program: Overview of Phase I Results”, Bulletin of the American Meteorological Society, 94(7), 1075-1077, 2013.
    29. Piniewski, M., F. Voss, I. Bärlund, T. Okruszko and Z. W. Kundzewicz, Effect of modelling scale on the assessment of climate change impact on river runoff, Hydrological Sciences Journal, 58 (4), 737-754, 2013.
    30. #Pielke R. A. Sr., J. Adegoke, F. Hossain, G. Kallos, D. Niyogi, T. Seastedt, K. Suding, C. Y. Wright, and D. Staley, Preface, Climate Vulnerability: Understanding and Addressing Threats to Essential Resources, Pielke, R. (editor), xxi-xxix, Elsevier Science, 2013.
    31. #Lang, M. A., Renewable energy and water resources, Climate Vulnerability: Understanding and Addressing Threats to Essential Resources, Pielke, R. (editor), Vol. 3, 149-166, Elsevier Science, 2013.
    32. #He, Y., F. Pappenberger, D. Manful, H. Cloke, P. Bates, F. Wetterhall, and B. Parkes, Flood inundation dynamics and socioeconomic vulnerability under environmental change, Climate Vulnerability: Understanding and Addressing Threats to Essential Resources, Pielke, R. (editor), Vol. 5, 241-255, Elsevier Science, 2013.
    33. Kumar, S., P. A. Dirmeyer, V. Merwade, T. DelSole, J. M. Adams, and D. Niyogi, Land use/cover change impacts in CMIP5 climate simulations – A new methodology and 21st century challenges, Journal of Geophysical Research: Atmospheres, 118(12), 6337-6353, 2013.
    34. #Loukas, A., and L. Vasiliades, Review of applied methods for flood-frequency analysis in a changing environment in Greece, In: A review of applied methods in Europe for flood-frequency analysis in a changing environment, Floodfreq COST action ES0901: European procedures for flood frequency estimation (ed. by H. Madsen et al.), Centre for Ecology & Hydrology, Wallingford, UK, 2013.
    35. Ruffault, J., N. K .Martin-StPaul, C. Duffet, F. Goge and F. Mouillot, Projecting future drought in Mediterranean forests: bias correction of climate models matters!, Theoretical and Applied Climatology, 117 (1-2), 113-122, 2014.
    36. Nazemi, A., and H. S. Wheater, How can the uncertainty in the natural inflow regime propagate into the assessment of water resource systems? Advances in Water Resources, 63, 131-142, 2014.
    37. Kundzewicz, Z. W., S. Kanae, S. I. Seneviratne, J. Handmer, N. Nicholls, P. Peduzzi, R. Mechler, L. M. Bouweri, N. Arnell, K. Mach, R. Muir-Wood, G. R. Brakenridge, W. Kron, G. Benito, Y. Honda, K. Takahashi, and B. Sherstyukov, Flood risk and climate change: global and regional perspectives, Hydrological Sciences Journal, 59(1), 1–28, 2014.
    38. Grygoruk, M., U. Biereżnoj-Bazille, M. Mazgajski and J.Sienkiewicz, Climate-induced challenges for wetlands: revealing the background for the adaptive ecosystem management in the Biebrza Valley, Poland, Advances in Global Change Research, 58, 209-232, 2014.
    39. Gilioli, G., S. Pasquali, S. Parisi and S. Winter, Modelling the potential distribution of Bemisia tabaci in Europe considering climate change scenario, Pest Management Science, 70(1), 1611–1623, 10.1002/ps.3734, 2014.
    40. Krakauer, N. Y., and B. M. Fekete, Are climate model simulations useful for forecasting precipitation trends? Hindcast and synthetic-data experiments, Environmental Research Letters, 9(2), 024009, 2014.
    41. Hughes, D. A., S. Mantel and T. Mohobane, An assessment of the skill of downscaled GCM outputs in simulating historical patterns of rainfall variability in South Africa, Hydrology Research, 45 (1), 134-147, 2014.
    42. #Jiménez Cisneros, B.E., T. Oki, N.W. Arnell, G. Benito, J.G. Cogley, P. Döll, T. Jiang, and S.S. Mwakalila, Freshwater resources. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 229-269, 2014.
    43. Hromadka, T. V., H. D. McInvale, B. Gatzke, M. Phillips, and B. Espinosa, Cumulative departure model of the cryosphere during the Pleistocene, Journal of Cold Regions Engineering, 06014002, 2014.
    44. Nova, J., Government monopoly in science and the role of independent scientists, Energy and Environment, 25(6-7), 1219–1224, 2014.
    45. #McKitrick, R., Climate Policy Implications of the Hiatus in Global Warming, Fraser Institute, 2014.
    46. Galbraith, H., D. W. DesRochers, S. Brown and J. M. Reed, Predicting vulnerabilities of North American shorebirds to climate change, PLoS ONE, 9(9), 10.1371/journal.pone.0108899, 2014.
    47. Yao, Y., S. Zhao, Y. Zhang, K. Jia and M. Liu, Spatial and decadal variations in potential evapotranspiration of China based on reanalysis datasets during 1982–2010, Atmosphere, 5(4), 737-754, 2014.
    48. Kundzewicz, Z., and D. Gerten, Grand challenges related to assessment of climate change impacts on freshwater resources, Journal of Hydrologic Engineering, 20 (1), 10.1061/(ASCE)HE.1943-5584.0001012, A4014011, 2015.
    49. Hromadka II, T.V., H.D. McInvale, M. Phillips and B. Espinosa, Assessment of ice volume changes in the cryosphere via simplified heat transport model, American Journal of Climate Change, 3, 421-428, 2014.
    50. Hesse, C., V. Krysanova, A. Stefanova, M. Bielecka and D. A. Domnin, Assessment of climate change impacts on water quantity and quality of the multi-river Vistula Lagoon catchment, Hydrological Sciences Journal, 60(5), 890-911, doi:10.1080/02626667.2014.967247, 2015.
    51. Stefanova, A., V. Krysanova, C. Hesse, and A. I. Lillebø, Climate change impact assessment on water inflow to a coastal lagoon: the Ria de Aveiro watershed, Portugal, Hydrological Sciences Journal, 60(5), 929-948, 2015.
    52. Hesse, C., A. Stefanova, and V. Krysanova, Comparison of water flows in four European lagoon catchments under a set of future climate scenarios, Water, 7(2), 716-746, doi:10.3390/w7020716, 2015.
    53. Gelfan, A., V. A. Semenov, E. Gusev, Y. Motovilov, O. Nasonova, I. Krylenko, and E. Kovalev, Large-basin hydrological response to climate model outputs: uncertainty caused by the internal atmospheric variability, Hydrology and Earth System Sciences, 19, 2737-2754, doi:10.5194/hess-19-2737-2015, 2015.
    54. Nayak, P. C., R. Wardlaw, and A. K. Kharya, Water balance approach to study the effect of climate change on groundwater storage for Sirhind command area in India, International Journal of River Basin Management, 13(2), 243-261, doi:10.1080/15715124.2015.1012206, 2015.
    55. Yu, Z., P. Jiang, M. R. Gautam, Y. Zhang, and K. Acharya, Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections, Journal of Geophysical Research: Atmospheres, 120(7), 2676-2688, doi:10.1002/2014JD022414, 2015.
    56. Legates, D. R., W. Soon, W. M. Briggs and C. Monckton of Brenchley, Climate consensus and ‘misinformation’: a rejoinder to agnotology, scientific consensus, and the teaching and learning of climate change, Science and Education, 24, 299-318, doi:10.1007/s11191-013-9647-9, 2015.
    57. Frank, P., Negligence, non-science, and consensus climatology, Energy and Environment, 26(3), doi:10.1260/0958-305X.26.3.391, 2015.
    58. Kundzewicz, Z.W., Climate change track in river floods in Europe, Proc. IAHS, 369, 189–194, 10.5194/piahs-369-189-2015, 2015.
    59. Kara, F., I. Yucel, and Z. Akyurek, Climate change impacts on extreme precipitation of water supply area in Istanbul: Use of ensemble climate modelling and geo-statistical downscaling, Hydrological Sciences Journal, 61(14), 2481-2495, doi:10.1080/02626667.2015.1133911, 2016.
    60. Refsgaard, J. C., T. O. Sonnenborg, M. B. Butts, J. H. Christensen, S. Christensen, M. Drews, K. H. Jensen, F. Jørgensen, L. F. Jørgensen, M. A. D. Larsen, S. H. Rasmussen, L. P. Seaby, D. Seifert, and T. N. Vilhelmsen, Climate change impacts on groundwater hydrology – where are the main uncertainties and can they be reduced?, Hydrological Sciences Journal, 61(13), 2312-2324, doi:10.1080/02626667.2015.1131899, 2016.
    61. #Kundzewicz, Z. W., Climate change impacts and adaptation in water and land context, Environmental Resource Management and the Nexus Approach – Managing Water, Soil, and Waste in the Context of Global Change, H. Hettiarachchi, and R. Ardakanian (editors), 11-39, Springer, doi:10.1007/978-3-319-28593-1_2, 2016.
    62. #Serrat-Capdevila, A., D. A. García Ramírez, and N. Tayebi, Key global water challenges and the role of remote sensing, Earth Observation for Water Resources Management: Current Use and Future Opportunities for the Water Sector, 9-31, doi:10.1596/978-1-4648-0475-5_ch1, 2016.
    63. Jiang, P., Z. Yu, M. R. Gautam, F. Yuan, and K. Acharya, Changes of storm properties in the United States: Observations and multimodel ensemble projections, Global and Planetary Change, 142, 41–52, doi:10.1016/j.gloplacha.2016.05.001, 2016.
    64. #Fekete, B. M., G. Pisacane, and D. Wisser, Crystal balls into the future: are global circulation and water balance models ready?, Proc. IAHS, 374, 41-51, doi:10.5194/piahs-374-41-2016, 2016.
    65. Kundzewicz, Z. W., V. Krysanova, R. Dankers, Y. Hirabayashi, S. Kanae, F. F. Hattermann, S. Huang, P. C. D. Milly, M. Stoffel, P. P. J. Driessen, P. Matczak, P. Quevauviller, and H.-J. Schellnhuber, Differences in flood hazard projections in Europe – their causes and consequences for decision making, Hydrological Sciences Journal, 62(1), 1-14, doi:10.1080/02626667.2016.1241398, 2017.
    66. Grygoruk, M., and S. Rannowb, Mind the gap! Lessons from science-based stakeholder dialogue in climate-adapted management of wetlands, Journal of Environmental Management, 186, 108-119, doi:10.1016/j.jenvman.2016.10.066, 2017.
    67. Hossain, F., E. Beighley, S. Burian, J. Chen, A. Mitra, D. Niyogi, R. Pielke Sr, and D. Wegner, Review of approaches and recommendations for improving resilience of water management infrastructure: the case for large dams, Journal of Infrastructure Systems, doi:10.1061/(ASCE)IS.1943-555X.0000370, 2017.
    68. Gusev, Y. M., V. A. Semenov, O. N. Nasonova, and E E. Kovalev, Weather noise impact on the uncertainty of simulated water balance components of river basins, Hydrological Sciences Journal, 62(8), 1181-1199, doi:10.1080/02626667.2017.1319064, 2017.
    69. #Shalby, A., M. Elshemy, and B. A. Zeidan, Selecting of regional climate model simulations for modeling climate change impacts on the water quality status of Lake Burullus, Egypt, Twentieth International Water Technology Conference, Hurghada, 2017.
    70. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, 1, 28-35, doi:10.1016/j.wasec.2017.06.001, 2017.
    71. Loehle, C., The epistemological status of general circulation models, Climate Dynamics, 50(5-6), 1719-1731, doi:10.1007/s00382-017-3717-7, 2018.
    72. Gupta, H. V., G. Sapriza-Azuri, J. Jódar, and J. Carrera, Circulation pattern-based assessment of projected climate change for a catchment in Spain, Journal of Hydrology, 556, 944-960, doi:10.1016/j.jhydrol.2016.06.032, 2018.
    73. #Maraun, D., and M. Widmann, Statistical Downscaling and Bias Correction for Climate Research, Cambridge University Press, 2018.
    74. Stefanidis, S., and D. Stathis, Effect of climate change on soil erosion in a mountainous Mediterranean catchment (Central Pindus, Greece), Water, 10(10), 1469, doi:10.3390/w10101469, 2018.
    75. Connolly, R., M. Connolly, W. Soon, D. R. Legates, R. G. Cionco, and V. M. Velasco Herrera, Northern hemisphere snow-cover trends (1967–2018): A comparison between climate models and observations, Geosciences, 9(3), 135, doi:10.3390/geosciences9030135, 2019.
    76. Kron, W., J. Eichner, and Z. W. Kundzewicz, Reduction of flood risk in Europe – Reflections from a reinsurance perspective, Journal of Hydrology, 576, 197-209, doi:10.1016/j.jhydrol.2019.06.050, 2019.
    77. Shalby, A., M. Elshemy, and B. A. Zeidan, Assessment of climate change impacts on water quality parameters of Lake Burullus, Egypt, Environmental Science and Pollution Research, doi:10.1007/s11356-019-06105-x, 2019.
    78. Wine, M. L., Toward strong science to support equitable water sharing in securitized transboundary watersheds, Biologia, doi:10.2478/s11756-019-00334-8, 2019.
    79. Frank, P., Propagation of error and the reliability of global air temperature projections, Frontiers in Earth Science, 7, 223, doi:10.3389/feart.2019.00223, 2019.
    80. #Hossain, F., D. Niyogi, R. A. Pielke, J. Chen, D. Wegner, A. Mitra, S. Burian, E. Beighley, C. Brown, and V. Tidwell, Current approaches for resilience assessment, Resilience of Large Water Management Infrastructure, Hossain, F. (editor), 35-43, Springer International Publishing, doi:10.1007/978-3-030-26432-1_3, 2020.
    81. Wine, M. L., Climatization of environmental degradation: A widespread challenge to the integrity of earth science, Hydrological Sciences Journal, 65(6), 867-883, doi:10.1080/02626667.2020.1720024, 2020.
    82. Verbist, K. M. J., H. Maureira, P. Rojas, and S.Vicuna, A stress test for climate change impacts on water security: a CRIDA case study, Climate Risk Management, 28, 100222, doi:10.1016/j.crm.2020.100222, 2020.
    83. Hosseini-Moghari, S.-M., and Q. Tang, Validation of GPM IMERG-V05 and V06 precipitation products over Iran, Journal of Hydrometeorology, 21(5), 1011-1037, doi:10.1175/JHM-D-19-0269.1, 2020.
    84. Stefanidis, S., S. Dafis, and D. Stathis, Evaluation of regional climate models (RCMs) performance in simulating seasonal precipitation over mountainous Central Pindus (Greece), Water, 12(10), 2750, doi:10.3390/w12102750, 2020.
    85. Dong, Z., W. Jia, R. Sarukkalige, G. Fu, Q. Meng, and Q. Wang, Innovative trend analysis of air temperature and precipitation in the Jinsha river basin, China, Water, 12(11), 3293, doi:10.3390/w12113293, 2020.
    86. Turner, S. W. D., and P. J. Jeffrey, A simple drought risk analysis procedure to supplement water resources management planning in England and Wales, Water and Environment Journal, 35(1), 417-424, doi:10.1111/wej.12639, 2021.
    87. Sun, B., S. Chen, Q. Liu, Y. Lu, C. Zhang, and H. Fang, Review of sewage flow measuring instruments, Ain Shams Engineering Journal, 12(2), 2089-2098, doi:10.1016/j.asej.2020.08.031, 2021.
    88. Baran-Zgłobicka, B., D. Godziszewska, and W. Zgłobicki, The flash floods risk in the local spatial planning (case study: Lublin Upland, E Poland), Resources, 10(2), 14, doi:10.3390/resources10020014, 2021.
    89. Neupane, S., S. Shrestha, U. Ghimire, S. Mohanasundaram, and S. Ninsawat, Evaluation of the CORDEX regional climate models (RCMs) for simulating climate extremes in the Asian cities, Science of The Total Environment, 797, 149137, doi:10.1016/j.scitotenv.2021.149137, 2021.
    90. Manous, J., and E. Z. Stakhiv, Climate risk-informed decision analysis (CRIDA): ‘top-down’ vs ‘bottom-up’ decision making for planning water resources infrastructure, Water Policy, 23(S1), 54-76, doi:10.2166/wp.2021.243, 2021.
    91. Stakhiv, E. Z., The centrality of engineering codes and risk-based design standards in climate adaptation strategies, Water Policy, 23(S1), 106-127, doi:10.2166/wp.2021.345, 2021.
    92. Ramadhan, R., H. Yusnaini, M. Marzuki, R. Muharsyah, W. Suryanto, S. Sholihun, M. Vonnisa, H. Harmadi, A. P. Ningsih, A. Battaglia, H. Hashiguchi, and A. Tokay, Evaluation of GPM IMERG performance using gauge data over Indonesian maritime continent at different time scales, Remote Sensing, 14(5), 1172, doi:10.3390/rs14051172, 2022.
    93. Haji-Aghajany, S., Y. Amerian, and A. Amiri-Simkooei, Function-based troposphere tomography technique for optimal downscaling of precipitation, Remote Sensing, 14(11), 2548, doi:10.3390/rs14112548, 2022.
    94. Mohebbi, A., K. R. Adams, S. Akbariyeh, M. Maruf, and A. H. Baghanam, Application of weather research and forecasting (WRF) model in evaluating depth–duration–frequency estimates under a future climate scenario, Hydrology Research, nh2022045, doi:10.2166/nh.2022.045, 2022.
    95. Girma, R., C. Fürsta, and A. Moges, Performance evaluation of CORDEX-Africa regional climate models in simulating climate variables over Ethiopian main rift valley: Evidence from Gidabo river basin for impact modeling studies, Dynamics of Atmospheres and Oceans, 99, 101317, doi:10.1016/j.dynatmoce.2022.101317, 2022.
    96. Ahamed, M. R. A., A. Sharma, J. M. Wani, and A. P. Dimri, The representation of summer monsoon rainfall over northeast India: assessing the performance of CORDEX-CORE model experiments, Theoretical and Applied Climatology, doi:10.1007/s00704-023-04369-5, 2023.
    97. Frank, P., LiG metrology, correlated error, and the integrity of the global surface air-temperature record, Sensors, 23(13), 5976, doi:10.3390/s23135976, 2023.

  1. D. Koutsoyiannis, C. Makropoulos, A. Langousis, S. Baki, A. Efstratiadis, A. Christofides, G. Karavokiros, and N. Mamassis, Climate, hydrology, energy, water: recognizing uncertainty and seeking sustainability, Hydrology and Earth System Sciences, 13, 247–257, doi:10.5194/hess-13-247-2009, 2009.

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

    Remarks:

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

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

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

    Additional material:

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

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

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

    1. Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry, HESS Opinions "Crash tests for a standardized evaluation of hydrological models", Hydrology and Earth System Sciences, 13, 1757-1764, 2009.
    2. Hunt, D. V. L., I. Jefferson, M. R. Gaterell, and C. D. F. Rogers, Planning for sustainable utility infrastructure, Proceedings of the Institution of Civil Engineers – Urban Design and Planning, 162(DP4), 187-201, 2009.
    3. Makropoulos, C. K., and D. Butler, Distributed water infrastructure for sustainable communities, Water Resources Management, 24(11), 2795-2816, 2010.
    4. Jódar, J., J. Carrera, and A. Cruz, Irrigation enhances precipitation at the mountains downwind, Hydrology and Earth System Sciences, 14, 2003-2010, 2010.
    5. #Ladanai, S., and J. Vinterbäck, Biomass for Energy versus Food and Feed, Land Use Analyses and Water Supply, Report 022, Swedish University of Agricultural Sciences, ISSN 1654-9406, Uppsala, 2010.
    6. Ward, J. D., A. D. Werner, W. P. Nel, and S. Beecham, The influence of constrained fossil fuel emissions scenarios on climate and water resource projections, Hydrology and Earth System Sciences, 15, 1879-1893, 2011.
    7. #Montanari, A, Uncertainty of hydrological predictions, In: P. Wilderer (ed.) Treatise on Water Science, Vol. 2, 459–478, Oxford Academic Press, 2011.
    8. #Willems, P., J. Olsson, K. Arnbjerg-Nielsen, S. Beecham, A. Pathirana, I. Bulow Gregersen, H. Madsen, V.-T.-V. Nguyen, Practices and Impacts of Climate Change on Rainfall Extremes and Urban Drainage, IWA Publishing, London, 2012.
    9. Andrés-Doménech, I., A. Montanari and J. B. Marco, Efficiency of storm detention tanks for urban drainage systems under climate variability, Journal of Water Resources Planning and Management, 138 (1), 36-46, 2012.
    10. Montanari, A., Hydrology of the Po River: looking for changing patterns in river discharge, Hydrology and Earth System Sciences, 16, 3739-3747, doi:10.5194/hess-16-3739-2012, 2012.
    11. Voulvoulis, N., Water and sanitation provision in a low carbon society: The need for a systems approach, Journal of Renewable and Sustainable Energy, 4(4), 041403, doi:10.1063/1.3665797, 2012.
    12. #Skaggs, R., K. A. Hibbard, T. C. Janetos, and J. S. Rice, Climate and energy-water-land system interactions, Technical report to the U.S. Department of Energy in Support of the National Climate Assessment, Report No. PNNL-21185, Pacific Northwest National Laboratory, Richland, WA, 152 pp., 2012.
    13. Gunasekara, N. K., S. Kazama, D. Yamazaki and T. Oki, The effects of country-level population policy for enhancing adaptation to climate change, Hydrol. Earth Syst. Sci., 17, 4429-4440, 2013.
    14. Nastos, P. T., N. Politi, and J. Kapsomenakis, Spatial and temporal variability of the aridity index in Greece, Atmospheric Research, 19, 140-152, 2013.
    15. Hrachowitz, M., H.H.G. Savenije, G. Blöschl, J.J. McDonnell, M. Sivapalan, J.W. Pomeroy, B. Arheimer, T. Blume, M.P. Clark, U. Ehret, F. Fenicia, J.E. Freer, A. Gelfan, H.V. Gupta, D.A. Hughes, R.W. Hut, A. Montanari, S. Pande, D. Tetzlaff, P.A. Troch, S. Uhlenbrook, T. Wagener, H.C. Winsemius, R.A. Woods, E. Zehe, and C. Cudennec, A decade of Predictions in Ungauged Basins (PUB) — a review, Hydrological Sciences Journal, 58(6), 1198-1255, 2013.
    16. Thompson, S. E., M. Sivapalan, C. J. Harman, V. Srinivasan, M. R. Hipsey, P. Reed, A. Montanari and G. and Blöschl, Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene, Hydrology and Earth System Sciences, 17, 5013-5039, 2013.
    17. #Voulvoulis, N., The potential of water reuse as a management option for water security under the ecosystem services approach, Win4Life Conference, Tinos Island, Greece, 2013.
    18. Dette, H., and K. Sen, Goodness-of-fit tests in long-range dependent processes under fixed alternatives, ESAIM: Probability and Statistics, 17, 432-443, 2013.
    19. Ilich, N., An effective three-step algorithm for multi-site generation of stochastic weekly hydrological time series, Hydrological Sciences Journal, 59 (1), 85-98, 2014.
    20. Jain, S., Reference climate and water data networks for India, Journal of Hydrologic Engineering, 20(4), 02515001, doi:10.1061/(ASCE)HE.1943-5584.0001170, 2015.
    21. Voulvoulis, N., The potential of water reuse as a management option for water security under the ecosystem services approach, Desalination and Water Treatment, 53 (12), 3263-3271, doi:10.1080/19443994.2014.934106, 2015.
    22. #Rohli, R. V., Overview of applied climatology and water/energy resources, Selected Readings in Applied Climatology, R. V. Rohli and T. A. Joyner (editors), 144-155, Cambridge Scholars Publishing, 2015.
    23. #Kim, S.S.H., J.D. Hughes, D. Dutta, and J. Vaze, Why do sub-period consistency calibrations outperform traditional optimisations in streamflow prediction? Proceedings of 21st International Congress on Modelling and Simulation, 2061-2067, Gold Coast, Australia, 2015.
    24. Kim, S. S. H., J. D. Hughes, J. Chen, D. Dutta, and J. Vaze, Determining probability distributions of parameter performances for time-series model calibration: A river system trial, Journal of Hydrology, 530, 361–371, doi:10.1016/j.jhydrol.2015.09.073, 2015.
    25. Clark, C., Two rural temperature records in Somerset, UK, Weather, 70(10), 280-284, doi:10.1002/wea.2512, 2015.
    26. Tsonis, A. A., Randomness: a property of the mathematical and physical systems, Hydrological Sciences Journal, 61(9), 1591-1610, doi:10.1080/02626667.2014.992434, 2016.
    27. Di Baldassarre, G., L. Brandimarte, and K. Beven, The seventh facet of uncertainty: wrong assumptions, unknowns and surprises in the dynamics of human-water systems, Hydrological Sciences Journal, 61(9), 1748-1758, doi:10.1080/02626667.2015.1091460, 2016.
    28. Chrs, C. C., Models, the establishment, and the real world: Why do so many flood problems remain in the UK?, Journal of Geoscience and Environment Protection, 5, 44-59, doi:10.4236/gep.2017.52004, 2017.
    29. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, 1, 28-35, doi:10.1016/j.wasec.2017.06.001, 2017.
    30. Madani, E. M., P. E. Jansson, and I. Babelon, Differences in water balance between grassland and forest watersheds using long-term data, derived using the CoupModel, Hydrology Research, 49(1), 72-89, doi:10.2166/nh.2017.154, 2018.
    31. #Oliveira da Silva Araújo, R. C., L. Gomes Lourenço, O. Siena, and C. A. da Silva Müller, Inovação e sustentabilidade na produção e uso de energia: uma meta-análise, Sustentabilidade e Responsabilidade Social em Foco – Volume 4, Capítulo 3, Organização Editora Poisson, doi:10.5935/978-85-93729-64-5.2018B001, 2018.
    32. Biondi, D., and E. Todini, Comparing hydrological post‐processors including ensembles predictions into full predictive probability distribution of streamflow, Water Resources Research, 54(12), 9860-9882, doi:10.1029/2017WR022432, 2018.
    33. Dahlke, H. E., G. T. LaHue, M. R. L. Mautner, N. P. Murphy, N. K. Patterson, H. Waterhouse, F. Yang, and L. Foglia, Managed aquifer recharge as a tool to enhance sustainable groundwater management in California: Examples from field and modeling studies, Advances in Chemical Pollution, Environmental Management and Protection, 3, 215-275, doi:10.1016/bs.apmp.2018.07.003, 2018.
    34. Giudici, F., A. Castelletti, E. Garofalo, M. Giuliani, and H. R. Maier, Dynamic, multi-objective optimal design and operation of water-energy systems for small, off-grid islands, Applied Energy, 250, 605-616, doi:10.1016/j.apenergy.2019.05.084, 2019.
    35. Tzanakakis, V. A., A. N. Angelakis, N. V. Paranychianakis, Y. G. Dialynas, and G. Tchobanoglous, Challenges and opportunities for sustainable management of water resources in the island of Crete, Greece, Water, 12(6), 1538, doi:10.3390/w12061538, 2020.
    36. Ayzel, G., L. Kurochkina, and S. Zhuravlev, The influence of regional hydrometric data incorporation on the accuracy of gridded reconstruction of monthly runoff, Hydrological Sciences Journal, doi:10.1080/02626667.2020.1762886, 2020.
    37. Yang, W., F. Jin, Y. Si, and Z. Li, Runoff change controlled by combined effects of multiple environmental factors in a headwater catchment with cold and arid climate in northwest China, Science of The Total Environment, 756, 143995, doi:10.1016/j.scitotenv.2020.143995, 2021.
    38. Kourgialas, N. N., A critical review of water resources in Greece: The key role of agricultural adaptation to climate-water effects, Science of the Total Environment, 775, 145857, doi:10.1016/j.scitotenv.2021.145857, 2021.
    39. #Eslamian S., and S. Parvizi, Engineering Hydrology: Impact on Sustainable Development, Climate Action, Encyclopedia of the UN Sustainable Development Goals, Leal Filho W., Azul A.M., Brandli L., Özuyar P.G., Wall T. (eds), Springer, Cham, doi:10.1007/978-3-319-71063-1_134-1, 2021.
    40. Lemonis, A. S. Skroufouta, and E. Baltas, An economic evaluation towards sustainability: The case of a hybrid renewable energy system in Greece, American Journal of Environmental and Resource Economics, 7(1), 37-47, doi:10.11648/j.ajere.20220701.15, 2022.
    41. Cui, Y., J. Jin, X. Bai, S. Ning, L. Zhang, C. Wu, and Y. Zhang, Quantitative evaluation and obstacle factor diagnosis of agricultural drought disaster risk using connection number and information entropy, Entropy, 24(7), 872, doi:10.3390/e24070872, 2022.
    42. Antwi, K., G. Adu, S. Adu, and J. Appiah-Yeboah, Physical and fuel properties of Bambusa Vulgaris of different age groups and their effect on producing biofuel, South-East European Forestry, 13(1), 53-64, doi:10.15177/seefor.22-05, 2022.
    43. Caixeta F., A. M. Carvalho, P. Saraiva, and F. Freire, Sustainability-focused excellence: A novel model integrating the water-energy-food nexus for agro-industrial companies, Sustainability, 14(15), 9678, doi:10.3390/su14159678, 2022.
    44. Angelakis, A. N., J. Krasilnikoff, and V. A. Tzanakakis, Evolution of water technologies and corresponding philosophy and sciences focusing on the Hellenic world through the millennia, Water, 14, 3149, doi:10.3390/w14193149, 2022.
    45. Li, C., J. Hao, G. Zhang, H. Fang, Y. Wang, and H. Lu, Runoff variations affected by climate change and human activities in Yarlung Zangbo River, southeastern Tibetan Plateau, Catena, doi:10.1016/j.catena.2023.107184, 2023.
    46. Jorquera, J., and A. Pizarro, Unlocking the potential of stochastic simulation through Bluecat: Enhancing runoff predictions in arid and high‐altitude regions, Hydrological Processes, 37(12), e15046, doi:10.1002/hyp.15046, 2023.
    47. De León Pérez, D., R. Acosta Vega, S. Salazar Galán, J. Á. Aranda, and F. Francés García, Toward systematic literature reviews in hydrological sciences, Water, 16(3), 436, doi:10.3390/w16030436, 2024.

  1. D. Koutsoyiannis, A. Efstratiadis, N. Mamassis, and A. Christofides, On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671–684, doi:10.1623/hysj.53.4.671, 2008.

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

    Remarks:

    The paper has been widely discussed in weblogs and forums.

    Weblogs and forums that discussed this article during 2008:

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

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

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

    Related works:

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

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

    Additional material:

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

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

    1. Carter, R. M., Knock, knock: Where is the evidence for dangerous human-caused global warming?, Economic Analysis & Policy, 38(2), 177-202, 2008.
    2. #Crockford, S., Some things we know — and don’t know —about polar bears, Report, Science and Public Policy Institute, 2008.
    3. #Green, K. C., J. S. Armstrong and W. Soon, Benchmark forecasts for climate change, Munich Personal RePEc Archive, 2008.
    4. #Drinkwater, K., M. Skogen, S. Hjøllo, C. Schrum, I. Alekseeva, M. Huret and F. Léger, The effects of future climate change on the physical oceanography and comparisons of the mean and variability of the future physical properties with present day conditions, Report, RECLAIM EU/FP6 project (REsolving CLimAtic IMpacts on fish stocks), WP4 Future oceanographic changes, 28 pp., 2008.
    5. Halley, J. M., Using models with long-term persistence to interpret the rapid increase of earth’s temperature, Physica A: Statistical Mechanics and its Applications, 388(12), 2492-2502, 2009.
    6. Kundzewicz, Z. W., L. J. Mata, N. W. Arnell, P. Döll, B. Jimenez, K. Miller, T. Oki and Z. Şen, Water and climate projections—Reply to discussion “Climate, hydrology and freshwater: towards an interactive incorporation of hydrological experience into climate research”, Hydrological Sciences Journal, 54(2), 406-415, 2009.
    7. Hollowed, A. B., N. A. Bond, T. K. Wilderbuer, W. T. Stockhausen, Z. T. Amar, R. J. Beamish, J. E. Overland, and M. J. Schirripa, A framework for modelling fish and shellfish responses to future climate change, ICES Journal Of Marine Science, 66(7), 1584-1594, 2009.
    8. MacDonald, A. M., R. C. Calow, D. M. J. MacDonald, W. G. Darling, and B. É. Ó. Dochartaigh, What impact will climate change have on rural groundwater supplies in Africa?, Hydrological Sciences Journal, 54(4), 690-703, 2009.
    9. #Pilkey, O. H., and R. Young, The Rising Sea, 203 p., Island Press, Washington, DC, 2009.
    10. Chiew, F.H.S., J. Tenga, J. Vazea, and D.G.C. Kirono, Influence of global climate model selection on runoff impact assessment, Journal of Hydrology, 379(1-2), 172-180, 2009.
    11. McIntyre, D.R., James Hansen's 1988 predictions compared to observations, Energy and Environment, 20(4), 587-594, 2009.
    12. Matthews, J., and A. J. Wickel, Embracing uncertainty in freshwater climate change adaptation: A natural history approach, Climate and Development, 1(3), 269-279, 2009.
    13. #Taylor, P., Chill, a reassessment of global warming theory: does climate change mean the world is cooling, and if so what should we do about it?, Clairview Books, 404 pp., 2009.
    14. #Franklin, J., What Science Knows: And How It Knows It, Encounter Books, New York, 2009.
    15. Pittock, J., Lessons for climate change adaptation from better management of rivers, Climate and Development, 1(3), 194-211, 2009.
    16. #McKenzie, J. M., D. I. Siegel, and D. O. Rosenberry, Improving conceptual models of water and carbon transfer through peat, Northern Peatlands and Carbon Cycling, Baird, A. J., L. R. Belyea, X. Comas, A. S. Reeve, and L. D. Slater (eds.), American Geophysical Union Geophysical Monograph Series, 184, 265-275, 2009.
    17. #Roudier, P., et P. Quirion, Bilan des changements climatiques passés et futurs au Mali: rapport pour action contre la faim, Centre International de Recherche sur l’Environnement et le Développement (CIRED), 42 p., Juin 2009.
    18. Blöschl, G., and A. Montanari, Climate change impacts - throwing the dice?, Hydrological Processes, 24(3), 374-381, 2010.
    19. Kundzewicz, Z. W., Y. Hirabayashi and S. Kanae, River floods in the changing climate—Observations and projections, Water Resources Management, 24(11), 2633-2646, 2010.
    20. Romanowicz, R. J., A. Kiczko and J. J. Napiórkowski, Stochastic transfer function model applied to combined reservoir management and flow routing, Hydrological Sciences Journal, 55(1), 27–40, 2010.
    21. Liu, S., X. Mo, Z. Lin, Y. Xu, J. Ji, G. Wen, and J. Richey, Crop yield responses to climate change in the Huang-Huai-Hai Plain of China, Agricultural Water Management, 97(8), 1195-1209, 2010.
    22. Kawasaki, A., M. Takamatsu, J. He, P. Rogers, and S. Herath, An integrated approach to evaluate potential impact of precipitation and land-use change on streamflow in Srepok River Basin, Theory and Applications of GIS, 2010.
    23. Vastila, K., M. Kummu, C. Sangmanee, and S. Chinvanno, Modelling climate change impacts on the flood pulse in the Lower Mekong floodplains, Journal of Water and Climate Change, 01.1, 67-86, 2010.
    24. Kundzewicz, Z. W., and E. Z. Stakhiv, Are climate models “ready for prime time” in water resources management applications, or is more research needed? Hydrological Sciences Journal, 55(7), 1085–1089, 2010.
    25. Zhang, S.-F., Y. Gu, and J. Lin, Uncertainty analysis in the application of climate models, Shuikexue Jinzhan/Advances in Water Science, 21(4), 504-511, 2010.
    26. Wu, S.-Y., Potential impact of climate change on flooding in the Upper Great Miami River Watershed, Ohio, USA: a simulation-based approach, Hydrological Sciences Journal, 55(8), 1251-1263, 2010.
    27. Soon, W., and D. R. Legates, Avoiding carbon myopia: three considerations for policy makers concerning manmade carbon dioxide, Ecology Law Currents, 37(1), 2010.
    28. #Liebscher, H.-J., and H. G. Mendel, Vom empirischen Modellansatz zum komplexen hydrologischen Flussgebietsmodell – Rückblick und Perspektiven, 132 p., Koblenz, Bundesanstalt für Gewässerkunde, 2010.
    29. #Maletta, H. E., and E. Maletta, Climate Change, Agriculture and Food Security in Latin America and the Caribbean, 319 p., 2010.
    30. Stockwell, D. R. B., Critique of drought models in the Australian Drought Exceptional Circumstances Report (DECR), Energy and Environment, 21(5), 425-436, 2010.
    31. Kigobe, M., N. McIntyre, H. Wheater and R. Chandler, Multi-site stochastic modelling of daily rainfall in Uganda, Hydrological Sciences Journal, 56(1), 17–33, 2011.
    32. Hänggi, P., and R. Weingartner, Inter-annual variability of runoff and climate within the Upper Rhine River basin, 1808–2007, Hydrological Sciences Journal, 56(1), 34–50, 2011.
    33. Di Baldassarre, G., M. Elshamy, A. van Griensven, E. Soliman, M. Kigobe, P. Ndomba, J. Mutemi, F. Mutua, S. Moges, J.-Q. Xuan, D. Solomatine and S. Uhlenbrook, Future hydrology and climate in the River Nile basin: a review, Hydrological Sciences Journal, 56(2), 199-211, 2011.
    34. Fatichi, S., V. Y. Ivanov, and E. Caporali, Simulation of future climate scenarios with a weather generator, Advances in Water Resources, 34(4), 448-467, doi: 10.1016/j.advwatres.2010.12.013, 2011.
    35. Mann, M. E., On long range dependence in global surface temperature series, Climatic Change, 107 (3), 267-276, 2011.
    36. Kundzewicz, Z. W., Nonstationarity in water resources – Central European perspective, Journal of the American Water Resources Association, 47(3), 550-562, 2011.
    37. #Carter, B., D. Evans, S. Franks and W. Kininmonth, Scientific audit of a report from the Climate Commission: The Critical Decade ‐ Climate science, risks and responses, 14 pp., 2011.
    38. Tertrais, B., The climate wars myth, The Washington Quarterly, 34 (3), 17-29, 2011.
    39. Kiem, A. S., and D. C. Verdon-Kidd, Steps toward “useful” hydroclimatic scenarios for water resource management in the Murray-Darling Basin, Water Resources Research, 47, W00G06, doi: 10.1029/2010WR009803, 2011.
    40. Sivakumar, B., Water crisis: From conflict to cooperation – an overview, Hydrological Sciences Journal, 56(4), 531-552, 2011.
    41. Burke, E. J., Understanding the sensitivity of different drought metrics to the drivers of drought under increased atmospheric CO2, Journal of Hydrometeorology, 12(6), 1378-1394, 2011.
    42. #Rolim da Paz, A., C. Uvo, J. Bravo, W. Collischonn and H. R. da Rocha, Seasonal precipitation forecast based on artificial neural networks, Computational Methods for Agricultural Research: Advances and Applications, IGI Global, 326-354, doi: 10.4018/978-1-61692-871-1.ch016, 2011.
    43. Fildes, R., and N. Kourentzes, Validation and forecasting accuracy in models of climate change, International Journal of Forecasting, 27(4), 968-995, 2011.
    44. #Huard, D., The challenges of climate change interpretation, Ouranos Newsletter, Montreal, Quebec, 3 pp., 21 September 2011.
    45. Rao, A. R., M. Azli and L. J. Pae, Identification of trends in Malaysian monthly runoff under the scaling hypothesis, Hydrological Sciences Journal, 56(6), 917–929, 2011.
    46. Huard, D., A black eye for the Hydrological Sciences Journal, Discussion of “A comparison of local and aggregated climate model outputs with observed data”, by G. G. Anagnostopoulos et al. (2010, Hydrol. Sci. J. 55 (7), 1094–1110), Hydrological Sciences Journal, 56(7), 1330–1333, 2011.
    47. Halley, J. M., and D. Kugiumtzis, Nonparametric testing of variability and trend in some climatic records, Climatic Change, 107(3-4), 267-276, 2011.
    48. Stakhiv, E. Z., Pragmatic approaches for water management under climate change uncertainty, JAWRA Journal of the American Water Resources Association, 47(6), 1183-1196, 2011.
    49. #Bourqui, M., T. Mathevet, J. Gailhard and F. Hendrickx, Hydrological validation of statistical downscaling methods applied to climate model projections, IAHS Publication 344, 32-38, 2011.
    50. #Kundzewicz, Z. W., Comparative assessment: fact or fiction? Paper presented at the Workshop Including long-term climate change in hydrologic design, World Bank, Washington, D.C., USA, November 21, 2011.
    51. Collischonn, B., J. A. Louzada, Impacto potencial de mudanças climáticas sobre as necessidades de irrigação da cultura do milho no Rio Grande do Sul, Revista de Gestão de Água da América Latina, 8(2), 19-29, 2011.
    52. del Monte-Luna, P., V. Guzmán-Hernández, E. A. Cuevas, F. Arreguín-Sánchez, and D. Lluch-Belda, Effect of North Atlantic climate variability on hawksbill turtles in the Southern Gulf of Mexico, Journal of Experimental Marine Biology and Ecology, 412, 103-109, 2012.
    53. Lacombe, G., C. T. Hoanh and V. Smakhtin, Multi-year variability or unidirectional trends? Mapping long-term precipitation and temperature changes in continental Southeast Asia using PRECIS regional climate model, Climatic Change, 113(2), 285-299, doi: 10.1007/s10584-011-0359-3, 2012.
    54. #Ortiz, R., Climate Change and Agricultural Production, Inter-American Development Bank, 2012.
    55. Whitfield, P. H., Floods in future climates: a review, Journal of Flood Risk Management, 5(4), 336–365, 2012.
    56. Fan, Z., T. Yue, and C. Chen, Downscaling of global mean annual temperature under different scenarios, Progress in Geography, 31(3), 267-274, 2012.
    57. Sivakumar, B., Socio-hydrology: not a new science, but a recycled and re-worded Hydrosociology, Hydrological Processes, 26(24), 3788–3790, 2012.
    58. Kim, J. J., H. S. Min, C.-H. Kim, J. Yoon and S. Kim, Prediction of the spawning ground of Todarodes pacificus under IPCC climate A1B scenario, Ocean and Polar Research, 34 (2), 253-264, 2012.
    59. #Mesa, O. J., V. K. Gupta, and P. E. O'Connell, Dynamical system exploration of the Hurst phenomenon in simple climate models, in: Extreme Events and Natural Hazards: The Complexity Perspective, Geophys. Monogr. Ser., vol. 196, edited by A. S. Sharma et al. 209–229, AGU, Washington, D. C., 2012.
    60. da Silva, W. T. P., A. C. L. Duarte and de M. A. A. Souza, Implementation and optimization project for CDM certification in wastewater treatment plant, Engenharia Sanitaria e Ambiental, 17(1), 13-24, 2012.
    61. #Fekete, B. M., and E. Stakhiv, Water management preparation strategies for adaptation to changing climate, Climatic Change and Global Warming of Inland Waters: Impacts and Mitigation for Ecosystems and Societies, C. R. Goldman, M. Kumagai, and R. D. Robarts (eds.), 413-427, 2012.
    62. #Hamilton, D. P., C. McBride, D. Özkundakci, M. Schallenberg, P. Verburg, M. de Winton, D. Kelly, C. Hendy, and W. Ye, Effects of climate change on New Zealand Lakes, Climatic Change and Global Warming of Inland Waters: Impacts and Mitigation for Ecosystems and Societies, C. R. Goldman, M. Kumagai, and R. D. Robarts (eds.), 337-366, 2012.
    63. #Verdon-Kidd, D., A. Kiem, and E. Austin, Decision-making under uncertainty – Bridging the gap between end user needs and science capability, National Climate Change Adaptation Research Facility, Gold Coast, pp.116., ISBN: 978-1-921609-67-1, 2012.
    64. Jiang, P., M. R. Gautam, J. Zhu, and Z. Yu, How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?, Journal of Hydrology, 479, 13-23, 2013.
    65. Lien, W.-Y., C.-P. Tung, Y.-H. Ho, C.-H. Tai and L.-H. Chuang, Establish methods to evaluate the projection ability of general circulation models, Journal of Taiwan Agricultural Engineering, 59 (1), 1-14, 2013.
    66. Bayer, T. K., C. W. Burns, and M. Schallenberg, Application of a numerical model to predict impacts of climate change on water temperatures in two deep, oligotrophic lakes in New Zealand, Hydrobiologia, 713 (1), 53-71, 2013.
    67. Hrachowitz, M., H.H.G. Savenije, G. Blöschl, J.J. McDonnell, M. Sivapalan, J.W. Pomeroy, B. Arheimer, T. Blume, M.P. Clark, U. Ehret, F. Fenicia, J.E. Freer, A. Gelfan, H.V. Gupta, D.A. Hughes, R.W. Hut, A. Montanari, S. Pande, D. Tetzlaff, P.A. Troch, S. Uhlenbrook, T. Wagener, H.C. Winsemius, R.A. Woods, E. Zehe, and C. Cudennec, A decade of Predictions in Ungauged Basins (PUB) — a review, Hydrological Sciences Journal, 58(6), 1198-1255, 2013.
    68. Varotsos, C.A., M.N. Efstathiou, and A.P. Cracknell, On the scaling effect in global surface air temperature anomalies, Atmospheric Chemistry and Physics, 13, 5243-5253, doi:10.5194/acp-13-5243-2013, 2013.
    69. #Mortazavi, M., G. Kuczera, A. S. Kiem, B. Henley, B. Berghout and E. Turner, Robust optimisation of urban drought security for an uncertain climate, National Climate Change Adaptation Research Facility, Gold Coast, Australia, pp. 74, 2013.
    70. Kiem, A. S., and E. K. Austin, Drought and the future of rural communities: Opportunities and challenges for climate change adaptation in regional Victoria, Australia, Global Environmental Change, 23(5), 1307–1316, doi:10.1016/j.gloenvcha.2013.06.003, 2013.
    71. #Tomlinson, E., B. Kappel, G. Muhlestein, D. Hultstrand and T. Parzybok, Probable Maximum Precipitation Study for Arizona, Arizona Department of Water Resources, Arizona, USA, 2013.
    72. #Kappel, B., G. Muhlestein, E. Tomlinson, D. Hultstrand and M. Johnson, Calculating Arizona basin-specific PMP using the PMP evaluation tool, Association of State Dam Safety Officials Annual Conference 2013, Dam Safety 2013, 2, 904-969, 2013.
    73. EFSA Panel on Plant Health (PLH), Scientific Opinion on the risks to plant health posed by Bemisia tabaci species complex and viruses it transmits for the EU territory, EFSA Journal, 11(4), 3162, doi:10.2903/j.efsa.2013.3162, 2013.
    74. Jayakody, P., P. B. Parajuli, T. P. Cathcart, Impacts of climate variability on water quality with best management practices in subtropical climate of USA, Hydrological Processes, 28(23), 5776–5790, 2014.
    75. Kundzewicz, Z.W., S. Kanae, S. I. Seneviratne, J. Handmer, N. Nicholls, P. Peduzzi, R. Mechler, L. M. Bouweri, N. Arnell, K. Mach, R. Muir-Wood, G. R. Brakenridge, W. Kron, G. Benito, Y. Honda, K. Takahashi, and B. Sherstyukov, Flood risk and climate change: global and regional perspectives, Hydrological Sciences Journal, 59(1), 1–28, 2014.
    76. Honti, M., A. Scheidegger, and C. Stamm, The importance of hydrological uncertainty assessment methods in climate change impact studies, Hydrology and Earth System Sciences, 18, 3301-3317, 10.5194/hess-18-3301-2014, 2014.
    77. Gilioli, G., S. Pasquali, S. Parisi and S. Winter, Modelling the potential distribution of Bemisia tabaci in Europe considering climate change scenario, Pest Management Science, 70(1), 1611–1623, 10.1002/ps.3734, 2014.
    78. #Jiménez Cisneros, B.E., T. Oki, N.W. Arnell, G. Benito, J.G. Cogley, P. Döll, T. Jiang, and S.S. Mwakalila, Freshwater resources. In: Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)], Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 229-269, 2014.
    79. #Kiem, A. S., Climate variability and change, ch. 2 in Climate Change and Water Resources, 31-67, 2014.
    80. Kiem, A. S., D. C. Verdon-Kidd, and E. K. Austin, Bridging the gap between end user needs and science capability: decision making under uncertainty, Climate Research, 61(1), 57-74, 2014.
    81. Stonevičius, E., G. Valiuškevičius, E. Rimkus and J. Kažys, Climate induced changes of Lithuanian rivers runoff in 1960–2009, Water Resources, 41 (5), 592-603, 2014.
    82. #McKitrick, R., Climate Policy Implications of the Hiatus in Global Warming, Fraser Institute, 2014.
    83. Yao, Y., S. Zhao, Y. Zhang, K. Jia and M. Liu, Spatial and decadal variations in potential evapotranspiration of China based on reanalysis datasets during 1982–2010, Atmosphere, 5(4), 737-754, 2014.
    84. #Verdon-Kidd, D. C., A. S. Kiem, and E. K. Austin, 7 Bridging the gap between researchers and decision-makers, ch. 7 in Applied Studies in Climate Adaptation (ed. by J. P. Palutikof, S. L. Boulter, J. Barnett, and D. Rissik) Applied Studies in Climate Adaptation, Wiley-Blackwell, Oxford, UK, 51-59, 2014.
    85. Nova, J., Government monopoly in science and the role of independent scientists, Energy and Environment, 25(6-7), 1219–1224, 2014.
    86. Bravo, J. M., W. Collischonn, A. R. Paz, D. Allasia, and F. Domecq, Impact of projected climate change on hydrologic regime of the Upper Paraguay River basin, Climatic Change, 127(1), 27–41, 2014.
    87. #Ranzi, R., and M. Tomirotti, Long term statistics of river flow regime: climatic or anthropogenic changes?, Proceedings of 3rd IAHR Europe Congress, Porto, 2014.
    88. Kundzewicz, Z., and D. Gerten, Grand challenges related to assessment of climate change impacts on freshwater resources, Journal of Hydrologic Engineering, 20 (1), 10.1061/(ASCE)HE.1943-5584.0001012, A4014011, 2015.
    89. Stefanova, A., V. Krysanova, C. Hesse, and A. I. Lillebø, Climate change impact assessment on water inflow to a coastal lagoon: the Ria de Aveiro watershed, Portugal, Hydrological Sciences Journal, 60(5), 929-948, 2015.
    90. Vallebona, C., E. Pellegrino, P. Frumento, and E. Bonari, Temporal trends in extreme rainfall intensity and erosivity in the Mediterranean region: a case study in southern Tuscany, Italy, Climatic Change, 128(1-2), 139-151, 2015.
    91. Gil-Alana, L.A., Linear and segmented trends in sea surface temperature data, Journal of Applied Statistics, 42(7), 1531-1546, doi:10.1080/02664763.2014.1001328, 2015.
    92. Wi, S., Y.C.E. Yang, S. Steinschneider, A. Khalil, and C.M. Brown, Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change, Hydrology and Earth System Sciences, 19, 857-876, doi:10.5194/hess-19-857-2015, 2015.
    93. Hesse, C., A. Stefanova, and V. Krysanova, Comparison of water flows in four European lagoon catchments under a set of future climate scenarios, Water, 7(2), 716-746, doi:10.3390/w7020716, 2015.
    94. Yu, Z., P. Jiang, M. R. Gautam, Y. Zhang, and K. Acharya, Changes of seasonal storm properties in California and Nevada from an ensemble of climate projections, Journal of Geophysical Research: Atmospheres, 120(7), 2676-2688, doi:10.1002/2014JD022414, 2015.
    95. Mortazavi-Naeini, M., G. Kuczera, A. S. Kiem, L. Cui, B. Henley, B. Berghout, and E. Turner, Robust optimization to secure urban bulk water supply against extreme drought and uncertain climate change, Environmental Modelling and Software, 69, 437-451, doi:10.1016/j.envsoft.2015.02.021, 2015.
    96. Verdon-Kidd, D. C. and A. S. Kiem, Non–stationarity in annual maxima rainfall across Australia – implications for Intensity–Frequency–Duration (IFD) relationships, Hydrology and Earth System Sciences, 19, 4735-4746, doi:10.5194/hessd-12-3449-2015, 2015.
    97. Legates, D. R., W. Soon, W. M. Briggs and C. Monckton of Brenchley, Climate consensus and ‘misinformation’: a rejoinder to agnotology, scientific consensus, and the teaching and learning of climate change, Science and Education, 24, 299-318, 10.1007/s11191-013-9647-9, 2015.
    98. Deb, P., A. S. Kiem, M. S. Babel, S. T. Chu, and B. Chakma, Evaluation of climate change impacts and adaptation strategies for maize cultivation in the Himalayan foothills of India, Journal of Water and Climate Change, 6(3) 596-614, doi:10.2166/wcc.2015.070, 2015.
    99. Frank, P., Negligence, non-science, and consensus climatology, Energy and Environment, 26(3), 391-415, doi:10.1260/0958-305X.26.3.391, 2015.
    100. Oyekale, A. S., Factors explaining farm households’ access to and utilization of extreme climate forecasts in Sub-Saharan Africa (SSA), Environmental Economics, 6(1), 91-103, 2015.
    101. Munshi, J., A robust test for OLS trends in daily temperature data, Social Science Research Network, doi:10.2139/ssrn.2631298, 2015.
    102. #McKitrick, R. Energy policy and environmental stewardship: risk management not risk avoidance, Greer-Heard Point-Counterpoint Forum, 2015.
    103. Kiem, A. S., E. K. Austin, and D. C. Verdon-Kidd, Water resource management in a variable and changing climate: hypothetical case study to explore decision making under uncertainty, Journal of Water and Climate Change, 7(2), 263-279, doi:10.2166/wcc.2015.040, 2016.
    104. Jiang, P., Z. Yu, M. R. Gautam, F. Yuan, and K. Acharya, Changes of storm properties in the United States: Observations and multimodel ensemble projections, Global and Planetary Change, 142, 41–52, doi:10.1016/j.gloplacha.2016.05.001, 2016.
    105. Becker, M., M. Karpytchev, M. Marcos, S. Jevrejeva, and S. Lennartz-Sassinek, Do climate models reproduce complexity of observed sea level changes?, Geophysical Research Letters, 43(10), 5176-5184, doi:10.1002/2016GL068971, 2016.
    106. #Kianfar, B., S. Fatichi, A. Paschalis, M. Maurer, and P. Molnar, Climate change and uncertainty in high-resolution rainfall extremes, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2016-536, 2016.
    107. #Fekete, B. M., G. Pisacane, and D. Wisser, Crystal balls into the future: are global circulation and water balance models ready?, Proc. IAHS, 374, 41-51, doi:10.5194/piahs-374-41-2016, 2016.
    108. #Ranzi, R., P. Caronna, and M. Tomirotti, Impact of climatic and land use changes on river flows in the Southern Alps, Sustainable Water Resources Planning and Management Under Climate Change, 61-83, Springer Singapore, doi:10.1007/978-981-10-2051-3_3, 2017.
    109. Manage, N. P., N. Lockart, G. Willgoose, G. Kuczera, A. S. Kiem, K. Chowdhury, L. Zhang, and C. Twomey, Statistical testing of dynamically downscaled rainfall data for the Upper Hunter region, New South Wales, Australia, Journal of Southern Hemisphere Earth Systems Science, 66, 203–227, doi:10.22499/3.6602.008, 2016.
    110. Stakhiv, E. Z., W. Werick, and R. W. Brumbaugh, Evolution of drought management policies and practices in the United States, Water Policy, 18(S2), 122-152, doi:10.2166/wp.2016.017, 2016.
    111. Camici, S., L. Brocca, and T. Moramarco, Accuracy versus variability of climate projections for flood assessment in central Italy, Climatic Change, 141(2), 273–286, doi:10.1007/s10584-016-1876-x, 2017.
    112. Machiwal, D., D. Dayal, and S. Kumar, Long-term rainfall trends and change points in hot and cold arid regions of India, Hydrological Sciences Journal, 62(7), 1050-1066, doi:10.1080/02626667.2017.1303705, 2017.
    113. Munshi, J., Event attribution and the precipitation record for England and Wales, Social Science Research Network, doi:10.2139/ssrn.2929159, 2017.
    114. Bukovsky, M. S., R. R. McCrary, A. Seth, and L. O. Mearns, A mechanistically credible, poleward shift in warm-season precipitation projected for the U.S. Southern Great Plains?, Journal of Climate, 30(20), 8275–8298, doi:10.1175/JCLI-D-16-0316.1, 2017.
    115. Vogel, M., Stochastic watershed models for hydrologic risk management, Water Security, 1, 28-35, doi:10.1016/j.wasec.2017.06.001, 2017.
    116. Serago, J. M., and R. M. Vogel, Parsimonious nonstationary flood frequency analysis, Advances in Water Resources, 112, 1-16, doi:10.1016/j.advwatres.2017.11.026, 2018.
    117. Stefanidis, S., and D. Stathis, Effect of climate change on soil erosion in a mountainous Mediterranean catchment (Central Pindus, Greece), Water, 10(10), 1469, doi:10.3390/w10101469, 2018.
    118. Kundzewicz, Z. W., Quo vadis, hydrology?, Hydrological Sciences Journal, 63(8), 1118-1132, doi:10.1080/02626667.2018.1489597, 2018.
    119. Zolghadr-Asli, B., O. Bozorg-Haddad, P. Sarzaeim, and X. Chu, Investigating the variability of GCMs' simulations using time series analysis, Journal of Water and Climate Change, 10(3), 449-463, doi:10.2166/wcc.2018.099, 2019.
    120. #Garrard, G., A. Goodbody, G. B. Handley, and S. Posthumus, Climate Change Scepticism: A Transnational Ecocritical Analysis, Bloomsbury Academic, 2019.
    121. Momblanch, A., I. P. Holman, and S. K. Jain, Current practice and recommendations for modelling global change impacts on water resource in the Himalayas, Water, 11(6), 1303, doi:10.3390/w11061303, 2019.
    122. Frank, P., Propagation of error and the reliability of global air temperature projections, Frontiers in Earth Science, 7, 223, doi:10.3389/feart.2019.00223, 2019.
    123. Wine, M. L., Toward strong science to support equitable water sharing in securitized transboundary watersheds, Biologia, 75, 907-915, doi:10.2478/s11756-019-00334-8, 2020.
    124. Wine, M. L., Climatization of environmental degradation: A widespread challenge to the integrity of earth science, Hydrological Sciences Journal, 65(6), 867-883, doi:10.1080/02626667.2020.1720024, 2020.
    125. Vogel, R. M., and C. N. Kroll, A comparison of estimators of the conditional mean under non-stationary conditions, Advances in Water Resources, 143, 103672, doi:10.1016/j.advwatres.2020.103672, 2020.
    126. Stefanidis, S., S. Dafis, and D. Stathis, Evaluation of regional climate models (RCMs) performance in simulating seasonal precipitation over mountainous Central Pindus (Greece), Water, 12(10), 2750, doi:10.3390/w12102750, 2020.
    127. Danáčová, M., G. Földes, M.M. Labat, S. Kohnová, and K. Hlavčová, Estimating the effect of deforestation on runoff in small mountainous basins in Slovakia, Water, 12(11), 3113, doi:10.3390/w12113113, 2020.
    128. Dong, Z., W. Jia, R. Sarukkalige, G. Fu, Q. Meng, and Q. Wang, Innovative trend analysis of air temperature and precipitation in the Jinsha river basin, China, Water, 12(11), 3293, doi:10.3390/w12113293, 2020.
    129. Kiem, A. S., G. Kuczera, P. Kozarovski, L. Zhang, and G. Willgoose, Stochastic generation of future hydroclimate using temperature as a climate change covariate, Water Resources Research, 57(2), 2020WR027331, doi:10.1029/2020WR027331, 2021.
    130. Beven, K., Issues in generating stochastic observables for hydrological models, Hydrological Processes, 35(6), e14203, doi:10.1002/hyp.14203, 2021.
    131. Kundzewicz, Z. W., and P. Licznar, Climate change adjustments in engineering design standards: European perspective, Water Policy, 23(S1), 85-105, doi:10.2166/wp.2021.330, 2021.
    132. Manous, J., and E. Z. Stakhiv, Climate risk-informed decision analysis (CRIDA): ‘top-down’ vs ‘bottom-up’ decision making for planning water resources infrastructure, Water Policy, 23(S1), 54-76, doi:10.2166/wp.2021.243, 2021.
    133. Bekri, E. S., P. Economou, P. C. Yannopoulos, and A. C. Demetracopoulos, Reassessing existing reservoir supply capacity and management resilience under climate change and sediment deposition, Water, 13(13), 1819, doi:10.3390/w13131819, 2021.
    134. Kawamleh, S., Confirming (climate) change: a dynamical account of model evaluation, Synthese, 200, 122, doi:10.1007/s11229-022-03659-1, 2022.
    135. Földes, G., M. M. Labat, S. Kohnová, and K. Hlavčová, Impact of changes in short-term rainfall on design floods: Case study of the Hnilec river basin, Slovakia, Slovak Journal of Civil Engineering, 30(1), 68-74, doi:10.2478/sjce-2022-0008, 2022.
    136. Gökçekuş, H., Y. Kassem, M. P. Quoigoah, and P. N. Aruni, Climate change, water resources, and wastewater reuse in Cyprus, Future Technology, 2(1), 1012, 2023.
    137. Marcos-Garcia, P., M. Pulido-Velazquez, C. Sanchis-Ibor, M. García-Mollá, M. Ortega-Reig, A. Garcia-Prats, and C. Girard, From local knowledge to decision making in climate change adaptation at basin scale. Application to the Jucar River Basin, Spain, Climatic Change, 176, 38, doi:10.1007/s10584-023-03501-8, 2023.
    138. Frank, P., LiG metrology, correlated error, and the integrity of the global surface air-temperature record, Sensors, 23(13), 5976, doi:10.3390/s23135976, 2023.

  1. K. Hadjibiros, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, A. Stamou, A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Multi-criteria reservoir water management, Global Network for Environmental Science and Technology, 7 (3), 386–394, doi:10.30955/gnj.000394, 2005.

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

    Related works:

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

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

    Additional material:

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

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

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

    1. #Sarkar, A., & M. Chakrabarti, Feasibility of corridor between Singhalilla National Park and Senchal Wild Life Sanctuary: a study of five villages between Poobong and 14th Mile Village, Parks, Peace and Partnerships Conf., Waterton, Canada, 2007
    2. Chakrabarti, M., and S. K. Datta, Evolving an effective management information system to monitor co-management of forests, Economic and Political Weekly, 44(18), 53-60, 2009.
    3. Vassoney, E., A. M. Mochet, and C. Comoglio, Use of multicriteria analysis (MCA) for sustainable hydropower planning and management, Journal of Environmental Management, 196, 48–55, doi:10.1016/j.jenvman.2017.02.067, 2017.
    4. Duc, D. X., L. D. Hai, and D. H. Tuan, Self-cleaning ability of pollutants containing nitrogen and phosphorus transformed into NH4+, NO2-, NO3-, PO43-, of SonLa hydropower reservoir, VNU Journal of Science: Earth and Environmental Sciences, 36(3), 12-24, doi:10.25073/2588-1094/vnuees.4510, 2020.

  1. A. Christofides, A. Efstratiadis, D. Koutsoyiannis, G.-F. Sargentis, and K. Hadjibiros, Resolving conflicting objectives in the management of the Plastiras Lake: can we quantify beauty?, Hydrology and Earth System Sciences, 9 (5), 507–515, doi:10.5194/hess-9-507-2005, 2005.

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

    Remarks:

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

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

    Additional material:

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

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

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

    1. Chung, E. S., and K. S. Lee, A social-economic-engineering combined framework for decision making in water resources planning, Hydrology and Earth System Sciences, 13, 675-686, 2009.
    2. Parisopoulos, G. A., M. Malakou, and M. Giamouri, Evaluation of lake level control using objective indicators: The case of Micro Prespa, Journal of Hydrology, 367(1-2), 86-92, 2009.
    3. #Romanescu, G., C. Stoleriu, and A. Lupascu, Morphology of the lake basin and the nature of sediments in the area of Red Lake (Romania), Annals of the University of Oradea – Geography Series, XX(1), 44-57, 2010.
    4. #Sargentis G. F., V. Symeonidis, and N. Symeonidis, Rules and methods for the development of a prototype landscape (Almyro) in north Evia by the creation of a thematic park, Proceedings of the 12th International Conference on Environmental Science and Technology (CEST2011), Rhodes, Greece, 2011.
    5. Shamsudin, S., A. A. Rahman and Z. B. Haron, Water level evaluation at Southern Malaysia reservoir using fuzzy composite programming, International Journal of Engineering and Advanced Technology, 2(4), 127-132, 2013.
    6. #Romanescu, G., C. C. Stoleriu, and A. Enea, Water management, Limnology of the Red Lake, Romania, Springer, 2013.
    7. Zhang, T., W. H. Zeng, S. R. Wang, and Z. K. Ni, Temporal and spatial changes of water quality and management strategies of Dianchi Lake in southwest China, Hydrology and Earth System Sciences, 18, 1493-1502, doi:10.5194/hess-18-1493-2014, 2014.
    8. Zhang, T., W. H. Zeng, and F. L. Yang, Applying a BP neural network approach to the evolution stage classification of China Rift Lakes, International Journal of Modeling and Optimization, 4(6), 450-454, 2014.
    9. Tegos, M., I. Nalbantis, and A. Tegos, Environmental flow assessment through integrated approaches, European Water, 60, 167-173, 2017.

  1. D. Koutsoyiannis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, and A. Christofides, A decision support system for the management of the water resource system of Athens, Physics and Chemistry of the Earth, 28 (14-15), 599–609, doi:10.1016/S1474-7065(03)00106-2, 2003.

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

    Full text: http://www.itia.ntua.gr/en/getfile/579/2/documents/2001PCEAthensDSS.pdf (604 KB)

    Additional material:

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

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

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

    1. de Kok, J.-L., and H. G. Wind, Design and application of decision-support systems for integrated water management: lessons to be learnt, Physics and Chemistry of the Earth, 28(14-15), 571-578, 2003.
    2. #Xu, C., Huang, Q., Zhao, M., and Tian, F., Economical operation of hydropower plant based on self-adaptive mutation evolutionary programming, Fifth World Congress on Intelligent Control and Automation, Vol. 6, 5646-5648, 2004.
    3. Parcharidis, I., E. Lagios, V. Sakkas, D. Raucoules, D. Feurer, S. Le Mouelic, C. King, C. Carnec, F. Novali, A. Ferretti, R. Capes, and G. Cooksley, Subsidence monitoring within the Athens Basin (Greece) using space radar interferometric techniques, Earth Planets Space, 58(5), 505-513, 2006.
    4. #Makropoulos, C., Decision support tools for water demand management, Water Demand Management, D. Butler and F.A. Memon (eds.), IWA Publishing, 331-353, 2006.
    5. #Othman, F., and M. Naseri, Decision support systems in water resources management, Proceedings of the 9th Asia Pacific Industrial Engineering and Management Systems Conference, 1772-1780, Nusa Dua, Bali, 2008.
    6. Kizito, F., H. Mutikanga, G. Ngirane-Katashaya, and R. Thunvik, Development of decision support tools for decentralised urban water supply management in Uganda: An Action Research approach, Computers, Environment and Urban Systems, 33(2), 122-137, 2009.
    7. #Comas, J., and M. Poch, Decision support systems for integrated water resources management under water scarcity, Water Scarcity in the Mediterranean: Perspectives Under Global Change, S. Sabater and D. Barcelo (eds.), The Handbook of Environmental Chemistry, Springer-Verlag Berlin Heidelberg, 2009.
    8. Silva-Hidalgo, H., I. R. Martín-Domínguez, M. T. Alarcón-Herrera, and A. Granados-Olivas, Mathematical modelling for the integrated management of water resources in hydrological basins, Water Resources Management, 23 (4), 721-730, 2009.
    9. #Wang, B., and H. Cheng, Regional environmental risk management decision support system based on optimization model for Minhang District in Shanghai, Challenges in Environmental Science and Computer Engineering, 1, 14-17, 2010 International Conference on Challenges in Environmental Science and Computer Engineering, 2010.
    10. #Zhang, R., J. Wei, J. Lu, and G. Zhang, A Decision Support System for Ore Blending Cost Optimization Problem of Blast Furnaces, In: G. Phillips-Wren et al. (Eds.), Advances in Intelligent Decision Technologies, Smart Innovation, Systems and Technologies, 1(4), III, 143-152, Springer-Verlag Berlin Heidelberg, 2010.
    11. #Καρύμπαλης, Ε., Το νερό της Αθήνας: οι επιπτώσεις στον Μόρνο και τον Εύηνο, Γεωγραφίες, 15, 75-93, 2010.
    12. Sechi, G. M., and A. Sulis, Drought mitigation using operative indicators in complex water systems, Physics and Chemistry of the Earth, Parts A/B/C, 35(3-5), 195-203, 2010.
    13. Zhang, R., J. Lu, and G. Zhang, A knowledge-based multi-role decision support system for ore blending cost optimization of blast furnaces, European Journal of Operational Research, 215(1), 194-203, doi: 10.1016/j.ejor.2011.05.037, 2011.
    14. Gallardo, M. M., P. Merino, L. Panizo, and A. Linares, A practical use of model checking for synthesis: generating a dam controller for flood management, Software: Practice and Experience, 41(11), 1329-1347, DOI: 10.1002/spe.1048, 2011.
    15. Zeng, Y., Y. Cai, P. Jia, and H. Jee, Development of a web-based decision support system for supporting integrated water resources management in Daegu City, South Korea, Expert Systems with Applications, 39(11), 10091-10102, 2012.
    16. Patil, A., and Z.-Q. Deng, Input data measurement-induced uncertainty in watershed modelling, Hydrological Sciences Journal, 57(1), 118–133, 2012.
    17. Zhang, X. Q., H. Gao, and X. Yu, A multiobjective decision framework for river basin management, Applied Mechanics and Materials, 238, 288-291, 2012.
    18. Ge, Y., X. Li, C. Huang, and Z. Nan, A decision support system for irrigation water allocation along the middle reaches of the Heihe River Basin, Northwest China, Environmental Modelling & Software, 47, 182-192, 2013.
    19. Adewumi, J. R., A. A. Ilemobade, and J. E. van Zyl, Application of a multi-criteria decision support tool in assessing the feasibility of implementing treated wastewater reuse, International Journal of Decision Support System Technology, 5(1), 1-23, 2013.
    20. Sahoo, S. N., and P. Sreeja, A review of decision support system applications in flood management, International Journal of Hydrology Science and Technology, 3, 206–220, 2013.
    21. #Aher, P. D., J. Adinarayana, S. D. Gorantiwar, and S. A. Sawant, Information system for integrated watershed management using remote sensing and GIS, Remote Sensing Applications in Environmental Research, 17-34, Society of Earth Scientists Series, 2014.
    22. Nouiri, I., Multi-objective tool to optimize the water resources management using genetic algorithm and the Pareto optimality concept, Water Resources Management, 28(10), 2885-2901, 2014.
    23. Heracleous, C., Z. Zinonos, and C. Panayiotou, Water supply optimization: An IPA approach, IFAC Proceedings Volumes: 12th IFAC/IEEE Workshop on Discrete Event Systems, 47(2), 265-270, doi:10.3182/20140514-3-FR-4046.00088, 2014.
    24. #Heidari A., and E. Bozorgzadeh, Decision Support System for water resources planning in Karun river basin, International Symposium on Dams in a Global Environmental Challenges, 35-45, Bali, Indonesia, 2014.
    25. Stefanovic, N., I. Radojevic, A. Ostojic, L. Comic, and M. Topuzovic, Composite web information system for management of water resources, Water Resources Management, 29(7), 2285-2301, doi:10.1007/s11269-015-0941-y, 2015.
    26. Nouiri, I., F. Chemak, D. Mansour, H. Bellali, J. Ghrab, J. Baaboub, and M. K. Chahed, Impacts of irrigation water management on consumption indicators and exposure to the vector of Zoonotic Cutaneous Leishmaniasis (ZCL) in Sidi Bouzid, Tunisia, International Journal of Agricultural Policy and Research, 3(2), 93-103, doi:10.15739/IJAPR.031, 2015.
    27. Nouiri , I., M. Yitayew, J. Maßmann, and J. Tarhouni, Multi-objective optimization tool for integrated groundwater management, Water Resources Management, 29(14), 5353-5375, doi:10.1007/s11269-015-1122-8, 2015.
    28. Khairy, M. F. A., M. M. Tawfik, and M. Attaya, Tools for enhancing crop patterns in the summer season in middle delta of Egypt, 20th Annual Conference of Misr. Soc. of Ag. Eng., 367-386, Egypt, 2015.
    29. Wang, G., S. Mang, H. Cai, S. Liu, Z. Zhang, L. Wang, and J. L. Innes, Integrated watershed management: evolution, development and emerging trends, Journal of Forestry Research, 27(5), 967–994, doi:10.1007/s11676-016-0293-3, 2016.
    30. #Bouziotas, D., and M. Ertsen, Socio-hydrology from the bottom up: A template for agent-based modeling in irrigation systems, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2017-107, 2017.
    31. #Payano, R., J.A. Pascual-Aguilar, and I. de Bustamante, Criterios para la incorporación de la información sobre usos del suelo en un Sistema de Apoyo a la Toma de Decisiones sobre Patrimonio Hidráulico, Nuevas perspectivas de la Geomática aplicadas al estudio de los paisajes y el patrimonio hidráulico (Geomatics: New perspectives for the study of water landscapes and cultural heritage), J.A. Pascual-Aguilar, J. Sanz, and I. de Bustamante (eds.), Centro para el Conocimiento del Paisaje-Civilscape, 2017.
    32. Stamou, A. T., and P. Rutschmann, Pareto optimization of water resources using the nexus approach, Water Resources Management, 32(15), 5053-5065, doi:10.1007/s11269-018-2127-x, 2018.
    33. Kazak, J. K., J. Chruściński, and S. Szewrański, The development of a novel decision support system for the location of green infrastructure for stormwater management, Sustainability, 10(12), 4388; doi:10.3390/su10124388, 2018.
    34. Heidari, A., Application of multidisciplinary water resources planning tools for two of the largest rivers of Iran, Journal of Applied Water Engineering and Research, 6(2), 150-161, doi:10.1080/23249676.2016.1215271, 2018.
    35. Ghobadi M., and H. S. Kaboli, Developing a Web-based decision support system for reservoir flood management, Journal of Hydroinformatics, 22(3), 641-662, doi:10.2166/hydro.2020.185, 2020.
    36. Poursanidis, D., S. Kalogirou, E. Azzurro, V. Parravicini, M. Barich, and H. zu Dohna, Habitat suitability, niche unfilling and the potential spread of Pterois miles in the Mediterranean Sea, Marine Pollution Bulletin, 154, 111054, doi:10.1016/j.marpolbul.2020.111054, 2020.
    37. 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.
    38. Alamanos, A., A. Rolston, and G. Papaioannou, Development of a decision support system for sustainable environmental management and stakeholder engagement, Hydrology, 8(1), 40, doi:10.3390/hydrology8010040, 2021.
    39. Izady, A., A. Joodavi, M. Ansarian, M. Shafiei, M. Majidi, K. Davary, A. N. Ziaei, H. Ansari, M. R. Nikoo, A. Al-Maktoumi, M. Chen, and O. Abdalla, A scenario-based coupled SWAT-MODFLOW decision support system for advanced water resource management, Journal of Hydroinformatics, 24(1), 56-77, doi:10.2166/hydro.2021.081, 2022.
    40. Xu, H. A. Berres, Y. Liu, M. R. Allen-Dumas, and J. Sanyal, An overview of visualization and visual analytics applications in water resources management, Environmental Modelling & Software, 153, 105396, doi:10.1016/j.envsoft.2022.105396, 2022.
    41. Ma, Q., and P. Gourbesville, Integrated water resources management: A new strategy for DSS development and implementation, River, 1(2), 189-206, doi:10.1002/rvr2.17, 2022.
    42. Dehghanisanij, H., S. Emami, A. Nourjou, and V. Rezaverdinejad, Investigating the compatibility of an irrigation decision support system with water rights and allocation in a selected irrigation network, Irrigation and Drainage, doi:10.1002/ird.2934, 2024.

Book chapters and fully evaluated conference publications

  1. A. Efstratiadis, A. D. Koussis, S. Lykoudis, A. Koukouvinos, A. Christofides, G. Karavokiros, N. Kappos, N. Mamassis, and D. Koutsoyiannis, Hydrometeorological network for flood monitoring and modeling, Proceedings of First International Conference on Remote Sensing and Geoinformation of Environment, Paphos, Cyprus, 8795, 10-1–10-10, doi:10.1117/12.2028621, Society of Photo-Optical Instrumentation Engineers (SPIE), 2013.

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

    Additional material:

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

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

    1. Damte, F., B. G. Mariam, M. Teshome, T. K. Lohani, G. Dhiman, and M. Shabaz, Computing the sediment and ensuing its erosive activities using HEC-RAS to surmise the flooding in Kulfo River in Southern Ethiopia, World Journal of Engineering, 18(6), 948-955, doi:10.1108/WJE-01-2021-0002, 2021.
    2. Mahamat Nour, A., C. Vallet-Coulomb, J. Gonçalves, F. Sylvestre, and P. Deschamps, Rainfall-discharge relationship and water balance over the past 60 years within the Chari-Logone sub-basins, Lake Chad basin, Journal of Hydrology: Regional Studies, 35, 1008242021, doi:10.1016/j.ejrh.2021.100824, 2021.

  1. S. Kozanis, A. Christofides, N. Mamassis, and D. Koutsoyiannis, openmeteo.org: a web service for the dissemination of free meteorological data, Advances in Meteorology, Climatology and Atmospheric Physics, edited by C.G. Helmis and P. Nastos, Athens, 203–208, doi:10.1007/978-3-642-29172-2_29, Springer, Athens, 2012.

    Individuals or organisations managing meteorological or hydrological stations typically need to either collect the data on personal computers or bear the costs required to setup a server. As an alternative, the openmeteo.org database provides users and organisations the option to upload their time series, on condition that their data will be available to the public under a free license (the Open Database License and the Creative Commons Attribution-ShareAlike License, depending on the type of data). Each user has write access to his own data, whereas the public has read access to all the data. Enhydris, the software that powers openmeteo.org, is also free, available under the GNU General Public License v.3, and provides several useful features like time series graphs and plots, display of online data, maps etc. The purpose of openmeteo.org is not only to enable people to manage their data more easily, but also to bring people into a community and encourage a spirit of openness and sharing.

    Additional material:

    See also: http://dx.doi.org/10.1007/978-3-642-29172-2_29

  1. G.-F. Sargentis, K. Hadjibiros, and A. Christofides, Plastiras lake: the impact of water level on the aesthetic value of landscape, Proceedings of the 9th International Conference on Environmental Science and Technology (9CEST), Rhodes, B, 817–824, Department of Environmental Studies, University of the Aegean, 2005.

    The Plastiras Lake is an artificial reservoir created in 1959 for hydroelectric production. Following different changes in the social, economic and physical context of the area, the water of the lake has been used mainly for irrigation and drinking water supply. Recently, the beautiful scenery of the lake has been considered attractive by visitors and therefore the area has seen a significant touristic development. However, because of the water release mainly for agricultural, but also for hydroelectric purposes, the surface level of the lake varies significantly in the range between the lowest level of 776 m and the overflow level of 792 m. The result is a considerably negative impact on the landscape. The aesthetic value of the scenery has been assessed by a research team through field visits, landscape visual examination, photographic recording, digital image processing, as well as with a survey among visitors. It has been noticed that the most important impact from the level variation is the development of a dead-zone around the lake shore. This zone has different characteristics in the northern and in the southern part. The analysis of the form and size of the dead-zone may provide a concrete assessment of the aesthetic impact, although a quantified approach remains difficult. Moreover, information from the survey gives a significant, yet subjective, estimation of the aesthetic impact. The inhabitants, the regular and the occasional visitors are partially in agreement that the scenery is significantly more valuable when the water level is around 786 m or higher, as compared to when it is around 782 m or lower. If the conservation of the environment and the touristic development of the area are priority objectives, the management of water release through the establishment of a lower limit for the surface level appears to be mandatory.

    Full text: http://www.itia.ntua.gr/en/getfile/1005/1/documents/srcosmos.pdf (1136 KB)

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

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

  1. K. Hadjibiros, A. Katsiri, A. Andreadakis, D. Koutsoyiannis, A. Stamou, A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Multi-criteria reservoir water management, Proceedings of the 9th International Conference on Environmental Science and Technology (9CEST), Rhodes, A, 535–543, Department of Environmental Studies, University of the Aegean, 2005.

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

    Related works:

    • [9] Posterior more complete version.

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

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

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

  1. N. Mamassis, A. Christofides, and D. Koutsoyiannis, Hydrometeorological data acquisition, management and analysis for the Athens water supply system, BALWOIS Conference on Water Observation and Information System for Decision Support, Ochrid, FYROM, doi:10.13140/RG.2.1.1845.5284, Ministry of Environment and Physical Planning FYROM, Skopie, 2004.

    A hydrolometeorological telemetric network has been installed, in the framework of a decision support system (DSS) for the management of the Athens water resource system, that extends over an area of 5000 km2. In this paper the telemetric network and data management and analysis are described. The information collected includes meteorological data, reservoir water levels and stream flow data. The data acquisition procedure is executed periodically, by a computer at the data centre and all data is stored in the database for immediate use by other subsystems of the DSS. Some data by conventional instruments are also stored for comparison and tests. A software application (Hydrognomon) is used for management and analysis of the various types of raw data and for producing a large number of derivative time series. The whole procedure has been standardised for easy implementation in other similar networks.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.1.1845.5284

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

    1. #Grammatokogiannis, A., N. Mamassis, E. Baltas and M. Mimikou, A meteorological telemetric network for monitoring of the Athens wider Area, Proc. 9th International Conference on Environmental Science and Technology, Rhodes, Greece, 2005.
    2. Meyer, M.L., and G.M. Huey, Telemetric system for hydrology and water quality monitoring in watersheds of northern New Mexico, USA, Environmental Monitoring and Assessment, 116(1-3), 9-19, 2006.

  1. K. Hadjibiros, D. Koutsoyiannis, A. Katsiri, A. Stamou, A. Andreadakis, G.-F. Sargentis, A. Christofides, A. Efstratiadis, and A. Valassopoulos, Management of water quality of the Plastiras reservoir, 4th International Conference on Reservoir Limnology and Water Quality, Ceske Budejovice, Czech Republic, doi:10.13140/RG.2.1.4872.4723, 2002.

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

    Remarks:

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

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

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

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

  1. D. Koutsoyiannis, N. Mamassis, and A. Christofides, Experience from the operation of the automatic telemetric meteorological station in the National Technical University, Proceedings of the 8th National Congress of the Greek Hydrotechnical Association, edited by G. Christodoulou, A. Stamou, and A. Nanou, Athens, 301–308, doi:10.13140/RG.2.1.4577.5603, Greek Hydrotechnical Association, 2000.

    An automatic telemetric meteorological station has been set up in the National Technical University of Athens campus at Zographou, whose operation has completed six years. Several types of sensors and devices for energy supply, as well as techniques for data acquisition, logging and transmission were tested. Emphasis was given to the direct availability and easy access to the data, both real time and historical, for any interested user. To this aim, the Internet was utilised and several software applications were developed to allow data access through the World Wide Web.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.1.4577.5603

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

    1. #Grammatokogiannis, A., N. Mamassis, E. Baltas and M. Mimikou, A meteorological telemetric network for monitoring of the Athens wider Area, Proc. 9th International Conference on Environmental Science and Technology, Rhodes, Greece, 2005.

Conference publications and presentations with evaluation of abstract

  1. D. Koutsoyiannis, C. Onof, Z. W. Kundzewicz, and A. Christofides, A stochastic approach to causality (Invited talk), AGU 2022 Fall Meeting, doi:10.13140/RG.2.2.25180.87681, American Geophysical Union, 2022.

    We give a brief overview of conceptions of causality and attempts to find probabilistic characterizations of it. We argue that a useful criterion for causal links in open systems would apply to time-series of causally related phenomena, and that it only makes sense to seek necessary conditions for causality.

    The criterion we develop uses an impulse response function g that relates two phenomena X and Y (for which contemporaneous time-series of observations are available) according to a convolution equation. The existence of such a function g which fulfils criteria of non-negativity and smoothness and leaves us with a residual random noise V with a minimal variance that is small compared to the variance of Y, is a condition for there being a causal or hen-or-egg link between two series (or two non-linear transforms thereof).

    We understand a hen-or-egg case as one in which a clear causal link in one rather than the other direction cannot be identified. As seen in the figure, from the general case of a hen-or-egg causal system, we have as special cases potentially causal, potentially auticausal, and non-causal cases.

    We demonstrate the plausibility of this necessary condition for causality by examining (i) a few artificial cases in which we show the role of the criteria we impose, (ii) the key hydrological causal link between rainfall and catchment runoff.

    Full text: http://www.itia.ntua.gr/en/getfile/2262/1/documents/ChrisOnof-AGU2022-Slides.pdf (745 KB)

    Additional material:

    See also: https://agu.confex.com/agu/fm22/meetingapp.cgi/Paper/1081471

  1. A. Efstratiadis, N. Mamassis, A. Koukouvinos, D. Koutsoyiannis, K. Mazi, A. D. Koussis, S. Lykoudis, E. Demetriou, N. Malamos, A. Christofides, and D. Kalogeras, Open Hydrosystem Information Network: Greece’s new research infrastructure for water, European Geosciences Union General Assembly 2020, Geophysical Research Abstracts, Vol. 22, Vienna, EGU2020-4164, doi:10.5194/egusphere-egu2020-4164, 2020.

    The Open Hydrosystem Information Network (OpenHi.net) is a state-of-the-art information infrastructure for the collection, management and free dissemination of hydrological and environmental information related to Greece’s surface water resources. It was launched two years ago as part of the national research infrastructure “Hellenic Integrated Marine Inland water Observing, Forecasting and offshore Technology System” (HIMIOFoTS), which also comprises a marine-related component (https://www.himiofots.gr/). The OpenHi.net system receives and processes real-time data from automatic telemetric stations that are connected to a common web environment (https://openhi.net/). In particular, for each monitoring site it accommodates stage measurements, raw and automatically post-processed. Furthermore, in some specially selected sites time series related to water quality characteristics (pH, water temperature, salinity, DO, electrical conductivity) are provided. The web platform also offers automatically-processed information in terms of discharge data, statistics, and graphs, alerts for extreme events, as well as geographical data associated with surface water bodies. At the present time, the network comprises about 20 stations. However, their number is continuously increasing, due to the open access policy of the system (the platform is fully accessible to third-parties uploading their data). In the long run, it is envisioned that a national-scale hydrometric infrastructure will be established, covering all important rivers, lakes and reservoirs of the country.

    Full text:

    See also: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-4164.html

  1. N. Malamos, A. Tegos, I. L. Tsirogiannis, A. Christofides, and D. Koutsoyiannis, Implementation of a regional parametric model for potential evapotranspiration assessment, IrriMed 2015 – Modern technologies, strategies and tools for sustainable irrigation management and governance in Mediterranean agriculture, Bari, doi:10.13140/RG.2.1.3992.0725, 2015.

    Potential evapotranspiration (PET) is key input in water resources, agricultural and environmental modelling. For many decades, several approaches have been proposed for the consistent estimation of PET at several time scales of interest. The most recognized is the Penman‐Monteith formula, which is yet difficult to apply, since it requires simultaneous measurements of four meteorological variables (temperature, sunshine duration, humidity, wind velocity). For this reason, simplified approaches prove very useful in absence of a complete data set and are strongly preferred. In the present study, we implement a recent parametric formula to model PET in the Arta plain, located in the Region of Epirus ‐ Greece, which is based on a simplified formulation of the original Penman‐Monteith expression and requires only mean hourly, daily or monthly temperature data, depending on the desired time step. The methodology is generic, yet parsimonious in terms of the input data, with its parameters adjusted through calibration, to the available PET data. A spatial analysis concerning the regionalization of the parameters and PET estimates of the proposed methodology by implementing interpolation techniques is performed. The results are very satisfactory, illustrating that the proposed framework is efficient and constitutes a reliable alternative in the assessment of potential evapotranspiration field

    Full text: http://www.itia.ntua.gr/en/getfile/1576/1/documents/2015Bari_Implementation_of_a_regional_parametric.pdf (2372 KB)

    See also: http://dx.doi.org/10.13140/RG.2.1.3992.0725

  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. Efstratiadis, I. Tsoukalas, P. Kossieris, G. Karavokiros, A. Christofides, A. Siskos, N. Mamassis, and D. Koutsoyiannis, Computational issues in complex water-energy optimization problems: Time scales, parameterizations, objectives and algorithms, European Geosciences Union General Assembly 2015, Geophysical Research Abstracts, Vol. 17, Vienna, EGU2015-5121, doi:10.13140/RG.2.2.11015.80802, European Geosciences Union, 2015.

    Modelling of large-scale hybrid renewable energy systems (HRES) is a challenging task, for which several open computational issues exist. HRES comprise typical components of hydrosystems (reservoirs, boreholes, conveyance networks, hydropower stations, pumps, water demand nodes, etc.), which are dynamically linked with renewables (e.g., wind turbines, solar parks) and energy demand nodes. In such systems, apart from the well-known shortcomings of water resources modelling (nonlinear dynamics, unknown future inflows, large number of variables and constraints, conflicting criteria, etc.), additional complexities and uncertainties arise due to the introduction of energy components and associated fluxes. A major difficulty is the need for coupling two different temporal scales, given that in hydrosystem modeling, monthly simulation steps are typically adopted, yet for a faithful representation of the energy balance (i.e. energy production vs. demand) a much finer resolution (e.g. hourly) is required. Another drawback is the increase of control variables, constraints and objectives, due to the simultaneous modelling of the two parallel fluxes (i.e. water and energy) and their interactions. Finally, since the driving hydrometeorological processes of the integrated system are inherently uncertain, it is often essential to use synthetically generated input time series of large length, in order to assess the system performance in terms of reliability and risk, with satisfactory accuracy. To address these issues, we propose an effective and efficient modeling framework, key objectives of which are: (a) the substantial reduction of control variables, through parsimonious yet consistent parameterizations; (b) the substantial decrease of computational burden of simulation, by linearizing the combined water and energy allocation problem of each individual time step, and solve each local sub-problem through very fast linear network programming algorithms, and (c) the substantial decrease of the required number of function evaluations for detecting the optimal management policy, using an innovative, surrogate-assisted global optimization approach.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.11015.80802

  1. S. Kozanis, A. Christofides, A. Efstratiadis, A. Koukouvinos, G. Karavokiros, N. Mamassis, D. Koutsoyiannis, and D. Nikolopoulos, Using open source software for the supervision and management of the water resources system of Athens, European Geosciences Union General Assembly 2012, Geophysical Research Abstracts, Vol. 14, Vienna, 7158, doi:10.13140/RG.2.2.28468.04482, European Geosciences Union, 2012.

    The water supply of Athens, Greece, is implemented through a complex water resource system, extending over an area of around 4 000 km2 and including surface water and groundwater resources. It incorporates four reservoirs, 350 km of main aqueducts, 15 pumping stations, more than 100 boreholes and 5 small hydropower plants. The system is run by the Athens Water Supply and Sewerage Company (EYDAP). Over more than 10 years we have developed, information technology tools such as GIS, database and decision support systems, to assist the management of the system. Among the software components, “Enhydris”, a web application for the visualization and management of geographical and hydrometeorological data, and “Hydrognomon”, a data analysis and processing tool, are now free software. Enhydris is entirely based on free software technologies such as Python, Django, PostgreSQL, and JQuery. We also created http://openmeteo.org/, a web site hosting our free software products as well as a free database system devoted to the dissemination of free data. In particular, “Enhydris” is used for the management of the hydrometeorological stations and the major hydraulic structures (aqueducts, reservoirs, boreholes, etc.), as well as for the retrieval of time series, online graphs etc. For the specific needs of EYDAP, additional GIS functionality was introduced for the display and monitoring of the water supply network. This functionality is also implemented as free software and can be reused in similar projects. Except for “Hydrognomon” and “Enhydris”, we have developed a number of advanced modeling applications, which are also generic-purpose tools that have been used for a long time to provide decision support for the water resource system of Athens. These are “Hydronomeas”, which optimizes the operation of complex water resource systems, based on a stochastic simulation framework, “Castalia”, which implements the generation of synthetic time series, and “Hydrogeios”, which employs conjunctive hydrological and hydrogeological simulation, with emphasis to human-modified river basins. These tools are currently available as executable files that are free for download though the ITIA web site (http://itia.ntua.gr/). Currently, we are working towards releasing their source code as well, through making them free software, after some licensing issues are resolved.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.28468.04482

  1. A. Christofides, S. Kozanis, G. Karavokiros, and A. Koukouvinos, Enhydris, Filotis & openmeteo.org: Free software for environmental management, FLOSS Conference 2011, Athens, http://conferences.ellak.gr/2011/, 2011.

    A presentation of two free software application for environmental management, developed in National Technical University of Athens. Enhydris is an Information system - server software for the management, storage and retrieval of hydrometeorological data, accessible through the internet. Enhydris is used by the National Data Bank of Hydrometeorolical Information (Hydroscope) and it also used by other agencies in Greece and European Union. In addition it is provided as a service of free content under the web address: openmeteo.org where individuals can download or upload their data. The Information System for the Greek Nature "Filotis", contains biotopes and species of flora and fauna of Greece.

    The development of the application is based on Python Computer Language and Django. Finally applications are providing geospatial data in a Web-GIS form by using free software GIS tools.

    Speach video is here: http://www.vimeo.com/25340067

    Related works:

    • [28] Enhydris presentation (Poster)
    • [37] HYDROSCOPE: National Databank for Hydrological, Meteorological and Geographical Information, presentation of the third phase
    • [38] Presentation of the first phase of Hydroscope since 1995

    Full text: http://www.itia.ntua.gr/en/getfile/1145/1/documents/2011_FLOSS_Enhydris_presentation.pdf (3847 KB)

    Additional material:

    See also: http://conferences.ellak.gr/2011/

  1. D. Tsaknias, D. Bouziotas, A. Christofides, A. Efstratiadis, and D. Koutsoyiannis, Statistical comparison of observed temperature and rainfall extremes with climate model outputs, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-3454, doi:10.13140/RG.2.2.15321.52322, European Geosciences Union, 2011.

    Climate model outputs have widely been used to support decision making for social and financial policies, with special focus on extreme events. Moreover, it is a general perception that extreme events will be more frequent in the future. To evaluate whether climate models provide a credible basis for predictions of extremes, we study their ability to reproduce annual extreme values of daily temperature and precipitation. The results from climate models are compared to observed data from stations in the Mediterranean. Furthermore, we fit probability distributions which describe the extreme events in both cases and compare the results.

    Remarks:

    Related blog posts and discussions: De staat van het klimaat, Climate Science: Roger Pielke Sr..

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.15321.52322

  1. A. Christofides, and D. Koutsoyiannis, Causality in climate and hydrology, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, EGU2011-7440, doi:10.13140/RG.2.2.33776.46082, European Geosciences Union, 2011.

    We often see statements such as “90% of climate change is caused by X” and debates on whether the dominant cause of climate change is human activity, or the sun, or something else. However, in chaotic systems, it can be difficult to defend the meaning of such assertions, because if the “effect” occurs sufficiently later than the supposed “cause”, the relationship between the two is effectively lost because of the sensitivity of the “effect” to the initial conditions. In fact, although “A causes B” initially seems clear, closer examination of what it actually means reveals problems that have tortured philosophers for centuries. We review the meaning of causation in the context of hydroclimatology as well as its possible reformulation in probabilistic terms.

    Remarks:

    Related blog posts and discussions can be seen in Climate Science: Roger Pielke Sr., Bishop Hill, PlazaMoyua.org, Climate Etc.: Judith Curry.

    Full text: http://www.itia.ntua.gr/en/getfile/1130/1/documents/causality_4.pdf (136 KB)

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.33776.46082

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

    1. Ward, J. D., A. D. Werner, W. P. Nel, and S. Beecham, The influence of constrained fossil fuel emissions scenarios on climate and water resource projections, Hydrology and Earth System Sciences, 15, 1879-1893, 2011.

  1. A. Christofides, S. Kozanis, G. Karavokiros, Y. Markonis, and A. Efstratiadis, Enhydris: A free database system for the storage and management of hydrological and meteorological data, European Geosciences Union General Assembly 2011, Geophysical Research Abstracts, Vol. 13, Vienna, 8760, European Geosciences Union, 2011.

    Enhydris is a database system for the storage and management of hydrological and meteorological data. It allows the storage and retrieval of raw data, processed time series, model parameters, curves and meta-information such as measurement stations overseers, instruments, events etc. The database is accessible through a web interface, which includes several data representation features such as tables, graphs and mapping capabilities. Data access is configurable to allow or to restrict user groups and/or privileged users to contribute or to download data. With these capabilities, Enhydris can be used either as a public repository of free data or as a fully secured – restricted system for data storage. Time series can be downloaded in plain text format that can be directly loaded to Hydrognomon (http://hydrognomon.org/), a free tool for analysis and processing of meteorological time series. Enhydris can optionally work in a distributed way. Many organisations can install one instance each, but an additional instance, common to all organisations, can be setup as a common portal. This additional instance can be configured to replicate data from the other databases, but without the space consuming time series, which it retrieves from the other databases on demand. A user can transparently use this portal to access the data of all participating organisations collectively. Enhydris is free software, available under the terms of the GNU General Public License version 3. It is developed with Python, Django, and C. Its modular design allows adding new features through the development of small applications. Enhydris is hosted by the Openmeteo project (http://openmeteo.org/), which aims to provide free tools and data.

    Full text:

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

    1. #Papathanasiou C., C. Makropoulos, E. Baltas, and M. Mimikou, The Hydrological Observatory of Athens: A state-of-the-art network for the assessment of the hydrometeorological regime of Attica, Proceedings of the 13th International Conference on Environmental Science and Technology, Athens, 2013.
    2. #Makropoulos, C., P. Kossieris, S. Kozanis, E. Katsiri, and L. Vamvakeridou-Lyroudia, From smart meters to smart decisions: Web-based support for the water efficient household, Proceedings of 11th International Conference on Hydroinformatics (HIC 2014), New York City, 2014.
    3. #Makropoulos, C., Thinking platforms for smarter urban water systems: Fusing technical and socio-economic models and tools. In: Riddick, A.T., Kessler, H., and Giles, J. R. A. (eds.), Integrated Environmental Modelling to Solve Real World Problems: Methods, Vision and Challenges, Geological Society, London, Special Publications, 408, 2014.
    4. Vantas, K., hydroscoper: R interface to the Greek National Data Bank for Hydrological and Meteorological Information, Journal of Open Source Software, 3(23), 625, doi:10.21105/joss.0062, 2018.
    5. Athanasiou, T., D. Salmas, P. Karvelis, I. Angelis, V. Andrea, P. Schismenos, M. Styliou, and C. Stylios, A web-geographical information system for real time monitoring of Arachthos River, Greece, IFAC PapersOnLine, 51(30), 384-389, doi:10.1016/j.ifacol.2018.11.335, 2018.
    6. #Karvelis, P., D. Salmas, and C. Stylios, Monitoring real time the Arachthos River (Greece) using a web GIS platform, 2020 International Conference on Information Technologies (InfoTech), Varna, Bulgaria, 1-5, doi:10.1109/InfoTech49733.2020.9211016, 2020.

  1. S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon – open source software for the analysis of hydrological data, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 12419, doi:10.13140/RG.2.2.21350.83527, European Geosciences Union, 2010.

    Hydrognomon is a software tool for the processing of hydrological data. It is an open source application running on standard Microsoft Windows platforms, and it is part of the openmeteo.org framework. Data are imported through standard text files, spreadsheets or by typing. Standard hydrological data processing techniques include time step aggregation and regularization, interpolation, regression analysis and infilling of missing values, consistency tests, data filtering, graphical and tabular visualisation of time series, etc. It supports several time steps, from the finest minute scales up to decades; specific cases of irregular time steps and offsets are also supported. The program also includes common hydrological applications, such as evapotranspiration modelling, stage-discharge analysis, homogeneity tests, areal integration of point data series, processing of hydrometric data, as well as lumped hydrological modelling with automatic calibration facilities. Here the emphasis is given on the statistical module of Hydrognomon, which provides tools for data exploration, fitting of distribution functions, statistical prediction, Monte-Carlo simulation, determination of confidence limits, analysis of extremes, and construction of ombrian (intensity-duration-frequency) curves. Hydrognomon is available for download from http://hydrognomon.org/.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.21350.83527

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

    1. #Sebastianelli, S., M. Giglioni, C. Mineo, and S. Magnald, On the hydrologic-hydraulic revaluation of large dams, International Conference of Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015), 1738, 430003-1–430003-4, doi:10.1063/1.4952216, 2016.
    2. #Mineo, C., S. Sebastianelli, L. Marinucci, and F. Russo, Assessment of the watershed DEM mesh size influence on a large dam design hydrograph, AIP Conference Proceedings, 1738, 430003, 2016.
    3. Tsitroulis, I., K. Voudouris, A. Vasileiou, C. Mattas, M. Sapountzis, and F. Maris, Flood hazard assessment and delimitation of the likely flood hazard zones of the upper part in Gallikos river basin, Bulletin of the Geological Society of Greece, 50(2), 995-1005, doi:10.12681/bgsg.11804, 2016.
    4. López J. J., O. Delgado, and M. A. Campo, Determination of the IDF curves in Igueldo-San Sebastián. Comparison of different methods, Ingeniería del Agua, 22(4), 209-223, doi:10.4995/Ia.2018.9480, 2018.
    5. Nyaupane, N., B. Thakur, A. Kalra, and S. Ahmad, Evaluating future flood scenarios using CMIP5 climate projections, Water, 10, 1866, doi:10.3390/w10121866, 2018.
    6. Vargas, M. M., S. Beskow, T. L. Caldeira, L. de Lima Corrêa, and Z. Almeida da Cunha, SYHDA – System of Hydrological Data Acquisition and Analysis, Brazilian Journal of Water Resources, 24, e11, doi:10.1590/2318-0331.241920180152, 2019.
    7. Houessou-Dossou, E. A. Y., J. M. Gathenya, M. Njuguna, and Z. A. Gariy, Flood frequency analysis using participatory GIS and rainfall data for two stations in Narok Town, Kenya, Hydrology, 6(4), 90, doi:10.3390/hydrology6040090, 2019.
    8. López Díez, A., P. Máyer Suárez, J. Díaz Pacheco, and P. Dorta Antequera, Rainfall and flooding in coastal tourist areas of the Canary Islands (Spain), Atmosphere, 10(12), 809, doi:10.3390/atmos10120809, 2019.
    9. Pamirbek, M., X. Chen, S. Aher, A. Salamat, P. Deshmukh, and C. Temirbek, Analysis of discharge variability in the Naryn river basin, Kyrgyzstan, Hydrospatial Analysis, 3(2), 90-106, doi:10.21523/gcj3.19030204, 2019.
    10. Tadesse, M., Spatial and temporal variability analysis and mapping of reference evapotranspiration for Jimma Zone, Southwestern Ethiopia, International Journal of Natural Resource Ecology and Management, 6(3), 108-115, doi:10.11648/j.ijnrem.20210603.12, 2021.
    11. Hayder, A. M., and M. Al-Mukhtar, Modelling the IDF curves using the temporal stochastic disaggregation BLRP model for precipitation data in Najaf City, Arabian Journal of Geosciences, 14, 1957, doi:10.1007/s12517-021-08314-6, 2021.
    12. Bekri, E. S., P. Economou, P. C. Yannopoulos, and A. C. Demetracopoulos, Reassessing existing reservoir supply capacity and management resilience under climate change and sediment deposition, Water, 13(13), 1819, doi:10.3390/w13131819, 2021.
    13. #Ridzuan, N. A. M., N. M. Noor, N. A. A. A. Rahim, I. A. M. Jafri, and D. Gyeorgy, Spatio-temporal variation of particulate matter (PM10) during high particulate event (HPE) in Malaysia, In: Mohamed Noor N., Sam S.T., Abdul Kadir A. (eds.), Proceedings of the 3rd International Conference on Green Environmental Engineering and Technology, Lecture Notes in Civil Engineering, 214, Springer, Singapore, doi:10.1007/978-981-16-7920-9_6, 2022.
    14. Tegos, A., A. Ziogas, V. Bellos, and A. Tzimas, Forensic hydrology: a complete reconstruction of an extreme flood event in data-scarce area, Hydrology, 9(5), 93, doi:10.3390/hydrology9050093, 2022.
    15. Nikas-Nasioulis, I., M. M. Bertsiou, and E. Baltas, Investigation of energy, water, and electromobility through the development of a hybrid renewable energy system on the island of Kos, WSEAS Transactions on Environment and Development, 18, 543-554, doi:10.37394/232015.2022.18.53, 2022.
    16. Vangelis, H., I. Zotou, I. M. Kourtis, V. Bellos, and V. A. Tsihrintzis, Relationship of rainfall and flood return periods through hydrologic and hydraulic modeling, Water, 14(22), 3618, doi:10.3390/w14223618, 2022.
    17. Reyes Flores, C. A., H. Ferreira Albuquerque Cunha, and A. Cavalcanti da Cunha, Hydrometeorological characterization and estimation of landfill leachate generation in the Eastern Amazon/Brazil, PeerJ, 11, e14686, doi:10.7717/peerj.14686, 2023.
    18. Vargas, M. M., S. Beskow, M. M. de Moura, Z. A. da Cunha, T. L. C. Beskow, and J. P. de Morais da Silveira, GAM-IDF: a web tool for fitting IDF equations from daily rainfall data, International Journal of Hydrology Science and Technology, 16(1), 37-60, doi:10.1504/IJHST.2023.131882, 2023.
    19. Carrasco, G. A., L. Villegas, J. Fernandez, J. Vallejos, and C. Idrogo, Assessment of parameters of the generalized extreme value distribution in rainfall of the Peruvian North, Revista Politécnica, 52(2), 99-112, doi:10.33333/rp.vol52n2.10, 2023.
    20. Arinaitwe, M., and J. Okedi, IoT-based data and analytic hierarchy process to map groundwater recharge with stormwater, Water Science and Technology, wst2024017, doi:10.2166/wst.2024.017, 2024.

  1. G. G. Anagnostopoulos, D. Koutsoyiannis, A. Efstratiadis, A. Christofides, and N. Mamassis, Credibility of climate predictions revisited, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 611, doi:10.13140/RG.2.2.15898.24009, European Geosciences Union, 2009.

    In a recent study (Koutsoyiannis et al., On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671–684, 2008), the credibility of climate predictions was assessed based on comparisons with long series of observations. Extending this research, which compared the outputs of various climatic models to temperature and precipitation observations from 8 stations around the globe, we test the performance of climate models at over 50 additional stations. Furthermore, we make comparisons at a large sub-continental spatial scale after integrating modelled and observed series.

    Remarks:

    Please visit/cite the peer-reviewed version of this article:

    Anagnostopoulos, G. G., D. Koutsoyiannis, A. Christofides, A. Efstratiadis, and N. Mamassis, A comparison of local and aggregated climate model outputs with observed data, Hydrological Sciences Journal, 55 (7), 1094–1110, 2010.

    Related works:

    • [31] Prior related presentation
    • [8] Prior related publication
    • [6] A comparison of local and aggregated climate model outputs with observed data

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.15898.24009

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

    1. Stockwell, D. R. B., Critique of Drought Models in the Australian Drought Exceptional Circumstances Report (DECR), Energy & Environment, 21 (5), 425-436, 2010.

  1. D. Koutsoyiannis, N. Mamassis, A. Christofides, A. Efstratiadis, and S.M. Papalexiou, Assessment of the reliability of climate predictions based on comparisons with historical time series, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 09074, doi:10.13140/RG.2.2.16658.45768, European Geosciences Union, 2008.

    As falsifiability is an essential element of science (Karl Popper), many have disputed the scientific basis of climatic predictions on the grounds that they are not falsifiable or verifiable at present. This critique arises from the argument that we need to wait several decades before we may know how reliable the predictions will be. However, elements of falsifiability already exist, given that many of the climatic model outputs contain time series for past periods. In particular, the models of the IPCC Third Assessment Report have projected future climate starting from 1990; thus, there is an 18-year period for which comparison of model outputs and reality is possible. In practice, the climatic model outputs are downscaled to finer spatial scales, and conclusions are drawn for the evolution of regional climates and hydrological regimes; thus, it is essential to make such comparisons on regional scales and point basis rather than on global or hemispheric scales. In this study, we have retrieved temperature and precipitation records, at least 100-year long, from a number of stations worldwide. We have also retrieved a number of climatic model outputs, extracted the time series for the grid points closest to each examined station, and produced a time series for the station location based on best linear estimation. Finally, to assess the reliability of model predictions, we have compared the historical with the model time series using several statistical indicators including long-term variability, from monthly to overyear (climatic) time scales. Based on these analyses, we discuss the usefulness of climatic model future projections (with emphasis on precipitation) from a hydrological perspective, in relationship to a long-term uncertainty framework.

    Remarks:

    Please visit/cite the peer-reviewed version of this article:

    Koutsoyiannis, D., A. Efstratiadis, N. Mamassis, and A. Christofides, On the credibility of climate predictions, Hydrological Sciences Journal, 53 (4), 671-684, 2008.

    Blogs and forums that discussed this article during 2008:

    Blogs with comments about this article during 2008:

    Real Climate 1, Real Climate 2, Prometheus: The Science Policy Weblog 2, Environmental Niche Modeling, Rabett Run, Internet Infidels Discussion Board, Science Forums, BBC News Blogs, Jim Miller on Politics, James' Empty Blog, Green Car Congress, Channel 4 Forums, Deltoid, Washington Post Blogs, Herald Sun Blogs 1, Herald Sun Blogs 2, Herald Sun Blogs 3, AccuWeather, Skeptical Science, Debunkers, Yahoo groups: AlasBabylon, Sciforums, Lughnasa, Jennifer Marohasy 2, Jennifer Marohasy 3, Jennifer Marohasy 4, Bruin Skeptics, Changement Climatique, Klimatika, JFER Forum, The Sydney Morning Herald Blogs: Urban Jungle

    Errata: In slide 3 "regional projections" should read "geographically distributed projections" and the reference of figures to IPCC chapter 11 (Christensen et al., 2007) should change to Chapter 10 (Meehl et al., 2007; also in list of references in slide 20). In slide 11 "Albany, Florida" should read "Albany, Georgia" (thanks to QE in the Small Dead Animals blog who spotted them).

    Related works:

    • [30] Credibility of climate predictions revisited (follow up study)
    • [8] On the credibility of climate predictions

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.16658.45768

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

    1. #Ekmann, J., and R.C. Dolence, Energy project risk amidst climate change regulatory uncertainty, 25th Annual International Pittsburgh Coal Conference, PCC – Proceedings, 2008.
    2. #Taylor, P., Chill, a reassessment of global warming theory: does climate change mean the world is cooling, and if so what should we do about it?, Clairview Books, 404 pp., 2009.
    3. #Howell, B., The Kyoto Premise and the catastrophic failure of rational, logical, and scientific thinking by essentially all scientists, Lies, Damned Lies, and Scientists: the Kyoto Premise example, Chapter A.1, 2011.
    4. Bakker, A. M. R., and B. J. J. M. van den Hurk, Estimation of persistence and trends in geostrophic wind speed for the assessment of wind energy yields in Northwest Europe, Climate Dynamics, 39 (3-4), 767-782, 2012.

  1. A. Efstratiadis, G. Karavokiros, S. Kozanis, A. Christofides, A. Koukouvinos, E. Rozos, N. Mamassis, I. Nalbantis, K. Noutsopoulos, E. Romas, L. Kaliakatsos, A. Andreadakis, and D. Koutsoyiannis, The ODYSSEUS project: Developing an advanced software system for the analysis and management of water resource systems, European Geosciences Union General Assembly 2006, Geophysical Research Abstracts, Vol. 8, Vienna, 03910, doi:10.13140/RG.2.2.24942.20805, European Geosciences Union, 2006.

    The ODYSSEUS project (from the Greek acronym of its full title "Integrated Management of Hydrosystems in Conjunction with an Advanced Information System") aims at providing support to decision-makers towards integrated water resource management. The end-product comprises a system of co-operating software applications, suitable to handle a wide spectrum of water resources problems. The key methodological concepts are the holistic modelling approach, through the conjunctive representation of processes regarding water quantity and quality, man-made interventions, the parsimony of both input data requirements and system parameterization, the assessment of uncertainties and risks, and the extended use of optimization both for modelling (within various scales) and derivation of management policies. The core of the system is a relational database, named HYDRIA, for storing hydrosystem information; this includes geographical data, raw and processed time series, characteristics of measuring stations and facilities, and a variety of economic, environmental and water quality issues. The software architecture comprises various modules. HYDROGNOMON supports data retrieval, processing and visualization, and performs a variety of time series analysis tasks. HYDROGEIOS integrates a conjunctive hydrological model within a systems-oriented water management scheme, which estimates the available water resources at characteristic sites of the river basin and at the underlying aquifer. HYDRONOMEAS is the hydrosystem control module and locates optimal operation policies that minimize the risk and cost of decision-making. Additional modules are employed to prepare input data. DIPSOS estimates water needs for various uses (water supply, irrigation, industry, etc.), whereas RYPOS estimates pollutant loads from point and non-point sources, at a river basin scale. A last category comprises post-processing modules, for evaluating the proposed management policies by means of economical efficiency and water quality requirements. The latter include sophisticated models that estimate the space and time variation of specific pollutants within rivers (HERIDANOS) and lakes (LERNE), as well as simplified versions of them to be used within the hydrosystem simulation scheme. An interactive framework enables the exchange of data between the various modules, either off-line (through the database) or on-line, via appropriate design of common information structures. The whole system is in the final phase of its development and parts of it have been already tested in operational applications, by water authorities, organizations and consulting companies.

    Full text:

    Additional material:

    See also: http://dx.doi.org/10.13140/RG.2.2.24942.20805

  1. S. Kozanis, A. Christofides, N. Mamassis, A. Efstratiadis, and D. Koutsoyiannis, Hydrognomon - A hydrological data management and processing software tool, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04644, doi:10.13140/RG.2.2.34222.10561, European Geosciences Union, 2005.

    Hydrognomon is a software tool for the management and analysis of hydrological data. It is built on a standard Windows platform based on client-server architecture; a database server is holding hydrological data whereas several workstations are executing Hydrognomon, sharing common data. Data retrieval, processing and visualisation are supported by a multilingual Graphical User Interface. Data management is based on geographical organisation to entities such as measuring stations, river basins, and reservoirs. Each entity may possess time series, physical properties, calculation parameters, multimedia content, etc. The main part of hydrological data analysis consists of time series processing applications, such as time step aggregation and regularisation, interpolation, regression analysis and filling in of missing values, consistency tests, data filtering, graphical and tabular visualisation of time series, etc. The program supports also specific hydrological applications, including evapotranspiration modelling, stage-discharge analysis, homogeneity tests, water balance methods, etc. The statistical module provides tools for sampling analysis, distribution functions, statistical forecast, Monte-Carlo simulation, analysis of extreme events and construction of intensity-duration-frequency curves. A final module is a lumped hydrological model, with alternative configurations, also supported by automatic calibration facilities. Hydrognomon is operationally used by the largest water organisation as well as technical corporations in Greece.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.34222.10561

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

    1. #Zarris, D., Analysis of the environmental flow requirement incorporating the effective discharge concept, Proceedings of the 6th International Symposium on Environmental Hydraulics, Athens, 1125–1130, International Association of Hydraulic Research, National Technical University of Athens, 2010.
    2. Puricelli, M., Update and analysis of intensity - duration - frequency curves for Balcarce, Buenos Aires province, Argentina, Revista de Geología Aplicada a la Ingeniería y al Ambiente, 32, 61-70, 2014.
    3. Radevski, I., S. Gorin, O. Dimitrovska, I. Milevski, B. Apostolovska-Toshevska, M. Taleska, and V. Zlatanoski, Estimation of maximum annual discharges by frequency analysis with four probability distributions in case of non-homogeneous time series (Kazani karst spring in Republic of Macedonia), Acta Carsologica, 45(3), 253-262, doi:10.3986/ac.v45i3.1544, 2016.
    4. #Mineo, C., S. Sebastianelli, L. Marinucci, and F. Russo, Assessment of the watershed DEM mesh size influence on a large dam design hydrograph, AIP Conference Proceedings, 1863, 470005, doi:10.1063/1.4992636, 2017.
    5. #Matingo, T., W. Gumindoga, and H. Makurira, Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin, Proc. IAHS, 378, 59–65, doi:10.5194/piahs-378-59-2018, 2018.
    6. #Ummah, R., A. A. Kuntoro, and H. Alamsyah, Effect of water level elevation in Madiun river on flooding in Jeroan river, Proceedings of the 3rd ITB Graduate School Conference “Enhancing Creativity in Research Through Developing Innovative Capabilities”, 2(2), 315-328, 2022.
    7. #Nikas-Nasioulis, I., and E. Baltas, Investigation of the energy coverage for wastewater treatment and desalination in the island of Kos based on a hybrid renewable energy system, Proceedings of 2nd World Conference on Sustainability, Energy and Environment, doi:10.33422/2nd.wscee.2022.12.120, 2022.

  1. A. Efstratiadis, D. Koutsoyiannis, K. Hadjibiros, A. Andreadakis, A. Stamou, A. Katsiri, G.-F. Sargentis, and A. Christofides, A multicriteria approach for the sustainable management of the Plastiras reservoir, Greece, EGS-AGU-EUG Joint Assembly, Geophysical Research Abstracts, Vol. 5, Nice, doi:10.13140/RG.2.2.23631.48801, European Geophysical Society, 2003.

    The Plastiras reservoir, sited in Western Thessaly, Greece, is a multipurpose project used for irrigation, water supply, hydropower, and recreation; the importance of the latter is continuously increasing as the reservoir landscape becomes attractive to tourists. These uses are competitive and result in a particularly complex problem of water management. Recently, a multidisciplinary analysis was attempted, aiming at determining a rational and sustainable management policy for the Plastiras Lake. This consists of establishing a minimum allowable water level for abstractions, in addition to a proper release policy. Until now, the reservoir level has had a 16 m fluctuation range, affecting negatively both the landscape, due to the exposure of the dead (no-vegetation) zone and the water quality. Three types of analyses were employed, to determine the variation of the corresponding criteria as a function of the allowable minimum level. The first one was the annual safe yield for various reliability levels, derived through a stochastic simulation model for the reservoir operation. The second criterion was the average summer concentration of chlorophyll-a (as indicator of the eutrophic regime of the lake), estimated through a one-dimensional eutrophication model. The final criterion was the aesthetics of the landscape; the relative study was focused on the effects of level variation and determined five fluctuation zones to characterise the quality of the landscape. After multiobjective analysis, and in cooperation with the local authorities and the public, a specific value of the minimum allowable level and a release policy were selected, which are currently on the way to be formally legislated.

    Full text:

    See also: http://dx.doi.org/10.13140/RG.2.2.23631.48801

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

    1. Gounaridis, D., and G. N. Zaimes, GIS-based multicriteria decision analysis applied for environmental issues: the Greek experience, International Journal of Applied Environmental Sciences, 7(3), 307–321, 2012.

Presentations and publications in workshops

  1. A. Christofides, Language and Large Language Models, Stuff we don't mention in the normal course of studies, Rovies, National Technical University of Athens (NTUA), 2023.

    I make a tour in various misleading terminologies, concluding with "artificial intelligence". I add some comments about Large Language Models and what they mean for our future.

    Full text: http://www.itia.ntua.gr/en/getfile/2308/1/documents/rovies2023-antonis-christofides.pdf (240 KB)

  1. A. Christofides, and D. Koutsoyiannis, God and the arrogant species: Contrasting nature's intrinsic uncertainty with our climate simulating supercomputers, 104th Annual Conference & Exhibition, Orlando, Florida, Air & Waste Management Association, 2011.

    Although the climate has always been in perpetual change, many scientists who support the anthropogenic global warming hypothesis claim that this time it's different, because their climate models show that the increase in carbon dioxide fits the current climate change better than any alternative explanation. This argument is circular, since the models reproduce the hypotheses of their programmers. What is most important, however, is that this way of reasoning is rooted in the fallacy that climate can, in principle, be described in deterministic terms; that if we could analyze the system with sufficient granularity and make sufficient measurements then we would be able to produce sufficiently good predictions; and that there must necessarily exist an identifiable causal agent behind every trend or shift. We explain that climate, like many natural systems, exhibits "Hurst-Kolmogorov behavior", which means it is intrinsically uncertain, with real limits to the potential for attribution and prediction.

    Remarks:

    Discussions in blogs: Climate etc., EuroEconom.cz, Environmental trends.

    Full text: http://www.itia.ntua.gr/en/getfile/1153/1/documents/god-and-the-arrogant-species.pdf (2532 KB)

  1. N. Mamassis, E. Tiligadas, D. Koutsoyiannis, M. Salahoris, G. Karavokiros, S. Mihas, K. Noutsopoulos, A. Christofides, S. Kozanis, A. Efstratiadis, E. Rozos, and L. Bensasson, HYDROSCOPE: National Databank for Hydrological, Meteorological and Geographical Information, Towards a rational handling of current water resource problems: Utilizing Data and Informatics for Information, Hilton Hotel, Athens, 2010.

    Full text:

  1. D. Koutsoyiannis, G. Tsakalias, A. Christofides, A. Manetas, A. Sakellariou, R. Mavrodimou, N. Papakostas, N. Mamassis, I. Nalbantis, and Th. Xanthopoulos, HYDROSCOPE: Creation of a national data bank of hydrological and meteorological information, Research and Technology Days '95, National Technical University of Athens, 1995.

    Full text: http://www.itia.ntua.gr/en/getfile/94/1/documents/1995EMPhydroscopeXanth.pdf (435 KB)

  1. A. Christofides, How much time does it take to write tests? A case study, EuroPython, Dublin, July 2022.

    Writing automated tests takes time. As developers, we are constantly pressed by management to deliver early, which means we are tempted to skip writing some of the tests. Of course, in the long term, the time needed to write tests is paid off.

    But how much of our time do we spend in order to write tests? Is it half? Is it three-quarters? This can be difficult to measure, particularly if we are using test-driven development, because in that case writing tests is integrated in the process of writing code.

    While I like test-driven development, I can only practice it when I have a good idea of what code I want to write. But sometimes my idea of how to approach the problem at hand is quite vague and I experiment a lot. In these cases, I write the code first and the tests after that.

    In one such case I first finished the functionality I was developing and proclaimed it "beta". I then went on to write the unit tests for it. As a result, I have a clear idea how much time I spent writing documentation and main code, and how much I spent writing tests. In this talk I examine the implications of all this.

    Remarks:

    See also: https://ep2022.europython.eu/session/how-much-time-does-it-take-to-write-tests-a-case-study

    Full text: http://www.itia.ntua.gr/en/getfile/2223/1/documents/europython-2022-christofides.pdf (461 KB)

  1. A. Tsitouras, A. Christofides, T. Smirnis, A. Peppas, R. Limnaiou, E. Evangelou, M. Tziouvalekas, Ch. Petsoulas, G. Karavokiros, and Ch. Tsantilas, ChemicalSE: Internet application for the managment of a large volume of geographical invormation using exclusively free sofware, 4th Congress of Geographical Information Systems and Spatial Analysis in Agriculture and Environment, Agricultural University of Athens, May 2022.

    he volume of data produced during the preparation of the project "Chemical quality check of irrigation waters (surface and groundwater) at the level of river basins of Sterea Greece (Prefecture of Fthiotida – Fokida – Biotia - Evritania and Evia)", which came from sampling of surface waters (water and sediment) and groundwaters (water) as well as level measurement, was large. More specifically, in order to collect the necessary data it has been designed and installed a network of sampling in rivers (Sperchios, Biotian Kifissos, Acheloos, Tavropos, Karpenisiotis, Krikelopotamos, Mornos, Asopos, Kallas, Kireas, Nileas, Voudouros, Lilas, Nireas and Mornos), in lakes ( Mornou, Yliki, Paralimni, Dystos, Kremaston), in drainage canals and boreholes - wells of Sterea Greece. In addition, an extensive network of level measurements was designed in order to measure the groundwater level. A total of 1,590 water samples and 966 sediment samples were collected. A series of parameters were determined in these samples. The total number of measurements in the collected samples is estimated at 1,173,204 values.

    Taking into account the above, the question that arosed was the possibility of registering all this data, in combination with the basic geographical, geomorphological and hydrographic data of the study area, in a system with some basic principles, such as: a) to be dynamic and enable processing , b) to use only free and open source software in all software used in the application, c) any browser will be sufficient for the access to the application, d) to have compatibility and adaptation of the application to all types of devices ( responsive design), recognizing the growing importance of mobile devices e) to enable the input of large volumes of data in an automated way, while setting limits to avoid errors and f) to have provision for viability and scalability of the application. Based on the above, ChemicalSE was created, which is a web application that combines geospatial information with a database. The website https://chemicalse.minagric.gr is the main access portal (portal) for the GIS that includes an interactive map that can display the metering network, while providing all the data to certified users. Last but not least all the above have as a result that the spatial analysis and management of geographical information through ChemicalSE will be comprehensible by all, without requiring specialized GIS knowledge, while ensuring its scalability.

    Full text:

  1. I. L. Tsirogiannis, N. Malamos, P. Barouchas, P. Baltzoi, K. Fotia, G. Tenedios, D. Giotis, D. Kateris, E. Tsoumani, S. Chiras, and A. Christofides, Evaluation of the application of the IRMA_SYS irrigation DSS on kiwi crop, 28th Conference of the Hellenic Horticulture Science Company, Thessaloniki, 465–468, October 2017.

    Full text: http://www.itia.ntua.gr/en/getfile/2013/1/documents/irma_sys_dss_aktinidio.pdf (363 KB)

Various publications

  1. A. Christofides, D. Koutsoyiannis, C. Onof, and Z. W. Kundzewicz, Causality, Climate, Etc., doi:10.13140/RG.2.2.21608.44803, Climate Etc. (Judith Curry's blog), 2023.

    This “book” is a copy of the blog discussion "Causality and climate" in Judith Curry’s blog "Climate Etc." taken on 2023-11-11 by Demetris Koutsoyiannis.

    Main post by Antonis Christofides, Demetris Koutsoyiannis, Christian Onof and Zbigniew W. Kundzewicz with a comment by Judith Curry.

    Featuring 989 contributions in 184 groups from 83 commenters.

    The blog content was retained as faithful to that in the blog as possible. The images linked in the blog have been reproduced here for the reader’s convenience. The repetitions appearing in the blog were also kept here, including in the images linked. Hyperlinks are kept, except those pertaining to reply to particular comments. In addition, internal links are added to help navigation in the document; for this reason, the comments are numbered.

    Full text: http://www.itia.ntua.gr/en/getfile/2353/1/documents/CausalityClimateEtc.pdf (13190 KB)

    See also: https://judithcurry.com/2023/09/26/causality-and-climate/

  1. A. Christofides, Why Andreas writes suboptimal code and why this hinders scientific research, 3 pages, 11 May 2014.

    Remarks:

    A presentation given at a meeting of Python programmers

    Full text: http://www.itia.ntua.gr/en/getfile/1453/1/documents/2014-05-andreas-writes-suboptimal-code_NaATeFi.pdf (118 KB)

  1. S. Kozanis, and A. Christofides, A webservice API to access free data from hydroscope and openmeteo.org projects, Athens Green Hackathon, Athens, http://athens.greenhackathon.com/, 2012.

    Full text: http://www.itia.ntua.gr/en/getfile/1313/1/documents/2012-12-13_AthensGreenHackathon.pdf (60 KB)

    See also: http://athens.greenhackathon.com/

  1. A. Christofides, and G. Milonaki, What problems are hidden in the agreement between the State and Microsoft, Newspaper Eleftherotipia, 63, 13 March 2006.

    Full text: http://www.itia.ntua.gr/en/getfile/1577/1/documents/agreement-between-state-and-ms.pdf (34444 KB)

Educational notes

  1. A. Christofides, A. Efstratiadis, and G.-F. Sargentis, Presentation of the research project "Investigation of scenarios for the management and protection of the quality of the Plastiras Lake", 79 pages, 1 April 2003.

    Remarks:

    Slides from presentation in the postgraduate course "Environmental impacts of hydraulic works".

    Full text:

Academic works

  1. A. Christofides, Summary of "Associates systems for decision support" by A. P. Sage, Course work, 3 pages, Department of Computer Science – University of Manchester, Manchester, 7 March 2000.

    Associates Decision Support Systems (DSS) are DSS's that are specific to a particular domain, in contrast to general-purpose DSS's. A. P. Sage wrote a paper in 1993, "Associates systems for decision support", which is supposed to provide an overview of associates DSS's. This work is a summary and a critique of Sage's paper.

    Remarks:

    This essay is part of a work for course CS635 "Decision Analysis and Decision Support Systems", which was taught by Prof. Simon French.

    Full text: http://www.itia.ntua.gr/en/getfile/284/1/documents/associates_dss.pdf (102 KB)

  1. A. Christofides, Short Term Rain Prediction with Artificial Neural Networks, MSc thesis, 46 pages, Manchester, October 2000.

    Virtually all research concerning short-term rain prediction to date makes use of spatial rainfall data, sometimes also taking another variable, such as wind direction, into account. This thesis explores the possibility of using neural networks for short-term rain predictions from several meteorological variables from only one gauging station. The input variables examined, besides rainfall, are wind speed and direction, temperature, humidity, and barometric pressure. The method cannot compete with spatial methods, and the results are indeed impractical, but they show some correlation which could be used to improve the spatial methods.

    Remarks:

    Thesis submitted to the University of Manchester for the degree of Master of Science in the Faculty of Science and Engineering

    Full text: http://www.itia.ntua.gr/en/getfile/118/1/documents/anthonymsc.pdf (377 KB)

  1. A. Christofides, Infilling of missing values of hydrometeorological time series in distributed relational databases, Diploma thesis, 75 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 1994.

    Infilling of missing values and extension of records are related procedures, performed either to facilitate other procedures or to improve the statistical characteristics of a time series. In this thesis, some of the most important existing methods are examined. These are: mean value, reciprocal distance, normal ratio, linear regression, maintenance-of-variance extension (MOVE), use of an AR(1) and PAR(1) model, and use of a multivariate stohastic model. Most of these have been implemented in a computer program in order to serve the needs of the national databank of hydrological and meteorological data, named "Hydroscope", which is based on a distributed relational database. Some significant elements of the implementation are described. Finally, an application on daily rainfall time series, together with a brief evaluation of the methods, is presented.

    Full text: http://www.itia.ntua.gr/en/getfile/363/1/documents/1994christofides.pdf (4623 KB)

Research reports

  1. A. Siskos, G. Karavokiros, A. Christofides, and A. Efstratiadis, Development of decision support system for renewable energy managment, Combined REnewable Systems for Sustainable ENergy DevelOpment (CRESSENDO), 103 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, July 2015.

    We describe the decision support system that implements the simulation and optimization model for combined water and energy systems. The report follows the structure of a user manual, in which are explained in detail the software operations.

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

    Full text: http://www.itia.ntua.gr/en/getfile/1604/1/documents/Report_EE3.pdf (3006 KB)

  1. S. Kozanis, A. Christofides, and A. Efstratiadis, Scientific documentation of the Hydrognomon software (version 4 ), Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information" , Contractor: Department of Water Resources and Environmental Engineering – National Technical University of Athens, 173 pages, Athens, June 2010.

    Hydrognomon software version 4 scientific documentation

    "Hydrognomon" is an application for the analysis of hydrological data. Hydrological data analysis consists of time series processing applications, such as time step aggregation and regularisation, interpolation, regression analysis and filling in of missing values, consistency tests, data filtering, graphical and tabular visualisation of time series, etc.

    The program supports also specific hydrological applications, including evapotranspiration modelling, stage-discharge and discharge-sediment discharge analysis, homogeneity tests, water balance methods, hydrometry, etc. The statistical module provides tools for sampling analysis, distribution functions, statistical forecast, Monte-Carlo simulation, analysis of extreme events and construction of intensity-duration-frequency curves.

    A final module is a lumped hydrological model, with alternative configurations, also supported by automatic calibration facilities.

    Document source in Microsoft Word Format: http://www.itia.ntua.gr/~soulman/hydrognomon/2009HydrognomonTheory.doc

    Remarks:

    Document version 1.02 - 2010-06-23 (Greek)

    Related works:

    • [54]
    • [55]
    • [67]
    • [33]

    Related project: Development of Database and software applications in a web platform for the "National Databank for Hydrological and Meteorological Information"

    Full text: http://www.itia.ntua.gr/en/getfile/928/1/documents/HydrognomonV4TheoryGR-v1.02.pdf (3356 KB)

    See also: http://hydrognomon.org/

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

    1. Tsanis, I. K., M. G. Grillakis, and A. G. Koutroulis, Climate change impact on the hydrology of Spencer Creekwatershed in Southern Ontario, Canada, Journal of Hydrology, 409(1-2), 1-19, doi:10.1016/j.jhydrol.2011.06.018, 2011.
    2. #Τσιντσάρης Α., και Φ. Μάρης, Αξιολόγηση των ορεινών υδρονομικών έργων του χείμαρρου Ελαιώνα Σερρών με την εφαρμογή υδρολογικών μοντέλων και γεωγραφικών συστημάτων πληροφοριών, Υδροτεχνικά, 20, 2011.
    3. Bekri, E., M. Disse, P. Yannopoulos, Optimizing water allocation under uncertain system conditions in Alfeios River Basin (Greece), Part A: Two-stage stochastic programming model with deterministic boundary intervals, Water, 7(10), 5305-5344, doi:10.3390/w7105305, 2015.
    4. Bekri, E., M. Disse, P. Yannopoulos, Optimizing water allocation under uncertain system conditions in Alfeios River Basin (Greece), Part B: Fuzzy-boundary intervals combined with multi-stage stochastic programming model, Water, 7(10), 6427-6466, doi:10.3390/w7116427, 2015.
    5. Ahmed, S., and I. Tsanis, Climate change impact on design storm and performance of urban storm-water management system – A case study on West Central Mountain drainage area in Canada, Hydrology Current Research, 7(1), 229, doi:10.4172/2157-7587.1000229, 2016.
    6. Charizopoulos, N., and A. Psilovikos, Hydrologic processes simulation using the conceptual model Zygos: the example of Xynias drained Lake catchment (central Greece), Environmental Earth Sciences, 75:777, doi:10.1007/s12665-016-5565-x, 2016.
    7. Charizopoulos, N., A. Psilovikos, and E. Zagana, A lumped conceptual approach for modeling hydrological processes: the case of Scopia catchment area, Central Greece, Environmental Earth Sciences, 76:18, doi:10.1007/s12665-017-6967-0, 2017.
    8. Mentzafou, A., S. Wagner, and E. Dimitriou, Historical trends and the long-term changes of the hydrological cycle components in a Mediterranean river basin, Science of The Total Environment, 636, 558-568, doi:10.1016/j.scitotenv.2018.04.298, 2018.
    9. #Πετροπούλου, Μ., Ε. Ζαγγάνα, Ν. Χαριζόπουλος, Μ. Μιχαλοπούλου, Α. Μυλωνάς, και Κ. Περδικάρης, Εκτίμηση του υδρολογικού ισοζυγίου της λεκάνης απορροής του Πηνειού ποταμού Ηλείας με χρήση του μοντέλου «Ζυγός», 14ο Πανελλήνιο Συνέδριο της Ελληνικής Υδροτεχνικής Ένωσης (ΕΥΕ), Βόλος, 2019.
    10. Bemmoussat, A., K. Korichi, D. Baahmed, N. Maref, O. Djoukbala, Z. Kalantari, and S. M. Bateni, Contribution of satellite-based precipitation in hydrological rainfall-runoff modeling: Case study of the Hammam Boughrara region in Algeria, Earth Systems and Environment, doi:10.1007/s41748-021-00256-z, 2021.
    11. Renima, M., A. Zeroual, Y. Hamitouche, A. Assani, S. Zeroual, A. A. Soltani, C. Mulowayi Mubulayi, S. Taibi, S. Bouabdelli, S. Kabli, A. Ghammit, I. Bara, A. Kastali, and R. Alkama, Improving future estimation of Cheliff-Mactaa-Tafna streamflow via an ensemble of bias correction approaches, Climate, 10(8), 123, doi:10.3390/cli10080123, 2022.

  1. D. Koutsoyiannis, A. Andreadakis, R. Mavrodimou, A. Christofides, N. Mamassis, A. Efstratiadis, A. Koukouvinos, G. Karavokiros, S. Kozanis, D. Mamais, and K. Noutsopoulos, National Programme for the Management and Protection of Water Resources, Support on the compilation of the national programme for water resources management and preservation, 748 pages, doi:10.13140/RG.2.2.25384.62727, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, February 2008.

    Related project: Support on the compilation of the national programme for water resources management and preservation

    Full text:

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

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

    1. Baltas, E. A., Climatic conditions and availability of water resources in Greece, International Journal of Water Resources Development, 24(4), 635-649, 2008
    2. Gikas, P., and G.Tchobanoglous, Sustainable use of water in the Aegean Islands, Journal of Environmental Management, 90(8), 2601-2611, 2009.
    3. Gikas, P., and A.N.Angelakis, Water resources management in Crete and in the Aegean Islands, with emphasis on the utilization of non-conventional water sources, Desalination, 248 (1-3), 1049-1064, 2009.
    4. Agrafioti, E., and E. Diamadopoulos, A strategic plan for reuse of treated municipal wastewater for crop irrigation on the Island of Crete, Agricultural Water Management, 105,57-64, 2012.
    5. #Zafirakis, D., C. Papapostolou, E. Kondili, and J. K. Kaldellis, Water use in the electricity generation sector: A regional approach evaluation for Greek thermal power plants, Protection and Restoration of the Environment XI, 1459-1468, 2012.
    6. Pisinaras, V., C. Petalas, V. A. Tsihrintzis and G. P. Karatzas, Integrated modeling as a decision-aiding tool for groundwater management in a Mediterranean agricultural watershed, Hydrological Processes, 27 (14), 1973-1987, 2013.
    7. Efstathiou, G.A., C. J. Lolis, N. M. Zoumakis, P. Kassomenos and D. Melas, Characteristics of the atmospheric circulation associated with cold-season heavy rainfall and flooding over a complex terrain region in Greece, Theoretical and Applied Climatology, 115 (1-2), 259-279, 2014.
    8. #Antoniou, G. P., Residential rainwater cisterns in Ithaki, Greece, IWA Regional Symposium on Water, Wastewater & Environment: Traditions & Culture (ed. by I. K. Kalavrouziotis and A. N. Angelakis), Patras, Greece, 675-685, International Water Association & Hellenic Open University, 2014.
    9. Kougioumoutzis, K., S.M. Simaiakis, and A. Tiniakou, Network biogeographical analysis of the central Aegean archipelago, Journal of Biogeography, 41 (10) 848-1858, 2014.
    10. Zafirakis, D., C. Papapostolou, E. Kondili, and J. K. Kaldellis, Evaluation of water‐use needs in the electricity generation sector of Greece, International Journal of Environment and Resource, 3(3), 39-45, doi:10.14355/ijer.2014.0303.01, 2014.
    11. Manakos, I., K. Chatzopoulos-Vouzoglanis, Z. I. Petrou, L. Filchev, and A. Apostolakis, Globalland30 Mapping capacity of land surface water in Thessaly, Greece, Land, 4 (1), 1-18, doi:10.3390/land4010001, 2015.
    12. Kallioras, A., and P. Marinos, Water resources assessment and management of karst aquifer systems in Greece, Environmental Earth Sciences, 74(1), 83-100, doi:10.1007/s12665-015-4582-5, 2015.
    13. #Grimpylakos , G., K. Albanakis, and T. S. Karacostas, Watershed size, an alternative or a misguided parameter for river’s waterpower? Implementation in Macedonia, Greece, Perspectives on Atmospheric Sciences, Springer Atmospheric Sciences, 295-301, doi:10.1007/978-3-319-35095-0_41, 2017.
    14. Tsangaratos, P. A. Kallioras , Th. Pizpikis, E. Vasileiou, I. Ilia, and F. Pliakas, Multi-criteria Decision Support System (DSS) for optimal locations of Soil Aquifer Treatment (SAT) facilities, Science of The Total Environment, 603–604, 472–486, doi:10.1016/j.scitotenv.2017.05.238, 2017.
    15. Soulis, K. X., and D. E. Tsesmelis, Calculation of the irrigation water needs spatial and temporal distribution in Greece, European Water, 59, 247-254, 2017.
    16. Piria, M., P. Simonović, E. Kalogianni, L. Vardakas, N. Koutsikos, D. Zanella, M. Ristovska, A. Apostolou, A. Adrović, D. Mrdak, A. S. Tarkan, D. Milošević, L. N. Zanella, R. Bakiu, F. G. Ekmekçi, M. Povž, K. Korro, V. Nikolić, R. Škrijelj, V. Kostov, A. Gregori, and M. K. Joy, Alien freshwater fish species in the Balkans — Vectors and pathways of introduction, Fish and Fisheries, 19(1), 138–169, doi:10.1111/faf.12242, 2018.
    17. Falalakis, G. and A. Gemitzi, A simple method for water balance estimation based on the empirical method and remotely sensed evapotranspiration estimates, Journal of Hydroinformatics, 22(2), 440-451, doi:10.2166/hydro.2020.182, 2020.
    18. Laspidou, C. S., N. Mellios, A. Spyropoulou, D. Kofinas, and M. P. Papadopoulou, Systems thinking on the resource nexus: Modeling and visualisation tools to identify critical interlinkages for resilient and sustainable societies and institutions, Science of The Total Environment, 717, 137264, doi:10.1016/j.scitotenv.2020.137264, 2020.
    19. Tzanakakis, V. A., A. N. Angelakis, N. V. Paranychianakis, Y. G. Dialynas, and G. Tchobanoglous, Challenges and opportunities for sustainable management of water resources in the island of Crete, Greece, Water, 12(6), 1538, doi:10.3390/w12061538, 2020.
    20. Skrimizea, E., and C. Parra, An adaptation pathways approach to water management and governance of tourist islands: the example of the Southern Aegean Region in Greece, Water International, 45(7-8), 746-764, doi:10.1080/02508060.2020.1791683, 2020.
    21. Alamanos, A., P. Koundouri, L. Papadaki, and T. Pliakou, A system innovation approach for science-stakeholder interface: theory and application to water-land-food-energy nexus, Frontiers in Water, 3, 744773, doi:10.3389/frwa.2021.744773, 2022.
    22. Zafeirakou, A., A. Karavi, A. Katsoulea, A. Zorpas, and I. Papamichael, Water resources management in the framework of the circular economy for touristic areas in the Mediterranean: case study of Sifnos Island in Greece, Euro-Mediterranean Journal for Environmental Integration, doi:10.1007/s41207-022-00319-1, 2022.
    23. Alamanos, A., P. Koundouri, L. Papadaki, T. Pliakou, and E. Toli, Water for tomorrow: A living lab on the creation of the science-policy-stakeholder interface, Water, 14(18), 2879, doi:10.3390/w14182879, 2022.

  1. A. Christofides, and G. Karavokiros, Database design, Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 1, 144 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2007.

    The design of the central database of HYDROGAEA is described. The database obeys the relational model and encompasses all data. The database consists of subsystems for the management of time series, the representation of the "real world", i.e., the geographical entities for measuring stations, cities, dams, conduits, lakes etc., and the mathematical models.

    Related project: Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)

    Full text: http://www.itia.ntua.gr/en/getfile/764/1/documents/report_1.pdf (2095 KB)

    Additional material:

  1. S. Kozanis, A. Christofides, and A. Efstratiadis, Description of the data management and processing system "Hydrognomon", Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS), Contractor: NAMA, Report 2, 141 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 2005.

    "Hydrognomon" is a software tool for the management and analysis of hydrological data. It is built on a standard Windows platform based on client-server architecture; a database server is holding hydrological data whereas several workstations are executing Hydrognomon, sharing common data. Data retrieval, processing and visualisation are supported by a multilingual Graphical User Interface. Data management is based on geographical organisation to entities such as measuring stations, river basins, and reservoirs. Each entity may possess time series, physical properties, calculation parameters, multimedia content, etc. The main part of hydrological data analysis consists of time series processing applications, such as time step aggregation and regularisation, interpolation, regression analysis and filling in of missing values, consistency tests, data filtering, graphical and tabular visualisation of time series, etc. The program supports also specific hydrological applications, including evapotranspiration modelling, stage-discharge analysis, homogeneity tests, water balance methods, etc. The statistical module provides tools for sampling analysis, distribution functions, statistical forecast, Monte-Carlo simulation, analysis of extreme events and construction of intensity-duration-frequency curves. A final module is a lumped hydrological model, with alternative configurations, also supported by automatic calibration facilities. This report is the scientific documentation of the "Hydrognomon" system.

    Related project: Integrated Management of Hydrosystems in Conjunction with an Advanced Information System (ODYSSEUS)

    Full text: http://www.itia.ntua.gr/en/getfile/676/1/documents/report_2.pdf (5332 KB)

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

    1. #Psarianou, P., I. Nalbantis, and I. Kydonaki, Data inadequacy in water quality modelling: the case of Lake Pamvotis, Proceedings of the 12th International Conference on Environmental Science and Technology (CEST2011), A1513-A1520, Rhodes, 2011.
    2. Papagiannis, N., I. Koumantakis, and E. Vasileiou, Karstic aquifer of Orfana-Iperia of West Thessaly. The research and analysis of the hydrodynamic and hydrochemical status before the application of artificial ground water recharge, Bulletin of the Geological Society of Greece, 50, 917-926, doi:10.12681/bgsg.14398, 2016.
    3. #Πετροπούλου, Μ., Ε. Ζαγγάνα, Ν. Χαριζόπουλος, Μ. Μιχαλοπούλου, Α. Μυλωνάς, και Κ. Περδικάρης, Εκτίμηση του υδρολογικού ισοζυγίου της λεκάνης απορροής του Πηνειού ποταμού Ηλείας με χρήση του μοντέλου «Ζυγός», 14ο Πανελλήνιο Συνέδριο της Ελληνικής Υδροτεχνικής Ένωσης (ΕΥΕ), Βόλος, 2019.

  1. A. Christofides, and S. Kozanis, Hydrognomon (version 1.0) - Software for data management, Modernisation of the supervision and management of the water resource system of Athens, Report 22, 90 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.

    This report documents the "Hydrognomon" software and constitutes its user manual. First, the features of the software are briefly presented. Then, the user is introduced to essential operations and options and to the functionality that is common to all components. Next, the Timeseries processing module is presented, including details of the interpolation functions (calculation of discharge and of reservoir volume and surface) and of evaporation calculation. Next, the functionality concerning the management of geographical entities is presented. Finally, the application for the calculation of reservoir balance is explained. Appendices describe helper software, certain data processing operations, and file format.

    Related project: Modernisation of the supervision and management of the water resource system of Athens

    Full text: http://www.itia.ntua.gr/en/getfile/618/1/documents/report22.pdf (2153 KB)

  1. D. Koutsoyiannis, I. Nalbantis, G. Karavokiros, A. Efstratiadis, N. Mamassis, A. Koukouvinos, A. Christofides, E. Rozos, A. Economou, and G. M. T. Tentes, Methodology and theoretical background, Modernisation of the supervision and management of the water resource system of Athens, Report 15, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 2004.

    The methodology that was developed for the analysis of the water supply system of Athens, even though it was dictated by the special requirements of this particular system, has a broader character and a generalised orientation. In this respect, a series of publications in international scientific journals and communications in scientific conferences and workshops were done, so that the methodology becomes known to the international scientific community and raises its critique. These publications and communications are classified into two categories, with the fist one containing those referring to the core of the water supply system analysis, i.e., to the system optimisation based on the original methodology parameterisation-simulation-optimisation, and the second one containing those dealing with stochastic simulation and prediction of the hydrological inputs to the system. For a clear description and explanation of the methodology, the publications in scientific journals are reproduced in this volume and, for completeness, the summaries of the communications in conferences are included as well.

    Related project: Modernisation of the supervision and management of the water resource system of Athens

  1. Ministry of Development, NTUA, Institute of Geological and Mining Research, and Centre for Research and Planning, Master plan for water resource management of the country, Completion of the classification of quantitative and qualitative parameters of water resources in water districts of Greece, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 549 pages, Ministry of Development, Athens, January 2003.

    Remarks:

    See the newer version of this report:

    National Programme for Water Resources Management and Preservation

    Related works:

    • [52] Newer version

    Related project: Completion of the classification of quantitative and qualitative parameters of water resources in water districts of Greece

    Full text:

  1. K. Hadjibiros, D. Koutsoyiannis, A. Andreadakis, A. Katsiri, A. Stamou, A. Valassopoulos, A. Efstratiadis, I. Katsiris, M. Kapetanaki, A. Koukouvinos, N. Mamassis, K. Noutsopoulos, G.-F. Sargentis, and A. Christofides, Overview report, Investigation of scenarios for the management and protection of the quality of the Plastiras Lake, Report 1, 23 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2002.

    The Plastiras Lake is a reservoir used for irrigation, water supply, hydropower, and tourism. These uses are competitive and result in an especially complex problem of water management. In this report the problem is presented and the main points of the three parts of the project are summarised; these three parts are the hydrological study, the quality study, and the landscape study. The conflicting demands are arranged, and water release scenarios are suggested.

    Related project: Investigation of scenarios for the management and protection of the quality of the Plastiras Lake

    Full text:

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

    1. Andreadakis, A., K. Noutsopoulos, and E. Gavalaki, Assessment of the water quality of Lake Plastira through mathematical modelling for alternative management scenarios, Global Nest: the International Journal, 5(2), pp 99-105, 2003.
    2. #Karalis, S. and A . Chioni, 1-D Hydrodynamic modeling of Greek lakes and reservoirs, Ch. 59 in Environmental Hydraulics, Proceedings of the 6th International Symposium on Environmental Hydraulics (ed. by A. I . Stamou), Athens, Greece, 397–401, 2010.
    3. Kalavrouziotis, I. K., A. Τ. Filintas, P. H. Koukoulakis, and J. N. Hatzopoulos, Application of multicriteria analysis in the management and planning of treated municipal wastewater and sludge reuse in agriculture and land development: the case of Sparti’s wastewater treatment plant, Greece, Fresenius Environmental Bulletin, 20(2), 287-295, 2011.

  1. G.-F. Sargentis, and A. Christofides, The landscape, Investigation of scenarios for the management and protection of the quality of the Plastiras Lake, Report 4, 73 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, March 2002.

    The level of Lake Plastira varies widely due to water release. Specifically, the level varies from 792 m, which is spill level, to 776 m, which is the lowest level. This variation affects the landscape to a high degree. In this report the aesthetics of the landscape of Lake Plastira is examined, focusing on the effects of level variation. The conclusion is that for levels around 786 m or greater, there are minimal effects on the landscape and virtually everyone finds it wonderful. For lower levels, down to about 782 m, the landscape is significantly affected, mostly due to the dead zone revealed by the lowering of the level; most first or second-time visitors find it beautiful, but many inhabitants of the area and people who visit it regularly anticipate problems. For even lower levels, only visitors who do not come regularly may find the landscape satisfactory, and only in a few observation points. Apart from level variation, other problems of the landscape are discussed, namely those resulting from development. Such problems concern roads, boats, buildings, signs, and light pollution, and it is concluded that the area must be protected. In addition, some preliminary suggestions are made concerning the creation of tourist attractions and infrastructure which should fit the character of the area.

    Related project: Investigation of scenarios for the management and protection of the quality of the Plastiras Lake

    Full text:

  1. A. Koukouvinos, and A. Christofides, Development of a geographic information system for hydrology, water use and related works, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3, Report 38, 50 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, January 1999.

    Related project: Evaluation of Management of the Water Resources of Sterea Hellas - Phase 3

    Full text:

  1. Team of the YBET96 project, Master plan for the country's water resource management, Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 339 pages, Ministry of Development, Athens, November 1996.

    Related works:

    • [57] Newer edition

    Related project: Classification of quantitative and qualitative parameters of the water resources of Greece using geographical information systems

  1. A. Christofides, and N. Mamassis, Hydrometeorological data processing, Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2, Report 18, 268 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, September 1995.

    Related project: Evaluation of Management of the Water Resources of Sterea Hellas - Phase 2

    Full text:

  1. N. Papakostas, G. Tsakalias, and A. Christofides, Instructions manual, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, 50 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 1994.

    Related project: Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information

    Full text: http://www.itia.ntua.gr/en/getfile/350/1/documents/er1_1-84.pdf (4966 KB)

  1. NTUA Hydroscope Team, HYDROSCOPE, User manual for the database and applications for hydrology and meteorology, Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information, Contractor: Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, 180 pages, National Technical University of Athens, Athens, December 1994.

    Related project: Hydroscope: Creation of a National Databank for Hydrological and Meteorological Information

    Full text: http://www.itia.ntua.gr/en/getfile/338/1/documents/er1_1-73.pdf (13830 KB)

Miscellaneous works

  1. A. Christofides, and N. Mamassis, Comments on the proposal for a law on the renewable energy sources, 4 pages, 15 January 2010.

    Full text: http://www.itia.ntua.gr/en/getfile/945/1/documents/2010-01-sxolia-nomosxedio-aiolikis.pdf (154 KB)

  1. A. Christofides, Openmeteo database description, 8 pages, 2005.

    Remarks:

    Openmeteo was an idea about the creation of an open database of meteorological data, accessible through the web. This document describes the database.

    Full text: http://www.itia.ntua.gr/en/getfile/845/1/documents/omdb.pdf (840 KB)

  1. A. Christofides, and D. Koutsoyiannis, Hydrognomon: A database for hydrological and meteorological time series and a processing system of time series, 16 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, February 2002.

    Full text: http://www.itia.ntua.gr/en/getfile/498/1/documents/hydrognomon_presentation.pdf (400 KB)

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

    1. #Michas, S.N., M.N. Pikounis, I. Nalbantis, P.L. Lazaridou and E.I. Daniil, On the hydrologic analysis for water resources management in Aegean Islands, Proceedings, Protection and Restoration of the Environment VIII, Mykonos, Greece, 2006.

  1. A. Christofides, Software for the management of measuring stations and time series, 12 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, October 2001.

    The software presented in this report part of a large system being developed in order to assist the management of the 4000 sq. km hydrosystem from which Athens, Greece, is supplied with water. The software development is being funded by the Water Supply and Sewerage Company of Athens. It embodies experience from the Hydroscope project (1992-1993), but makes use of the latest technology in relational databases and software development tools.

    Remarks:

    This is a temporary report and may be altered in the future or it may be removed from the web site.

    Full text: http://www.itia.ntua.gr/en/getfile/484/1/documents/ihm_presentation.pdf (182 KB)

  1. A. Christofides, The meteorological station of NTUA, 50 pages, June 1999.

    Internal report that describes the meteorological station, its history and its software. Most parts are obsolete (e.g. Chapter 5 has been replaced by the software documentation, which can be viewed with "man deltacom").

    Full text: http://www.itia.ntua.gr/en/getfile/892/1/documents/meteo.pdf (730 KB)