HYDROGEIOS: A semi-distributed GIS-based hydrological model for modified river basins

A. Efstratiadis, I. Nalbantis, A. Koukouvinos, E. Rozos, and D. Koutsoyiannis, HYDROGEIOS: A semi-distributed GIS-based hydrological model for modified river basins, Hydrology and Earth System Sciences, 12, 989–1006, doi:10.5194/hess-12-989-2008, 2008.

[doc_id=787]

[English]

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

PDF Full text (3843 KB)

PDF Additional material:

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

Remarks:

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

Our works referenced by this work:

1. A. Efstratiadis, and D. Koutsoyiannis, An evolutionary annealing-simplex algorithm for global optimisation of water resource systems, Proceedings of the Fifth International Conference on Hydroinformatics, Cardiff, UK, 1423–1428, doi:10.13140/RG.2.1.1038.6162, International Water Association, 2002.
2. D. Koutsoyiannis, A. Efstratiadis, and G. Karavokiros, A decision support tool for the management of multi-reservoir systems, Journal of the American Water Resources Association, 38 (4), 945–958, doi:10.1111/j.1752-1688.2002.tb05536.x, 2002.
3. I. Nalbantis, E. Rozos, G. M. T. Tentes, A. Efstratiadis, and D. Koutsoyiannis, Integrating groundwater models within a decision support system, Proceedings of the 5th International Conference of European Water Resources Association: "Water Resources Management in the Era of Transition", edited by G. Tsakiris, Athens, 279–286, European Water Resources Association, 2002.
4. 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.
5. A. Efstratiadis, D. Koutsoyiannis, and D. Xenos, Minimising water cost in the water resource management of Athens, Urban Water Journal, 1 (1), 3–15, 2004.
6. K. Mazi, A. D. Koussis, P. J. Restrepo, and D. Koutsoyiannis, A groundwater-based, objective-heuristic parameter optimisation method for a precipitation-runoff model and its application to a semi-arid basin, Journal of Hydrology, 290, 243–258, 2004.
7. E. Rozos, A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows, Hydrological Sciences Journal, 49 (5), 819–842, doi:10.1623/hysj.49.5.819.55130, 2004.
8. E. Rozos, and D. Koutsoyiannis, Application of the Integrated Finite Difference Method in groundwater flow, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 00579, doi:10.13140/RG.2.2.30185.08803, European Geosciences Union, 2005.
9. E. Rozos, and D. Koutsoyiannis, A multicell karstic aquifer model with alternative flow equations, Journal of Hydrology, 325 (1-4), 340–355, 2006.
10. D. Koutsoyiannis, A. Efstratiadis, and K. Georgakakos, Uncertainty assessment of future hydroclimatic predictions: A comparison of probabilistic and scenario-based approaches, Journal of Hydrometeorology, 8 (3), 261–281, doi:10.1175/JHM576.1, 2007.
11. A. Efstratiadis, and D. Koutsoyiannis, Fitting hydrological models on multiple responses using the multiobjective evolutionary annealing simplex approach, Practical hydroinformatics: Computational intelligence and technological developments in water applications, edited by R.J. Abrahart, L. M. See, and D. P. Solomatine, 259–273, doi:10.1007/978-3-540-79881-1_19, Springer, 2008.
12. A. Efstratiadis, Non-linear methods in multiobjective water resource optimization problems, with emphasis on the calibration of hydrological models, PhD thesis, 391 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, February 2008.

Our works that reference this work:

1. A. Efstratiadis, and D. Koutsoyiannis, On the practical use of multiobjective optimisation in hydrological model calibration, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 2326, doi:10.13140/RG.2.2.10445.64480, European Geosciences Union, 2009.
2. A. Efstratiadis, K. Mazi, A. D. Koussis, and D. Koutsoyiannis, Flood modelling in complex hydrologic systems with sparsely resolved data, European Geosciences Union General Assembly 2009, Geophysical Research Abstracts, Vol. 11, Vienna, 4157, doi:10.13140/RG.2.2.13801.08807, European Geosciences Union, 2009.
3. A. Efstratiadis, and N. Mamassis, Evaluating models or evaluating modelling practices? - Interactive comment on HESS Opinions “Crash tests for a standardized evaluation of hydrological models”, Hydrology and Earth System Sciences Discussions, 6, C1404–C1409, 2009.
4. A. Efstratiadis, and D. Koutsoyiannis, One decade of multiobjective calibration approaches in hydrological modelling: a review, Hydrological Sciences Journal, 55 (1), 58–78, 2010.
5. A. Efstratiadis, I. Nalbantis, E. Rozos, and D. Koutsoyiannis, Accounting for water management issues within hydrological simulation: Alternative modelling options and a network optimization approach, European Geosciences Union General Assembly 2010, Geophysical Research Abstracts, Vol. 12, Vienna, 10085, doi:10.13140/RG.2.2.22189.69603, European Geosciences Union, 2010.
6. E. Rozos, and D. Koutsoyiannis, Error analysis of a multi-cell groundwater model, Journal of Hydrology, 392 (1-2), 22–30, 2010.
7. I. Nalbantis, A. Efstratiadis, E. Rozos, M. Kopsiafti, and D. Koutsoyiannis, Holistic versus monomeric strategies for hydrological modelling of human-modified hydrosystems, Hydrology and Earth System Sciences, 15, 743–758, doi:10.5194/hess-15-743-2011, 2011.
8. K. Hadjibiros, A. Katsiri, A. Koukouvinos, N. Moutafis, and G. Vilandou, Sustainable management of a large-scale tourist facility with significant water demand, Proceedings of the 12th International Conference on Environmental Science and Technology, A672–A679, Rhodes, 2011.
9. 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.
10. E. Rozos, Ε. Akylas, and A. D. Koussis, An automated inverse method for slug tests – over-damped case – in confined aquifers, Hydrological Sciences Journal, doi:10.1080/02626667.2014.892207, 2015.
11. A. Efstratiadis, I. Nalbantis, and D. Koutsoyiannis, Hydrological modelling of temporally-varying catchments: Facets of change and the value of information, Hydrological Sciences Journal, 60 (7-8), 1438–1461, doi:10.1080/02626667.2014.982123, 2015.
12. I. Tsoukalas, P. Kossieris, A. Efstratiadis, and C. Makropoulos, Surrogate-enhanced evolutionary annealing simplex algorithm for effective and efficient optimization of water resources problems on a budget, Environmental Modelling and Software, 77, 122–142, doi:10.1016/j.envsoft.2015.12.008, 2016.
13. E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, A curve number approach to formulate hydrological response units within distributed hydrological modelling, Hydrology and Earth System Sciences Discussions, doi:10.5194/hess-2016-627, 2016, (in review).

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

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

1. #Soulis, K., and N. Dercas, AgroHydroLogos: development and testing of a spatially distributed agro-hydrological model on the basis of ArcGIS, International Environmental Modelling and Software Society (iEMSs), 2010 International Congress on Environmental Modelling and Software, Modelling for Environment’s Sake, Fifth Biennial Meeting, Ottawa, Canada, D. A. Swayne, Wanhong Yang, A. A. Voinov, A. Rizzoli, T. Filatova (Eds.), 2010.
2. #Isidoro, J. M. G. P., J. I. J, Rodrigues, J. M. R. Martins, and J. L. M. P. De Lima, Evolution of urbanization in a small urban basin: DTM construction for hydrologic computation, Status and Perspectives of Hydrology in Small Basins, edited by A. Herrmann and S. Schumann, IAHS-AISH Publication 336, 109-114, 2010.
3. Price, C., Y. Yair, A. Mugnai, K. Lagouvardos, M. C. Llasat, S. Michaelides, U. Dayan, S. Dietrich, E. Galanti, L. Garrote, N. Harats, D. Katsanos, M. Kohn, V. Kotroni, M. Llasat-Botija, B. Lynn, L. Mediero, E. Morin, K. Nicolaides, S. Rozalis, K. Savvidou, and B. Ziv, The FLASH Project: using lightning data to better understand and predict flash floods, Environmental Science and Policy, 14(7), 898-911, 2011.
4. Bahadur, K. K. C., Assessing strategic water availability using remote sensing, GIS and a spatial water budget model: case study of the Upper Ing Basin, Thailand, Hydrological Sciences Journal, 56(6), 994-1014, 2011.
5. #SIRRIMED (Sustainable use of irrigation water in the Mediterranean Region), D4.2 and D5.2 Report on Models to be Implemented in the District Information Systems (DIS) and Watershed Information Systems (WIS), 95 pp., Universidad Politécnica de Cartagena, 2011.
6. Mediero, L., L. Garrote and F. J. Martín-Carrasco, Probabilistic calibration of a distributed hydrological model for flood forecasting, Hydrological Sciences Journal, 56(7), 1129–1149, 2011.
7. Flipo, N., C. Monteil, M. Poulin, C. de Fouquet, and M. Krimissa, Hybrid fitting of a hydrosystem model: Long term insight into the Beauce aquifer functioning (France), Water Recourses Research, 48, W05509, doi: 10.1029/2011WR011092, 2012.
8. Soulis, K.X., Development of a simplified grid cells ordering method facilitating GIS-based spatially distributed hydrological modeling, Computers & Geosciences, 54, 160-163, 2013.
9. 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.
10. #Loukas, A., and L. Vasiliades, Review of applied methods for flood-frequency analysis in a changing environment in Greece, In: A review of applied methods in Europe for flood-frequency analysis in a changing environment, Floodfreq COST action ES0901: European procedures for flood frequency estimation (ed. by H. Madsen et al.), Centre for Ecology & Hydrology, Wallingford, UK, 2013.
11. Varni, M., R. Comas, P. Weinzettel and S. Dietrich, Application of the water table fluctuation method to characterize groundwater recharge in the Pampa plain, Argentina, Hydrological Sciences Journal, 58 (7), 1445-1455, 2013.
12. Han, J.-C., G.-H. Huang, H. Zhang, Z. Li, and Y.-P Li, Effects of watershed subdivision level on semi-distributed hydrological simulations: case study of the SLURP model applied to the Xiangxi River watershed, China, Hydrological Sciences Journal, 59(1), 108-125, 2014.
13. Gharari, S., M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije, Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrology and Earth System Sciences, 18, 4839-4859, doi:10.5194/hessd-10-14801-2013, 2013.
14. #Savvidou, E., O. Tzoraki and D. Skarlatos, Delineating hydrological response units in a mountainous catchment and its evaluation on water mass balance and model performance, Proc. SPIE 9229, Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 922918, doi:10.1117/12.2068592, 2014.
15. Wi, S., Y.C.E. Yang, S. Steinschneider, A. Khalil, and C.M. Brown, Calibration approaches for distributed hydrologic models in poorly gaged basins: implication for streamflow projections under climate change, Hydrology and Earth System Sciences, 19, 857-876, doi:10.5194/hess-19-857-2015, 2015.
16. 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.
17. #Soulis, K. X., D. Manolakos, J. Anagnostopoulos, and D. Panantonis, Assessing the hydropower potential of historical hydro sites using a geo-information system and hydrological modeling in poorly gauged areas, 9th World Congress of the European Water Resources Association (EWRA) “Water Resources Management in a Changing World: Challenges and Opportunities”, Istanbul, 2015.
18. Bellin, A., B. Majone, O. Cainelli, D. Alberici, and F. Villa, A continuous coupled hydrological and water resources management model, Environmental Modelling and Software, 75, 176–192, doi:10.1016/j.envsoft.2015.10.013, 2016.
19. Hughes, J. D., S. S. H. Kim, D. Dutta, and J. Vaze, Optimisation of a multiple gauge, regulated river–system model. A system approach, Hydrological Processes, 30(12), 1955–1967, doi:10.1002/hyp.10752, 2016.
20. Merheb, M., R. Moussa, C. Abdallah, F. Colin, C. Perrin, and N. Baghdadi, Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis, Hydrological Sciences Journal, 61(14), 2520-2539, doi:10.1080/02626667.2016.1140174, 2016.
21. Beskow, S., L. C. Timm, V. E. Q. Tavares, T. L. Caldeira, and L. S. Aquino, Potential of the LASH model for water resources management in data-scarce basins: a case study of the Fragata River basin, southern Brazil, Hydrological Sciences Journal, 61(14), 2567-2578, doi:10.1080/02626667.2015.1133912, 2016.
22. Soulis, K. X., D. Manolakos, J. Anagnostopoulos, and D. Papantonis, Development of a geo-information system embedding a spatially distributed hydrological model for the preliminary assessment of the hydropower potential of historical hydro sites in poorly gauged areas, Renewable Energy, 92, 222-232, doi:10.1016/j.renene.2016.02.013, 2016.
23. Ercan, A., E. C. Dogrul, and T. N. Kadir, Investigation of the groundwater modelling component of the Integrated Water Flow Model (IWFM), Hydrological Sciences Journal, 61(16), 2834-2848, doi:10.1080/02626667.2016.1161765, 2016.
24. Sadaoui, M., W. Ludwig, F. Bourrin, E. Romero, The impact of reservoir construction on riverine sediment and carbon fluxes to the Mediterranean Sea, Progress in Oceanography, doi:10.1016/j.pocean.2017.08.003, 2017.
25. #Gourgoulios, V., and I. Nalbantis, Ungauged drainage basins: Investigation on the basin of Peneios River, Thessaly, Greece, Proceedings of the 10th World Congress of EWRA “Panta Rhei”, European Water Resources Association, Athens, 2017.
26. #Soulis, K. X., and D. E. Tsesmelis, Calculation of the irrigation water needs spatial and temporal distribution in Greece, Proceedings of the 10th World Congress of EWRA “Panta Rhei”, European Water Resources Association, Athens, 2017.
27. #Peng, Y., K. Wang, P. Zhou, and W. Qin, Research on multi-scale optimal allocation of land resources in Savan district, Laos, 25th International Conference on Geoinformatics, Buffalo, NY, Institute of Electrical and Electronics Engineers (IEEE), doi:10.1109/GEOINFORMATICS.2017.8090930, 2017.

Tagged under: Groundwater, Hydrological models, Optimization, Software