Calibration of a semi-distributed model for conjunctive simulation of surface and groundwater flows

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.

[doc_id=630]

[English]

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

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Our works referenced by this work:

1.	G. C. Koukis, and D. Koutsoyiannis, Greece, Geomorphological hazards in Europe, edited by C.&C. Embleton, 215–241, doi:10.1016/S0928-2025(97)80010-7, Elsevier, 1997.
2.	I. Nalbantis, and E. Rozos, A system for the simulation of the hydrological cycle in the Boeoticos Kephisos basin, Modernisation of the supervision and management of the water resource system of Athens, Report 10, 72 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, December 2000.
3.	A. Efstratiadis, Investigation of global optimum seeking methods in water resources problems, MSc thesis, 139 pages, Department of Water Resources, Hydraulic and Maritime Engineering – National Technical University of Athens, Athens, May 2001.
4.	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.
5.	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.
6.	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.

Our works that reference this work:

1.	A. Efstratiadis, and D. Koutsoyiannis, The multiobjective evolutionary annealing-simplex method and its application in calibrating hydrological models, European Geosciences Union General Assembly 2005, Geophysical Research Abstracts, Vol. 7, Vienna, 04593, doi:10.13140/RG.2.2.32963.81446, European Geosciences Union, 2005.
2.	D. Koutsoyiannis, A toy model of climatic variability with scaling behaviour, Journal of Hydrology, 322, 25–48, doi:10.1016/j.jhydrol.2005.02.030, 2006.
3.	D. Koutsoyiannis, Nonstationarity versus scaling in hydrology, Journal of Hydrology, 324, 239–254, doi:10.1016/j.jhydrol.2005.09.022, 2006.
4.	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.
5.	C. Cudennec, C. Leduc, and D. Koutsoyiannis, Dryland hydrology in Mediterranean regions -- a review, Hydrological Sciences Journal, 52 (6), 1077–1087, doi:10.1623/hysj.52.6.1077, 2007.
6.	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.
7.	C. Makropoulos, D. Koutsoyiannis, M. Stanic, S. Djordevic, D. Prodanovic, T. Dasic, S. Prohaska, C. Maksimovic, and H. S. Wheater, A multi-model approach to the simulation of large scale karst flows, Journal of Hydrology, 348 (3-4), 412–424, 2008.
8.	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.
9.	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.
10.	N. Evelpidou, N. Mamassis, A. Vassilopoulos, C. Makropoulos, and D. Koutsoyiannis, Flooding in Athens: The Kephisos River flood event of 21-22/10/1994, International Conference on Urban Flood Management, Paris, doi:10.13140/RG.2.1.4065.5601, UNESCO, 2009.
11.	A. Efstratiadis, and D. Koutsoyiannis, One decade of multiobjective calibration approaches in hydrological modelling: a review, Hydrological Sciences Journal, 55 (1), 58–78, doi:10.1080/02626660903526292, 2010.
12.	E. Rozos, and D. Koutsoyiannis, Error analysis of a multi-cell groundwater model, Journal of Hydrology, 392 (1-2), 22–30, 2010.
13.	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.
14.	D. Koutsoyiannis, N. Mamassis, A. Efstratiadis, N. Zarkadoulas, and Y. Markonis, Floods in Greece, Changes of Flood Risk in Europe, edited by Z. W. Kundzewicz, Chapter 12, 238–256, IAHS Press, Wallingford – International Association of Hydrological Sciences, 2012.
15.	H. Tyralis, D. Koutsoyiannis, and S. Kozanis, An algorithm to construct Monte Carlo confidence intervals for an arbitrary function of probability distribution parameters, Computational Statistics, 28 (4), 1501–1527, doi:10.1007/s00180-012-0364-7, 2013.
16.	H. Tyralis, and D. Koutsoyiannis, A Bayesian statistical model for deriving the predictive distribution of hydroclimatic variables, Climate Dynamics, 42 (11-12), 2867–2883, doi:10.1007/s00382-013-1804-y, 2014.
17.	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.
18.	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.
19.	T. Vergou, A. Efstratiadis, and D. Dermatas, Water balance model for evaluation of landfill malfunction due to leakage, Proceedings of ISWA 2016 World Congress, Novi Sad, Ιnternational Solid Waste Association, 2016.
20.	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.
21.	E. Savvidou, A. Efstratiadis, A. D. Koussis, A. Koukouvinos, and D. Skarlatos, The curve number concept as a driver for delineating hydrological response units, Water, 10 (2), 194, doi:10.3390/w10020194, 2018.

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1.	Ireson, A., C. Makropoulos and C. Maksimovic, Water resources modelling under data scarcity: Coupling MIKE BASIN and ASM groundwater model, Water Resources Management, 20(4), 567-590, 2006.
2.	Goswami, M., and K.M. O'Connor, Comparative assessment of six automatic optimization techniques for calibration of a conceptual rainfall-runoff model, Hydrological Sciences Journal, 52(3), 432-449, 2007.
3.	#Watershed Science Centre, Research Priorities for Source Water Protection: Filling the Gap between Science and Implementation, Final Report, 333 p., Trent University, Ontario, 2007.
4.	#Burton, A., H. Fowler, C. Kilsby, and M. Marani, Investigation of intensity and spatial representations of rainfall within stochastic rainfall model, AquaTerra: Integrated modelling of the river-sediment-soil-groundwater system; advanced tools for the management of catchment areas and river basins in the context of global change, Deliverable H1.8, 57 pp., 2007.
5.	Malpica, J.A., J.G. Rejas, and M.C. Alonso, A projection pursuit algorithm for anomaly detection in hyperspectral imagery, Pattern Recognition, 41(11), 3313-3327, 2008.
6.	Burton, A., C.G. Kilsby, H.J. Fowler, P.S.P. Cowpertwait, and P.E. O'Connell, RainSim: A spatial–temporal stochastic rainfall modelling system, Environmental Modelling and Software, 23(12), 1356-1369, 2008.
7.	Kourakos, G., and A. Mantoglou, Pumping optimization of coastal aquifers based on evolutionary algorithms and surrogate modular neural network models, Advances in Water Resources, 32(4), 507-521, 2009.
8.	Wang, G.-S, J. Xia, and J.-F. Chen, A multi-parameter sensitivity and uncertainty analysis method to evaluate relative importance of parameters and model performance, Geographical Research, 29(2), 263-270, 2010.
9.	Kustamar, S., S. Sari, Y. Erni, and Sunik, ITN-2 River basin hydrology model: A distributed conceptual model for predicting flood without using calibration, Dinamika Teknik Sipil, 10(3), 233-240, 2010.
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11.	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.
12.	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.
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14.	Wang, W.-C., C.-T. Cheng, K.-W. Chau, and D.-M. Xu, Calibration of Xinanjiang model parameters using hybrid genetic algorithm based fuzzy optimal model, Journal of Hydroinformatics, 14 (3), 784-799, 2012.
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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.	#Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers using radial basis function metamodels, Proceedings of 9th World Congress EWRA “Water Resources Management in a Changing World: Challenges and Opportunities”, Istanbul, 2015.
18.	Christelis, V., and A. Mantoglou, Coastal aquifer management based on the joint use of density-dependent and sharp interface models, Water Resources Management, 30(2), 861-876, doi:10.1007/s11269-015-1195-4, 2016.
19.	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.
20.	Tigkas, D., V. Christelis, and G. Tsakiris, Comparative study of evolutionary algorithms for the automatic calibration of the Medbasin-D conceptual hydrological model, Environmental Processes, 3(3), 629–644, doi:10.1007/s40710-016-0147-1, 2016.
21.	Liao, S.-L., G. Li, Q.-Y. Sun, and Z.F. Li, Real-time correction of antecedent precipitation for the Xinanjiang model using the genetic algorithm, Journal of Hydroinformatics, 18(5), 803-815, doi:10.2166/hydro.2016.168, 2016.
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23.	Christelis, V., and A. Mantoglou, Pumping optimization of coastal aquifers assisted by adaptive metamodelling methods and radial basis functions, Water Resources Management, 30(15), 5845–5859, doi:10.1007/s11269-016-1337-3, 2016.
24.	Yu, X., C. Duffy, Y. Zhang, G. Bhatt, and Y. Shi, Virtual experiments guide calibration strategies for a real-world watershed application of coupled surface-subsurface modeling, Journal of Hydrologic Engineering, 04016043, doi:10.1061/(ASCE)HE.1943-5584.0001431, 2016.
25.	Partsinevelou, Α.-S., and L. Evrenoglou, Heavy metal contamination in surface water and impacts in public health. The case of Kifissos River, Athens, Greece, International Journal of Energy and Environment, 10, 213-218, 2016.
26.	#Christelis, V., V. Bellos, and G. Tsakiris, Employing surrogate modelling for the calibration of a 2D flood simulation model, Sustainable Hydraulics in the Era of Global Change: Proceedings of the 4th IAHR Europe Congress (Liege, Belgium, 27-29 July 2016), A. S. Erpicum, M. Pirotton, B. Dewals, P. Archambeau (editors), CRC Press, 2016.
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28.	Christelis, V., and A. Mantoglou, Physics-based and data-driven surrogate models for pumping optimization of coastal aquifers, European Water, 57, 481-488, 2017.
29.	Evrenoglou, L., A. S. Partsinevelou, and P. Nicolopoulou-Stamati, Correlation between concentrations of heavy metals in children’s scalp hair and the environment. A case study from Kifissos River in Attica, Greece, Global NEST Journal, 19, 2017.
30.	Christelis, V., R. G. Regis, and A. Mantoglou, Surrogate-based pumping optimization of coastal aquifers under limited computational budgets, Journal of Hydroinformatics, 20(1), 164-176, doi:10.2166/hydro.2017.063, 2018.
31.	Nguyen, V. T., and J. Dietrich, Modification of the SWAT model to simulate regional groundwater flow using a multi-cell aquifer, Hydrological Processes, 32(7), 939-953, doi:10.1002/hyp.11466, 2018.
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