A multicell karstic aquifer model with alternative flow equations

E. Rozos, and D. Koutsoyiannis, A multicell karstic aquifer model with alternative flow equations, Journal of Hydrology, 325 (1-4), 340–355, 2006.



A multicell groundwater model was constructed to investigate the potential improvement in the modelling of karstic aquifers by using a mixed equation suitable for both the free surface and pressure flow conditions in karstic conduits. To estimate the model parameters the shuffled complex evolution (SCE) optimisation method was used. This ensured a fast and objective model calibration. The model was applied to two real-world karstic aquifers and it became clear that in case of absence of water level measurements, the use of the mixed equation did not improved the performance. In cases where both spring discharge and water level measurements were available, the use of the mixed equation proved to be advantageous in reproducing the features of the observed time series especially of the water level.

Full text is only available to the NTUA network due to copyright restrictions

PDF Additional material:

See also: http://dx.doi.org/10.1016/j.jhydrol.2005.10.021

Related works:

Our works that reference this work:

1. A. Efstratiadis, I. Nalbantis, A. Koukouvinos, E. Rozos, and D. Koutsoyiannis, HYDROGEIOS: A semi-distributed GIS-based hydrological model for modified river basins, Hydrology and Earth System Sciences, 12, 989–1006, doi:10.5194/hess-12-989-2008, 2008.
2. 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.
3. E. Rozos, and D. Koutsoyiannis, Error analysis of a multi-cell groundwater model, Journal of Hydrology, 392 (1-2), 22–30, 2010.
4. 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.
5. 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.
6. 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.
7. 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.

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

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

1. Fleury, P., V. Plagnes and M. Bakalowicz, Modelling of the functioning of karst aquifers with a reservoir model: Application to Fontaine de Vaucluse (South of France), Journal of Hydrology, 345(1-2), 38-49, 2007.
2. Prelovsek, M., J. Turk and F. Gabrovsek, Hydrodynamic aspect of caves, International Journal of Speleology, 37(1), 11-26, 2008.
3. Terwey, W.D., and M.T. Montgomery, Secondary eyewall formation in two idealized, full-physics modeled hurricanes, Journal of Geophysical Research-Atmospheres, 113(D12), D12112, 2008.
4. Fleury, P., B. Ladouche, Y. Conroux, H. Jourde and N. Dörfliger, Modelling the hydrologic functions of a karst aquifer under active water management -- The Lez spring, Journal of Hydrology, 365 (3-4), 235-243, 2009.
5. Orban, P., S. Brouyère, J. Batlle-Aguilar, J. Couturier, P. Goderniaux, M. Leroy, P. Maloszewski and A. Dassargues, Regional transport modelling for nitrate trend assessment and forecasting in a chalk aquifer, Journal of Contaminant Hydrology, 118 (1-2), 79-93, doi: 10.1016/j.jconhyd.2010.08.008, 2010.
6. Moussu, F., L. Oudin, V. Plagnes, A. Mangin, and H. Bendjoudi, A multi-objective calibration framework for rainfall-discharge models applied to karst systems, Journal of Hydrology, 400(3-4), 364-376, 2011.
7. Dong, G.-M., L.-C. Shu, J. Tian and Y.-F. Ji, Numerical model of groundwater flow in karst underground river system, southwestern China, Jilin Daxue Xuebao (Diqiu Kexue Ban)/Journal of Jilin University (Earth Science Edition), 41 (4), 1136-1143+1156, 2011.
8. Nikolaidis, N. P., F. Bouraoui and G. Bidoglio, Hydrologic and geochemical modeling of a karstic Mediterranean watershed, Hydrol. Earth Syst. Sci. Discuss., 9, 1-27, doi: 10.5194/hessd-9-1-2012, 2012.
9. Nikolaidis, N. P., F. Bouraoui and G. Bidoglio, Hydrologic and geochemical modeling of a karstic Mediterranean watershed, Journal of Hydrology, 477, 129-138, 2013.
10. Loper, D. E., An analytic benchmark test for karst-aquifer flow, Geophysical & Astrophysical Fluid Dynamics, 10.1080/03091929.2012.758720, 2013.
11. César, E., S. Wildemeersch, P. Orban, S. Carrière, S. Brouyère and A. Dassargues, Simulation of spatial and temporal trends in nitrate concentrations at the regional scale in the Upper Dyle basin, Belgium, Hydrogeology Journal, 10.1007/s10040-014-1124-2, 2014.
12. Steiakakis, E., D. Vavadakis and M. Kritsotakis, Simulation of springs discharge from a karstic aquifer (Crete, Greece), using limited data, Environmental Earth Sciences, 10.1007/s12665-015-4496-2, 2015.
13. 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, doi:10.1080/02626667.2016.1140174, 2016.

Tagged under: Groundwater, Hydrological models