Huang*, P., & Y.Chiu. (2018). A simulation-optimization model for seawater intrusion management at Pingtung Coastal Area, Taiwan. Water, 10, 251.
Abstract: The coastal regions of Pingtung Plain in southern Taiwan rely on groundwater as their main source of fresh water for aquaculture, agriculture, domestic, and industrial sectors. The availability of fresh groundwater is threatened by unsustainable groundwater extraction and the over-pumpage leads to the serious problem of seawater intrusion. It is desired to find appropriate management strategies to control groundwater salinity and mitigate seawater intrusion. In this study, a simulation–optimization model has been presented to solve the problem of seawater intrusion along the coastal aquifers in Pingtung Plain and the objective is using injection well barriers and minimizing the total injection rate based on the pre-determined locations of injection barriers. The SEAWAT code is used to simulate the process of seawater intrusion and the surrogate model of artificial neural networks (ANNs) is used to approximate the seawater intrusion (SWI) numerical model to increase the computational efficiency during the optimization process. The heuristic optimization scheme of differential evolution (DE) algorithm is selected to identify the global optimal management solution. Two different management scenarios, one is the injection barriers located along the coast and the other is the injection barrier located at the inland, are considered and the optimized results show that the deployment of injection barriers at the inland is more effective to reduce total dissolved solids (TDS) concentrations and mitigate seawater intrusion than that along the coast. The computational time can be reduced by more than 98% when using ANNs to replace the numerical model and the DE algorithm has been confirmed as a robust optimization scheme to solve groundwater management problems. The proposed framework can identify the most reliable management strategies and provide a reference tool for decision making with regard to seawater intrusion remediation.
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Naranjo-Fernández, N., Guardiola-Albert, C., & Montero-González, E. (2019). Applying 3D geostatistical simulation to improve the groundwater management modelling of sedimentary aquifers: The case of Doñana (Southwest Spain). Water, 11, 39.
Abstract: Mathematical groundwater modelling with homogeneous permeability zones has been used for decades to manage water resources in the Almonte-Marismas aquifer (southwest Spain). This is a highly heterogeneous detrital aquifer which supports valuable ecological systems in the Doñana National Park. The present study demonstrates that it is possible to better characterize this heterogeneity by numerical discretization of the geophysical and lithological data available. We identified six hydrofacies whose spatial characteristics were quantified with indicator variogram modelling. Sequential Indicator Simulation then made it possible to construct a 3D geological model. Finally, this detailed model was included in MODFLOW through the Model Muse interface. This final process is still a challenge due to the difficulty of downscaling to a handy numerical modelling scale. New piezometric surfaces and water budgets were obtained. The classical model with zones and the model with 3D simulation were compared to confirm that, for management purposes, the effort of improving the geological heterogeneities is worthwhile. This paper also highlights the relevance of including subsurface heterogeneities within a real groundwater management model in the present global change scenario.
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Eliades, M., Bruggeman, A., Djuma, H., Christofi, C., & Kuells, C. (2022). Quantifying evapotranspiration and drainage losses in a semi-arid nectarine (Prunus persica var. nucipersica) field with a dynamic crop coefficient (Kc) derived from leaf area index measurements. Water, 14(5), 734.
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Mehraein, M., Mohanavelu, A., Naganna, S. R., Kulls, C., & Kisi, O. (2022). Monthly streamflow prediction by metaheuristic regression approaches considering satellite precipitation data. Water, 14(22), 3636.
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Herckenrath*, D., Langevin, C. D., & Doherty, J. (2011). Predictive uncertainty analysis of a saltwater intrusion modelusing null‐space Monte Carlo. Water Resour. Res., 47, 05504.
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