Abstract
This report examines the problem involving the pumping of groundwater from a group of 90 existing wells along the banks of the Yamuna River, northwest of Delhi (India), underlain with geologically occurring saline water. It is known that unregulated pumping will lead to upconing of saline water and therefore it is necessary to determine optimal rates and associated well locations (from an existing group of candidate wells that supply drinking water to the city of Delhi) that will minimize the total salinity. The nonlinear, non-convex problem is solved by embedding the calibrated groundwater model within a simulation-optimisation (S/O) framework. Optimisation is accomplished by using simulated annealing (SA), a search algorithm. The computational burden is primarily managed by replacing the numerical model with a surrogate simulator-artificial neural network (ANN). The model is applied to the real system to determine the optimal pumping schedule. The results of the operational model suggest that the skimming wells must be operated from optimal locations such that they are staggered in space and time to obtain the least saline water.
Résumé
Le présent article examine, par un modèle conceptuel de gestion, un problème impliquant des pompages par un groupe de 90 puits existant le long des berges de la rivière Yamuna, au nord-est de Delhi (Inde), surmontant des eaux salées d’origine géologique. Des pompages non contrôlés vont occasionner la remontée des eaux salées. C’est pourquoi il est nécessaire de déterminer les débits optimaux ainsi que les implantations des puits (parmi un groupe de puits proposés alimentant en eau potable la ville de Delhi) qui permettront de minimiser la salinité totale. Le problème non-linéaire et non-convexe est résolu en incorporant le modèle calibré dans un schéma simulation / optimisation (S/O). L’optimisation utilise le recuit simulé, un algorithme de recherche. La charge informatique est tout d’abord gérée en remplaçant le modèle numérique par un simulateur de substitution-réseau neuronal artificiel (ANN). Le modèle est appliqué au système réel afin de déterminer le plan de pompage optimal. Les résultats du modèle opérationnel suggèrent que les puits d’écrémage doivent fonctionner sur des implantations optimales, étalées dans l’espace et dans le temps afin d’obtenir moins d’eau salée.
Resumen
Se ha examinado un problema referente al bombeo de agua subterránea mediante un grupo de 90 pozos existentes a lo largo de la orilla del río Yamuna, al noroeste de Delhi (India), situados sobre aguas salinas de origen geológico. Bombeos irregulares producirán el ascenso de aguas salinas. Por ello, es necesario determinar los bombeos óptimos y las localización de los pozos para minimizar la salinidad total (a partir de un grupo de pozos existentes que suministran agua de abastecimiento a la ciudad de Delhi). El problema no linear, no convexo se resuelve incluyendo el modelo calibrado de aguas subterráneas dentro de un marco de simulación-optimización (S/O). Para la optimización se ha utilizado el método de recocido simulado. La carga computacional se gestiona primeramente reemplazando el modelo numérico con un simulador sustituto-red neural artificial (ANN). El modelo se aplica al sistema real para determinar el plan óptimo de bombeo. Los resultados del modelo operativo sugieren que los pozos superficiales deben ser explotados en localizaciones óptimas tales que se escalonen en el espacio y en el tiempo para obtener menos agua salina.
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Acknowledgements
The authors acknowledge the leadership of Dr. K.D. Sharma, Director, National Institute of Hydrology, Roorkee and Dr. Saleem Romani, Chairman, Central Groundwater Board, New Delhi, for conceiving the problem and providing financial and logistical support to undertake this study. The authors are grateful to the anonymous peer reviewers for their useful comments, which significantly improved the report. The authors are also very grateful to Sue Duncan, International Association of Hydrogeologists, for careful technical editing of this manuscript.
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Rao, S.V.N., Kumar, S., Shekhar, S. et al. Optimal pumping from skimming wells from the Yamuna River flood plain in north India. Hydrogeol J 15, 1157–1167 (2007). https://doi.org/10.1007/s10040-007-0173-1
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DOI: https://doi.org/10.1007/s10040-007-0173-1