No abstract

The groundwater planning problems are often multiobjective. Due to conflicting objectives and non-linearity of the variables involved, several feasible solutions may have to be evolved rather than single optimal solution. In this study, the simulation model built on an Analytic Element Method (AEM) and the optimization model built on a Non-dominated Sorting Genetic Algorithm (NSGA-II) were coupled and applied to study a part of the Dore river catchment, France. The maximization of discharge, the minimization of pumping cost and the minimization of piping cost are the three objectives considered. 2105 non-dominated groundwater planning strategies were generated. K-Means cluster analysis was employed to classify the strategies, and clustering was performed for 3 to 25 clusters. A cluster validation technique, namely Davies–Bouldin (DB) index, was employed to find the optimal number of clusters of groundwater strategies which were found to be 20. Multicriterion Decision-Making (MCDM) techniques, namely VIKOR and TOPSIS, were developed to rank the 20 representative strategies. Both these decision-making techniques preferred representative strategy A5 (piping cost, pumping cost and discharge respectively of 880,000 Euro, 679,000 Euro and 1,263.1 m3/s). The sensitivity analysis of parameter v in VIKOR suggested that there were changes in ranking pattern for various values of v. However, the first position remained unchanged.

A novel methodology for suitable site selection for groundwater development based on river capture, pumping cost and groundwater potential has been proposed for better groundwater utilization. River capture and cost map have been generated from a calibrated groundwater model, simulated with forecasted hydrological time series data. The groundwater potential has been calculated with weighted overlay analysis. These three variables have been used to classify the model domain into five zones of groundwater development by K-Means clustering. The area with lower river capture, low cost of pumping and high groundwater potential is found to be the best location for groundwater extraction. The methodology has been applied to the lower Ain river basin, France.

We propose a novel methodology for the groundwater potential zonation with the integration of capture fraction in a multi-objective problem. Each hydrogeological feature such as lakes, ponds and river stretches are influenced by the groundwater extraction through pumping wells and the specific distance of the pumping wells from these features. Analysis of the capture is crucial in managing the quantity aspect of surface water & groundwater resources, as properly developed capture maps could help in taking safety measures for present and future water usage in the area. This paper discusses the methodology for the identification of groundwater potential areas based on capture maps and their application in water resources management. The optimum location of pumping wells has been identified based on the capture and pumping cost. The methodology has been applied on the lower Ain River basin, France. Using the prediction capabilities of the groundwater model, capture map for the river inflow, river outflow, storage-in, storage-out and drawdown were developed up to the year 2060 and the results were interpreted. Time series forecast algorithms were applied in predicting the water levels and flow into the river. Results show that leakage in was more dominated in the region considered in comparison to leakage out.

A novel methodology for suitable site selection for groundwater development based on river capture, pumping cost, and groundwater potential has been proposed for better groundwater utilisation. River capture and cost map have been generated from a calibrated groundwater model, simulated with forecasted hydrological time series data. The groundwater potential has been calculated with weighted overlay analysis. These three variables have been used to classify the model domain into five zones of groundwater development by K-Means clustering. The area with lower river capture, low cost of pumping, and high groundwater potential is found to be the best location for groundwater extraction. The methodology has been applied to the lower Ain River basin, in France.