Abstract:
A real-life problem involving pumping of groundwater from a series of ninety existing wells along river Yamuna floodplain, northwest of Delhi (India) underlain with geologically occurring saline water is examined within a conceptual management model. Unplanned pumping often leads to upconing of saline water. Therefore it is required to determine optimal rates and their locations from an existing group of pre-selected candidate wells that minimize total salinity concentration in space and time. 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 optimal pumping schedule. The results of the operational model suggests that the skimming wells must be operated from optimal locations such that they are staggered in space and time to obtain least saline water.
