Groundwater–Surface Water Management With Stochastic Surface Water Supplies: A Simulation Optimization Approach

Abstract

A new simulation optimization model for groundwater–surface water management identifies efficient strategies for meeting water demand and controlling a regional water quality problem, while accounting for varying availability of surface water supplies. Optimal values of model variables are computed for ranges of surface water availability. Expected groundwater levels are computed using a response function approach, which incorporates a probability for each hydraulic stress. Three objective functions are considered: (1) minimize need for supplemental water, (2) minimize imposed water use reductions, and (3) minimize changes from current pumping patterns. The model imposes constraints on expected groundwater levels, expected hydraulic gradients (surrogates for controlling contaminant transport), capacities of pipeline and recharge facilities, and water demand requirements. Capacity and demand constraints must be met every year for all possible surface water conditions. Application to the Santa Clara–Calleguas Basin in southern California indicates that a large quantity of supplemental water or significant pumpage reductions, particularly in the lower aquifer, may be required to control seawater intrusion with current facilities. Supplemental water would be delivered directly to users through pipelines and artificially recharged. Results also indicate that the current artificial‐recharge program has been valuable and that construction of new artificial‐recharge facilities might be beneficial. It should be noted that local agencies are currently developing several potential sources of supplemental water. Monte Carlo simulations yield estimates of the reliability of gradient constraints in controlling advective transport and the likelihood that water level constraints will be violated.