Optimal remediation policy selection under general conditions

A new simulation-optimization model has been developed for the optimal design of ground-water remediation systems under a variety of field conditions. The model couples genetic algorithm (GA), a global search technique inspired by biological evolution, with MODFLOW and MT3D, two commonly used ground-water flow and solute transport codes. The model allows for multiple management periods in which optimal pumping/injection rates vary with time to reflect the changes in the flow and transport conditions during the remediation process. The objective function of the model incorporates multiple cost terms including the drilling cost, the installation cost, and the costs to extract and treat the contaminated ground water. The simulation-optimization model is first applied to a typical two-dimensional pump-and-treat example with one and three management periods to demonstrate the effectiveness and robustness of the new model. The model is then applied to a large-scale three-dimensional field problem to determine the minimum pumping needed to contain an existing contaminant plume. The optimal solution as determined in this study is compared with a previous solution based on trial-and-error selection.