Efficient Groundwater Remediation System Designs with Flow and Concentration Constraints Subject to Uncertainty

Abstract

A nested optimization problem that utilizes a multiscenario approach based upon a method known as robust optimization is employed to determine a groundwater remediation design that considers the uncertainty in the hydraulic conductivity in the flow and transport model. This optimization approach reduces a complicated multiscenario approach to a simple deterministic method for optimization. The parameter values associated with the final deterministic model represent not the true physical model, but rather a model that results in a conservatively designed remediation system that accounts for the uncertainty in the hydraulic conductivity. Both flow constraints and concentration constraints are considered in this approach, and as such the optimization problem is nonlinear in both its objective function and its constraints. A search method that combines simulated annealing and a downhill simplex algorithm is used to determine the solution to this optimization problem.