A Stochastic Optimization Approach in the Design of an Aquifer Remediation under Hydrogeologic Uncertainty

Abstract

A stochastic optimization approach is presented for the remediation design of a contaminated aquifer with limited hydrogeologic information. Stochastic simulation using the Monte Carlo technique, produces a series of equally probable realisations of the spatially varying random hydraulic conductivity field. The stochastic flow and transport simulation model is coupled, using the response matrix approach, with a nonlinear optimization algorithm. The whole process is integrated into an algorithm which is effectively applied in the case study of the Kalamaria aquifer, Chalkidiki, Greece. The stochastic optimization procedure is followed by a reliability analysis, giving useful information to the decision makers concerning the effectiveness of the optimal results.