Optimal groundwater remediation under uncertainty using multi-objective optimization

A methodology is developed for optimal remediation of groundwater aquifers under hydraulic conductivity uncertainty. A multi-objective management method, based on pump-and-treat remediation technology, is proposed. The pumping rates and the well locations are the decision variables and two objectives are chosen: minimization of contaminated groundwater present in the aquifer and minimization of remediation cost. A Monte Carlo simulation method is used to cope with hydraulic conductivity uncertainty. A number of equally probable realizations of hydraulic conductivity are created and a Pareto front is obtained using a modified multi-objective Genetic Algorithm. A penalty function is utilized to maintain the algebraic sum of pumping and recharging rates equal to zero. Since Monte Carlo simulation is CPU time consuming, a method is proposed to identify the most critical realizations. A Pareto front with an assigned probability can be derived, so that the decision maker can make decisions of known reliability.