A method for the optimal location of monitoring wells for detection of groundwater contamination in three-dimensional heterogenous aquifers

We present an optimization method for the design of monitoring well networks to detect initial groundwater contamination in three-dimensional heterogenous aquifers. A Monte Carlo-based approach generates a large number of equally likely realizations of a random hydraulic conductivity field and a contaminant leak location. A finite difference groundwater flow model and a particle-tracking model generate a contaminant plume for each realization. Information from the flow and transport simulations is passed to an optimization model based upon a facility location analogy. The optimization model is a large integer programming problem which is solved approximately by the method of simulated annealing to determine optimal trade-off curves among the following three conflicting objectives: (1) maximum detection probability, (2) minimum cost (i.e., number of monitoring wells), and (3) minimum volume of contaminated groundwater at the time of detection. The method is applied to a unit-scaled hypothetical three-dimensional site to determine the sensitivity of the trade-off curves to various model parameters. Application to an existing landfill site reveals that the existing well network is suboptimal with respect to the considered objectives.