A method for locating wells in a groundwater monitoring network under conditions of uncertainty

TLDR

The paper proposes a method to locate wells in a groundwater monitoring network under uncertainty. The method couples a contaminant‑transport simulation with a facility‑location model, using Monte Carlo to propagate parameter uncertainty into plume concentration distributions and selecting a fixed number of wells that maximize detection of realizations above a threshold. The resulting well network maximizes detection probability, and despite computational intensity, the approach proves tractable for practical problems.

Abstract

A method is presented for locating wells in a monitoring network under conditions of uncertainty. The method couples the use of a simulation model of contaminant transport and a facility location model. The Monte Carlo technique is used with the simulation model to translate uncertainty in the simulation model parameters into uncertainty in the contaminant concentration distribution. The simulation model determines which well locations would detect a given realization of a contaminant plume with a concentration above a specified limit. The facility location model is then used to select a fixed number of well locations so that a maximum number of such plume realizations are detected. The selected well network maximizes the probability of detection. The method is applied to an example problem. Although the technique is computationally intensive, the results indicate that practical problems are tractable.