Monitoring network design to provide initial detection of groundwater contamination

TLDR: In this article, the authors present a method that incorporates system uncertainty in monitoring network design and provides network alternatives that are noninferior with respect to several objectives, such as minimizing the number of monitoring wells, maximizing the probability of detecting a contaminant leak, and minimizing the expected area of contamination at the time of detection.

Abstract: The design of a monitoring network to provide initial detection of groundwater contamination at a waste disposal facility is complicated by uncertainty in both the characterization of the subsurface and the nature of the contaminant source. In addition, monitoring network design requires the resolution of multiple conflicting objectives. A method is presented that incorporates system uncertainty in monitoring network design and provides network alternatives that are noninferior with respect to several objectives. Monte Carlo simulation of groundwater contaminant transport is the method of uncertainty analysis. The random inputs to the simulation are the hydraulic conductivity field and the contaminant source location. The design objectives considered are (1) minimize the number of monitoring wells, (2) maximize the probability of detecting a contaminant leak, and (3) minimize the expected area of contamination at the time of detection. The network design problem is formulated as a multiobjective, integer programming problem and is solved using simulated annealing. An application of the method illustrates the configurations of noninferior network solutions and the trade-offs between objectives. The probability of detection can be increased either by using more monitoring wells or by locating the wells farther from the source. The latter case results in an increase in the average area of the detected contaminant plumes at the time of initial detection. If monitoring is carried out very close to the contaminant source to reduce the expected area of a detected plume, a large number of wells are required to provide a high probability of detection. A sensitivity analysis showed that the predicted performance of a given number of wells decreases significantly as the heterogeneity of the porous medium increases. In addition, a poor estimate of hydraulic conductivity was shown to result in optimistic estimates of network performance. In general, the trade-offs between monitoring objectives are an important factor in network design unless the cost (as expressed by the number of monitoring wells) is of limited concern.