Regresar

A new method for groundwater plume detection under uncertainty

Abstract:

Groundwater contamination plume characterization is a very hard task to perform and usually requires a large number of sampling sites. In this article a method for optimizing a monitoring network for plume detection and delimitation is proposed. It is assumed that an extensive sampling campaign has already been conducted and that only a few sampling sites should be included in the optimal monitoring network. The objective function incorporates the prior knowledge about concentration variability in the form of its density function, and also a measure of spatial coverage (space-filling method) in order to best distribute the stations over the field. The method was applied to a synthetic case study with 160 sampling locations, and a final optimal monitoring network with 40 stations was obtained. A simulated annealing optimization algorithm was used to solve this very difficult combinatorial problem, which has more than 8.6 × 1037 possible solutions. Copyright © 2007 IAHS Press.