Optimizing groundwater long‐term monitoring networks using Delaunay triangulation spatial analysis techniques

Abstract

AbstractGroundwater long‐term monitoring (LTM) is a costly activity required at most subsurface remediation sites. Many existing LTM networks need to be optimized to reflect changes in site conditions and to increase their effectiveness in defining the plume. A spatial analysis method using Delaunay triangulation techniques was developed to eliminate redundant monitoring points and to locate new wells where additional data are needed. This method uses Delaunay triangulation of the monitoring network for site discretization and assesses the concentration estimation error at each monitoring location to judge its relative contribution to the spatial plume characterization. Locations where the concentration estimation error is small are considered redundant and become candidates for elimination. New monitoring locations are identified where the projected concentration estimation errors are high. Tests comparing the Delaunay method to a fate and transport analytical model illustrated the attributes and effectiveness of the method. Application to a benzene plume site demonstrated that results from Delaunay triangulation agree well with geostatistical approaches. Although the method is relatively less accurate, and lacks the resolution obtained with the geostatistical approach, it is computationally efficient and simple to implement by non‐statisticians. Copyright © 2005 John Wiley & Sons, Ltd.