Abstract
Contamination created by dense non-aqueous phase liquids (DNAPLs) is a serious threat to the quality of the groundwater supply; thus, delineating and removing the DNAPL source is an essential step in a successful remediation strategy. The goal of this work is to create an optimal search strategy that identifies a DNAPL source using the least number of water quality samples.
The search strategy includes a Monte Carlo stochastic groundwater flow and transport model, a predetermined set of potential source locations and a Kalman filter that updates the simulated contaminant concentration field using contaminant concentration data. The updated plume is compared to the concentration fields that emanate from each individual potential source using a technique rooted in fuzzy set theory. The comparison provides weights that reflect the degree of truth regarding the location of the source at the selected potential source locations. The steps described above are repeated until the weights stabilize and the optimal source location is determined.
This paper presents the various mathematical tools employed in the search algorithm and their modifications for incorporation into the proposed methodology. The algorithm’s effectiveness in identifying a DNAPL source is shown using a synthetic example.