Abstract

A feedback-based methodology has been developed for identifying the unknown pollution sources in groundwater-contaminated aquifers. The methodology consists of models within an iterative feedback system, with the capacity of feeding back real-time measurements of pollutant concentrations for the sequential optimal designs and characterization of the contaminated aquifer study area. The resulting linked-simulation optimization model considers the delineation of the contaminant plume, optimally characterizing the site in terms of pollutant sources and the optimal monitoring network leading to the remediation and/or management of the contaminated aquifer. As part of the methodology, a simulation-optimization code was developed by linking a groundwater flow and transport model with an optimization code for the purpose of identifying the unknown pollution sources. The proposed methodology addresses the source identification process with very limited information available regarding the observed contamination data for the identification of unknown pollution sources. This methodology is applied to a chlorinated hydrocarbon contaminated site for the identification of unknown pollution sources. Information regarding the sources such as the magnitude, location and the duration of contamination activity were not known for the study area considered in this work except the information regarding the likely activities that led to its contamination. Developed methodology is applied to choose the optimal source locations from the identified potential locations. Depending on the availability of observed contaminant concentration values the domain for the methodology application is divided into three different management periods. The optimal source estimates obtained at the end of the third management period suggests that only one potential source location, S2, confirms to be the source and active. The qualitative assessment of the results also performed utilizing the contamination information obtained during the field investigations. The results demonstrate the practicability of the feedback-based methodology in identifying the unknown pollution sources in groundwater.

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