Application of a genetic algorithm to groundwater pollution source identification

K Han, R Zuo, P Ni, Z Xue, D Xu, J Wang, D Zhang - Journal of Hydrology, 2020 - Elsevier
K Han, R Zuo, P Ni, Z Xue, D Xu, J Wang, D Zhang
Journal of Hydrology, 2020Elsevier
The accurate identification of groundwater pollution sources is the key to site remediation
and management, which directly relates to the cost and effect of remediation during later
periods. Studying the identification of some small-area site pollution sources by using a
small amount of groundwater monitoring data is difficult and is currently a hot topic in the
field of groundwater management. In this study, a method combining the Advection-
Dispersion Equation (ADE) of contaminants in groundwater with Genetic Algorithm (GA) was …
Abstract
The accurate identification of groundwater pollution sources is the key to site remediation and management, which directly relates to the cost and effect of remediation during later periods. Studying the identification of some small-area site pollution sources by using a small amount of groundwater monitoring data is difficult and is currently a hot topic in the field of groundwater management. In this study, a method combining the Advection-Dispersion Equation (ADE) of contaminants in groundwater with Genetic Algorithm (GA) was proposed to identify groundwater pollution sources, that is, the location of the pollution source, the time of pollution release, and the intensity of pollution release. A sandbox experiment for the migration and transformation of deterministic petroleum hydrocarbons in groundwater is designed to verify the method. The results show that the method code program has basically the same identification parameters as the deterministic experimental pollution source parameters. The ADE-GA method was applied to an actual site polluted by a gas station in Beijing, China. The parameters of the pollution source obtained from the detailed site investigation are basically consistent with the calculated values. Therefore, the source code established in this work is a reliable tool for identifying the parameters of groundwater pollution sources in small areas.
Elsevier
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