Study on the Fine Characterization of Spatial Distribution and Predictive Modeling of Remediation of Site Pollution

The present study focuses on a site contaminated with halogenated hydrocarbons, utilizing a detailed inventory of contamination data to achieve the precise characterization of groundwater pollution. Employing MOFLOW-2000 software, a groundwater flow model was established for the study area. In conjunction with MT3DMS, a predictive model was constructed to simulate and forecast the spatiotemporal distribution of contaminant migration and attenuation following site remediation. The simulation area was delineated based on geographical features, with the vertical simulation range of strata also determined. To establish a hydrogeological conceptual model for the target remediation site, comprehensive hydrogeological data were collected, encompassing geological structures, hydrological parameters, and rainfall information. Model calibration was based on the six layers of low-permeability aquifer intervals revealed by geological exploration wells MW1–5, as well as the distribution of groundwater-level contours and rainfall data. Based on data from September 2010, an initial three-dimensional model of tetrachloroethylene (PCE) distribution was generated. Subsequently, a solute transport model for PCE was established, incorporating various enhanced reductive dechlorination (ERD) remediation strategies applied at different times and locations. Calibration against actual monitoring data revealed the presence of unmonitored dense non-aqueous phase liquids (DNAPLs) at the site, contributing to the continuous release and elevation of PCE concentrations. By accounting for DNAPL release, the calibrated transport and attenuation model closely matched observed concentration decay patterns, effectively capturing the actual dynamics of contaminant transport and attenuation within the groundwater system. The modeling approach proposed in this study provides important support for contamination remediation and attenuation at the current site, and it is also applicable to simulating and predicting pollution scenarios at similar sites.