资源环境科技发展态势分析平台

Contaminant mass discharge is a commonly applied tool to evaluate the environmental impact of contaminated sites on water resources. At large contaminated sites with heterogeneous sources, such as landfills, the number of wells available is often not sufficient, leading to a high uncertainty of mass discharge estimates. In this study, we tackle the uncertainty of the contaminant mass discharge due to low sampling densities by interpolating limited water-sample data with the support of surface direct current resistivity and induced polarization geophysical data. The method relies on finding a conceptual link between the bulk conductivity imaged from geophysics and the contaminant concentrations. We investigate the link between (1) imaged bulk and electrical water conductivity, (2) water conductivity and conservative ionic species, (3) water conductivity and redox-sensitive species, (4) water conductivity and semipersistent organic species, and (5) water conductivity and biodegradable organic compounds. The method successfully identify similarities between the distribution of the bulk conductivity and chloride and pharmaceutical compounds in a landfill leachate plume and between the bulk conductivity data and benzene and chlorinated ethenes for a contaminant plume from a former pharmaceutical factory. Contaminant concentrations were interpolated through regression kriging, using geophysical data as the dependent variable. The distribution of concentration determined with the novel method showed a lower mean relative estimation error than the traditional method of kriging only contaminant concentration data. At large sites, the method can improve contaminant mass discharge estimates, especially if surface geophysical measurements are integrated in the site investigation at an early stage.