Combining multivariate statistical analysis with geographic information systems mapping: a tool for delineating groundwater contamination

Abstract

Multivariate Statistical Analysis (MSA) has successfully been coupled with geographic information system (GIS) mapping tools to delineate zones of aquifer contamination potential. While delineating contaminants is key to site remediation, it is often compromised by a poor understanding of hydrogeologic conditions, and by uncertainties in contaminant observations. MSA provides improved estimates of contamination potential by augmenting observed contaminant concentrations with auxiliary information from other water-quality parameters. GIS is useful for organizing and managing water-quality information by visually communicating large amounts of information. The proposed method first establishes appropriate areal extents, GIS coverages, and scales for displaying groundwater contamination concentrations of tritium and the volatile organic contaminants trichloroethylene (TCE) and tetrachloroethylene (PCE) at the Savannah River Site, South Carolina, USA. Principal components analysis is used to group variables that are most indicative of contamination potential. Tritium contamination potential is best represented as the combination of tritium with the cations Al, Mg, Na and total dissolved solids, while PCE contamination potential is predicted using PCE and Cl. Maps of contamination potentials for 1993–1995 geochemical data compare favorably with measured contaminant concentrations during 1999. Cluster analysis of water-quality data groups geochemical and contaminant concentrations into zones of homogeneous behavior.