Using Multivariate Statistical Analysis and GIS to Determine Groundwater ContaminationCombining MSA & GISMethods, Data, and TestResultscConclusionsUsing Multivariate Statistical Analysis and GIS to Determine Groundwater Contamination•Combining multivariate statistical analysis with geographic information systems mapping: a tool for delineating groundwater contamination•Paper by Mathes S. E., T. C. Rasmussen. 2006. Combining multivariate statistical analysis with geographic information systems mapping: a tool for delineating groundwater contamination. Hydrogeology Journal, 14(8): 1493-1507.•Presented by Chelsea Wrenn Lindley, Athletic Training, GEOG 370, February 25, 2008Combining MSA & GIS•Problem: Properly delineating groundwater contamination zones is extremely important for environmental and health purposes. However, there are often many uncertainties in contaminant observations. •Hypothesis: Combining Multivariate Statistical Analysis (MSA) and geographic information systems (GIS) in delineating groundwater contamination zones will improve estimates of contamination potentials.Methods, Data, and Test•Site: two areas of the Savannah River Site (the administration and manufacturing area and the general separations area)•Datasets were collected and compared, establishing size, scale, and aerial extent of contamination for different areas at SRS. Based on these characteristics, patterns were found that allowed for grouping of observation sites by geochemical zone (cluster analysis). •Inverse distance weighting was used to estimate values of factor scores for components correlated with the contaminant variables, tritium and PCE. These factor scores were symbolized using graduated color scales, which were used in mapping the data.Results•Cluster analysis divided wells into five different groups based on water-quality measurements, suggesting there were five distinct groundwater quality zones in both areas at SRS. •By using GIS, groundwater concentration levels of tritium and TCE (the two factors with the most reliably measured variables) were able to be mapped, showing the approximate aerial extent of contamination at SRS.cConclusions•There is a stronger likelihood of contamination near seepage basins and other waste disposal sites. •PCE contamination was found to be more likely in the administration and manufacturing area at SRS.•In the general separations area at SRS, tritium contamination was found to have the highest potential for existence. •Criticisms: Wells were not established in zones that weren’t already known for contamination at SRS; they only used the wells that had already been
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