Assessing groundwater vulnerability to agrichemical contamination in the Midwest

Agrichemicals (herbicides and nitrate) are significant sources of diffuse p ollution to groundwater. Indirect methods are needed to assess the potentia l for groundwater contamination by diffuse sources because groundwater moni toring is too costly to adequately define the geographic extent of contamin ation at a regional or national scale. This paper presents examples of the application of statistical, overlay and index, and process-based modeling m ethods for groundwater vulnerability assessments to a variety of data from the Midwest U.S. The principles for vulnerability assessment include both i ntrinsic (pedologic, climatologic, and hydrogeologic factors) and specific (contaminant and other anthropogenic factors) vulnerability of a location. Statistical methods use the frequency of contaminant occurrence, contaminan t concentration, or contamination probability as a response variable. Stati stical assessments are useful for defining the relations among explanatory and response variables whether they define intrinsic or specific vulnerabil ity. Multivariate statistical analyses are useful for ranking variables cri tical to estimating water quality responses of interest. Overlay and index methods involve intersecting maps of intrinsic and specific vulnerability p roperties and indexing the variables by applying appropriate weights. Deter ministic models use process-based equations to simulate contaminant transpo rt and are distinguished from the other methods in their potential to predi ct contaminant transport in both space and time. An example of a one-dimens ional leaching model linked to a geographic information system (GIS) to def ine a regional metamodel for contamination in the Midwest is included. (C) 1999 IAWQ Published by Elsevier Science Ltd. All rights reserved.