DEVELOPMENT OF A GIS-BASED MODEL FOR EXTRAPOLATING MESOSCALE GROUNDWATER RECHARGE ESTIMATES USING INTEGRATED GEOSPATIAL DATA SETS

Abstract

A geographic information systems (GIS)-based model was used to derive spatially explicit estimates of recharge using the elevation-dependent chloride mass-balance (EDCMB) approach in a 14-basin area in southwestern Nevada, USA. For each of the 14 basins, a non-linear regression equation was developed relating chloride enrichment to the elevation of spring watersheds. The ratio of chloride enrichment as a function of elevation was used in a GIS framework to transform continuous precipitation data to recharge. Spatial masks that represented two definitions of the lower limits of recharge-one definition based on alluvium/non-alluvium boundaries, the other based on both alluvium/non-alluvium boundaries and an elevation threshold - were applied to each basin. Resultant recharge estimates were then summed for each basin. When compared to summaries of previous recharge estimates for the study area, the EDCMB approach produced results that were within 14 and 3% of two studies, but were significantly greater (31%) than a third. GIS proved to be a very effective tool for combining large spatial data with widely different resolutions into an integrated data set, and also proved to be an efficient mechanism for implementing robust statistical models to estimate recharge.