INCORPORATING SPATIAL VARIABILITY INTO GIS TO ESTIMATE NITRATE LEACHING AT THE AQUIFER SCALE

We evaluated the effect of spatial variability of selected intrinsic s oil properties and extrinsic management practices on the groundwater q uality in the 330-ha recharge area of a high yield well site in Rhode Island. The analyses were performed at different support scales, rangi ng from point level to a support level equal to the entire recharge ar ea. We used a mass balance model that relates leaching from the vadose zone to long-term estimates of NO3-N concentration at the well. We us ed a GIS database and stratified sampling for both soil characterizati on and assessment of spatial variability of NO3 leaching. The LEACHA/N rootzone model was used in conjunction with Monte Carlo simulation to generate cumulative distribution functions (CDFs) for leaching from d ifferent land strata (given by combinations of soil type and land use) . To simulate the spatial variability of properties that served as inp uts to the root zone model, we used CDFs of spatial distributions of s oil properties and CDFs of the spatial variability of fertilizer appli cation rates within a field. These strata scale CDFs were then combine d to generate CDFs of the NO3-N concentrations at the well, i.e., at a recharge area support scale. Although considerable variability was fo und at a point support scale, the analyses generated a markedly lower variability at the recharge area support scale. The results suggest th at GIS data bases generated at scales available to resource managers ( i.e., 1:12 000 and 1:24 000) may be well suited to manage the water qu ality of large production scale wells.