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Incorporating Spatial Variability into GIS to Estimate Nitrate Leaching at the Aquifer Scale

Department of Natural Resources Science, 210B Woodward Hall, Univ. of Rhode Island, Kingston, RI 02881.

^* Corresponding author (joe{at}edcserv.edc.uri.edu).

ABSTRACT

We evaluated the effect of spatial variability of selected intrinsic soil properties and extrinsic management practices on the groundwater quality in the 330-ha recharge area of a high yield well site in Rhode Island. The analyses were performed at different support scales, ranging from point level to a support level equal to the entire recharge area. 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 used a GIS database and stratified sampling for both soil characterization 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 different land strata (given by combinations of soil type and land use). To simulate the spatial variability of properties that served as inputs to the root zone model, we used CDFs of spatial distributions of soil properties and CDFs of the spatial variability of fertilizer application rates within a field. These strata scale CDFs were then combined to generate CDFs of the NO₃-N concentrations at the well, i.e., at a recharge area support scale. Although considerable variability was found at a point support scale, the analyses generated a markedly lower variability at the recharge area support scale. The results suggest that 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 quality of large production scale wells.

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