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United States Department of Agriculture

Agricultural Research Service

Research Project: IMPROVING WATER PRODUCTIVITY AND NEW WATER MANAGEMENT TECHNOLOGIES TO SUSTAIN RURAL ECONOMIES

Location: Soil and Water Management Research

Title: Scale effects of STATSGO and SSURGO databases on flow and water quality predictions

Authors
item Gowda, Prasanna
item Mulla, David -
item Nangia, Vinay -
item Ale, Srinivasulu -

Submitted to: Journal of Water Resource and Protection
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 10, 2013
Publication Date: March 1, 2013
Citation: Gowda, P., Mulla, D.J., Nangia, V., Ale, S. 2013. Scale effects of STATSGO and SSURGO databases on flow and water quality predictions. Journal of Water Resource and Protection. 5:266-274.

Interpretive Summary: Nonpoint source pollution is a widespread problem in North America. Concerns typically include sediment, nitrogen and phosphorus, as well as herbicides and pathogen loadings from cropland. Soil information is one of the crucial inputs needed to assess impacts of existing and alternative agricultural management practices on water quality. So far, little is known about the effects of spatial scale on water quality when soil input is derived at different spatial resolution. In this study, a water quality model was calibrated and used to understand the scale effect of soil databases on prediction of flow and nutrient losses. Results indicated that prediction of magnitude of nutrient losses is affected by the selection of the databases for deriving soil input.

Technical Abstract: Soil information is one of the crucial inputs needed to assess the impacts of existing and alternative agricultural management practices on water quality. Therefore, it is important to understand the effects of spatial scale at which soil databases are developed on water quality evaluations. In the United States, STATSGO (STATe Soils GeOgraphic) and SSURGO (Soil SURvey GeOgraphic) are the most commonly available soil databases. The purpose of this paper is to quantify the effect of scale by employing STATSGO (1:250,000) and SSURGO (1:24,000) soil databases in predicting and comparing flow, sediment, nitrate and phosphorus losses for High Island Creek. This watershed is predominately agricultural and located in south-central Minnesota. The ADAPT (Agricultural Drainage and Pesticide Transport), model was calibrated for flow, sediment, nitrate and phosphorus losses over two years (2001-2002) using STATSGO and SSURGO soil databases. Then the calibrated model was used to evaluate alternative tillage and fertilizer management practices such as adoption of conservation tillage, and rate, timing and method of N– and P-fertilizer applications. Statistical comparison of calibration results with observed data indicated excellent agreement for both soil databases (STATSGO with r**2 of 0.95, 0.97, 0.77 and 0.92 and SSURGO with r**2 of 0.90, 0.97, 0.82 and 0.99 for flow, sediment, nitrate and phosphorus losses, respectively). However, STATSGO based predictions of annual nitrate losses were consistently greater than those with SSURGO database and vice-versa for predicted annual phosphorus losses for the alternative management practice that were evaluated.

Last Modified: 10/21/2014
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