American Society of Civil Engineers


Effect of Soil Data Resolution on Identification of Critical Source Areas of Sediment


by Harsh V. Singh, (Graduate student, School of Forestry and Wildlife Sciences, Auburn Univ., Auburn, AL 36849. E-mail: hvn0001@auburn.edu), Latif Kalin, (corresponding author), M.ASCE, (Assistant Professor, School of Forestry and Wildlife Sciences, Auburn Univ., Auburn, AL 36849 E-mail: kalinla@auburn.edu), and Puneet Srivastava, (Associate Professor, Biosystems Engineering Dept., 200 Corley Building, Auburn Univ., Auburn, AL 36849. E-mail: srivapu@auburn.edu)

Journal of Hydrologic Engineering, Vol. 16, No. 3, March 2011, pp. 253-262, (doi:  http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000318)

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Document type: Journal Paper
Abstract: Identification of critical source areas (CSAs) of pollution in a watershed is important for effective implementation of best management practices (BMPs). Process-based watershed models are often used for this purpose. One of the main inputs to these models is the spatially explicit soils data. The objective of this study was to evaluate whether the use of two commonly used soil data sets, the State Soil Geographic (STATSGO) and the Soil Survey Geographic (SSURGO) data, can lead to differences in location of CSAs of sediment. A watershed model, Soil and Water Assessment Tool (SWAT), in combination with the Tukey-Kramer test was used for locating CSAs in the Fish River watershed located in coastal Alabama. The model was calibrated and validated using flow data from a U.S. Geological Survey (USGS) gauging station located within the watershed. The locations of the CSAs of sediment were analyzed at subwatershed and hydrologic response unit (HRU) levels. Results show that the locations of the CSAs were different for the two soil data sets. The locations of the CSAs varied at both subwatershed and HRU levels. The use of STATSGO soil data resulted in higher soil erodibility factor and surface runoff. As a result, higher sediment yield was obtained from the use of the STATSGO data as compared with the sediment yield obtained from the use of the SSURGO data. Therefore, for accurate identification of CSAs of sediment (and potentially other pollutants) and for effective implementation of economically feasible BMPs, it is important to use the most detailed spatial data set available.


ASCE Subject Headings:
Best Management Practice
Sediment
Models
Geographic information systems
Runoff
Databases

Author Keywords:
Critical source area
Best management practice
SWAT
Sediment
Modeling
STATSGO
SSURGO
GIS