Assessment of runoff and sediment yield using remote sensing , GIS, and AGNPS
Dates
Year
2001
Citation
Bhuyan, S. J., Marzen, L. J., Koelliker, J. K., Harrington, J.A., and Barnes, P. L., 2001, Assessment of runoff and sediment yield using remote sensing , GIS, and AGNPS: Journal of Soil & Water Conservation, v. 57, no. 6, p. 351-363.
Summary
A model that can predict runoff and soil loss from a watershed is an important tool that can be used for planning and for watershed assessment and management. An application that combined the capabilities of remote sensing, Geographic Information Systems (GIS), and the Agricultural NonPoint Source Pollution (AGNPS) model was used to assess runoff and sediment yield from various sub-watersheds above Cheney Reservoir in Kansas. Remotely sensed Landsat thematic mapper (TM) images were used to obtain land cover and associated AGNPS model input parameters, including the Universal Soil Loss Equation's (USLE) cropping factors (C-factor), based on estimates of vegetative cover for rangeland and crop residue. Several input parameters of the [...]
Summary
A model that can predict runoff and soil loss from a watershed is an important tool that can be used for planning and for watershed assessment and management. An application that combined the capabilities of remote sensing, Geographic Information Systems (GIS), and the Agricultural NonPoint Source Pollution (AGNPS) model was used to assess runoff and sediment yield from various sub-watersheds above Cheney Reservoir in Kansas. Remotely sensed Landsat thematic mapper (TM) images were used to obtain land cover and associated AGNPS model input parameters, including the Universal Soil Loss Equation's (USLE) cropping factors (C-factor), based on estimates of vegetative cover for rangeland and crop residue. Several input parameters of the AGNPS model were extracted from GIS layers using the AGNPS-ARC/INFO interface. C-factors and curve numbers (CNs) of agricultural crops were adjusted on the basis of management practices and hydrologic conditions of the watershed during various runoff events. Surface-water quantity and quality data, including total suspended solids (TSS) for major runoff events, were obtained from United States Geological Survey (USGS) gaging stations in the watershed and were used for evaluation of this AGNPS modeling process. Base-flow separation was done so that measured runoff and TSS levels could be compared directly with the AGNPS model output. Use of remote sensing along with GIS reduced the time to obtain input for the modeling process and added to the confidence in the representation of watershed conditions. The modeling process was effective for small watersheds (up to 145 sq km [56 sq mil) with adequate available rainfall data. However, for larger watersheds with substantial variations of rainfall, this process was less satisfactory.
