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Estimating Pollutant Loading Using Remote Sensing and GIS-AGNPS model  

강문성 (서울대학교 농업생명과학연구원)
박승우 (서울대학교 농공학과)
전종안 (한국건설기술연구원 GIS 사업단)
Publication Information
Magazine of the Korean Society of Agricultural Engineers / v.45, no.1, 2003 , pp. 102-114 More about this Journal
Abstract
The objectives of the paper are to evaluate cell based pollutant loadings for different storm events, to monitor the hydrology and water quality of the Baran HP#6 watershed, and to validate AGNPS with the field data. Simplification was made to AGNPS in estimating storm erosivity factors from a triangular rainfall distribution. GIS-AGNPS interface model consists of three subsystems; the input data processor based on a geographic information system. the models. and the post processor Land use patten at the tested watershed was classified from the Landsat TM data using the artificial neural network model that adopts an error back propagation algorithm. AGNPS model parameters were obtained from the GIS databases, and additional parameters calibrated with field data. It was then tested with ungauged conditions. The simulated runoff was reasonably in good agreement as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.
Keywords
RS; GIS; AGNPS; Water quality; Artificial neural network;
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