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DEM-GIS Based Spatially Distributed Storm Runoff Response Study Using Remotely-sensed Data

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  022005,  2002 ASAE Annual Meeting . (doi: 10.13031/2013.9162) @2002
Authors:   Assefa M. Melesse, Wendy D. Graham, and Jonathan D. Jordan
Keywords:   runoff, travel time, curve number, DEM, GIS, remote sensing

The availability of spatial information from remote sensing, and the ability of geographic information system (GIS) to handle such data efficiently, have contributed much to the understanding of watershed runoff response and land cover changes. Distributed watershed models are commonly used to investigate rainfall-runoff processes. These watershed models require topographic drainage information, such as watershed boundaries and drainage divides which can be derived from Digital Elevation Models (DEMs). Spatially distributed runoff was estimated for the Simms creek in the St. Johns River Water Management District (SJRWMD), Florida using the United States Department of Agriculture, Natural Resources Conservation Service-Curve Number (USDA-NRCS-CN) method. Land use data from Digital Orthophoto Quarter Quadrangles (DOQQ) and Landsat Enhanced Thematic Mapper Plus (ETM+) for 1990, 1995 and 2000 were used to estimate spatially distributed curve numbers. A DEM-GIS based runoff routing technique based on 1-D kinematic wave flow was made to generate hydrographs based on travel time to the watershed outlet using spatially distributed data. Comparison was made between the observed and predicted runoff hydrographs and three existing models: the Time-Area method, the Snyder unit hydrograph model and TOPMODEL, a semi-distributed saturation excess model using, 17 storm events from 1990, 1995, 1999 and 2000. The results indicate that the distributed travel time method can accurately predict runoff response for large isolated storms and the travel time approach performed better with higher efficiencies than the other two models. The Time-Area method performed better than the other models with average efficiency of 0.7.

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