American Society of Agricultural and Biological Engineers



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Effects of DEM Source and Resolution on WEPP Hydrologic and Erosion Simulation: A Case Study of Two Forest Watersheds in Northern Idaho

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

Citation:  Transactions of the ASABE. 52(2): 447-457. (doi: 10.13031/2013.26838) @2009
Authors:   J. X. Zhang, J. Q. Wu, K. Chang, W. J. Elliot, S. Dun
Keywords:   DEM, Forest watershed, GIS, LIDAR, Water erosion modeling, WEPP

The recent modification of the Water Erosion Prediction Project (WEPP) model has improved its applicability to hydrology and erosion modeling in forest watersheds. To generate reliable topographic and hydrologic inputs for the WEPP model, carefully selecting digital elevation models (DEMs) with appropriate resolution and accuracy is essential because topography is a major factor controlling water erosion. Light detection and ranging (LIDAR) provides an alternative technology to photogrammetry for generating fine-resolution and high-quality DEMs. In this study, WEPP (v2006.201) was applied to hydrological and erosion simulation for two small forest watersheds in northern Idaho. Data on stream flow and total suspended solids (TSS) in these watersheds were collected and processed. A total of six DEMs from the National Elevation Dataset (NED), Shuttle Radar Topography Mission (SRTM), and LIDAR at three resolutions (30 m, 10 m, and 4 m) were obtained and used to calculate topographic parameters as inputs to the WEPP model. WEPP-simulated hydrologic and erosion results using the six DEMs were contrasted and then compared with field observations. For the study watersheds, DEMs with different resolutions and sources generated varied topographic and hydrologic attributes, which in turn led to significantly different erosion simulations. WEPP v2006.201 using the 10 m LIDAR DEM (vs. using other DEMs) produced a total amount of as well as seasonal patterns of watershed discharge and sediment yield that were closest to field observations.

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