WEPP and GLEAMS simulations of runoff and soil loss from grazed pasture in the southeastern United States
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Authors: W. E. Pitts, K. H. Yoo, M. S. Miller-Goodman, W. L. de los Santos, and K. S. Yoon
Date: 1999
Journal: Journal of Environmental Science and Health. Part A: Toxic/Hazardous Substances and Environmental Engineering
Volume: 34
Number: 7
Pages: 1397-1413
Summary of Methods: Predicted values of surface runoff and erosion from two current erosion models (WEPP and GLEAMS) were compared to observed data recorded during January (1995) to August (1996) from the Tennessee Valley region of Alabama. Twelve runoff plots were located in three forage types (common bermudagrass, tall fescue, and switchgrass) under two grazing practices (proper grazing (recommended) and heavy grazing). Proper grazing stubble heights of bermudagrass, tall fescue, and switchgrass were 10, 15, and 20 cm respectively. Heavy grazing stubble heights were half of proper grazing. Runoff was collected with buckets at the site and recorded after rainfall events.
Article Summary / Main Points: GLEAMS performed better than WEPP for each forage type and grazing pressure. Neither model predicted sediment loss within an acceptable level. Runoff and erosion from the experiment plots were not affected by grazing pressure. GLEAMS predicted values of sediment lost were highly correlated with observed data, whereas WEPP predicted values were not.
Vegetation Types: Other (includes Forest and Eastern)
MLRA Ecoregions: 129 Sand Mountain 133A Southern Coastal Plain
Agrovoc Control Words: Pastures Grazing Erosion
Article Review Type: Refereed
Article Type: Experimental Research
Keywords: erosion prediction models, wepp, gleams, switchgrass, bermudagrass, tall fescue, runoff, sediment yield
Annotation: This was a replicated study over two years and is only applicable to rangelands of the south and southeast. These types of simulated models are easy to apply and take less time for analyzing the data compared to experimental field and lab data. As is true for all grazing research, the results are most directly applicable to areas with similar landscapes, type of ungulate, weather conditions and season of use. One limitation of these models is the failure to incorporate more data and possibly more parameters to strengthen their predictions across a wider area.
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