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ARS Home » Pacific West Area » Boise, Idaho » Northwest Watershed Research Center » Research » Publications at this Location » Publication #124985
Title: EVALUATION OF USLE AND RUSLE ESTIMATED SOIL LOSS ON RANGELAND USING RAINFALL SIMULATION EXPERIMENTS

Author
item SPAETH, KENNETH - NRCS
item Pierson Jr, Frederick
item Weltz, Mark
item Blackburn, Wilbert

Submitted to: Journal of Range Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/13/2002
Publication Date: 5/20/2003
Citation: Spaeth, K.E., Pierson, Jr. F.B., Weltz, M. A., and Blackburn, W. H. 2003. Evaluation of USLE and RUSLE estimated soil loss on rangeland using rainfall simulation experiments. Journal of Range Management 56:234-246.

Interpretive Summary: A study was conducted to evaluate the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (USLE). USLE was originally developed in the1960's to predict sheet and rill erosion on cropland. Rangeland, woodland, and permanent pasture applications were added by extrapolating crop residue data to vegetation cover on range and woodland. The need for an accurate hydrology and erosion tool on rangeland was becoming increasingly important. For example, in the 1985 Farm Bill, congress required that conservation plans on highly erodible cropland were necessary in order to participate in certain USDA farm programs and cost/share programs. It was becoming increasingly clear that government land management and service agencies needed and desired improved erosion prediction technology. USLE was evolving using subfactor methods and was being programmed for computer use. This effort was termed RUSLE. The results of this study showed that comparisons between USLE, RUSLE, and actual soil loss was weak on rangelands. The findings of this study are important because land management and service agencies have relied on USLE in the past and were considering using the enhanced technology (RUSLE). The study also explored the real needs of government land management and service agencies and determined that a hydrology and erosion model on rangeland should provide information on infiltration, runoff, evaporation, transpiration, deep percolation, and water storage. Other rangeland hydrology and erosion tools such as the Water Erosion Prediction Project (WEPP) show promising application to rangeland.

Technical Abstract: The Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE 1.06) were evaluated with large -plot rainfall simulation data from a variety of rangeland vegetation types (8 states, 22 sites, 132 plots). Average soil loss for all plots for the representative simulation runs were: 0.011 kg/m2 (dry run); 0.007 kg/m2 (wet run); and 0.035 kg/m2 (very-wet run). Nash/Sutcliffe Model efficiencies (R2eff) of field measured soil loss compared to USLE predicted soil loss (dry, wet, very-wet, pooled) were negative. This indicates that the observed mean measured soil loss from the field rainfall simulations is better than predicted USLE soil loss. USLE tended to overpredict soil loss and as predicted values increased there was greater disparity between observed soil loss. R2eff between RUSLE and dry run soil loss was 0.16 using the NRCS assigned soil erodibility (K) value and 0.17 with K estimated from the soil-erodibility nomograph. RUSLE plant community code default values were used in calculating the cover management (C) subfactor values. RUSLE predicted soil loss was marginally better than using the average field measured soil loss value. R2eff values comparing RUSLE computed soil loss with observed soil loss were negative for the wet, very-wet, and pooled simulation runs. RUSLE performed more poorly as soil moisture, rainfall amounts, and rainfall intensity increased. When actual root, plant production and soil roughness values were used in calculating RUSLE C subfactors, R2eff values for the dry, wet, very-wet, and pooled simulation runs were all negative. RUSLE performed most poorly when actual field measured values for root biomass, plant production, and random soil roughness were used.