Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/2/1997
Publication Date: N/A
Citation: N/A Interpretive Summary: Models developed by ARS are being used to evaluate producer practices and to determine eligibility for farm programs. The accuracy of these models must be evaluated so that fair and unbiased decisions are made of producer practices. Erosion decreases when crop residues are allowed to remain on the soil surface. Residue effectiveness is a matter of how long the residues remain in place. Empirical models of residue decomposition are used within the RUSLE and RWEQ erosion models. An evaluation of these models was made to identify the strengths and weaknesses of the approaches used in these models. There were differences between the two approaches with RUSLE doing better for climates where rainfall amounts were above 35 inches per year. RWEQ was better in dryer climates. A combination of the two approaches will need to be incorporated into future releases of the models.
Technical Abstract: Crop residues protect soil from water and wind erosion. Residue effectiveness depends on decomposition rate. Decomposition sub- models developed for the Revised Wind Erosion Equation (RWEQ) and Revised Universal Soil Loss Equation (RUSLE) use different approaches for water and temperature effects on decomposition and may not agree when simulations are made for the same location. Prediction differences need to be identified because the models are used to determine the effectiveness of conservation practices. The climatic indices used in RWEQ and RUSLE were compared or simulated climatic scenarios as well as for field data. Simulated climatic regimes evaluated the relative responsiveness of the temperature and water functions and indicated that the two models estimated different numbers of decomposition days when water and temperature were not limiting. In water limiting conditions, decomposition days were similar for the two models. In comparisons with field decomposition data, mass loss predictions by RWEQ were as good or better than RUSLE for most locations with only small differences between the two models. Additional data are needed for evaluation of both models for decomposition in very wet or very dry environments.