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Comparison of Residue Decomposition Models Used in Erosion Prediction

USDA-ARS, Southern Piedmont Conservation Res. Ctr., 1420 Experiment Station Rd., Watkinsille, GA 30677-2373

^* Corresponding author (hschomberg{at}ag.gov).

Crop residues protect soil from water and wind erosion. How long the residues remain effective depends on their decomposition rate. The crop residue decomposition submodels developed for the Revised Wind Erosion Equation (RWEQ) and Revised Universal Soil Loss Equation (RUSLE), which are used to determine the effectiveness of conservation practices, use different approaches to account for water and temperature effects on decomposition. Because of these differences, residue losses may not agree between the two models for a given location. We compared the climatic indices used in RWEQ and RUSLE to determine the similarity of results for simulated climatic scenarios, as well as for field data. Simulated climatic regimes were used to evaluate the relative responsiveness of the temperature and water functions. The two models estimated different numbers of decomposition days (DD) when water and temperature were not limiting. RUSLE usually predicted more DDs than RWEQ. Under water-limiting conditions, the estimation of DD was similar for the two models. In comparisons with field decomposition data, mass loss predictions by RWEQ were as good as or better than those by RUSLE for locations in Texas, Oregon, and Georgia. RUSLE overpredicted decomposition by 20 to 50% when residues were irrigated. RWEQ underpredicted decomposition by 20 to 50% in the Pacific Northwest. Interactions between the climatic indices (CF) and decomposition coefficients influenced the differences between measured and predicted values. Differences in the CF were related to the method of calculating the water coefficient (WC) and interpretation of the interaction between the temperature coefficient and WC. The models could be improved by developing water and temperature functions that give results closer to those produced with daily time-step functions.

Received for publication August 19, 1996.

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