Climatic influence on residue decomposition prediction in the Wind Erosion Prediction System

Summary The effectiveness of crop residues to protect the soil surface and reduce soil erosion decreases as residues decompose. The rate of residue decomposition is directly related to the temperature and moisture regimes of the residues. Predicting changes in residue mass, orientation, and soil cover requires the use of functions that relate changes in decomposition rates to changes in the temperature and water regimes. Temperature and water functions used in the residue decomposition submodel of the Wind Erosion Prediction System (WEPS) were evaluated for their effects on predictions of residue decomposition. A precipitation function (PC) was found to produce relatively more accurate estimates of decomposition than a near surface soil water content function (SWC) for describing water regime effects. The estimated accuracies of the two functions were similar when bias in the estimation was considered. Predictions made with PC had estimated accuracies of ± 11.4, 14.5, 13.5% for alfalfa, sorghum and wheat, respectively, while those made with SWC had estimated accuracies of ± 13.8, 16.2, and 16.9%, respectively. Three temperature functions were compared for use in predicting residue decomposition over a range of locations and crops. There was little difference between the temperature functions over all the locations but, for several locations, one function overpredicted decomposition more often than the other two functions. Accuracies ranged from ±4 to ±51% of the observed values. The highest values were obtained at one location, and all three temperature functions produced similar high values. Over most of the data, estimated accuracies were generally between ± 15 and ± 25%. The prediction intervals were similar to those observed for decomposition of surface-placed residues. This evaluation indicates that the temperature and water functions used in the WEPS decomposition submodel will give reasonable estimates of mass loss from surface residues using easy-to-obtain weather data.With 8 Figures