|SCHOMBERG H H|
|STEINER J L|
|EVETT S R|
|MOULIN A P|
Submitted to: Journal of Theoretical and Applied Climatology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/28/1995
Publication Date: N/A
Interpretive Summary: An evaluation of the crop residue decomposition model developed for the Wind Erosion Prediction System was performed with published data sets from several locations. The analysis involved the comparison of two methods of calculating the water coefficient and three methods for determining the temperature coefficient. The simple precipitation based index performed as swell as the more mechanistic soil water content function for relating wate availability to rates of residue decomposition. The three temperature functions gave similar predictions of residue decomposition, however, the function from Stroo et al. (SSSAJ, 53:91) predicted slightly faster rates of residue decomposition than the other two functions. Overall model accuracy was generally within +/- 15 to 25% of the observed values. Variability in the observed values was at least this great and contributed to the lack of greater prediction accuracy.
Technical Abstract: Effectiveness of crop residues to protect soil surface and reduce soil erosion decreases as residues decompose. Residue decomposition is directly related to temperature and moisture. Predicting in residue mass, orientation, and soil cover requires the use of functions that relate temperature and water to decomposition. Temperature and water functions used in the residue decomposition submodel of the Wind Erosion Prediction System were evaluated for effects on predictions of residue decomposition. A precipitation function (PC) was found to produce as accurate estimates of decomposition as a near surface soil water content function (SWC). Predictions made with PC had accuracies of +/- 11.4, 14.5, 13.5% for alfalfa, sorghum and wheat, respectively, while those made with SWC had accuracies of +/- 13.8, 16.2, and 16.9%, respectively. Three temperature functions were compared over a range of locations and crops. There was little difference between the temperature functions over all locations, bu for several locations, one function over-predicted decomposition more often than the other two. 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, accuracies were generally between +/- 15 and +/- 25%. The prediction intervals were similar to variation present in observed data. This evaluation indicates that the temperature and water functions used in the decomposition submodel give reasonable estimates of mass loss from surface residues using easy-to-obtain weather data.