An improved temperature function for modeling crop residue decomposition

摘要

Models like the Revised Universal Soil Loss Equation (RUSLE) and Revised Wind Erosion Equation (RWEQ) that estimate erosion potential need good estimates of crop residue decomposition to evaluate changes in soil surface cover Decomposition is modeled based on climate and residue chemical characteristics as controlling factors. Crop-specific decomposition coefficients account for differences in the chemical and physical properties of the residues. Temperature and water functions relate climatic conditions in the field to optimum conditions. The models use a scaled temperature function (TF) to relate monthly temperature to relative biological activity. The half-month time steps and monthly data used in RUSLE and RWEQ result in the loss of temporal information about temperature effects. Use of average temperature or maximum and minimum temperatures to estimate TF were compared with TF estimated as the integral from maximum to minimum for monthly or daily data. The numerically integrated approach appeared to be more robust and was theoretically more appealing than the two original approaches. However because RUSLE and RWEQ have been developed for users with limited computer resources, the integrated junction was not considered appropriate. A system of equations for calculating TF on a monthly basis was developed that captured the dynamic effect of daily temperatures but required less computation time than the integrated method. Comparison to the original approach in RUSLE for estimating decomposition of wheat residues at several locations in the U.S. indicates significant improvement in model performance. This system of equations should improve decomposition estimates in monthly time step models and could be applicable to daily time step models and other biological processes.