A Web‐Based Model of N Mineralization from Cover Crop Residue Decomposition

Abstract

Core Ideas The model provided good estimates of N mineralized when linked to climate data. Modifications to rate constants and some parameters led to good model fit. The model predictions in the validation were accurate for incorporated residues. Cover crops can provide substantial quantities of N for subsequent crops, but estimating the amount of N that will be mineralized from residues is challenging. Complex interactions of residue chemistry with soil temperature and soil water content affect N mineralization during residue decomposition. A simulation model can describe these interactions and provide estimates of N mineralized if specific soil water and temperature data are available. Our objectives are (i) to describe a web‐based N mineralization model and its operation, (ii) to calibrate the model with results from published N mineralization studies, and (iii) to validate it using field studies investigating decomposition of surface‐applied or incorporated crimson clover (Trifolium incarnatum L.) or rye (Secale cereale L.) residues over 3 yr. Inputs required by the model include residue N, nonstructural carbohydrates, cellulose + hemi‐cellulose, and lignin contents, as well as 5‐yr average values of daily soil temperature and soil water content from a user‐selected weather station. The model was successfully calibrated with published data from eight laboratory and field studies and was validated with data from field studies that used soil cores with cover crop residues. Simulated values of N mineralized were acceptable for incorporated residues but tended to overpredict N mineralized from surface residues because soil temperature and water content are not good drivers to simulate N mineralization from residues on the soil surface. Additional research is needed to develop algorithms to estimate temperature and water content/water potential of surface residues so they can be used as driver variables for the model.