Predicting Daily Mean Soil Temperatures in the EPIC Simulation Model
Soil temperature is an important component of crop simulation models, because it affects crop growth and development, nutrient cycling, and, in some cases, water infiltration. This study was conducted to determine the efficacy of the EPIC (Erosion/Productivity Impact Calculator) mean soil temperature model and to evaluate the Parton mean surface temperature model developed for a shortgrass steppe in an agricultural simulation model. Simulated mean daily 0.05-m soil temperatures were compared with measured mean daily 0.05-m soil temperatures from three locations (Bushland, TX; Boone, IA; and Mandan, ND) for a range of residue management practices. The EPIC model simulated mean 0.05-m soil temperature trends, although the predicted temperature lagged measured temperatures by 3 to 5 d, and the predicted temperature oscillations were dampened compared with the measured temperatures. The Parton model followed the mean daily temperature oscillations, but generally overestimated early spring mean soil temperatures. Simple adjustments to both models greatly enhanced temperature predictions.
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