Comparing an Annual and a Daily Time‐Step Model for Predicting Field‐Scale Phosphorus Loss

A wide range of mathematical models are available for predicting phosphorus (P) losses from agricultural fields, ranging from simple, empirically based annual time‐step models to more complex, process‐based daily time‐step models. In this study, we compare field‐scale P‐loss predictions between the Annual P Loss Estimator (APLE), an empirically based annual time‐step model, and the Texas Best Management Practice Evaluation Tool (TBET), a process‐based daily time‐step model based on the Soil and Water Assessment Tool. We first compared predictions of field‐scale P loss from both models using field and land management data collected from 11 research sites throughout the southern United States. We then compared predictions of P loss from both models with measured P‐loss data from these sites. We observed a strong and statistically significant (p < 0.001) correlation in both dissolved (ρ = 0.92) and particulate (ρ = 0.87) P loss between the two models; however, APLE predicted, on average, 44% greater dissolved P loss, whereas TBET predicted, on average, 105% greater particulate P loss for the conditions simulated in our study. When we compared model predictions with measured P‐loss data, neither model consistently outperformed the other, indicating that more complex models do not necessarily produce better predictions of field‐scale P loss. Our results also highlight limitations with both models and the need for continued efforts to improve their accuracy. Core Ideas We compared predictions of P loss between an empirically‐based and process‐based model. Predictions from both models were well correlated with each other. The process‐based model did not result in noticeably better predictions of P loss. APLE predicted greater DP loss and TBET predicted greater PP loss. Results indicate the need for improving accuracy of both models.