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

Bolster, C. H., Forsberg, A., Mittelstet, A., Radcliffe, D. E., Storm, D., Ramirez-Avila, J. J., Sharpley, A. N., & Osmond, D. (2017). Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss. Journal of Environmental Quality. DOI:10.2134/jeq2016.04.0159.


Request Permissions Share »Email this content »Recommend to librarian Facebook Twitter Printer-friendly PDF doi:10.2134/jeq2016.04.0159 Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss Carl H. Bolster *a, Adam Forsbergbc, Aaron Mittelstetde, David E. Radcliffeb, Daniel Stormd, John Ramirez-Avilaf, Andrew N. Sharpleyg and Deanna Osmondh + Author Affiliations 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. Abstract 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 (&#961; = 0.92) and particulate (&#961; = 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.

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