SWAT Literature Database for Peer-Reviewed Journal Articles

Title:Comparing an annual and a daily time-step model for predicting field-scale phosphorus loss 
Authors:Bolster, C.H., A. Forsberg, A. Mittelstet, D.E. Radcliffe, D. Storm, J. Ramirez-Avila, A.N. Sharpley and D. Osmond 
Journal:Journal of Environmental Quality 
Volume (Issue):46(6) 
Article ID: 
URL (non-DOI journals): 
Broad Application Category:pollutant only 
Primary Application Category:phosphorus cycling/loss and transport 
Secondary Application Category:model and/or data comparison 
Watershed Description:11 research sites located in the Southern U.S. 
Calibration Summary: 
Validation Summary: 
General Comments:This study describes a comparison between the Texas Best Management Practice Evaluation Tool (TBET) and the APLE model. The authors state that TBET is a daily time step model but it is really an interface based on output from underlying SWAT simulations, and thus SWAT is identified as the model for this study. 
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 fieldscale 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 (r = 0.92) and particulate (r = 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.