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.Comparing an Annual and a Daily Time-Step Model for Predicting Field-Scale Phosphorus Loss Carl H. Bolster,* Adam Forsberg, Aaron Mittelstet, David E. Radcliffe, Daniel Storm, John Ramirez-Avila, Andrew N. Sharpley, and Deanna Osmond A pplication of phosphorus (P) to agricultural lands can lead to increased offsite transport of P via surface runoff, erosion, and/or subsurface leaching to groundwater. Delivery of this P to P-sensitive water bodies can lead to water quality deterioration, primarily by accelerating the natural eutrophication process. Notable examples where excess P loading is contributing to water quality degradation include the Baltic Sea, Chesapeake Bay, the Florida Everglades, the Gulf of Mexico, and Lake Erie (Richardson et al., 2007;Chesapeake Bay Program, 2009;Dale et al., 2010;Andersson et al., 2014;Schoumans et al., 2014). In response to concerns over P losses from agricultural fields, research has focused on improving our understanding of the processes controlling P movement through the landscape (Radcliffe and Cabrera, 2007). This in turn has led to the development, improvement, and testing of models for predicting P fate and transport in the environment. When properly developed and used, these models can be useful tools for evaluating different management strategies for reducing P loss from agricultural fields (Sharpley et al., 2003;Radcliffe et al., 2009).Models for describing P movement through the landscape range in complexity depending on the theoretical rigor of the governing equations, the number of processes included in the mo...