Predicting phosphorus dynamics in complex terrains using a variable source area hydrology model

Authors

Amy S. Collick, Pasture Systems and Watershed Management Research Unit, USDA-ARS
Daniel R. Fuka, Department of Biological Systems Engineering, Virginia Tech
Peter J.A. Kleinman, Pasture Systems and Watershed Management Research Unit, USDA-ARS
Anthony R. Buda, Pasture Systems and Watershed Management Research Unit, USDA-ARS
Jennifer L. Weld, Department of Ecosystem Science and Management, Pennsylvania State University
Mike J. White, USDA-ARS Grassland Soil and Water Research LaboratoryFollow
Tamie L. Veith, Pasture Systems and Watershed Management Research Unit, USDA-ARS
Ray B. Bryant, Pasture Systems and Watershed Management Research Unit, USDA-ARS
Carl H. Bolster, Animal Waste Management Research Unit, USDA-ARS
Zachary M. Easton, Department of Biological Systems Engineering, Virginia TechFollow

Date of this Version

2014

Citation

John Weily & Sons, 2014

Comments

U.S. Governement work

Abstract

Phosphorus (P) loss from agricultural watersheds has long been a critical water quality problem, the control of which has been the focus of considerable research and investment. Preventing P loss depends on accurately representing the hydrological and chemical processes governing P mobilization and transport. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict run-off and non-point source pollution transport. SWAT simulates run-off employing either the curve number (CN) or the Green and Ampt methods, both assume infiltration-excess run-off, although shallow soils underlain by a restricting layer commonly generate saturation-excess run-off from variable source areas (VSA). In this study, we compared traditional SWAT with a re-conceptualized version, SWAT-VSA, that represents VSA hydrology, in a complex agricultural watershed in east central Pennsylvania. The objectives of this research were to provide further evidence of SWAT-VSA’s integrated and distributed predictive capabilities against measured surface run-off and stream P loads and to highlight the model’s ability to drive sub-field management of P. Thus, we relied on a detailed field management database to parameterize the models. SWAT and SWAT-VSA predicted discharge similarly well (daily Nash–Sutcliffe efficiencies of 0.61 and 0.66, respectively), but SWAT-VSA outperformed SWAT in predicting P export from the watershed. SWAT estimated lower P loss (0.0–0.25 kg ha^-1) from agricultural fields than SWAT-VSA (0.0–1.0+ kg ha^-1), which also identified critical source areas – those areas generating large run-off and P losses at the sub-field level. These results support the use of SWAT-VSA in predicting watershed-scale P losses and identifying critical source areas of P loss in landscapes with VSA hydrology.