Modeling watershed-scale effectiveness of agricultural best management practices to reduce phosphorus loading.
Planners advocate best management practices (BMPs) to reduce loss of sediment and nutrients in agricultural areas. However, the scientific community lacks tools that use readily available data to investigate the relationships between BMPs and their spatial locations and water quality. In rural, humid regions where runoff is associated with saturation-excess processes from variable source areas (VSAs), BMPs are potentially most effective when they are located in areas that produce the majority of the runoff. Thus, two critical elements necessary to predict the water quality impact of BMPs include correct identification of VSAs and accurate predictions of nutrient reduction due to particular BMPs. The objective of this research was to determine the effectiveness of BMPs using the Variable Source Loading Function (VSLF) model, which captures the spatial and temporal evolutions of VSAs in the landscape. Data from a long-term monitoring campaign on a 164-ha farm in the New York City source watersheds in the Catskills Mountains of New York state were used to evaluate the effectiveness of a range of BMPs. The data spanned an 11-year period over which a suite of BMPs, including a nutrient management plan, riparian buffers, filter strips and fencing, was installed to reduce phosphorus (P) loading. Despite its simplicity, VSLF predicted the spatial distribution of runoff producing areas well. Dissolved P reductions were simulated well by using calibrated reduction factors for various BMPs in the VSLF model. Total P losses decreased only after cattle crossings were installed in the creek. The results demonstrated that BMPs, when sited with respect to VSAs, reduce P loss from agricultural watersheds, providing useful information for targeted water quality management.
Rao
Nalini S
NS
Department of Biological and Environmental Engineering, 206 Riley-Robb Hall, Cornell University, Ithaca, NY 14853, United States. nsr7@cornell.edu
Easton
Zachary M
ZM
Schneiderman
Elliot M
EM
Zion
Mark S
MS
Lee
David R
DR
Steenhuis
Tammo S
TS
D000383:Agriculture / Q000379:methods*; D003198:Computer Simulation; D004784:Environmental Monitoring; D008962:Models, Theoretical; D010758:Phosphorus / Q000737:chemistry*; D014874:Water Pollutants, Chemical / Q000737:chemistry*
D014874:Water Pollutants, Chemical; D010758:Phosphorus