Abstract:
Riparian zones serve an important role in the ecological landscape. They serve as habitat for wildlife, prevent erosion, and act as buffers to help reduce and filter the amount of pollutants entering surface waters. The United States Geological Survey (USGS) SPARROW model is a spatially referenced regression model that uses source and transport variables to estimate pollutant loadings throughout surface water systems. The SPARROW model for the southeastern United States has not previously incorporated a variable that takes riparian buffers into account, but given their importance to ecosystem services and their effects on hydrologic processes we attempted to introduce riparian buffer effects as a variable into the model. We performed several analyses that quantified the success of riparian buffers in filtering pollutants from non-point source (NPS) agricultural runoff, and incorporated each into the Southeastern United States regional SPARROW to measure improvement. Results show that riparian buffer metrics that take into account topography and landscape pattern improved the SPARROW model to a greater extent than fixed-distance or catchment-wide measurements of buffer size. The most successful buffer variable shows promise and maybe incorporated into the existing SPARROW model. The current SPARROW is calibrated to predict phosphorous, but the next iteration of the model will be calibrated to predict nitrogen and will be capable of analyses at a finer scale. As nitrogen is a better predictor for cropland, we expect the predictive power of the riparian metric to improve in the future. Results of this project suggest that the SPARROW model is capable of being augmented with more explicitly ecologically based variables in the future.
