HR: 1340h
AN: H13E-1374    [Abstracts]
TI: Landscape-Scale Patterns in the Capacity of Riparian Buffers to Reduce Stream Nutrient and Sediment Loads
AU: * Diebel, M W
EM: mwdiebel@wisc.edu
AF: University of Wisconsin - Madison, Center for Limnology, 680 N. Park Street, Madison, WI 53706 United States
AU: Maxted, J T
EM: jtmaxted@wisc.edu
AF: University of Wisconsin - Madison, Center for Limnology, 680 N. Park Street, Madison, WI 53706 United States
AU: Han, S
EM: hanseung@cs.wisc.edu
AF: University of Wisconsin - Madison, Statistics Department, 1300 University Avenue, Madison, WI 53706 United States
AU: Robertson, D M
EM: dzrobert@usgs.gov
AF: U.S. Geological Survey, Wisconsin Water Science Center, 8505 Research Way, Middleton, WI 53562 United States
AU: Vander Zanden, M J
EM: mjvanderzand@wisc.edu
AF: University of Wisconsin - Madison, Center for Limnology, 680 N. Park Street, Madison, WI 53706 United States
AB: Riparian buffers have the potential to reduce nutrient and sediment loads in streams. This load reduction potential varies among watersheds and describes the utility of buffers as a management practice. We present a model for estimating sediment and phosphorus load reduction potential at the spatial grain of the small watershed. Load reduction potential is the current load minus the sum of unbufferable sources. We built regression models from measured annual loads and landscape metrics to estimate current annual loads. Unbufferable sources cannot be attenuated by riparian buffers and include point sources, fine-textured soils, and meander belt erosion. We estimate the model parameters for a set of 1600 small (average 52 sq. km) watersheds in Wisconsin. Sediment and phosphorus load reduction potential estimates are used rank these watersheds according to their suitability for riparian buffer implementation. A sensitivity analysis indicates that watershed ranks are moderately robust to errors in model parameters. This application is part of a geographic targeting scheme that seeks to invest conservation funds where water quality can be most improved.
DE: 1819 Geographic Information Systems (GIS)
DE: 1871 Surface water quality
DE: 1879 Watershed
DE: 1880 Water management (6334)
SC: Hydrology [H]
MN: Fall Meeting 2005