Abstract
Nonpoint source pollution from agriculture continues to be a burgeoning problem in the United States. Best management practices such as the use of riparian buffers, can significantly reduce the amount of agricultural runoff and thus the amount of nitrogen, phosphorous, and coliform contaminants reaching aquatic systems. In Vermont, efforts are underway by the Natural Resource Conservation Service (NRCS) to provide financial incentives to farmers to develop riparian buffers along rivers adjacent to their fields. The NRCS method involves identification of candidate fields through ground surveys and manual interpretation of aerial photographs. This approach, however, does not account for geophysical factors such as soil type, slope, and land cover that also influence surface drainage.
We, therefore, developed a method based on the Revised Universal Soil Loss Equation (RUSLE) that incorporates those factors to identify and prioritize candidate agricultural fields adjacent to the Mad River for riparian buffer development. Development and implementation of the RUSLE model within a GIS framework also provides a methodology that can be extrapolated to surrounding regions in a cost effective manner. In addition, we assessed the utility of panchromatic digital orthophotography, high-resolution multispectral IKONOS and medium resolution Landsat ETM+ satellite data to map land use and land cover for use in the RUSLE model. This approach provides a valuable tool for water quality management.