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USING ENERGY AND EMERGY TO COUPLE GEOMORPHOLOGY AND HUMAN INFLUENCES INTO A WATERSHED/LANDSCAPE INDEX AND LINK THE INDEX TO DOWNSTREAM WATER AND HABITAT QUALITY
Citation:
BrandtWilliams, S. USING ENERGY AND EMERGY TO COUPLE GEOMORPHOLOGY AND HUMAN INFLUENCES INTO A WATERSHED/LANDSCAPE INDEX AND LINK THE INDEX TO DOWNSTREAM WATER AND HABITAT QUALITY. Presented at 19th Annual Syposium of the United States Regioal Assocation of the International Association fo Landscape Ecology, Las Vegas, NV, March 30- April 3, 2004.
Description:
The Clean Water Act requires identification of all waters whose abiotic and biotic integrity have been compromised or impaired, but it is impossible to assess each water body in the nation. Although landscape studies attempting to find correlations between land use and water condition indices have provided mixed results, it is intuitively obvious that some connection exists between changes in the watershed and declining quality in the receiving water bodies. If a spatial model provided consistently significant correlation with known impaired water bodies, and was capable of incorporating geographic and watershed differences across the entire continent, the method could be used to predict unknown areas of impairment with a high level of confidence. A model that used variables physically linked to potential causes of impairment would provide the further advantage of pinpointing areas of potential intervention and support for creating national environmental policy that is both effective and socioeconomically feasible.
This study evaluated the link between watershed activities and estuarine/freshwater condition using spatial modeling of energy flows and emergy density in the watershed and field data from estuaries and lakes in Rhode Island and Florida. This approach allows disparate factors (soil water capacity and consumption of electricity for example) to be combined into a single index without loss of quantitative definition. The primary objective was to determine the watershed factors, both geologic and anthropogenic, demonstrating the strongest statistical relationship with water and habitat quality indices. A secondary objective was to determine the least data intensive method for assessing this connection.