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Analyzing Indicators of Stream Health for Minnesota Streams

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Watershed Management to Meet Water Quality Standards and Emerging TMDL (Total Maximum Daily Load) Proceedings of the Third Conference 5-9 March 2005 (Atlanta, Georgia USA) Publication Date 5 March 2005  701P0105.(doi:10.13031/2013.18120)
Authors:   Udai Singh, Matthew Kocian, Bruce Wilson, Angela Bolton, John Nieber, Bruce Vondracek, Jim Perry, and Joe Magner

Recent research has emphasized the importance of using physical, chemical, and biological indicators of stream health for diagnosing impaired watersheds and their receiving water bodies. A multidisciplinary team at the University of Minnesota is carrying out research to develop a stream classification system for Total Maximum Daily Load (TMDL) assessment. Funding for this research is provided by the United States Environmental Protection Agency and the Minnesota Pollution Control Agency . One objective of the research study involves investigating the relationships between indicators of stream health and localized stream characteristics. Measured data from Minnesota streams collected by various government and non-government agencies and research institutions have been obtained for the research study. Innovative Geographic Information Systems tools developed by the Environmental Science Research Institute and the University of Texas are being utilized to combine and organize the data. Simple linear relationships between index of biological integrity (IBI) and channel slope, two-year stream flow, and drainage area are presented for the Redwood River and the Snake River Basins. Results suggest that more rigorous techniques are needed to successfully capture trends in IBI scores. Additional analyses will be done using multiple regression, principal component analysis, and clustering techniques. Uncovering key independent variables and understanding how they fit together to influence stream health are critical in the development of a stream classification for TMDL assessment.

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