Stream Classification System Based on Susceptibility to Algal Growth in Response to Nutrients
Publication: Journal of Environmental Engineering
Volume 133, Issue 7
Abstract
We developed a stream classification system that is based on stream’s susceptibility to algal growth using a two-step approach. The model portrays algal biomass as a result of stream’s response to nutrient concentrations and the response is governed by various stream factors. In the first step, a nutrient-chlorophyll relationship was developed to characterize nutrient’s effects on algal biomass. Residuals of the relationship were attributed to stream’s susceptibility to algal growth in response to nutrients and referred to as “observed” susceptibility. In the second step, conditions of other contributing factors were used to explain the variation in the residuals and the developed relationship was used to generate “predicted” susceptibility. Existing data compiled from various monitoring projects of Illinois streams and rivers were used to illustrate the approach. Streams were classified into three (high, medium, and low) categories based on their observed and predicted susceptibility values, respectively. With the available data, the model showed a 40-50% success rate for classifying the streams based on three observed and predicted susceptibility categories. Model entropy also was calculated for selecting the best model. The results show the important role of both nutrients and other contributing factors in explaining the variation of algal biomass. The study also suggests ways to fine tune the model and improve its accuracy, which would make the presented model a more viable tool for stream classification for establishing nutrient criteria to prevent surface streams from eutrophication.
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Acknowledgments
This study was supported by the U.S. Environmental Protection Agency (Award No. X796525602), and National Center for Supercomputing Applications Faculty Fellow Grant. Derek Winstanley, Chief, ISWS, provided valuable advice in various stages of the research and manuscript preparation. Sally McConkey (ISWS) and Matthew Short (IEPA) provided the data sets, and Michael Machesky (ISWS) and Alena Bartosova (ISWS) provided very insightful review comments.
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Information & Authors
Information
Published In
Journal of Environmental Engineering
Volume 133 • Issue 7 • July 2007
Pages: 692 - 697
Copyright
© 2007 ASCE.
History
Received: Aug 3, 2006
Accepted: Feb 1, 2007
Published online: Jul 1, 2007
Published in print: Jul 2007
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