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Bacterial Total Maximum Daily Load (TMDL): Statistical Comparison of impaired and unimpaired watersheds in Texas

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

Citation:  Pp. 413-413 in Total Maximum Daily Load (TMDL) Environmental Regulations–II Proceedings of the 8-12 November 2003 Conference (Albuquerque, New Mexico USA), Publication Date 8 November 2003.  .(doi:10.13031/2013.15589)
Authors:   Sabu Paul, Raghavan Srinivasan, Saqib Mukhtar, Patricia Haan
Keywords:   Fecal Coliform, Discrimant analysis, TMDL

Under the Clean Water Act (CWA) program the Texas Commission on Environmental Quality (TCEQ) listed 110 stream segments in 2002 for pathogenic bacterial impairment. Previously a study was conducted to characterize the watersheds associated with these impaired waterbodies to find out the possibility of clustering the waterbodies into groups having similar watershed characteristics. The current study was aimed at finding out the important parameters that differentiate the watersheds corresponding to impaired stream segments from that of the unimpaired streams. Watershed parameters that could be used for analyzing the impaired watersheds were selected. These parameters include the landuse distribution, density of stream network, average distance of particular landuse to the closest stream, density of population, density of households, density of different types of septic systems, bacterial loading rates due to the presence of different types of animals, and ave! rage climatic conditions. In order to do the comparison of the watershed characteristics, 110 other watersheds that had no streams listed for impairment were randomly selected. The characteristics of the impaired watersheds were then compared with the characteristics of the unimpaired watersheds to find out any statistically significant difference between their means. The statistical tests included non-parametric Kruskal-Wallis (Wilcoxon) test and Student's T-test. A discriminant analysis was conducted to find out the important parameters that could distinguish the impaired watersheds from the unimpaired watersheds. Results from statistical analysis showed that parameters selected for the clustering analysis had significantly different means for impaired and unimpaired watersheds.

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