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Pathogen and indicator variability in a heavily impacted watershed
Author(s) -
Sarah Dorner,
William B. Anderson,
Terri Gaulin,
Heather Candon,
Robin M. Slawson,
Pierre Payment,
Peter M. Huck
Publication year - 2007
Publication title -
journal of water and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 59
eISSN - 1996-7829
pISSN - 1477-8920
DOI - 10.2166/wh.2007.010b
Subject(s) - pathogen , giardia , cryptosporidium , indicator bacteria , biology , watershed , turbidity , fecal coliform , clostridium perfringens , indicator organism , veterinary medicine , human pathogen , coliphage , water quality , microbiology and biotechnology , ecology , environmental science , feces , escherichia coli , bacteria , bacteriophage , medicine , genetics , machine learning , computer science , biochemistry , gene
Water samples were collected from 36 locations within the Grand River Watershed, in Southwestern Ontario, Canada from July 2002 to December 2003 and were analyzed for total coliforms, fecal coliforms, Escherichia coli, Escherichia coli O157:H7, and thermophilic Campylobacter spp. A subset of samples was also analyzed for Cryptosporidium spp., Giardia spp., culturable human enteric viruses, and Clostridium perfringens. Storm and snowmelt events were sampled at two locations including a drinking water intake. For the majority of the events, the Spearman rank correlation test showed a positive correlation between E. coli levels and turbidity. Peaks in pathogen numbers frequently preceded the peaks in numbers of indicator organisms and turbidity. Pathogen levels sometimes decreased to undetectable levels during an event. As pathogen peaks did not correspond to turbidity and indicator peaks, the correlations were weak. Weak correlations may be the result of differences in the sources of the pathogens, rather than differences in pathogen movement through the environment. Results from this investigation have implications for planning monitoring programs for water quality and for the development of pathogen fate and transport models to be used for source water risk assessment.

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