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Journal of Water and Health Vol 5 No 2 pp 241–257 © IWA Publishing 2007 doi:10.2166/wh.2007.010
Pathogen and indicator variability in a heavily impacted watershed
Sarah M. Dorner, William B. Anderson, Peter M. Huck, Terri Gaulin, Heather L. Candon, Robin M. Slawson and Pierre Payment
Department of Public Health, University of Massachusetts Amherst, Amherst, MA 01003, ,USA sdorner@tei.umass.edu
Department of Civil Engineering, University of Waterloo, 200 University Avenue West,Waterloo, ON N2L 3G1, ,Canada
Environmental Enforcement & Laboratory Services, Regional Municipality of Waterloo, 100 Maple Grove Road Cambridge, ON , N3H 4R6, ,Canada
Department of Microbiology and Immunology, University of British Columbia, #300 - 6174 University Boulevard,Vancouver, British Columbia , V6T 1Z3, ,Canada
Department of Biology, Wilfrid Laurier University, 75 University Avenue WestWaterloo, ON , N2L 3C5, ,Canada
INRS-Institut Armand-Frappier, Institut national de la recherche scientifique (INRS), 531 Boul. des PrairiesLaval, (Quebec) , H7V 1B7, Canada
ABSTRACT
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.
Keywords: Cryptosporidium; drinking water, E. coli O157:H7; pathogens; quantitative (real-time) PCR; watershed
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