Assessing the impacts of watershed indexes and precipitation on spatial in-stream E. coli concentrations

Pathogen contamination of waterbodies, which is often identified by the presence of pathogen indicators such as Escherichia coli, is a major water quality concern in the United States. Reducing in-stream pathogen contamination requires an understanding of the combined impacts of land cover, climatic...

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Bibliographic Details
Published in:Ecological indicators 2012-12, Vol.23, p.641-652
Main Authors: Pandey, Pramod K., Soupir, Michelle L., Haddad, Monica, Rothwell, James J.
Format: Article
Language:English
Subjects:
In-stream E. coli concentrations
Land
Land cover
Mathematical models
Nonpoint pollution
Pathogens
Rainfall
Sampling
Water quality
Watershed indexes
Watershed scale modeling
Watersheds
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Summary:Pathogen contamination of waterbodies, which is often identified by the presence of pathogen indicators such as Escherichia coli, is a major water quality concern in the United States. Reducing in-stream pathogen contamination requires an understanding of the combined impacts of land cover, climatic conditions, and anthropogenic activities at the watershed scale. In this study these factors are considered by assessing linear relationships between in-stream E. coli water quality data, watershed indexes, and rainfall for the Squaw Creek Watershed, IA, USA. The watershed indexes consider the undisturbed land cover which encompasses the natural land cover area, wetlands, and vegetated stream corridors, and the disturbed land cover extent which includes areas receiving manure from confined animal feeding operations (CAFOs), tile-drained areas, and areas in cropped and urban land. In addition to disturbed and undisturbed land, we also calculated indexes for barren land and slope. Bivariate analysis was used to assess the linkage between E. coli concentrations, watershed indexes and the cumulative rainfall 15, 30, 45, and 60 days prior to water sample collection. To predict in-stream E. coli concentrations, we developed multivariate regression models, and predictions were compared with observed E. coli concentrations at 46 sampling locations over four sampling periods in two years. Results show that areas receiving manure, wetlands, drained land, and cropped land all influence in-stream E. coli concentrations significantly (p
ISSN:1470-160X
1872-7034
DOI:10.1016/j.ecolind.2012.05.023