UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS
Identifieur interne : 001072 ( Main/Exploration ); précédent : 001071; suivant : 001073UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS
Auteurs : Jonathan H. Smith ; James D. Wickham ; Douglas Norton ; Tim G. Wade ; K. Bruce JonesSource :
- JAWRA Journal of the American Water Resources Association [ 1093-474X ] ; 2001-08.
Abstract
ABSTRACT: Many water bodies within the United States are contaminated by non‐point source (NPS) pollution, which is defined as those materials posing a threat to water quality arising from a number of individual sources and diffused through hydrologic processes. One such NPS pollutant that is of critical concern are pathogens derived from animal wastes, including humans. The potential presence of pathogens is identified by testing the water for fecal conform, a bacteria also associated with animal wastes. Water contaminated by animal wastes are most often associated with urban and agricultural areas, thus it is postulated that by utilizing land cover indicators, those water bodies that may be at risk of fecal coliform contamination may be identified. This study utilizes land cover information derived from the Multi‐Resolution Land Characterization (MRLC) project to analyze fecal coliform contamination in South Carolina. Also utilized are 14 digit hydro‐logic unit code (HUC) watersheds of the state, a digital elevation model, and test point data stating whether fecal coliform levels exceeded State Water Quality Standards. Proportions of the various land covers are identified within the individual watersheds and then analyzed using a logistic regression. The results reveal that watersheds with large proportions of urban land cover and agriculture on steep slopes had a very high probability of being impaired. (KEY TERMS: Geographic Information Systems; land use planning; nonpoint source pollution; statistical analysis; water quality; watershed management.)
Url:
DOI: 10.1111/j.1752-1688.2001.tb05513.x
Affiliations:
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Bruce Jones</name></author></analytic><monogr></monogr><series><title level="j">JAWRA Journal of the American Water Resources Association</title><idno type="ISSN">1093-474X</idno><idno type="eISSN">1752-1688</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><date type="published" when="2001-08">2001-08</date><biblScope unit="volume">37</biblScope><biblScope unit="issue">4</biblScope><biblScope unit="page" from="805">805</biblScope><biblScope unit="page" to="814">814</biblScope></imprint><idno type="ISSN">1093-474X</idno></series><idno type="istex">0CD583C05FB1D5625752AD6B23CCC7EBC1B3F965</idno><idno type="DOI">10.1111/j.1752-1688.2001.tb05513.x</idno><idno type="ArticleID">JAWR805</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1093-474X</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">ABSTRACT: Many water bodies within the United States are contaminated by non‐point source (NPS) pollution, which is defined as those materials posing a threat to water quality arising from a number of individual sources and diffused through hydrologic processes. One such NPS pollutant that is of critical concern are pathogens derived from animal wastes, including humans. The potential presence of pathogens is identified by testing the water for fecal conform, a bacteria also associated with animal wastes. Water contaminated by animal wastes are most often associated with urban and agricultural areas, thus it is postulated that by utilizing land cover indicators, those water bodies that may be at risk of fecal coliform contamination may be identified. This study utilizes land cover information derived from the Multi‐Resolution Land Characterization (MRLC) project to analyze fecal coliform contamination in South Carolina. Also utilized are 14 digit hydro‐logic unit code (HUC) watersheds of the state, a digital elevation model, and test point data stating whether fecal coliform levels exceeded State Water Quality Standards. Proportions of the various land covers are identified within the individual watersheds and then analyzed using a logistic regression. The results reveal that watersheds with large proportions of urban land cover and agriculture on steep slopes had a very high probability of being impaired. (KEY TERMS: Geographic Information Systems; land use planning; nonpoint source pollution; statistical analysis; water quality; watershed management.)</div></front></TEI><affiliations><list></list><tree><noCountry><name sortKey="Jones, K Bruce" sort="Jones, K Bruce" uniqKey="Jones K" first="K. Bruce" last="Jones">K. Bruce Jones</name><name sortKey="Norton, Douglas" sort="Norton, Douglas" uniqKey="Norton D" first="Douglas" last="Norton">Douglas Norton</name><name sortKey="Smith, Jonathan H" sort="Smith, Jonathan H" uniqKey="Smith J" first="Jonathan H." last="Smith">Jonathan H. Smith</name><name sortKey="Wade, Tim G" sort="Wade, Tim G" uniqKey="Wade T" first="Tim G." last="Wade">Tim G. Wade</name><name sortKey="Wickham, James D" sort="Wickham, James D" uniqKey="Wickham J" first="James D." last="Wickham">James D. Wickham</name></noCountry></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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