UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS
Identifieur interne : 000B56 ( Istex/Corpus ); précédent : 000B55; suivant : 000B57UTILIZATION 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.)
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DOI: 10.1111/j.1752-1688.2001.tb05513.x
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Bruce Jones</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:0CD583C05FB1D5625752AD6B23CCC7EBC1B3F965</idno><date when="2001" year="2001">2001</date><idno type="doi">10.1111/j.1752-1688.2001.tb05513.x</idno><idno type="url">https://api.istex.fr/document/0CD583C05FB1D5625752AD6B23CCC7EBC1B3F965/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000B56</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000B56</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS</title><author><name sortKey="Smith, Jonathan H" sort="Smith, Jonathan H" uniqKey="Smith J" first="Jonathan H." last="Smith">Jonathan H. Smith</name></author><author><name sortKey="Wickham, James D" sort="Wickham, James D" uniqKey="Wickham J" first="James D." last="Wickham">James D. Wickham</name></author><author><name sortKey="Norton, Douglas" sort="Norton, Douglas" uniqKey="Norton D" first="Douglas" last="Norton">Douglas Norton</name></author><author><name sortKey="Wade, Tim G" sort="Wade, Tim G" uniqKey="Wade T" first="Tim G." last="Wade">Tim G. Wade</name></author><author><name sortKey="Jones, K Bruce" sort="Jones, K Bruce" uniqKey="Jones K" first="K. Bruce" last="Jones">K. 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><istex><corpusName>wiley</corpusName><author><json:item><name>Jonathan H. Smith</name></json:item><json:item><name>James D. Wickham</name></json:item><json:item><name>Douglas Norton</name></json:item><json:item><name>Tim G. Wade</name></json:item><json:item><name>K. Bruce Jones</name></json:item></author><articleId><json:string>JAWR805</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>article</json:string></originalGenre><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. 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Discussions are open until April 1, 2002.</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS</title><author xml:id="author-1"><persName><forename type="first">Jonathan H.</forename><surname>Smith</surname></persName></author><author xml:id="author-2"><persName><forename type="first">James D.</forename><surname>Wickham</surname></persName></author><author xml:id="author-3"><persName><forename type="first">Douglas</forename><surname>Norton</surname></persName></author><author xml:id="author-4"><persName><forename type="first">Tim G.</forename><surname>Wade</surname></persName></author><author xml:id="author-5"><persName><forename type="first">K. Bruce</forename><surname>Jones</surname></persName></author></analytic><monogr><title level="j">JAWRA Journal of the American Water Resources Association</title><idno type="pISSN">1093-474X</idno><idno type="eISSN">1752-1688</idno><idno type="DOI">10.1111/(ISSN)1752-1688</idno><imprint><publisher>Blackwell Publishing Ltd</publisher><pubPlace>Oxford, UK</pubPlace><date type="published" when="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></monogr><idno type="istex">0CD583C05FB1D5625752AD6B23CCC7EBC1B3F965</idno><idno type="DOI">10.1111/j.1752-1688.2001.tb05513.x</idno><idno type="ArticleID">JAWR805</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2001</date></creation><langUsage><language ident="en">en</language></langUsage><abstract><p>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. 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Bruce</givenNames><familyName>Jones</familyName></personName></creator></creators><abstractGroup><abstract type="main" xml:lang="en"><p><b>ABSTRACT: </b> 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.)</p></abstract></abstractGroup></contentMeta><noteGroup><note xml:id="fn1"><p>Paper No. 00098 of the <i>Journal of the American Water Resources Association.</i> Discussions are open until April 1, 2002.</p></note><note xml:id="fn2"><p>Respectively, Ecologist and Research Biologist, Landscape Characterization Branch (MD‐56), National Exposure Research Laboratory, Research Triangle Park, North Carolina 27711; U.S. Environmental Protection Agency, 1200 Pennsylvania Ave. N.W., Washington, D.C. 20460; Geographer, U.S. Environmental Protection Agency, Landscape Characterization Branch (MD‐56), National Exposure Research Laboratory, Research Triangle Park, North Carolina 27711; and Ecologist, U.S. Environmental Protection Agency, Landscape Ecology Branch, P.O. Box 3478, Las Vegas, Nevada 89193‐3478 (E‐Mail <email>Smith:smith.jonathanh@epa.gov</email>).</p></note></noteGroup></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>UTILIZATION OF LANDSCAPE INDICATORS TO MODEL POTENTIAL PATHOGEN IMPAIRED WATERS1</title></titleInfo><name type="personal"><namePart type="given">Jonathan H.</namePart><namePart type="family">Smith</namePart><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">James D.</namePart><namePart type="family">Wickham</namePart><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Douglas</namePart><namePart type="family">Norton</namePart><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Tim G.</namePart><namePart type="family">Wade</namePart><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">K. Bruce</namePart><namePart type="family">Jones</namePart><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><place><placeTerm type="text">Oxford, UK</placeTerm></place><dateIssued encoding="w3cdtf">2001-08</dateIssued><copyrightDate encoding="w3cdtf">2001</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="references">19</extent></physicalDescription><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.)</abstract><note type="content">*Paper No. 00098 of the Journal of the American Water Resources Association. 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