Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment
Identifieur interne : 001279 ( Istex/Corpus ); précédent : 001278; suivant : 001280Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment
Auteurs : Tahir Ali Akbar ; Raza Ali AkbarSource :
- CLEAN – Soil, Air, Water [ 1863-0650 ] ; 2013-11.
English descriptors
Abstract
The extensive use of pesticides for increasing the agricultural production is affecting the quality of groundwater. The objectives of this article are to (i) develop pesticide relative leaching ranks for well sites, (ii) develop maps for human health risks due to pesticide applications, and (iii) identify the most significant parameters in pesticide simulations for groundwater vulnerability assessment. The methods include (i) development of acifluorfen relative leaching ranks for 25 well sites using ArcPRZM‐3, (ii) development of health risk maps using model simulated maximum dissolved bentazon concentrations on the basis of USA drinking water quality guidelines, (iii) sensitivity analysis for 14 ArcPRZM‐3 input parameters using the Plackett–Burman method. ArcPRZM‐3 is a user‐friendly system for spatial modeling of pesticide leaching from surface to groundwater. Thirteen acifluorfen relative leaching potential ranks were developed in which the pesticide leaching decrease from 1 to 13. The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. The ArcPRZM‐3 system could be efficiently applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.
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DOI: 10.1002/clen.201200232
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ISTEX:6F7F88681FA1281071D41DA28868FF4879B1C16DLe document en format XML
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The objectives of this article are to (i) develop pesticide relative leaching ranks for well sites, (ii) develop maps for human health risks due to pesticide applications, and (iii) identify the most significant parameters in pesticide simulations for groundwater vulnerability assessment. The methods include (i) development of acifluorfen relative leaching ranks for 25 well sites using ArcPRZM‐3, (ii) development of health risk maps using model simulated maximum dissolved bentazon concentrations on the basis of USA drinking water quality guidelines, (iii) sensitivity analysis for 14 ArcPRZM‐3 input parameters using the Plackett–Burman method. ArcPRZM‐3 is a user‐friendly system for spatial modeling of pesticide leaching from surface to groundwater. Thirteen acifluorfen relative leaching potential ranks were developed in which the pesticide leaching decrease from 1 to 13. The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. The ArcPRZM‐3 system could be efficiently applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Tahir Ali Akbar</name><affiliations><json:string>Department of Civil Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada</json:string><json:string>Department of Civil Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr NW, Calgary, Alberta, Canada T2N 1N4</json:string></affiliations></json:item><json:item><name>Raza Ali Akbar</name><affiliations><json:string>Acute and General Internal Medicine, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>ArcPRZM‐3</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Groundwater contamination</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Pesticide leaching</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Plackett–Burman</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Spatial modeling</value></json:item></subject><articleId><json:string>CLEN201200232</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>article</json:string></originalGenre><abstract>The extensive use of pesticides for increasing the agricultural production is affecting the quality of groundwater. 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The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. 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KGaA, Weinheim</p></availability><date>2013</date></publicationStmt><notesStmt><note>United States Department of Agriculture Cooperative State Research, Education, and Extension Service</note><note>Natural Sciences and Engineering Research Council of Canada and the University of Calgary, Canada</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment</title><author xml:id="author-1"><persName><forename type="first">Tahir Ali</forename><surname>Akbar</surname></persName><affiliation>Department of Civil Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada</affiliation><affiliation>Department of Civil Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr NW, Calgary, Alberta, Canada T2N 1N4</affiliation></author><author xml:id="author-2"><persName><forename type="first">Raza Ali</forename><surname>Akbar</surname></persName><affiliation>Acute and General Internal Medicine, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK</affiliation></author></analytic><monogr><title level="j">CLEAN – Soil, Air, Water</title><title level="j" type="abbrev">Clean Soil Air Water</title><idno type="pISSN">1863-0650</idno><idno type="eISSN">1863-0669</idno><idno type="DOI">10.1002/(ISSN)1863-0669</idno><imprint><publisher>WILEY‐VCH Verlag</publisher><pubPlace>Weinheim</pubPlace><date type="published" when="2013-11"></date><biblScope unit="volume">41</biblScope><biblScope unit="issue">11</biblScope><biblScope unit="page" from="1073">1073</biblScope><biblScope unit="page" to="1079">1079</biblScope></imprint></monogr><idno type="istex">6F7F88681FA1281071D41DA28868FF4879B1C16D</idno><idno type="DOI">10.1002/clen.201200232</idno><idno type="ArticleID">CLEN201200232</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2013</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>The extensive use of pesticides for increasing the agricultural production is affecting the quality of groundwater. 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The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. 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The objectives of this article are to (i) develop pesticide relative leaching ranks for well sites, (ii) develop maps for human health risks due to pesticide applications, and (iii) identify the most significant parameters in pesticide simulations for groundwater vulnerability assessment. The methods include (i) development of acifluorfen relative leaching ranks for 25 well sites using ArcPRZM‐3, (ii) development of health risk maps using model simulated maximum dissolved bentazon concentrations on the basis of USA drinking water quality guidelines, (iii) sensitivity analysis for 14 ArcPRZM‐3 input parameters using the Plackett–Burman method. ArcPRZM‐3 is a user‐friendly system for spatial modeling of pesticide leaching from surface to groundwater. Thirteen acifluorfen relative leaching potential ranks were developed in which the pesticide leaching decrease from 1 to 13. The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. The ArcPRZM‐3 system could be efficiently applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.</p></abstract><abstract type="graphical" xml:lang="en"><p>The ArcPRZM‐3 system was used to obtain pesticide related (i) leaching potential ranks, (ii) health risk maps, and (iii) significant parameters for groundwater vulnerability assessment. ArcPRZM‐3 system can be applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale. <blockFixed type="graphic"><mediaResourceGroup><mediaResource alt="image" eRights="yes" copyright="WILEY‐VCH Verlag" href="urn:x-wiley:18630650:media:CLEN201200232:content"></mediaResource></mediaResourceGroup></blockFixed></p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>Pesticide Health Risk Mapping and Sensitivity Analysis</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Pesticide Health Risk Mapping and Sensitivity Analysis of Parameters in Groundwater Vulnerability Assessment</title></titleInfo><name type="personal"><namePart type="given">Tahir Ali</namePart><namePart type="family">Akbar</namePart><affiliation>Department of Civil Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada</affiliation><affiliation>Department of Civil Engineering, Schulich School of Engineering, University of Calgary, 2500 University Dr NW, Calgary, Alberta, Canada T2N 1N4</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Raza Ali</namePart><namePart type="family">Akbar</namePart><affiliation>Acute and General Internal Medicine, Royal Victoria Infirmary, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article"></genre><originInfo><publisher>WILEY‐VCH Verlag</publisher><place><placeTerm type="text">Weinheim</placeTerm></place><dateIssued encoding="w3cdtf">2013-11</dateIssued><dateCaptured encoding="w3cdtf">2012-04-19</dateCaptured><dateValid encoding="w3cdtf">2012-11-20</dateValid><copyrightDate encoding="w3cdtf">2013</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="figures">4</extent><extent unit="tables">1</extent><extent unit="references">49</extent><extent unit="words">6020</extent></physicalDescription><abstract lang="en">The extensive use of pesticides for increasing the agricultural production is affecting the quality of groundwater. The objectives of this article are to (i) develop pesticide relative leaching ranks for well sites, (ii) develop maps for human health risks due to pesticide applications, and (iii) identify the most significant parameters in pesticide simulations for groundwater vulnerability assessment. The methods include (i) development of acifluorfen relative leaching ranks for 25 well sites using ArcPRZM‐3, (ii) development of health risk maps using model simulated maximum dissolved bentazon concentrations on the basis of USA drinking water quality guidelines, (iii) sensitivity analysis for 14 ArcPRZM‐3 input parameters using the Plackett–Burman method. ArcPRZM‐3 is a user‐friendly system for spatial modeling of pesticide leaching from surface to groundwater. Thirteen acifluorfen relative leaching potential ranks were developed in which the pesticide leaching decrease from 1 to 13. The model predicted ranks for well 34 and well 9 were 2nd and 3rd, respectively, and acifluorfen was detected in both wells during the physical monitoring. The percentages of high health risks in the agricultural areas were 48.38 and 72.72% for Randolph and Independence Counties, respectively. The most significant parameters were thickness of horizon compartment, runoff curve number of antecedent moisture condition II for cropping, soil bulk density, and total application of pesticide. The irrigation, soil permeability, and numerical dispersion could impact the pesticide leaching in soils toward groundwater. The ArcPRZM‐3 system could be efficiently applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.</abstract><abstract type="graphical" lang="en">The ArcPRZM‐3 system was used to obtain pesticide related (i) leaching potential ranks, (ii) health risk maps, and (iii) significant parameters for groundwater vulnerability assessment. ArcPRZM‐3 system can be applied for spatial modeling and mapping of pesticide concentrations for groundwater vulnerability assessment on a large scale.</abstract><note type="funding">United States Department of Agriculture Cooperative State Research, Education, and Extension Service</note><note type="funding">Natural Sciences and Engineering Research Council of Canada and the University of Calgary, Canada</note><subject lang="en"><genre>keywords</genre><topic>ArcPRZM‐3</topic><topic>Groundwater contamination</topic><topic>Pesticide leaching</topic><topic>Plackett–Burman</topic><topic>Spatial modeling</topic></subject><relatedItem type="host"><titleInfo><title>CLEAN – Soil, Air, Water</title></titleInfo><titleInfo type="abbreviated"><title>Clean Soil Air Water</title></titleInfo><genre type="journal">journal</genre><subject><genre>article-category</genre><topic>Research Article</topic></subject><identifier type="ISSN">1863-0650</identifier><identifier type="eISSN">1863-0669</identifier><identifier type="DOI">10.1002/(ISSN)1863-0669</identifier><identifier type="PublisherID">CLEN</identifier><part><date>2013</date><detail type="volume"><caption>vol.</caption><number>41</number></detail><detail type="issue"><caption>no.</caption><number>11</number></detail><extent unit="pages"><start>1073</start><end>1079</end><total>7</total></extent></part></relatedItem><identifier type="istex">6F7F88681FA1281071D41DA28868FF4879B1C16D</identifier><identifier type="DOI">10.1002/clen.201200232</identifier><identifier type="ArticleID">CLEN201200232</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright © 2013 WILEY‐VCH Verlag GmbH & Co. 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