Modeling vulnerability of groundwater to pollution under future scenarios of climate change and biofuels-related land use change: a case study in North Dakota, USA.
Identifieur interne : 000166 ( PubMed/Checkpoint ); précédent : 000165; suivant : 000167Modeling vulnerability of groundwater to pollution under future scenarios of climate change and biofuels-related land use change: a case study in North Dakota, USA.
Auteurs : Ruopu Li [États-Unis] ; James W. MerchantSource :
- The Science of the total environment [ 1879-1026 ] ; 2013.
English descriptors
- KwdEn :
- MESH :
- chemical : Biofuels, Fertilizers, Water Pollutants, Chemical.
- geographic : North Dakota.
- Climate Change, Crops, Agricultural, Geographic Information Systems, Groundwater, Models, Theoretical, Water Pollution, Water Quality.
Abstract
Modeling groundwater vulnerability to pollution is critical for implementing programs to protect groundwater quality. Most groundwater vulnerability modeling has been based on current hydrogeology and land use conditions. However, groundwater vulnerability is strongly dependent on factors such as depth-to-water, recharge and land use conditions that may change in response to future changes in climate and/or socio-economic conditions. In this research, a modeling framework, which employs three sets of models linked within a geographic information system (GIS) environment, was used to evaluate groundwater pollution risks under future climate and land use changes in North Dakota. The results showed that areas with high vulnerability will expand northward and/or northwestward in Eastern North Dakota under different scenarios. GIS-based models that account for future changes in climate and land use can help decision-makers identify potential future threats to groundwater quality and take early steps to protect this critical resource.
DOI: 10.1016/j.scitotenv.2013.01.011
PubMed: 23376514
Affiliations:
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pubmed:23376514Le document en format XML
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Merchant</name></author></analytic><series><title level="j">The Science of the total environment</title><idno type="eISSN">1879-1026</idno><imprint><date when="2013" type="published">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Biofuels</term><term>Climate Change</term><term>Crops, Agricultural</term><term>Fertilizers</term><term>Geographic Information Systems</term><term>Groundwater</term><term>Models, Theoretical</term><term>North Dakota</term><term>Water Pollutants, Chemical</term><term>Water Pollution</term><term>Water Quality</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>Biofuels</term><term>Fertilizers</term><term>Water Pollutants, Chemical</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>North Dakota</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Climate Change</term><term>Crops, Agricultural</term><term>Geographic Information Systems</term><term>Groundwater</term><term>Models, Theoretical</term><term>Water Pollution</term><term>Water Quality</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Modeling groundwater vulnerability to pollution is critical for implementing programs to protect groundwater quality. Most groundwater vulnerability modeling has been based on current hydrogeology and land use conditions. However, groundwater vulnerability is strongly dependent on factors such as depth-to-water, recharge and land use conditions that may change in response to future changes in climate and/or socio-economic conditions. In this research, a modeling framework, which employs three sets of models linked within a geographic information system (GIS) environment, was used to evaluate groundwater pollution risks under future climate and land use changes in North Dakota. The results showed that areas with high vulnerability will expand northward and/or northwestward in Eastern North Dakota under different scenarios. GIS-based models that account for future changes in climate and land use can help decision-makers identify potential future threats to groundwater quality and take early steps to protect this critical resource.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">23376514</PMID><DateCreated><Year>2013</Year><Month>02</Month><Day>28</Day></DateCreated><DateCompleted><Year>2013</Year><Month>09</Month><Day>24</Day></DateCompleted><DateRevised><Year>2013</Year><Month>02</Month><Day>28</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-1026</ISSN><JournalIssue CitedMedium="Internet"><Volume>447</Volume><PubDate><Year>2013</Year><Month>Mar</Month><Day>01</Day></PubDate></JournalIssue><Title>The Science of the total environment</Title><ISOAbbreviation>Sci. Total Environ.</ISOAbbreviation></Journal><ArticleTitle>Modeling vulnerability of groundwater to pollution under future scenarios of climate change and biofuels-related land use change: a case study in North Dakota, USA.</ArticleTitle><Pagination><MedlinePgn>32-45</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.scitotenv.2013.01.011</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S0048-9697(13)00017-X</ELocationID><Abstract><AbstractText>Modeling groundwater vulnerability to pollution is critical for implementing programs to protect groundwater quality. Most groundwater vulnerability modeling has been based on current hydrogeology and land use conditions. However, groundwater vulnerability is strongly dependent on factors such as depth-to-water, recharge and land use conditions that may change in response to future changes in climate and/or socio-economic conditions. In this research, a modeling framework, which employs three sets of models linked within a geographic information system (GIS) environment, was used to evaluate groundwater pollution risks under future climate and land use changes in North Dakota. The results showed that areas with high vulnerability will expand northward and/or northwestward in Eastern North Dakota under different scenarios. GIS-based models that account for future changes in climate and land use can help decision-makers identify potential future threats to groundwater quality and take early steps to protect this critical resource.</AbstractText><CopyrightInformation>Copyright © 2013 Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Ruopu</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Center for Advanced Land Management Information Technologies, School of Natural Resources, University of Nebraska-Lincoln, 3310 Holdrege Street, Lincoln, NE 68583-0973, United States. rli3@unl.edu</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Merchant</LastName><ForeName>James W</ForeName><Initials>JW</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2013</Year><Month>01</Month><Day>31</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Sci Total Environ</MedlineTA><NlmUniqueID>0330500</NlmUniqueID><ISSNLinking>0048-9697</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D056804">Biofuels</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D005308">Fertilizers</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D014874">Water Pollutants, Chemical</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D056804" MajorTopicYN="Y">Biofuels</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D057231" MajorTopicYN="N">Climate Change</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018556" MajorTopicYN="N">Crops, Agricultural</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005308" MajorTopicYN="N">Fertilizers</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D040362" MajorTopicYN="N">Geographic Information Systems</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060587" MajorTopicYN="Y">Groundwater</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="N">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009658" MajorTopicYN="N" Type="Geographic">North Dakota</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014874" MajorTopicYN="N">Water Pollutants, Chemical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014876" MajorTopicYN="Y">Water Pollution</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060753" MajorTopicYN="N">Water Quality</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2012</Year><Month>09</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2013</Year><Month>01</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2013</Year><Month>01</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2013</Year><Month>2</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2013</Year><Month>2</Month><Day>5</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2013</Year><Month>9</Month><Day>26</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">23376514</ArticleId><ArticleId IdType="pii">S0048-9697(13)00017-X</ArticleId><ArticleId IdType="doi">10.1016/j.scitotenv.2013.01.011</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Nebraska</li></region></list><tree><noCountry><name sortKey="Merchant, James W" sort="Merchant, James W" uniqKey="Merchant J" first="James W" last="Merchant">James W. Merchant</name></noCountry><country name="États-Unis"><region name="Nebraska"><name sortKey="Li, Ruopu" sort="Li, Ruopu" uniqKey="Li R" first="Ruopu" last="Li">Ruopu Li</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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