Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model.
Identifieur interne : 000052 ( PubMed/Corpus ); précédent : 000051; suivant : 000053Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model.
Auteurs : Mahmood Sadat-Noori ; Kumars EbrahimiSource :
- Environmental monitoring and assessment [ 1573-2959 ] ; 2016.
English descriptors
- KwdEn :
- MESH :
- chemical : Soil.
- geographic : Iran.
- analysis : Groundwater, Water Pollution.
- chemistry : Groundwater.
- methods : Environmental Monitoring.
- statistics & numerical data : Water Pollution, Water Supply.
- Agriculture, Geographic Information Systems, Models, Theoretical, Risk Assessment.
Abstract
Groundwater contamination is a major concern for groundwater resource managers worldwide. We evaluated groundwater pollution potential by producing a vulnerability map of an aquifer using a modified Depth to water, Net recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity (DRASTIC) model within a Geographic Information System (GIS) environment. The proposed modification which incorporated the use of statistical techniques optimizes the rating function of the DRASTIC model parameters, to obtain a more accurate vulnerability map. The new rates were computed using the relationships between the parameters and point data chloride concentrations in groundwater. The model was applied on Saveh-Nobaran plain in central Iran, and results showed that the coefficient of determination (R (2)) between the point data and the relevant vulnerability map increased significantly from 0.52 to 0.78 after modification. As compared to the original DRASTIC model, the modified version produced better vulnerability zonation. Additionally, single-parameter and parameter removal sensitivity analyses were performed to evaluate the relative importance of each DRASTIC parameter. The results from both analyses revealed that the vadose zone is the most sensitive parameter influencing the variability of the aquifers' vulnerability index. Based on the results, for non-point source pollution in agricultural areas, using the modified DRASTIC model is efficient compared to the original model. The proposed method can be effective for future groundwater assessment and plain-land management where agricultural activities are dominant.
DOI: 10.1007/s10661-015-4915-6
PubMed: 26650205
Links to Exploration step
pubmed:26650205Le document en format XML
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We evaluated groundwater pollution potential by producing a vulnerability map of an aquifer using a modified Depth to water, Net recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity (DRASTIC) model within a Geographic Information System (GIS) environment. The proposed modification which incorporated the use of statistical techniques optimizes the rating function of the DRASTIC model parameters, to obtain a more accurate vulnerability map. The new rates were computed using the relationships between the parameters and point data chloride concentrations in groundwater. The model was applied on Saveh-Nobaran plain in central Iran, and results showed that the coefficient of determination (R (2)) between the point data and the relevant vulnerability map increased significantly from 0.52 to 0.78 after modification. As compared to the original DRASTIC model, the modified version produced better vulnerability zonation. Additionally, single-parameter and parameter removal sensitivity analyses were performed to evaluate the relative importance of each DRASTIC parameter. The results from both analyses revealed that the vadose zone is the most sensitive parameter influencing the variability of the aquifers' vulnerability index. Based on the results, for non-point source pollution in agricultural areas, using the modified DRASTIC model is efficient compared to the original model. The proposed method can be effective for future groundwater assessment and plain-land management where agricultural activities are dominant.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26650205</PMID><DateCreated><Year>2015</Year><Month>12</Month><Day>15</Day></DateCreated><DateCompleted><Year>2016</Year><Month>07</Month><Day>14</Day></DateCompleted><DateRevised><Year>2015</Year><Month>12</Month><Day>15</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1573-2959</ISSN><JournalIssue CitedMedium="Internet"><Volume>188</Volume><Issue>1</Issue><PubDate><Year>2016</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Environmental monitoring and assessment</Title><ISOAbbreviation>Environ Monit Assess</ISOAbbreviation></Journal><ArticleTitle>Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model.</ArticleTitle><Pagination><MedlinePgn>19</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s10661-015-4915-6</ELocationID><Abstract><AbstractText>Groundwater contamination is a major concern for groundwater resource managers worldwide. We evaluated groundwater pollution potential by producing a vulnerability map of an aquifer using a modified Depth to water, Net recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity (DRASTIC) model within a Geographic Information System (GIS) environment. The proposed modification which incorporated the use of statistical techniques optimizes the rating function of the DRASTIC model parameters, to obtain a more accurate vulnerability map. The new rates were computed using the relationships between the parameters and point data chloride concentrations in groundwater. The model was applied on Saveh-Nobaran plain in central Iran, and results showed that the coefficient of determination (R (2)) between the point data and the relevant vulnerability map increased significantly from 0.52 to 0.78 after modification. As compared to the original DRASTIC model, the modified version produced better vulnerability zonation. Additionally, single-parameter and parameter removal sensitivity analyses were performed to evaluate the relative importance of each DRASTIC parameter. The results from both analyses revealed that the vadose zone is the most sensitive parameter influencing the variability of the aquifers' vulnerability index. Based on the results, for non-point source pollution in agricultural areas, using the modified DRASTIC model is efficient compared to the original model. The proposed method can be effective for future groundwater assessment and plain-land management where agricultural activities are dominant.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Sadat-Noori</LastName><ForeName>Mahmood</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Irrigation and Reclamation Engineering, University of Tehran, Karaj, Iran. m.sadatnoori@yahoo.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ebrahimi</LastName><ForeName>Kumars</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Department of Irrigation and Reclamation Engineering, University of Tehran, Karaj, Iran.</Affiliation></AffiliationInfo></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>2015</Year><Month>12</Month><Day>09</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Environ Monit Assess</MedlineTA><NlmUniqueID>8508350</NlmUniqueID><ISSNLinking>0167-6369</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D012987">Soil</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000383" MajorTopicYN="Y">Agriculture</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004784" MajorTopicYN="N">Environmental Monitoring</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D040362" MajorTopicYN="N">Geographic Information Systems</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060587" MajorTopicYN="N">Groundwater</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName><QualifierName UI="Q000737" MajorTopicYN="Y">chemistry</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007492" MajorTopicYN="N" Type="Geographic">Iran</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="Y">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018570" MajorTopicYN="N">Risk Assessment</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012987" MajorTopicYN="N">Soil</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014876" MajorTopicYN="N">Water Pollution</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014881" MajorTopicYN="N">Water Supply</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="Y">statistics & numerical data</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Groundwater contamination</Keyword><Keyword MajorTopicYN="N">Parameter removal sensitivity analysis</Keyword><Keyword MajorTopicYN="N">Saveh plain</Keyword><Keyword MajorTopicYN="N">Single-parameter sensitivity analysis</Keyword><Keyword MajorTopicYN="N">Water resources management</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>10</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2015</Year><Month>10</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>12</Month><Day>10</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>12</Month><Day>10</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>7</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">26650205</ArticleId><ArticleId IdType="doi">10.1007/s10661-015-4915-6</ArticleId><ArticleId IdType="pii">10.1007/s10661-015-4915-6</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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