Assessing sediment yield for selected watersheds in the Laurentian Great Lakes Basin under future agricultural scenarios.
Identifieur interne : 000185 ( PubMed/Checkpoint ); précédent : 000184; suivant : 000186Assessing sediment yield for selected watersheds in the Laurentian Great Lakes Basin under future agricultural scenarios.
Auteurs : Yang Shao [États-Unis] ; Ross S. Lunetta ; Alexander J. Macpherson ; Junyan Luo ; Guo ChenSource :
- Environmental management [ 1432-1009 ] ; 2013.
English descriptors
- KwdEn :
- MESH :
- analysis : Geologic Sediments.
- Agriculture, Lakes, Models, Theoretical.
Abstract
In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000-2005), and predicted stream flows were validated. The R(2) values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all "other" agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7-42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33-127 % compared with baseline conditions.
DOI: 10.1007/s00267-012-9903-9
PubMed: 22791140
Affiliations:
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Lunetta</name></author><author><name sortKey="Macpherson, Alexander J" sort="Macpherson, Alexander J" uniqKey="Macpherson A" first="Alexander J" last="Macpherson">Alexander J. Macpherson</name></author><author><name sortKey="Luo, Junyan" sort="Luo, Junyan" uniqKey="Luo J" first="Junyan" last="Luo">Junyan Luo</name></author><author><name sortKey="Chen, Guo" sort="Chen, Guo" uniqKey="Chen G" first="Guo" last="Chen">Guo Chen</name></author></analytic><series><title level="j">Environmental management</title><idno type="eISSN">1432-1009</idno><imprint><date when="2013" type="published">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Agriculture</term><term>Geologic Sediments (analysis)</term><term>Lakes</term><term>Models, Theoretical</term></keywords><keywords scheme="MESH" qualifier="analysis" xml:lang="en"><term>Geologic Sediments</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Agriculture</term><term>Lakes</term><term>Models, Theoretical</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000-2005), and predicted stream flows were validated. The R(2) values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all "other" agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7-42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33-127 % compared with baseline conditions.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">22791140</PMID><DateCreated><Year>2012</Year><Month>12</Month><Day>25</Day></DateCreated><DateCompleted><Year>2013</Year><Month>05</Month><Day>31</Day></DateCompleted><DateRevised><Year>2012</Year><Month>12</Month><Day>25</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1432-1009</ISSN><JournalIssue CitedMedium="Internet"><Volume>51</Volume><Issue>1</Issue><PubDate><Year>2013</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Environmental management</Title><ISOAbbreviation>Environ Manage</ISOAbbreviation></Journal><ArticleTitle>Assessing sediment yield for selected watersheds in the Laurentian Great Lakes Basin under future agricultural scenarios.</ArticleTitle><Pagination><MedlinePgn>59-69</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1007/s00267-012-9903-9</ELocationID><Abstract><AbstractText>In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000-2005), and predicted stream flows were validated. The R(2) values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all "other" agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7-42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33-127 % compared with baseline conditions.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Shao</LastName><ForeName>Yang</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Geography, Virginia Tech, Blacksburg, VA 24061, USA. yshao@vt.edu</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lunetta</LastName><ForeName>Ross S</ForeName><Initials>RS</Initials></Author><Author ValidYN="Y"><LastName>Macpherson</LastName><ForeName>Alexander J</ForeName><Initials>AJ</Initials></Author><Author ValidYN="Y"><LastName>Luo</LastName><ForeName>Junyan</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Guo</ForeName><Initials>G</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2012</Year><Month>07</Month><Day>13</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Environ Manage</MedlineTA><NlmUniqueID>7703893</NlmUniqueID><ISSNLinking>0364-152X</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000383" MajorTopicYN="Y">Agriculture</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D019015" MajorTopicYN="N">Geologic Sediments</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D060106" MajorTopicYN="N">Lakes</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="Y">Models, Theoretical</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2010</Year><Month>12</Month><Day>16</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2012</Year><Month>06</Month><Day>17</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2012</Year><Month>7</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2012</Year><Month>7</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2013</Year><Month>6</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">22791140</ArticleId><ArticleId IdType="doi">10.1007/s00267-012-9903-9</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Virginie</li></region></list><tree><noCountry><name sortKey="Chen, Guo" sort="Chen, Guo" uniqKey="Chen G" first="Guo" last="Chen">Guo Chen</name><name sortKey="Lunetta, Ross S" sort="Lunetta, Ross S" uniqKey="Lunetta R" first="Ross S" last="Lunetta">Ross S. Lunetta</name><name sortKey="Luo, Junyan" sort="Luo, Junyan" uniqKey="Luo J" first="Junyan" last="Luo">Junyan Luo</name><name sortKey="Macpherson, Alexander J" sort="Macpherson, Alexander J" uniqKey="Macpherson A" first="Alexander J" last="Macpherson">Alexander J. Macpherson</name></noCountry><country name="États-Unis"><region name="Virginie"><name sortKey="Shao, Yang" sort="Shao, Yang" uniqKey="Shao Y" first="Yang" last="Shao">Yang Shao</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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