A water quality monitoring network design methodology for the selection of critical sampling points: Part I.
Identifieur interne : 000371 ( PubMed/Checkpoint ); précédent : 000370; suivant : 000372A water quality monitoring network design methodology for the selection of critical sampling points: Part I.
Auteurs : R O Strobl [Pays-Bas] ; P D Robillard ; R D Shannon ; R L Day ; A J McdonnellSource :
- Environmental monitoring and assessment [ 0167-6369 ] ; 2006.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Phosphorus.
- analysis : Water Supply.
- methods : Environmental Monitoring.
- standards : Environmental Monitoring, Water Supply.
- Fuzzy Logic, Geographic Information Systems, Models, Theoretical, Quality Control, Water Movements.
Abstract
The principal instrument to temporally and spatially manage water resources is a water quality monitoring network. However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.
DOI: 10.1007/s10661-006-0774-5
PubMed: 16404538
Affiliations:
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However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">16404538</PMID><DateCreated><Year>2006</Year><Month>01</Month><Day>11</Day></DateCreated><DateCompleted><Year>2006</Year><Month>09</Month><Day>07</Day></DateCompleted><DateRevised><Year>2013</Year><Month>11</Month><Day>21</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0167-6369</ISSN><JournalIssue CitedMedium="Print"><Volume>112</Volume><Issue>1-3</Issue><PubDate><Year>2006</Year><Month>Jan</Month></PubDate></JournalIssue><Title>Environmental monitoring and assessment</Title><ISOAbbreviation>Environ Monit Assess</ISOAbbreviation></Journal><ArticleTitle>A water quality monitoring network design methodology for the selection of critical sampling points: Part I.</ArticleTitle><Pagination><MedlinePgn>137-58</MedlinePgn></Pagination><Abstract><AbstractText>The principal instrument to temporally and spatially manage water resources is a water quality monitoring network. However, to date in most cases, there is a clear absence of a concise strategy or methodology for designing monitoring networks, especially when deciding upon the placement of sampling stations. Since water quality monitoring networks can be quite costly, it is very important to properly design the monitoring network so that maximum information extraction can be accomplished, which in turn is vital when informing decision-makers. This paper presents the development of a methodology for identifying the critical sampling locations within a watershed. Hence, it embodies the spatial component in the design of a water quality monitoring network by designating the critical stream locations that should ideally be sampled. For illustration purposes, the methodology focuses on a single contaminant, namely total phosphorus, and is applicable to small, upland, predominantly agricultural-forested watersheds. It takes a number of hydrologic, topographic, soils, vegetative, and land use factors into account. In addition, it includes an economic as well as logistical component in order to approximate the number of sampling points required for a given budget and to only consider the logistically accessible stream reaches in the analysis, respectively. The methodology utilizes a geographic information system (GIS), hydrologic simulation model, and fuzzy logic.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Strobl</LastName><ForeName>R O</ForeName><Initials>RO</Initials><AffiliationInfo><Affiliation>Department of Water Resources, International Institute of GeoInformation Sciences and Earth Observation, Enschede, The Netherlands. strobl@itc.nl</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Robillard</LastName><ForeName>P D</ForeName><Initials>PD</Initials></Author><Author ValidYN="Y"><LastName>Shannon</LastName><ForeName>R D</ForeName><Initials>RD</Initials></Author><Author ValidYN="Y"><LastName>Day</LastName><ForeName>R L</ForeName><Initials>RL</Initials></Author><Author ValidYN="Y"><LastName>McDonnell</LastName><ForeName>A J</ForeName><Initials>AJ</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Environ Monit Assess</MedlineTA><NlmUniqueID>8508350</NlmUniqueID><ISSNLinking>0167-6369</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>27YLU75U4W</RegistryNumber><NameOfSubstance UI="D010758">Phosphorus</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D004784" MajorTopicYN="N">Environmental Monitoring</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName><QualifierName UI="Q000592" MajorTopicYN="Y">standards</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017143" MajorTopicYN="N">Fuzzy Logic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D040362" MajorTopicYN="N">Geographic Information Systems</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="Y">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010758" MajorTopicYN="N">Phosphorus</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="Y">analysis</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011786" MajorTopicYN="Y">Quality Control</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014872" MajorTopicYN="N">Water Movements</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014881" MajorTopicYN="N">Water Supply</DescriptorName><QualifierName UI="Q000032" MajorTopicYN="N">analysis</QualifierName><QualifierName UI="Q000592" MajorTopicYN="Y">standards</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2004</Year><Month>07</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2005</Year><Month>01</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2006</Year><Month>1</Month><Day>13</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2006</Year><Month>9</Month><Day>8</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2006</Year><Month>1</Month><Day>13</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">16404538</ArticleId><ArticleId IdType="doi">10.1007/s10661-006-0774-5</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Pays-Bas</li></country></list><tree><noCountry><name sortKey="Day, R L" sort="Day, R L" uniqKey="Day R" first="R L" last="Day">R L Day</name><name sortKey="Mcdonnell, A J" sort="Mcdonnell, A J" uniqKey="Mcdonnell A" first="A J" last="Mcdonnell">A J Mcdonnell</name><name sortKey="Robillard, P D" sort="Robillard, P D" uniqKey="Robillard P" first="P D" last="Robillard">P D Robillard</name><name sortKey="Shannon, R D" sort="Shannon, R D" uniqKey="Shannon R" first="R D" last="Shannon">R D Shannon</name></noCountry><country name="Pays-Bas"><noRegion><name sortKey="Strobl, R O" sort="Strobl, R O" uniqKey="Strobl R" first="R O" last="Strobl">R O Strobl</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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