Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.
Identifieur interne : 000060 ( PubMed/Checkpoint ); précédent : 000059; suivant : 000061Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.
Auteurs : Qing Gu [République populaire de Chine] ; Ke Wang [République populaire de Chine] ; Jiadan Li [République populaire de Chine] ; Ligang Ma [République populaire de Chine] ; Jinsong Deng [République populaire de Chine] ; Kefeng Zheng [République populaire de Chine] ; Xiaobin Zhang [République populaire de Chine] ; Li Sheng [République populaire de Chine]Source :
- International journal of environmental research and public health [ 1660-4601 ] ; 2015.
Descripteurs français
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- chemical : Drinking Water.
- geographic : China.
- Cluster Analysis, Geographic Information Systems, Water Quality, Water Resources, Water Supply.
Abstract
It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.
DOI: 10.3390/ijerph121013179
PubMed: 26492263
Affiliations:
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University, Hangzhou 310058, China. jsong_deng@zju.edu.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institution of Remote Sensing and Information System Application, Zhejiang University, Hangzhou 310058</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName><orgName type="university">Université de Zhejiang</orgName><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation></author><author><name sortKey="Zheng, Kefeng" sort="Zheng, Kefeng" uniqKey="Zheng K" first="Kefeng" last="Zheng">Kefeng Zheng</name><affiliation wicri:level="1"><nlm:affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. zhengkf@mail.zaas.ac.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation></author><author><name sortKey="Zhang, Xiaobin" sort="Zhang, Xiaobin" uniqKey="Zhang X" first="Xiaobin" last="Zhang">Xiaobin Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. riceipm1@zju.edu.cn.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation></author><author><name sortKey="Sheng, Li" sort="Sheng, Li" uniqKey="Sheng L" first="Li" last="Sheng">Li Sheng</name><affiliation wicri:level="1"><nlm:affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. LLANDLL070701@163.com.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation></author></analytic><series><title level="j">International journal of environmental research and public health</title><idno type="eISSN">1660-4601</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>China</term><term>Cluster Analysis</term><term>Drinking Water</term><term>Geographic Information Systems</term><term>Water Quality</term><term>Water Resources</term><term>Water Supply</term></keywords><keywords scheme="MESH" type="chemical" xml:lang="en"><term>Drinking Water</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>China</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cluster Analysis</term><term>Geographic Information Systems</term><term>Water Quality</term><term>Water Resources</term><term>Water Supply</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>République populaire de Chine</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26492263</PMID><DateCreated><Year>2015</Year><Month>10</Month><Day>23</Day></DateCreated><DateCompleted><Year>2016</Year><Month>05</Month><Day>23</Day></DateCompleted><DateRevised><Year>2015</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1660-4601</ISSN><JournalIssue CitedMedium="Internet"><Volume>12</Volume><Issue>10</Issue><PubDate><Year>2015</Year><Month>Oct</Month><Day>20</Day></PubDate></JournalIssue><Title>International journal of environmental research and public health</Title><ISOAbbreviation>Int J Environ Res Public Health</ISOAbbreviation></Journal><ArticleTitle>Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.</ArticleTitle><Pagination><MedlinePgn>13179-94</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3390/ijerph121013179</ELocationID><Abstract><AbstractText>It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Gu</LastName><ForeName>Qing</ForeName><Initials>Q</Initials><AffiliationInfo><Affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. funny@zju.edu.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Ke</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Institution of Remote Sensing and Information System Application, Zhejiang University, Hangzhou 310058, China. kwang@zju.edu.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Jiadan</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Institute of Rural Development and Information, Ningbo Academy of Agricultural Sciences, Ningbo 315040, China. vaneljd@163.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ma</LastName><ForeName>Ligang</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>College of Resource and Environmental Science, Xinjiang University, Urumqi 830046, China. mosanzju@126.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Deng</LastName><ForeName>Jinsong</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Institution of Remote Sensing and Information System Application, Zhejiang University, Hangzhou 310058, China. jsong_deng@zju.edu.cn.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>School of Civil Engineering and Environmental Sciences and School of Meteorology, University of Oklahoma, Norman, OK 73019, USA. jsong_deng@zju.edu.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zheng</LastName><ForeName>Kefeng</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. zhengkf@mail.zaas.ac.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Xiaobin</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. riceipm1@zju.edu.cn.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sheng</LastName><ForeName>Li</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Institute of Digital Agriculture, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China. 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RefType="Cites"><RefSource>Water Res. 2001 Oct;35(14):3462-72</RefSource><PMID Version="1">11547869</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Int J Environ Res Public Health. 2014 Jun;11(6):6069-84</RefSource><PMID Version="1">24919129</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>J Environ Manage. 2002 Dec;66(4):377-93</RefSource><PMID Version="1">12503494</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Water Res. 2003 Oct;37(17):4119-24</RefSource><PMID Version="1">12946893</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016000" MajorTopicYN="N">Cluster Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D060766" MajorTopicYN="Y">Drinking Water</DescriptorName></MeshHeading><MeshHeading><DescriptorName 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Zheng</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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