IHB OpenIR  > 淡水生态学研究中心  > 期刊论文
Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: A case study of the Xiangxi River basin, China
Wang, Xingzhong1,2; Cai, Qinghua1; Ye, Lin1,2; Qu, Xiaodong1,2; Cai, QH (reprint author), Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China.
2012-12-19
Source PublicationQUATERNARY INTERNATIONAL
ISSN1040-6182
Volume282Issue:-Pages:137-144
AbstractThe analysis and interpretation the spatiotemporal patterns of river water quality are a critical element in the assessment, restoration, and protection of local and region water quality. In this case study, multivariate statistical techniques, including cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA), had been integrated to evaluate and interpret spatiotemporal variations of water quality in Xiangxi River, with a 5-years (2002-2006) continual monitoring data (14 parameters at 12 sites). Hierarchical cluster analysis revealed all sites could be grouped into three clusters representing different levels of pollution: relatively less polluted upper catchments sites (US), medium polluted Middle catchments sites (MS), and highly polluted lower catchments sites (LS). Factor analysis/principal component analysis was used to explore the most important factors determining the spatiotemporal dynamics of water quality in Xiangxi River. Varifactors obtained from the factor analysis indicated the parameters responsible for water quality variation were mainly related to soluble salts (natural), point source pollution of phosphorus and non-point pollution of nitrogen (anthropogenic). Discriminant analysis provided an important data reduction as it uses six parameters (TN. Si0(2), hardness, Ca2+, WT and pH), affording 70.5% correct assignations in temporal analysis, and two parameters (NO3-N and Alk), affording 55.9% correct assignations in spatial analysis, of three different regions in the basin. The low correct assignation in spatial analysis was related to the anthropogenic influence. This study suggested that multivariate statistical techniques are useful tools for identification of important water quality monitoring sites parameters and design of a monitoring network for the effective management of water resources. (C) 2012 Elsevier Ltd and INQUA. All rights reserved.; The analysis and interpretation the spatiotemporal patterns of river water quality are a critical element in the assessment, restoration, and protection of local and region water quality. In this case study, multivariate statistical techniques, including cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA), had been integrated to evaluate and interpret spatiotemporal variations of water quality in Xiangxi River, with a 5-years (2002-2006) continual monitoring data (14 parameters at 12 sites). Hierarchical cluster analysis revealed all sites could be grouped into three clusters representing different levels of pollution: relatively less polluted upper catchments sites (US), medium polluted Middle catchments sites (MS), and highly polluted lower catchments sites (LS). Factor analysis/principal component analysis was used to explore the most important factors determining the spatiotemporal dynamics of water quality in Xiangxi River. Varifactors obtained from the factor analysis indicated the parameters responsible for water quality variation were mainly related to soluble salts (natural), point source pollution of phosphorus and non-point pollution of nitrogen (anthropogenic). Discriminant analysis provided an important data reduction as it uses six parameters (TN. Si0(2), hardness, Ca2+, WT and pH), affording 70.5% correct assignations in temporal analysis, and two parameters (NO3-N and Alk), affording 55.9% correct assignations in spatial analysis, of three different regions in the basin. The low correct assignation in spatial analysis was related to the anthropogenic influence. This study suggested that multivariate statistical techniques are useful tools for identification of important water quality monitoring sites parameters and design of a monitoring network for the effective management of water resources. (C) 2012 Elsevier Ltd and INQUA. All rights reserved.
SubtypeArticle
KeywordPrincipal Component Analysis Land-use Communities Region Greece India Dam
Department[Wang, Xingzhong; Cai, Qinghua; Ye, Lin; Qu, Xiaodong] Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China; [Wang, Xingzhong; Ye, Lin; Qu, Xiaodong] Chinese Acad Sci, Grad Univ, Beijing 100039, Peoples R China
DOI10.1016/j.quaint.2012.05.015
WOS HeadingsScience & Technology ; Physical Sciences
Funding OrganizationNational Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202] ; National Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202] ; National Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202] ; National Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202]
Indexed BySCI
Language英语
WOS Research AreaPhysical Geography ; Geology
WOS SubjectGeography, Physical ; Geosciences, Multidisciplinary
WOS IDWOS:000313610000016
WOS KeywordPRINCIPAL COMPONENT ANALYSIS ; LAND-USE ; COMMUNITIES ; REGION ; GREECE ; INDIA ; DAM
Funding OrganizationNational Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202] ; National Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202] ; National Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202] ; National Natural Science Foundation of China [30330140, 40671197]; State key Laboratory FEBL [2011FB202]
Citation statistics
Cited Times:36[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ihb.ac.cn/handle/342005/19297
Collection淡水生态学研究中心_期刊论文
Corresponding AuthorCai, QH (reprint author), Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China.
Affiliation1.Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100039, Peoples R China
Recommended Citation
GB/T 7714
Wang, Xingzhong,Cai, Qinghua,Ye, Lin,et al. Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: A case study of the Xiangxi River basin, China[J]. QUATERNARY INTERNATIONAL,2012,282(-):137-144.
APA Wang, Xingzhong,Cai, Qinghua,Ye, Lin,Qu, Xiaodong,&Cai, QH .(2012).Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: A case study of the Xiangxi River basin, China.QUATERNARY INTERNATIONAL,282(-),137-144.
MLA Wang, Xingzhong,et al."Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: A case study of the Xiangxi River basin, China".QUATERNARY INTERNATIONAL 282.-(2012):137-144.
Files in This Item:
File Name/Size DocType Version Access License
Evaluation of spatia(612KB) 开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang, Xingzhong]'s Articles
[Cai, Qinghua]'s Articles
[Ye, Lin]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang, Xingzhong]'s Articles
[Cai, Qinghua]'s Articles
[Ye, Lin]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang, Xingzhong]'s Articles
[Cai, Qinghua]'s Articles
[Ye, Lin]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques_ A case study of the Xiangxi River basin, China.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.