Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis

Detalhes bibliográficos
Autor(a) principal: Alves,José do Patrocinio Hora
Data de Publicação: 2018
Outros Autores: Fonseca,Lucas Cruz, Chielle,Raisa de Siqueira Alves, Macedo,Lúcia Calumby Barreto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: RBRH (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100223
Resumo: ABSTRACT This study evaluated the efficiency of the water quality monitoring network of the Sergipe river basin, using multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The PCA was applied to a data matrix consisting of 12 sampling stations and mean concentrations of 23 water quality parameters, obtained in four sampling campaigns from June/2013 to November/2015. All 12 sampling stations were considered as main (weight>0.7) and therefore should remain in the monitoring program. The PCA pointed out that of the 23 measured parameters, only 16 are essential for water quality assessment, in the dry period and 17 in the rainy season. The HCA separated the stations of the monitoring network in 4 groups according to the water quality characteristics, considering the natural and anthropogenic impacts. The main impacts were originated from natural sources (mineral constituents) and the anthropogenic contributions were associated with urban input, sewage, industrial dumps and surface runoff from agricultural areas.
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spelling Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysisMonitoringWater qualityPrincipal component analysisCluster analysisSergipe RiverABSTRACT This study evaluated the efficiency of the water quality monitoring network of the Sergipe river basin, using multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The PCA was applied to a data matrix consisting of 12 sampling stations and mean concentrations of 23 water quality parameters, obtained in four sampling campaigns from June/2013 to November/2015. All 12 sampling stations were considered as main (weight>0.7) and therefore should remain in the monitoring program. The PCA pointed out that of the 23 measured parameters, only 16 are essential for water quality assessment, in the dry period and 17 in the rainy season. The HCA separated the stations of the monitoring network in 4 groups according to the water quality characteristics, considering the natural and anthropogenic impacts. The main impacts were originated from natural sources (mineral constituents) and the anthropogenic contributions were associated with urban input, sewage, industrial dumps and surface runoff from agricultural areas.Associação Brasileira de Recursos Hídricos2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100223RBRH v.23 2018reponame:RBRH (Online)instname:Associação Brasileira de Recursos Hídricos (ABRH)instacron:ABRH10.1590/2318-0331.231820170124info:eu-repo/semantics/openAccessAlves,José do Patrocinio HoraFonseca,Lucas CruzChielle,Raisa de Siqueira AlvesMacedo,Lúcia Calumby Barretoeng2018-07-04T00:00:00Zoai:scielo:S2318-03312018000100223Revistahttps://www.scielo.br/j/rbrh/https://old.scielo.br/oai/scielo-oai.php||rbrh@abrh.org.br2318-03311414-381Xopendoar:2018-07-04T00:00RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)false
dc.title.none.fl_str_mv Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
title Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
spellingShingle Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
Alves,José do Patrocinio Hora
Monitoring
Water quality
Principal component analysis
Cluster analysis
Sergipe River
title_short Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
title_full Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
title_fullStr Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
title_full_unstemmed Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
title_sort Monitoring water quality of the Sergipe River basin: an evaluation using multivariate data analysis
author Alves,José do Patrocinio Hora
author_facet Alves,José do Patrocinio Hora
Fonseca,Lucas Cruz
Chielle,Raisa de Siqueira Alves
Macedo,Lúcia Calumby Barreto
author_role author
author2 Fonseca,Lucas Cruz
Chielle,Raisa de Siqueira Alves
Macedo,Lúcia Calumby Barreto
author2_role author
author
author
dc.contributor.author.fl_str_mv Alves,José do Patrocinio Hora
Fonseca,Lucas Cruz
Chielle,Raisa de Siqueira Alves
Macedo,Lúcia Calumby Barreto
dc.subject.por.fl_str_mv Monitoring
Water quality
Principal component analysis
Cluster analysis
Sergipe River
topic Monitoring
Water quality
Principal component analysis
Cluster analysis
Sergipe River
description ABSTRACT This study evaluated the efficiency of the water quality monitoring network of the Sergipe river basin, using multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The PCA was applied to a data matrix consisting of 12 sampling stations and mean concentrations of 23 water quality parameters, obtained in four sampling campaigns from June/2013 to November/2015. All 12 sampling stations were considered as main (weight>0.7) and therefore should remain in the monitoring program. The PCA pointed out that of the 23 measured parameters, only 16 are essential for water quality assessment, in the dry period and 17 in the rainy season. The HCA separated the stations of the monitoring network in 4 groups according to the water quality characteristics, considering the natural and anthropogenic impacts. The main impacts were originated from natural sources (mineral constituents) and the anthropogenic contributions were associated with urban input, sewage, industrial dumps and surface runoff from agricultural areas.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2318-03312018000100223
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2318-0331.231820170124
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Recursos Hídricos
publisher.none.fl_str_mv Associação Brasileira de Recursos Hídricos
dc.source.none.fl_str_mv RBRH v.23 2018
reponame:RBRH (Online)
instname:Associação Brasileira de Recursos Hídricos (ABRH)
instacron:ABRH
instname_str Associação Brasileira de Recursos Hídricos (ABRH)
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institution ABRH
reponame_str RBRH (Online)
collection RBRH (Online)
repository.name.fl_str_mv RBRH (Online) - Associação Brasileira de Recursos Hídricos (ABRH)
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