Characterization of spatial patterns in river water quality using chemometric techniques

Water pollution has become a growing threat to human society and natural ecosystem in recent decades, increasing the need to better understand the variabilities of pollutants within aquatic systems. This study presents the application of two chemometric techniques, namely, cluster analysis (CA) and...

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Published in:Sains Malaysiana
Main Author: Baharuddin N.; Saim N.; Zain S.M.; Juahir H.; Osman R.; Aziz A.
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907663510&partnerID=40&md5=c06647ab1f20ae8432101eeec38dbbdd
id 2-s2.0-84907663510
spelling 2-s2.0-84907663510
Baharuddin N.; Saim N.; Zain S.M.; Juahir H.; Osman R.; Aziz A.
Characterization of spatial patterns in river water quality using chemometric techniques
2014
Sains Malaysiana
43
9

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907663510&partnerID=40&md5=c06647ab1f20ae8432101eeec38dbbdd
Water pollution has become a growing threat to human society and natural ecosystem in recent decades, increasing the need to better understand the variabilities of pollutants within aquatic systems. This study presents the application of two chemometric techniques, namely, cluster analysis (CA) and principal component analysis (PCA). This is to classify and identify the water quality variables into groups of similarities or dissimilarities and to determine their significance. Six stations along Kinta River, Perak, were monitored for 30 physical and chemical parameters during the period of 1997-2006. Using CA, the 30 physical and chemical parameters were classified into 4 clusters; PCA was applied to the datasets and resulted in 10 varifactors with a total variance of 78.06%. The varifactors obtained indicated the significance of each of the variables to the pollution of Kinta River. © 2014, Penerbit Universiti Kebangsaan Malaysia. All rights resaerved.
Penerbit Universiti Kebangsaan Malaysia
1266039
English
Article

author Baharuddin N.; Saim N.; Zain S.M.; Juahir H.; Osman R.; Aziz A.
spellingShingle Baharuddin N.; Saim N.; Zain S.M.; Juahir H.; Osman R.; Aziz A.
Characterization of spatial patterns in river water quality using chemometric techniques
author_facet Baharuddin N.; Saim N.; Zain S.M.; Juahir H.; Osman R.; Aziz A.
author_sort Baharuddin N.; Saim N.; Zain S.M.; Juahir H.; Osman R.; Aziz A.
title Characterization of spatial patterns in river water quality using chemometric techniques
title_short Characterization of spatial patterns in river water quality using chemometric techniques
title_full Characterization of spatial patterns in river water quality using chemometric techniques
title_fullStr Characterization of spatial patterns in river water quality using chemometric techniques
title_full_unstemmed Characterization of spatial patterns in river water quality using chemometric techniques
title_sort Characterization of spatial patterns in river water quality using chemometric techniques
publishDate 2014
container_title Sains Malaysiana
container_volume 43
container_issue 9
doi_str_mv
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907663510&partnerID=40&md5=c06647ab1f20ae8432101eeec38dbbdd
description Water pollution has become a growing threat to human society and natural ecosystem in recent decades, increasing the need to better understand the variabilities of pollutants within aquatic systems. This study presents the application of two chemometric techniques, namely, cluster analysis (CA) and principal component analysis (PCA). This is to classify and identify the water quality variables into groups of similarities or dissimilarities and to determine their significance. Six stations along Kinta River, Perak, were monitored for 30 physical and chemical parameters during the period of 1997-2006. Using CA, the 30 physical and chemical parameters were classified into 4 clusters; PCA was applied to the datasets and resulted in 10 varifactors with a total variance of 78.06%. The varifactors obtained indicated the significance of each of the variables to the pollution of Kinta River. © 2014, Penerbit Universiti Kebangsaan Malaysia. All rights resaerved.
publisher Penerbit Universiti Kebangsaan Malaysia
issn 1266039
language English
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