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Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques

This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA)...

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Main Author: Abu Samah, Mohd Armi
Format: Article
Language:English
Published: Springer Netherlands 2011
Subjects:
GE Environmental Sciences
Online Access:http://irep.iium.edu.my/74200/1/Juahir2011_Article_SpatialWaterQualityAssessmentO.pdf
http://irep.iium.edu.my/74200/
https://link.springer.com
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spelling my.iium.irep.742002019-09-04T06:11:37Z http://irep.iium.edu.my/74200/ Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques Abu Samah, Mohd Armi GE Environmental Sciences This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderate-pollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data. Springer Netherlands 2011 Article PeerReviewed application/pdf en http://irep.iium.edu.my/74200/1/Juahir2011_Article_SpatialWaterQualityAssessmentO.pdf Abu Samah, Mohd Armi (2011) Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques. Environmental Monitoring and Assessment, 173 (1-4). pp. 625-641. ISSN 1573-2959 https://link.springer.com
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic GE Environmental Sciences
spellingShingle GE Environmental Sciences
Abu Samah, Mohd Armi
Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques
description This study investigates the spatial water quality pattern of seven stations located along the main Langat River. Environmetric methods, namely, the hierarchical agglomerative cluster analysis (HACA), the discriminant analysis (DA), the principal component analysis (PCA), and the factor analysis (FA), were used to study the spatial variations of the most significant water quality variables and to determine the origin of pollution sources. Twenty-three water quality parameters were initially selected and analyzed. Three spatial clusters were formed based on HACA. These clusters are designated as downstream of Langat river, middle stream of Langat river, and upstream of Langat River regions. Forward and backward stepwise DA managed to discriminate six and seven water quality variables, respectively, from the original 23 variables. PCA and FA (varimax functionality) were used to investigate the origin of each water quality variable due to land use activities based on the three clustered regions. Seven principal components (PCs) were obtained with 81% total variation for the high-pollution source (HPS) region, while six PCs with 71% and 79% total variances were obtained for the moderate-pollution source (MPS) and low-pollution source (LPS) regions, respectively. The pollution sources for the HPS and MPS are of anthropogenic sources (industrial, municipal waste, and agricultural runoff). For the LPS region, the domestic and agricultural runoffs are the main sources of pollution. From this study, we can conclude that the application of environmetric methods can reveal meaningful information on the spatial variability of a large and complex river water quality data.
format Article
author Abu Samah, Mohd Armi
author_facet Abu Samah, Mohd Armi
author_sort Abu Samah, Mohd Armi
title Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques
title_short Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques
title_full Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques
title_fullStr Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques
title_full_unstemmed Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques
title_sort spatial water quality assessment of langat river basin (malaysia) using environmetric techniques
publisher Springer Netherlands
publishDate 2011
url http://irep.iium.edu.my/74200/1/Juahir2011_Article_SpatialWaterQualityAssessmentO.pdf
http://irep.iium.edu.my/74200/
https://link.springer.com
_version_ 1646012485304582144
score 13.211869

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