Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems

This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU cat...

Full description

Bibliographic Details
Main Authors: Ajorlo, Majid, Abdullah, Ramdzani, Yusoff, Mohd Kamil, Abd Halim, Mohd Ridzwan, Mohd Hanif, Ahmad Husni, Willms, Walter D., Ebrahimian, Mahboubeh
Format: Article
Language:English
Published: Springer 2013
Online Access:http://psasir.upm.edu.my/id/eprint/29366/
http://psasir.upm.edu.my/id/eprint/29366/1/Multivariate%20statistical%20techniques%20for%20the%20assessment%20of%20seasonal%20variations%20in%20surface%20water%20quality%20of%20pasture%20ecosystems.pdf
_version_ 1848846379831525376
author Ajorlo, Majid
Abdullah, Ramdzani
Yusoff, Mohd Kamil
Abd Halim, Mohd Ridzwan
Mohd Hanif, Ahmad Husni
Willms, Walter D.
Ebrahimian, Mahboubeh
author_facet Ajorlo, Majid
Abdullah, Ramdzani
Yusoff, Mohd Kamil
Abd Halim, Mohd Ridzwan
Mohd Hanif, Ahmad Husni
Willms, Walter D.
Ebrahimian, Mahboubeh
author_sort Ajorlo, Majid
building UPM Institutional Repository
collection Online Access
description This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO3, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH3, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH3, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.
first_indexed 2025-11-15T09:01:47Z
format Article
id upm-29366
institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T09:01:47Z
publishDate 2013
publisher Springer
recordtype eprints
repository_type Digital Repository
spelling upm-293662019-11-14T07:47:22Z http://psasir.upm.edu.my/id/eprint/29366/ Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems Ajorlo, Majid Abdullah, Ramdzani Yusoff, Mohd Kamil Abd Halim, Mohd Ridzwan Mohd Hanif, Ahmad Husni Willms, Walter D. Ebrahimian, Mahboubeh This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO3, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH3, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH3, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures. Springer 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/29366/1/Multivariate%20statistical%20techniques%20for%20the%20assessment%20of%20seasonal%20variations%20in%20surface%20water%20quality%20of%20pasture%20ecosystems.pdf Ajorlo, Majid and Abdullah, Ramdzani and Yusoff, Mohd Kamil and Abd Halim, Mohd Ridzwan and Mohd Hanif, Ahmad Husni and Willms, Walter D. and Ebrahimian, Mahboubeh (2013) Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems. Environmental Monitoring and Assessment, 185 (10). pp. 8649-8658. ISSN 0167-6369; ESSN: 1573-2959 http://link.springer.com/article/10.1007%2Fs10661-013-3201-8 10.1007/s10661-013-3201-8
spellingShingle Ajorlo, Majid
Abdullah, Ramdzani
Yusoff, Mohd Kamil
Abd Halim, Mohd Ridzwan
Mohd Hanif, Ahmad Husni
Willms, Walter D.
Ebrahimian, Mahboubeh
Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
title Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
title_full Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
title_fullStr Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
title_full_unstemmed Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
title_short Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
title_sort multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems
url http://psasir.upm.edu.my/id/eprint/29366/
http://psasir.upm.edu.my/id/eprint/29366/
http://psasir.upm.edu.my/id/eprint/29366/
http://psasir.upm.edu.my/id/eprint/29366/1/Multivariate%20statistical%20techniques%20for%20the%20assessment%20of%20seasonal%20variations%20in%20surface%20water%20quality%20of%20pasture%20ecosystems.pdf