Pattern recognition of Kedah River water quality data by implementation of principal component analysis

This study examines Kedah River Basin, Kedah, Malaysia, to achieve the objective of identifying and recognizing pollutant sources contributing to the water quality using a large dataset extending over a period of eight years, from the year 1997 to 2006. Principal Component Analysis was applied to si...

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Main Authors: Mohd, Isahak, Mansor, Muhd Ariffin, Awaluddin, Mohammad Roshide Amir, Mohd Nasir, Mohd Fahmi, Samsudin, Mohd Saiful, Juahir, Hafizan, Ramli, Norlafifah
Format: Article
Language:English
Published: IDOSI Publications 2011
Online Access:http://psasir.upm.edu.my/id/eprint/23396/
http://psasir.upm.edu.my/id/eprint/23396/1/23396.pdf
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author Mohd, Isahak
Mansor, Muhd Ariffin
Awaluddin, Mohammad Roshide Amir
Mohd Nasir, Mohd Fahmi
Samsudin, Mohd Saiful
Juahir, Hafizan
Ramli, Norlafifah
author_facet Mohd, Isahak
Mansor, Muhd Ariffin
Awaluddin, Mohammad Roshide Amir
Mohd Nasir, Mohd Fahmi
Samsudin, Mohd Saiful
Juahir, Hafizan
Ramli, Norlafifah
author_sort Mohd, Isahak
building UPM Institutional Repository
collection Online Access
description This study examines Kedah River Basin, Kedah, Malaysia, to achieve the objective of identifying and recognizing pollutant sources contributing to the water quality using a large dataset extending over a period of eight years, from the year 1997 to 2006. Principal Component Analysis was applied to simplify and provide a better understanding for the complex relationships among water quality parameters such as DO, BOD, COD, SS, pH, NH3-NL, temperature, conductivity, turbidity, salinity, dissolved solids, total solids, NO3, Cl, Ca, PO4, As, Hg, Cd, Cr, Pb, Zn, Ca, Fe, K, Mg, Na, Oil and Grease, MBAS, E.coli and Coliform. Graphical presentation of the data also helps a better view of the overall analysis to appoint sources of pollutant in accordance to their effect. Similar pattern of water quality data reveals nine Principal Components responsible for the data structure and explained 73% of the total variance of the data set. PC score model provided apportionment of various sources contributing to the water quality. Consequently the nine causes of pollutants involved are natural causes in terms of strong river current and geological location of this river, industrial and factories effluent discharge, construction, coal and metal mining, agricultural and sewage plant, human waste and illegal oil dumping.
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spelling upm-233962020-06-02T03:51:58Z http://psasir.upm.edu.my/id/eprint/23396/ Pattern recognition of Kedah River water quality data by implementation of principal component analysis Mohd, Isahak Mansor, Muhd Ariffin Awaluddin, Mohammad Roshide Amir Mohd Nasir, Mohd Fahmi Samsudin, Mohd Saiful Juahir, Hafizan Ramli, Norlafifah This study examines Kedah River Basin, Kedah, Malaysia, to achieve the objective of identifying and recognizing pollutant sources contributing to the water quality using a large dataset extending over a period of eight years, from the year 1997 to 2006. Principal Component Analysis was applied to simplify and provide a better understanding for the complex relationships among water quality parameters such as DO, BOD, COD, SS, pH, NH3-NL, temperature, conductivity, turbidity, salinity, dissolved solids, total solids, NO3, Cl, Ca, PO4, As, Hg, Cd, Cr, Pb, Zn, Ca, Fe, K, Mg, Na, Oil and Grease, MBAS, E.coli and Coliform. Graphical presentation of the data also helps a better view of the overall analysis to appoint sources of pollutant in accordance to their effect. Similar pattern of water quality data reveals nine Principal Components responsible for the data structure and explained 73% of the total variance of the data set. PC score model provided apportionment of various sources contributing to the water quality. Consequently the nine causes of pollutants involved are natural causes in terms of strong river current and geological location of this river, industrial and factories effluent discharge, construction, coal and metal mining, agricultural and sewage plant, human waste and illegal oil dumping. IDOSI Publications 2011 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/23396/1/23396.pdf Mohd, Isahak and Mansor, Muhd Ariffin and Awaluddin, Mohammad Roshide Amir and Mohd Nasir, Mohd Fahmi and Samsudin, Mohd Saiful and Juahir, Hafizan and Ramli, Norlafifah (2011) Pattern recognition of Kedah River water quality data by implementation of principal component analysis. World Applied Sciences Journal, 14. pp. 66-72. ISSN 1818-4952; ESSN: 1991-6426 https://www.idosi.org/wasj/wasj14(UPM)2011.htm
spellingShingle Mohd, Isahak
Mansor, Muhd Ariffin
Awaluddin, Mohammad Roshide Amir
Mohd Nasir, Mohd Fahmi
Samsudin, Mohd Saiful
Juahir, Hafizan
Ramli, Norlafifah
Pattern recognition of Kedah River water quality data by implementation of principal component analysis
title Pattern recognition of Kedah River water quality data by implementation of principal component analysis
title_full Pattern recognition of Kedah River water quality data by implementation of principal component analysis
title_fullStr Pattern recognition of Kedah River water quality data by implementation of principal component analysis
title_full_unstemmed Pattern recognition of Kedah River water quality data by implementation of principal component analysis
title_short Pattern recognition of Kedah River water quality data by implementation of principal component analysis
title_sort pattern recognition of kedah river water quality data by implementation of principal component analysis
url http://psasir.upm.edu.my/id/eprint/23396/
http://psasir.upm.edu.my/id/eprint/23396/
http://psasir.upm.edu.my/id/eprint/23396/1/23396.pdf