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Source Apportionment and Quality Assessment of Surface Water Using Principal Component Analysis and Multiple Linear Regression statistics

Nasly, Mohamed Ali and Hossain, Mohamed Amjed and Islam, Mir Sujaul (2013) Source Apportionment and Quality Assessment of Surface Water Using Principal Component Analysis and Multiple Linear Regression statistics. Environment Conservation Journal, 14 (3). pp. 9-16. ISSN 0972-3099 (Print), 2278-5124 (Online)

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Abstract

Principal component analysis (PCA) and multiple linear regressions (MLR) analysis were applied on the data set of surface water quality for source identification of pollution and their contribution on the variation of water quality. Results revealed that, most of the water quality parameters were found to be toxic compare to the national standard of Malaysia. PCA identified the sources as, ionic groups of salts, soil erosion and agricultural runoff, organic and nutrient pollutions from domestic wastewater, industrial sewage and wastewater treatment plants. MLR investigated the R= 0.968 and R2=0.934 and it was highly significant (p<0.01).

Item Type: Article
Uncontrolled Keywords: Multiple linear regressions rotation; Water pollution, water quality
Subjects: T Technology > TD Environmental technology. Sanitary engineering
T Technology > TA Engineering (General). Civil engineering (General)
Faculty/Division: Faculty of Civil Engineering & Earth Resources
Depositing User: Prof Datin Dr Nasly Mohamed Ali
Date Deposited: 19 Feb 2014 01:11
Last Modified: 28 Sep 2018 02:36
URI: http://umpir.ump.edu.my/id/eprint/5052
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