Surface River Water Quality Interpretation Using Environmetric Techniques: Case Study at Perlis River Basin, Malaysia

Mohd Saiful Samsudin; Hafizan Juahir; Sharifuddin M. Zain; Nur Hazirah Adnan
Environmetric techniques, cluster analysis (CA), discriminant analysis (DA) and principle component analysis (PCA) were applied to the data on water quality of Perlis River Basin, generated from 2003 until 2007. There are eleven monitoring stations with different sites for 30 parameters. Three spatial clusters are designated as downstream and upstream of Perlis River regions. Forward and backward stepwise DA managed to discriminate ten and thirteen water quality variables, respectively, from the original 30 variables. The final results for this study showed that hydrological observations are supported by principle component analysis (PCA). Additionally, this joint analysis makes it possible to observe the significance of the pollutent sources which contribute to pollution. Nine PCs with eigenvalues greater than 1 explaining 77% of the total variance in the water-quality data set. The investigation from PCA showed nine main pollution sources on Perlis River which are a mineral component of the river water, surface runoff sources, anthropogenic pollution sources, municipal sewage and wastewater treatment plants, leachate from industrial activities, seasonal impact of discharge and temperature, agricultural waste, oil waste from restaurant and road runoff. Finally, the application of environmetric methods can result in significant cost reduction and will allow more effective and efficient river quality management activities.
Environmetric; Perlis River; Water quality; Cluster analysis; Discriminant analysis; Principle component; factor analysis
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