Assessment of surface water quality using multivariate statistical techniques in the terengganu river basin [Penilaian kualiti air permukaan menggunakan teknik statistik multivariat bagi lembangan sungai Terengganu] - Azman, Azid; Mohd Ekhwan, Toriman; Hafizan, Juahir (Malaysian Journal of Analytical Sciences, 2015)
Multivariate Statistical techniques including cluster analysis, discriminant analysis, and principal component analysis/factor analysis were applied to investigate the spatial variation and pollution sources in the Terengganu river basin during 5 years of monitoring 13 water quality parameters at thirteen different stations. Cluster analysis (CA) classified 13 stations into 2 clusters low polluted (LP) and moderate polluted (MP) based on similar water quality characteristics. Discriminant analysis (DA) rendered significant data reduction with 4 parameters (pH, NH3 -NL, PO4 and EC) and correct assignation of 95.80%. The PCA/FA applied to the data sets, yielded in five latent factors accounting 72.42% of the total variance in the water quality data. The obtained varifactors indicate that parameters in charge for water quality variations are mainly related to domestic waste, industrial, runoff and agricultural (anthropogenic activities). Therefore, multivariate techniques are important in environmental management.