Assessment of Surface Water Quality Using Multivariate Statistical Techniques: A Case Study of Saigon River
Analysis and management of surface water quality is a need for many economic and production fields, but requires much time and forces. Multivariate statistical algorithms are applied to the dataset, which made up from 19 water quality criteria collected from 10 sampling sites across waterways from Sai Gon river basin. PCA-X (PCA – Principle Component Analysis) model of the dataset provides grouping by geographical location and flow direction, with explanation of the first 2 principal components are 62.4 and 25.2 %, respectively, which overviews the quality of water of these sampling sites, and allows determination of unexpected pollution sources from the system. These results are the basis of developing a method for delimiting and securing local pollution sites, assisting water quality monitoring and environmental management.