Assessment of surface water quality of Songkhram River (Thailand) using environmetric techniques

Abstract

Environmetric techniques such as cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis were applied for the assessment of spatial and temporal variations of a large complex water-quality data set of the Songkhram River Basin, generated during 15 years (1995–2009) by monitoring of 17 parameters at 5 different sites. Hierarchical CA grouped five sampling sites into three clusters, i.e. upper stream (US), middle stream (MS) and lower stream (LS) sites, based on water-quality characteristics. FA/PCA applied to the data sets thus obtained resulted in six latent factors explaining 80.80, 73.95 and 73.78% of the total variance in water-quality data sets of LS, MS and US areas, respectively. This study highlights the usefulness of multivariate statistical assessment of complex databases in the identification of pollution sources and to better comprehend the spatial and temporal variations for effective river water-quality management.