Application of Multivariate Statistical Techniques in the surface water quality Assessment of Tigris River at Baghdad stretch, Iraq

Abstract

Multivariate statistical techniques namely factor analysis and cluster analysis were applied to evaluate spatial variations, and to interpret measured water quality data set in Tigris river at Baghdad. The water quality was monitored at seven different sites, along the water line, over a period of one year (2011) using 14 water quality parameters. When factor analysis was applied, three factors were identified, which were responsible from the 86.750% of the total variance of the water quality in the Tigris river. The first factor called the anthropogenic factor explained 49.829% of the total variance and the second factor called the erosion and rainfall factor explained 24.967% of the total variance. While, the third factor called the pH factor explained 11.954% of the total variance. Hierarchical cluster analysis was used to classify seven stations with similar properties and results distinguished three groups of stations. Results revealed that, water quality in Tigris river was strongly affected from anthropologic influences. Thus, these methods are believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality.