Abstract

In this study, Multivariate statistical techniques such as hierarchical cluster analysis (HCA), factor analysis (FA) and principle component analysis (PCA) are applied to surface water quality data sets obtained from drainage canals in Bafra Plain. The results of cluster analysis demonstrated that the months of year were divided into 2 seasons. The first period included irrigation season and second period included non-irrigation season. Cluster analysis classifies 7 drainage canals with 14 variables into two clusters reflecting different salinity levels. FA/PCA yielded three factors which are responsible for water quality variations explaining more than 90% of total variance of the data and allowed to group the selected water quality. The study have demonstrated the capability of multivariate statistical techniques for drainage water quality assessment and investigation of salinity in irrigated agricultural areas.

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