This study was carried out to evaluate the surface water quality of the Atikhisar Reservoir and Sari ay Creek. Multivariate statistical techniques such as Cluster analysis (CA), principal component analysis (PCA), multidimensional Scaling (MDS), and univariate statistical techniques such as two-way ANOVA were used to analyze the data. Three different groups were formed based on Cluster analysis. Two-way ANOVA test results showed that interaction effects of any variables of the reservoir were non-significant but the interaction effects of pH in the creek were significant. Temperature (T), electrical conductivity (EC), oxygen saturation (OS), biological oxygen demand (BOD), chemical oxygen demand (COD), total phosphate (TP), total nitrate (TN), salinity (Sal), pH, Chl-a, and total suspended solids (TSS) of the reservoir were significantly different among seasons. While differences of T, EC, DO, TP, Chl-a, and TSS of the Sari ay Creek were significant among seasons, only the differences of temperature among the stations were significant. Multi dimensional scaling (MDS) analysis results revealed that the variables such as EC, Sal, OS, T and TN affected the differences among the sites, while the other variable groups were showing a similarity with the COD, BOD, TSS, AD, TP, pH, DO and Chl-a. The principle component analysis (PCA) results showed that the eigenvalues of the first 5 PCA were larger than 1.00, suggesting that they explained 98 % of the total variation.