l This study has been carried out to assess the water quality of a drinking/using water reservoir in Turkey by using the different multivariate statistical techniques (Bray-Curtis cluster analysis (BCCA), principle component analysis (PCA), and correspondence analysis (CA) methods). The annual dataset belonging physical and chemical features in the reservoir was obtained by the monthly intervals between the years 2010 and 2011. A total of 15 parameters (temperature, dissolved oxygen (DO), biological oxygen demand (BOD5), light permeability, conductivity, salinity, chloride, pH, total hardness, Ca, Mg, NO2-N, NO3-N, o-PO4, SO4) have been monitored at three different sampling stations in the reservoir and a total of 495 observations were grouped statistically. The sampled periods have been classified into three different groups by using the BCCA. The results were supported by the PCA and CA statistical methods. Consequently, in order to determine and to evaluate for large complex datasets that belong to environmental properties, multivariate analyses are very useful techniques. Thus, the sampling periods to monitor the physicochemical including in a water resource can be determined.