Groundwater is one of the most important sources of freshwater globally and has a key role in sustaining the ecol. value of many areas.These valuable and vulnerable groundwater resources are under the pressure of many external pollution threats, such as industrial, domestic, and agricultural chems.To prevent undesirable consequences to future groundwater resources, comprehensive and proper knowledge of groundwater quality and contamination levels is vital at the local/regional scale.In this study, multivariate statistical techniques, such as a correlation matrix, hierarchical cluster anal., and factor anal., were applied to water quality data sets obtained from 24 wells located in the Goksu Plain.These techniques were applied primarily to nineteen hydrochem. parameters collected between May 2011 and Apr. 2012.The results obtained from the correlation matrix showed that the seawater descriptors such as EC, TDS, Cl-, Na+, and K+ were strongly correlated.Principal component anal. indicated that most of the variations in groundwater were caused by four factors that were responsible for the water quality, which represented more than 80.22% of the total data variance.The hierarchical average linkage cluster anal. produced two major clusters that reflected seawater salinity.