Application of multivariate statistical techniques in the assessment of groundwater quality in seawater intrusion area in Bafra Plain, Turkey.

Abstract

Multivariate statistical techniques such as cluster analysis and principal component analysis were performed on 28 groundwater wells in Bafra Plain. Cluster analysis results show that the groundwater in the study area is classified into three groups (A, B, and C), and factor analysis indicates that groundwater is composed of 89.64 % of total variance of 12 variables and is mainly affected by three factors. Factor 1 (seawater salinization) includes concentrations of electrical conductivity, TDS, Cl(-), Na(+), and sodium adsorption ratio, factor 2 (mixing water) includes δ(18)O, δD, and T, and factor 3 (fresh) includes Ca(2+). For determination of the source of water, Ca/Cl, Cl/HCO(3), Mg/Cl, and Ca/Na as initials and Mg/Ca and SO(4)/Cl as molar rates which were identified, the rates had been found to be very useful. Cluster analysis was made by using these rates and the waters were classified in two groups (group 1 and group 2). First group waters were affected by seawater, and the second group were very less affected by freshwater or seawater. According to the comparison of two different parameters, group 1 comprised group A and group B-2, -3, and -4 from the same wells, and group 2 comprised group B-1 and group C from the same well. As a result of this study, it could be said that multivariate statistical methods gave very useful results for the determination of the source.