Identification of chemical processes using principal component analysis

Abstract EN

Principal component analysis (PCA) is useful technique for interpreting commonly collected groundwater quality data and relating the data to specific hydrochemical processes.

Thus, multivariate analysis in hydrochemistry allows avoidance limitations that are associated with classical methods, such as Durov’s and trilinear diagrams.

Six components which represent different chemical processes were identified and their relative areal impact determined.

Comparisons made among the results presented and the findings of earlier studies high light the descriptive capabilities of principal component analysis as an effective exploratory tool in hydrochemical investigations.