Hydrochemical Characteristics and Groundwater Quality Assessment Using an Integrated Approach of the PCA, SOM, and Fuzzy c-Means Clustering: A Case Study in the Northern Sichuan Basin

Abstract

Groundwater is a precious resource that is vital for human life. Widespread human activities occur in the Sichuan basin due to befitting climate and geological conditions, inducing a series of groundwater contamination. In this article, hydrochemical analysis, principal component analysis (PCA), self-organizing map (SOM), and fuzzy c-means clustering (FCM) were integrated to reveal the hydrochemical process and assess groundwater quality in the northern part of the Sichuan Basin based on a collection of 203 groundwater samples. The groundwater hydrochemical types were dominated by the HCO3-Ca type. The PCA results show both natural and anthropogenic factors contributed to the hydrochemical compositions. The combination of the SOM and FCM classifies neurons into two categories: the first category where NO2− and NH4+ are most similar, perhaps as anthropogenic sources of pollution, which pose serious threats to human health; and the second category, where the total dissolved solids, Ca2+, Na+, Cl−, SO42, Mg2+, and K+ are most similar, explained as the influence of natural factors. The ion source was determined by water–rock interactions: Na+ mainly comes from the dissolution of silicate rocks, while Ca2+, Mg2+, and HCO3− from the dissolution of calcite and dolomite. Cation exchange was recognized in the water–rock interactions. The achievements would provide a significant reference for groundwater protection in the Sichuan Basin.