Hydrochemical interpretation of groundwater in Yinchuan basin using self-organizing maps and hierarchical clustering.

Self-organizing maps (SOM) is emerging as an alternative to traditional clustering methods for the hydrochemical analysis of groundwater due to the visualization of high-dimensional data. In this study, a combined method of the SOM and hierarchical clustering was applied to analyze the hydrochemical characteristics of groundwater in phreatic aquifer in the Yinchuan basin, China. 154 groundwater samples classified by SOM were projected on 65 neurons and grouped into 6 clusters with hierarchical clustering. The results showed that there exist three principal types of groundwater in the study area, namely high HCO type (Cluster-1, 2, and 6), high SO type (Cluster-3, and 4), and high Na type (Cluster-5). Chadha diagram indicated that the phreatic water in Yinchuan basin mainly belongs to the group of alkaline earths that exceed alkali metals (n = 107, 69%). Rock weathering and evaporation-crystallization are the predominant mechanism in the hydrogeochemical evolution of phreatic groundwater. The present study suggested that the combined method of the SOM and hierarchical clustering provides a reliable approach for interpreting the hydrochemical characteristics of groundwater with high-dimensional data.