A hydrogeochemical analysis of groundwater using hierarchical clustering analysis and fuzzy C-mean clustering methods in Arak plain, Iran

In recent years, groundwater level in Arak plain aquifer, Iran, declines due to overabstraction and sustainable management of the aquifer is changed to a vital issue. Spatiotemporal variation groundwater quality associated with identifying hydrogeochemical characteristics is the goal of this research. In the current study, graphical methods results are compared to two distinct clustering methods, hierarchical cluster analysis (HCA), and fuzzy C-mean (FCM) to analyze the hydrogeochemical dataset. Groundwater quality of Arak aquifer is monitored over an 11-year period in two-year intervals ranging from 2004 to 2014 (i.e., 2004, 2006, 2008, 2010, 2012, and 2014) by sampling from 52 abstraction wells for each year. Graphical methods identified dominant hydrogeochemical processes in the study area. The resulting clusters were categorized into freshwater (HC1, FC1), brackish-saline water (HC2, FC2), and saline water (HC3, FC3). The analysis resulted in three clusters including recharge, transition or mixing, and discharge zones, designated as FC1 and HC1, FC2 and HC2, and FC3 and HC3; respectively. The comparison of groundwater facies in 2004 and 2014 showed that the mixing zone (classes FC2 and FC3 and classes HC2 and HC3) has expanded with time. Observation well monitoring in the area showed that groundwater quality decrease due to groundwater level declines, especially in the residential zone. In addition, the role of geological formations in groundwater quality was evident in the distribution of clusters. Comprehensive regulation and integrated groundwater management is essential to prevent further degradation of groundwater quality in the region.