Multivariate analysis of the Morava river plain groundwater

Abstract

One of the most significant sources of drinking water is groundwater. Therefore, it is crucial to assess groundwater quality and ascertain potential causes of contamination to address pollution and provide people with clean drinking water. In this paper, groundwater in the Morava River plain is investigated and analyzed for 14 physicochemical parameters, such as pH, EC, HCO3 , NO3 - , PO4 3- , Cl- , SO4 2- , Na+ , K+ , Mg2+, Ca2+, Fe, Mn, and As. To determine groundwater facies and sources of pollution, three multivariate statistical analysis techniques were applied. Hierarchical Cluster Analysis (HCA) was used to group groundwater samples based on their similar chemical characteristics and to determine the dominant hydrochemical groundwater type. According to HCA results, groundwater samples were clustered into three groups, including Cluster 1 (72.3%), Cluster 2 (19.7%), and Cluster 3 (7.9%), and the main groundwater type was Ca-HCO3 type. Factor Analysis (FA) incorporated with Pearson correlation analysis was conducted to determine the main sources of pollution. Water-rock interactions and agricultural practices were identified as primary pollution sources in the investigated area.