Hydrochemical assessment of groundwater using multivariate statistical methods and water quality indices (WQIs)

• Published in: Applied water science Vol. 14; no. 2; pp. 33 - 18
• Main Authors: Hamma, Bellal, Alodah, Abdullah, Bouaicha, Foued, Bekkouche, Mohamed Faouzi, Barkat, Ayoub, Hussein, Enas E.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.02.2024; Springer Nature B.V; SpringerOpen
• Subjects: Anhydrite; Anthropogenic factors; Aquatic Pollution; Aragonite; Arid regions; Arid zones; Calcite; Calcium; Chemical composition; Cluster analysis; Comparative Law; Contamination; Dolomite; Dolostone; Earth and Environmental Science; Earth Sciences; Factor analysis; Freshwater; Geochemical modeling; Geochemistry; Groundwater; Groundwater chemistry; Groundwater quality; Gypsum; Halite; Hydrochemical characteristics; Hydrogeology; Industrial and Production Engineering; Inland water environment; International & Foreign Law; Ion exchange; Kaolinite; Magnesium; Mathematical models; Modelling; Multivariate analysis; Multivariate statistical methods; Nanotechnology; Original Article; Pollution; Private International Law; Quality assessment; Quality control; Saturation; Saturation index; Smectites; Statistical methods; Sulphates; Sustainability management; Waste Water Technology; Water analysis; Water Industry/Water Technologies; Water Management; Water Pollution Control; Water quality; Water quality indices; Water resources; Water resources management; Water sampling; Water supply; Multivariate statistical methods; Groundwater quality; Water quality indices; Hydrochemical characteristics; Geochemical modeling; Contamination
• ISSN: 2190-5487; 2190-5495
• DOI: 10.1007/s13201-023-02084-0

Groundwater quality assessment is crucial for the sustainable management of water resources in arid regions, where groundwater is the primary source of water supply and increasing demand raises concerns. The study area in Southwest Algeria relies heavily on groundwater as a source of water supply, and the increasing demand for freshwater raises concerns about the quality of groundwater. To assess the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region, multivariate statistical methods, geochemical modeling and water quality indices were employed. The study revealed that the groundwater samples could be classified into four water groups using hierarchical cluster analysis Q mode (HCA), namely Ca–Mg–HCO 3 , Ca–Mg–Cl–SO 4 , Ca–SO 4 and Na–Cl. Factor analysis was used to identify the main factors controlling the study area’s hydrochemical processes. The results indicated that water–rock interaction, reverse ion exchange and anthropogenic pollution were the main hydrochemical processes affecting groundwater chemistry. The water quality index indicated that the groundwater was suitable for human consumption, with only 2.32% of the samples being unsuitable. Additionally, the groundwater was suitable for agricultural use, but salinity control was necessary. The saturation index values showed that the groundwater was supersaturated with aragonite, calcite, dolomite, anhydrite and gypsum, and undersaturated with halite. Ca-smectite, Mg-smectite and kaolinite were identified as the primary processes controlling the chemical composition of groundwater. The application of multivariate statistical methods, geochemical modeling and water quality indices provided a comprehensive understanding of the hydrochemical characteristics and water quality of groundwater in the Ain Sefra region. The findings of the study can serve as a useful basis for future studies on groundwater quality assessment in the region.