Groundwater quality in the Wilaya of Djelfa, Algeria, was assessed using key physicochemical parameters combined with multivariate and index-based analyses. Principal Component Analysis (PCA) revealed two main hydrochemical patterns: PC1 (57.63% variance) reflects mineralization and salinity, driven by conductivity, TDS, and salinity, while PC2 (13.32% variance) captures contrasts in pH, turbidity, and bicarbonate. Hierarchical Cluster Analysis (HCA) corroborated these findings, grouping wells based on mineral content, salinity, and independent contamination indicators such as nitrate and pH. Water Quality Index (WQI) results classified 15 wells as Good (WQI 26-50), OS04 as Excellent (WQI = 24.04), DZ04 as Poor (WQI = 75.40), and DZ03 as Very Poor (WQI = 550.36) due to extreme turbidity (52.3 NTU). The sensitivity analysis identifies TDS as the most influential parameter affecting WQI, followed by bicarbonate and sulfate. These findings highlight the need for targeted interventions in high-risk wells, including regular monitoring, appropriate treatment, and mitigation of contamination from agricultural runoff and wastewater. The integrated PCA, HCA, and WQI framework provides a robust tool for understanding groundwater variability and guiding sustainable water management in semi-arid aquifers.