Hydrochemical Characterization and Water Quality Assessment of Pre-Monsoon Samples Using EWQI, Ionic Facies Analysis, and Correlation Statistics

Why It Matters

Understanding the dominant geochemical controls and ion relationships helps water managers prioritize treatment and monitoring, especially for contaminants like arsenic that exhibit localized behavior. Early assessment before monsoon influx can mitigate health risks and guide sustainable resource use.

Key Takeaways

• EWQI classifies 15% of samples as extremely poor, 2.5% excellent
• Rock‑water interaction dominates hydrochemistry, yielding alkaline, mineralized water
• Electrical conductivity strongly correlates with major cations and anions
• Arsenic shows weak correlation, indicating localized source controls

Pulse Analysis

Pre‑monsoon water quality assessments are critical for regions that rely on groundwater for drinking and agriculture. By employing the Entropy‑Weighted Water Quality Index, researchers can translate complex ion concentrations into a single, intuitive score that highlights problem areas. The EWQI’s nuanced grading—ranging from extremely poor to excellent—provides policymakers with a clear hierarchy of intervention priorities, especially in basins where seasonal recharge can rapidly alter chemical balances.

Beyond a single index, the study leveraged classic hydrogeochemical tools such as Gibbs, Piper, and Durov diagrams to decode the underlying processes shaping water chemistry. The dominance of rock‑water interaction points to natural mineral dissolution as the primary source of alkalinity and elevated total dissolved solids. This insight helps differentiate between anthropogenic pollution and geogenic contributions, guiding targeted remediation strategies. Moreover, the identification of specific ionic facies informs the selection of appropriate treatment technologies, such as ion exchange for high calcium‑magnesium waters.

Statistical correlation analysis added another layer of understanding, revealing that electrical conductivity serves as a reliable proxy for major ion loads, while trace elements like arsenic behave independently. The weak association of arsenic with major ions suggests localized contamination hotspots, perhaps linked to specific lithologies or industrial activities. Recognizing these patterns enables focused monitoring and early warning systems, reducing exposure risks before the monsoon dilutes concentrations. In sum, integrating EWQI scoring with geochemical visualizations and correlation statistics equips water managers with a comprehensive toolkit for proactive, science‑driven decision‑making.