Drinking water quality assessment through multivariate statistical approach and formulated PCA-based contamination...

Area of Science:

• Environmental Science
• Public Health
• Water Quality Management

Background:

• Ensuring safe drinking water is a critical global challenge, especially in rapidly urbanizing, groundwater-stressed, and semi-arid regions.
• Conventional water quality monitoring methods often lack statistical integration and holistic risk assessment capabilities.
• Semi-arid regions face unique pressures on water resources, exacerbating public health and sustainability concerns.

Purpose of the Study:

• To evaluate the physicochemical, heavy metal, and bacteriological contamination of drinking water sources in a water-stressed region.
• To assess the antibiotic resistance profiles of bacterial isolates from contaminated drinking water.
• To apply an advanced multivariate statistical framework for enhanced water quality assessment and risk stratification.

Main Methods:

• Analysis of 167 drinking water samples from surface and groundwater sources.
• Assessment of physicochemical parameters, heavy metals, bacteriological indicators (E. coli, total coliforms), and antibiotic resistance.
• Application of Principal Component Analysis (PCA) for a Drinking Water Contamination Index (DWCI), Mahalanobis Distance (MD) for outlier detection, and K-means clustering.

Main Results:

• Significant contamination detected, with multiple samples exceeding WHO limits for TDS, fluoride, lead, and chromium.
• High microbial loads and frequent exceedances of safe thresholds for E. coli and total coliforms, indicating fecal contamination.
• 93.6% of E. coli isolates showed multidrug resistance, with a high Multiple Antibiotic Resistance Index (MARI), and groundwater showed consistently higher contamination.

Conclusions:

• Integrated multivariate statistical techniques effectively characterize complex contamination patterns in drinking water.
• The developed DWCI framework provides a replicable and cost-effective approach for water quality monitoring and risk-based regulation.
• Findings support efforts towards achieving Sustainable Development Goal 6 (SDG-6) for safe drinking water access in water-stressed environments.