From contamination to decision-making: integrated indices and multivariate analysis for groundwater health risk assessment.

Abstract

This study assessed the health risks associated with groundwater contamination by metals and metalloids in the Tabalaopa-Aldama aquifer, located in the arid region of northern Mexico. A total of 40 drinking water wells were sampled and analyzed for elements including arsenic, aluminum, uranium, iron, nickel, and zinc. The results revealed that a significant proportion of the wells exceeded national and international permissible limits for these contaminants. To evaluate the potential impact on public health, three complementary indices were applied: the health risk index, the hazard quotient, and the water quality index. The integrated analysis demonstrated high consistency among the indices, particularly highlighting arsenic, iron, and nickel as critical contaminants. Multivariate statistical techniques further identified key patterns and groupings, revealing that contaminant levels are influenced by geological and hydrological factors such as well depth and flow rate. The integration of the results from these indices through multivariate statistical methods - specifically Principal Component Analysis (PCA) and cluster analysis - provided a valuable assessment of the concordance and divergences between the indices. This allowed for more robust identification of high-risk areas and contributed to better-informed decision-making for targeted water quality management and public health protection.