J Contam Hydrol 2025 May 28;274:104628. doi: 10.1016/j.jconhyd.2025.104628.

Spatial analysis of the potential impacts of contaminated areas in the Upper Tietê Basin (São Paulo, Brazil) on wells and aquifers.

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The Upper Tietê is prominent for being the basin with the highest contaminated areas in São Paulo, Brazil, and these areas significantly compromise the quality of groundwater in the basin, directly affecting the resident population. Acknowledging the criticality of formulating indicators for effective aquifer management, we attempted to identify and assess the risk, vulnerability, and contamination degrees of aquifers and wells in the Upper Tietê Basin. To do this, we applied the aquifer vulnerability index (AVI) method to evaluate the aquifer vulnerability in the region; the delineation and identification of wellhead protection areas and at-risk wells, respectively; and the integrated risk index by integrating the data on social and aquifer vulnerabilities, hazards, and exposure. As inputs for AVI analysis, we estimated the hydraulic conductivity and unsaturated-sedimentary-layer thickness of the aquifers. The hydraulic activity, which was estimated by an empirical flow method incorporating pipe-radius data, was interpolated by co-kriging (using well-flow parameters as auxiliary variables), and unsaturated thickness was interpolated by ordinary kriging. The results revealed the high vulnerability of the aquifers to contamination, mainly because of their minimal unsaturated-layer thicknesses. Furthermore, 7958 at-risk wells were identified around the basin (77.15 %), and the outskirts of the basin accounted for the most vulnerable municipalities. Further, the wellhead protection areas were also delimited by interpolating stabilization flow by indicator kriging. Furthermore, we developed an innovative social vulnerability indicator for groundwater usage and integrated it with AVI analysis. Overall, our findings offer relevant insights into aquifer management and contamination control, mainly because of the holistic approach, serving as a basis for identifying regions with the highest contamination risks for timely prevention and mitigation through appropriate actions.

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