Controls of Sedimentary Architecture on Groundwater Hydrochemistry and Human Health Risks in the Piedmont Alluvial Plain, Eastern Hebei

Quantifying how sedimentary architecture governs groundwater quality remains a critical research challenge in hydrogeology. This challenge spans from hydrochemical evolution to public health impacts. To address this knowledge gap, we developed an integrated quantitative framework to analyze the complete "geological-to-health" pathway in the northwestern Tangshan piedmont alluvial plain. We conducted a systematic analysis of 42 groundwater samples using three complementary approaches: hydrochemical characterization, absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling, and health risk assessment. This multi-method investigation demonstrates the fundamental control of sedimentary architecture over groundwater systems. This study establishes that groundwater in the study area is predominantly of the weakly alkaline HCO₃-Ca·Mg type. Ion correlation analysis indicates that mineral dissolution (mainly carbonates and evaporites) governs groundwater chemistry and enhances NO₂ ^- migration through increased ionic strength. Gibbs diagrams, ion ratios, and saturation index (SI) collectively demonstrate that sedimentary architecture exerts fundamental control over hydrogeochemical processes. The chemical evolution is primarily governed by coupled carbonate precipitation and evaporite dissolution. High-permeability zones within this architectural framework facilitate anthropogenic contamination. APCS-MLR receptor modeling quantifies the anthropogenic contribution at 20.7%, while also revealing that all contaminant sources are constrained by architectural heterogeneity. Health risk assessment identifies F^- as posing the most significant noncarcinogenic risk. Hazard indices for infants (3.318) and children (2.903) substantially exceed those for adults (1.288). These findings establish a mechanistic framework linking subsurface architectural heterogeneity to public health outcomes. This framework provides a transferable paradigm for predictive groundwater quality management.