Spatio-temporal variability of seawater mixing in the coastal aquifers based on hydrogeochemical fingerprinting and statistical modeling

Hydrochemical fingerprints and health risk assessment of groundwater contamination in the Bohai Sea region, China

Seawater intrusion and human activities have significantly impacted coastal groundwater quality in many regions worldwide. This study systematically assessed groundwater chemistry, its suitability for drinking and irrigation (sample size, n = 3034), and exposure risks (n = 2863) across three key sub-regions of the Bohai Sea area: Bohai Bay, Liaodong Bay, and Laizhou Bay. Significant seasonal variations observed in groundwater chemistry at different depths in Bohai Bay region, with severe contamination from salinity-alkalinity and nitrogen-fluoride. SO₄-Cl-Na type groundwater predominates in Bohai Bay and Laizhou Bay areas, primarily influenced by evaporation dissolution and seawater mixing, while carbonate weathering and reverse ion exchange play secondary roles. In the Liaodong Bay region, SO₄-Cl-Ca-Mg water is dominant, driven primarily by carbonate weathering and reverse ion exchange. Groundwater evolution over time follows a complex sequence: Bohai Bay (mainly freshening) < Liaodong Bay (freshening > intrusion) < Laizhou Bay (freshening ≈ intrusion). Groundwater in the Bohai Sea region exhibits high sodium percentage, sodium adsorption ratio, total hardness, corrosion ratio, and residual sodium carbonate, with exceedance levels ranked as Bohai Bay > Laizhou Bay > Liaodong Bay, while irrigation efficiency follows the opposite trend. Fluoride, nitrogen, and bromine contamination pose significant health risks, particularly to children, and are likely linked to both anthropogenic interventions (such as industrial layout) and natural (geological) factors. Diseases types and incidence rates among residents closely correlate with groundwater pollutant levels, emphasizing the need for targeted pollution reduction and dynamic management strategies.

Delineation of groundwater potential zones and its extent of contamination from the hard rock aquifers in west-Bengal, India

This study evaluates the groundwater potential and quality in the parts of Chhotanagpur Gneissic Complex situated in the East Indian Shield. The region has faced groundwater development challenges for several decades. Therefore, in the study area, it is crucial to address the depletion of both groundwater quality and quantity, as this facilitates the identification of potential uncontaminated groundwater zones. The present study interprets the groundwater potential zones (GWPZ) utilizing an analytical hierarchical process (AHP) integrated with hydrogeochemical analysis. Several thematic maps were prepared to delineate the GPWZ. It has been found that ∼0.6% of the study area has a very good potential zone, 14.4% has good, 52% has moderate, and approximately 32% and 0.9% have low to very low prospective groundwater resources, respectively. The authentication of results was found to be excellent (91.4%) with the Area Under Curve (AUC). Analysis of hydrogeochemical data suggests that Mixed Ca-Na-HCO3, Mixed Ca-Mg-Cl, Ca-HCO3, and Na-Cl are the dominant water types in the study area. The principal component analysis suggests that Na+, Mg2+, Cl-, NO3-, and SO42- significantly contribute to groundwater chemistry. The K-means clustering and hierarchical cluster analysis classified groundwater samples into three clusters based on the hydrogeochemical characteristics. It is inferred that silicate weathering and reverse ion reactions through rock-water interaction control geogenic processes for groundwater chemistry. It is also inferred that regions with poor to unsuitable water quality indexes also have low GWPZ. Further, groundwater for irrigation is also accessed and found unsuitable at some locations. This research contributes to comprehending groundwater characteristics in analogous geological regions globally. Additionally, it assists in implementing preventive actions to mitigate groundwater contamination, consequently lowering health risks and formulating sustainable plans for the future.

Determination of high-risk factors and related spatially influencing variables of heavy metals in groundwater

Identifying high-risk factors (heavy metals (HMs) and pollution sources) by coupling receptor models and health risk assessment model (HRA) is a novel approach within the field of risk assessment. However, this coupled model ignores the contribution of spatial differentiation to high-risk factors, resulting in the assessment being subjective. Taking Dongting Plain (DTP) as an example, a coupling framework by jointly using the positive matrix factorization model (PMF), HRA, Monte Carlo simulation, and geo-detector was developed, aiming to identify high-risk factors in groundwater, and further explore key environmental variables influencing the spatial heterogeneity of high-risk factors. The results showed that at least 82.86 % of non-carcinogenic risks and 97.41 % of carcinogenic risks were unacceptable for people of all ages, especially infants and children. According to the relationships among HMs, pollution sources, and health risks, As and natural sources were defined as high-risk HMs and sources, respectively. The interactions among Holocene thickness, oxidation-reduction potential, and dissolved organic carbon emerged as the primary drivers of spatial variability in high-risk factors, with their combined explanatory power reaching up to 74%. This proposed framework provides a scientific reference for future studies and a practical reference for environmental authorities in developing effective pollution management measures.