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Sahoo, P. K., Virk, H. S., Powell, M. A., Kumar, R., Pattanaik, J. K., Salomão, G. N., et al. (2022). Meta-analysis of uranium contamination in groundwater of the alluvial plains of Punjab, northwest India: Status, health risk, and hydrogeochemical processes. Science of The Total Environment, 807, 151753.
Abstract: Despite numerous studies, there are many knowledge gaps in our understanding of uranium (U) contamination in the alluvial aquifers of Punjab, India. In this study, a large hydrogeochemical dataset was compiled to better understand the major factors controlling the mobility and enrichment of uranium (U) in this groundwater system. The results showed that shallow groundwaters (\textless60 m) are more contaminated with U than from deeper depths (\textgreater60 m). This effect was predominant in the Southwest districts of the Malwa, facing significant risk due to chemical toxicity of U. Groundwaters are mostly oxidizing and alkaline (median pH: 7.25 to 7.33) in nature. Spearman correlation analysis showed that U concentrations are more closely related to total dissolved solids (TDS), salinity, Na, K, HCO3−, NO3− Cl−, and F− in shallow water than deep water, but TDS and salinity remained highly correlated (U-TDS: ρ = 0.5 to 0.6; U-salinity: ρ = 0.5). This correlation suggests that the salt effect due to high competition between ions is the principal cause of U mobilization. This effect is evident when the U level increased with increasing mixed water species (Na-Cl, Mg-Cl, and Na-HCO3). Speciation data showed that the most dominant U species are Ca2UO2(CO3)2− and CaUO2(CO3)3−, which are responsible for the U mobility. Based on the field parameters, TDS along with pH and oxidation-reduction potential (ORP) were better fitted to U concentration above the WHO guideline value (30 μg.L−1), thus this combination could be used as a quick indicator of U contamination. The strong positive correlation of U with F− (ρ = 0.5) in shallow waters indicates that their primary source is geogenic, while anthropogenic factors such as canal irrigation, groundwater table decline, and use of agrochemicals (mainly nitrate fertilizers) as well as climate-related factors i.e., high evaporation under arid/semi-arid climatic conditions, which result in higher redox and TDS/salinity levels, may greatly affect enrichment of U. The geochemical rationale of this study will provide Science-based-policy implications for U health risk assessment in this region and further extrapolate these findings to other arid/semi-arid areas worldwide.
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Jing, M., Kumar, R., Attinger, S., Li, Q., Lu, C., & Heße, F. (2021). Assessing the contribution of groundwater to catchment travel time distributions through integrating conceptual flux tracking with explicit Lagrangian particle tracking. Advances in Water Resources, 149, 103849.
Abstract: Travel time distributions (TTDs) provide an effective way to describe the transport and mixing processes of water parcels in a subsurface hydrological system. A major challenge in characterizing catchment TTD is quantifying the travel times in deep groundwater and its contribution to the streamflow TTD. Here, we develop and test a novel modeling framework for an integrated assessment of catchment scale TTDs through explicit representation of 3D-groundwater dynamics. The proposed framework is based on the linkage between a flux tracking scheme with the surface hydrologic model (mHM) for the soil-water compartment and a particle tracking scheme with the 3D-groundwater model OpenGeoSys (OGS) for the groundwater compartment. This linkage provides us with the ability to simulate the spatial and temporal dynamics of TTDs in these different hydrological compartments from grid scale to regional scale. We apply this framework in the Nägelstedt catchment in central Germany. Simulation results reveal that both shape and scale of grid-scale groundwater TTDs are spatially heterogeneous, which are strongly dependent on the topography and aquifer structure. The component-wise analysis of catchment TTD shows a time-dependent sensitivity of transport processes in soil zone and groundwater to driving meteorological forcing. Catchment TTD exhibits a power-law shape and fractal behavior. The predictive uncertainty in catchment mean travel time is dominated by the uncertainty in the deep groundwater rather than that in the soil zone. Catchment mean travel time is severely biased by a marginal error in groundwater characterization. Accordingly, we recommend to use multiple summary statistics to minimize the predictive uncertainty introduced by the tailing behavior of catchment TTD.
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