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Kumar, V., Setia, R., Pandita, S., Singh, S., & Mitran, T. (2022). Assessment of U and As in groundwater of India: A meta-analysis. Chemosphere, 303, 135199.
Abstract: More than 2.5 billion people depend upon groundwater worldwide for drinking, and giving quality water has become one of the great apprehensions of human culture. The contamination of Uranium (U) and Arsenic (As) in the groundwater of India is gaining global attention. The current review provides state-of-the-art groundwater contamination with U and As in different zones of India based on geology and soil texture. The average concentration of U in different zones of India was in the order: West Zone (41.07 μg/L) \textgreater North Zone (37.7 μg/L) \textgreater South Zone (13.5 μg/L)\textgreater Central Zone (7.4 μg/L) \textgreater East Zone (5.7 μg/L) \textgreaterSoutheast Zone (2.4 μg/L). The average concentration of As in groundwater of India is in the order: South Zone (369.7 μg/L)\textgreaterCentral Zone (260.4 μg/L)\textgreaterNorth Zone (67.7 μg/L)\textgreaterEast Zone (60.3 μg/L)\textgreaterNorth-east zone (9.78 μg/L)\textgreaterWest zone (4.14 μg/L). The highest concentration of U and As were found in quaternary sediments, but U in clay skeletal and As in loamy skeletal. Results of health risk assessment showed that the average health quotient of U in groundwater for children and adults was less than unity. In contrast, it was greater than unity for As posing a harmful impact on human health. This review provides the baseline data regarding the U and As contamination status in groundwater of India, and appropriate, effective control measures need to be taken to control this problem.
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Heidari, B., Prideaux, V., Jack, K., & Jaber, F. H. (2023). A planning framework to mitigate localized urban stormwater inlet flooding using distributed Green Stormwater Infrastructure at an urban scale: Case study of Dallas, Texas. Journal of Hydrology, 621, 129538.
Abstract: Mitigation of localized pluvial flooding is one of the major resiliency goals in urban environments, and Green Stormwater Infrastructure (GSI) has the potential to deliver such an outcome. However, there is a lack of systematic approaches to prioritize investment in different candidate areas. This study provides a framework to identify vulnerable stormwater drainage inlets and their contributing areas, prioritize them, identify dominant factors in their selection, assess the potential of GSI in mitigating their overflows, and compare the impact and its cost to gray infrastructure upgrade alternatives. Using SWMM 5.1.013, decision trees, and a volumetric-based assessment of GSI overflow capture, we applied the framework to the City of Dallas, Texas, for three design storms with three GSI practices— bioretention cells, raingardens, and rainwater harvesting tanks. Results showed that there was a significant increase in the number of overflowing stormwater drainage inlets, referred to as hotspots, and their contributing subwatersheds, referred to as opportunity areas, with more intense storms especially in problematic watersheds. Also, prioritization results provided a series of maps to rank the opportunity areas based on overflow severity, recurrence of the overflows, and GSI availability. Moreover, classification results showed that inlet features, especially the inlet depth, were the dominant factors in the identification of the non-problematic inlets. Finally, the GSI impact assessment showed substantial overflow mitigation even at the “very high” severity levels when GSI is comprehensively deployed across opportunity areas. Despite gray infrastructure upgrades yielding higher reduction levels, their cost per cubic meter was higher than GSI. Therefore, a combination of GSI and gray results in maximum overflow reduction at a lower cost compared to common practices.
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Bresinsky, L., Kordilla, J., Hector, T., Engelhardt, I., Livshitz, Y., & Sauter, M. (2023). Managing climate change impacts on the Western Mountain Aquifer: Implications for Mediterranean karst groundwater resources. Journal of Hydrology X, 20, 100153.
Abstract: Many studies highlight the decrease in precipitation due to climate change in the Mediterranean region, making it a prominent hotspot. This study examines the combined impacts of climate change and three groundwater demand scenarios on the water resources of the Western Mountain Aquifer (WMA) in Israel and the West Bank. While commonly used methods for quantifying groundwater recharge and water resources rely on regression models, it is important to acknowledge their limitations when assessing climate change impacts. Regression models and other data-driven approaches are effective within observed variability but may lack predictive power when extrapolated to conditions beyond historical fluctuations. A comprehensive assessment requires distributed process-based numerical models incorporating a broader range of relevant physical flow processes and, ideally, ensemble model projections. In this study, we simulate the dynamics of dual-domain infiltration and precipitation partitioning using a HydroGeoSphere (HGS) model for variably saturated water flow coupled to a soil-epikarst water balance model in the WMA. The model input includes downscaled high-resolution climate projections until 2070 based on the IPCC RCP4.5 scenario. The results reveal a 5% to 10% decrease in long-term average groundwater recharge compared to a 30% reduction in average precipitation. The heterogeneity of karstic flow and increased intensity of individual rainfall events contribute to this mitigated impact on groundwater recharge, underscoring the importance of spatiotemporally resolved climate models with daily precipitation data. However, despite the moderate decrease in recharge, the study highlights the increasing length and severity of consecutive drought years with low recharge values. It emphasizes the need to adjust current management practices to climate change, as freshwater demand is expected to rise during these periods. Additionally, the study examines the emergence of hydrogeological droughts and their propagation from the surface to the groundwater. The results suggest that the 48-month standardized precipitation index (SPI-48) is a suitable indicator for hydrogeological drought emergence due to reduced groundwater recharge.
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Merembayev, T., Yunussov, R., & Yedilkhan, A. (2019). Machine Learning Algorithms for Stratigraphy Classification on Uranium Deposits. Procedia Computer Science, 150, 46–52.
Abstract: Machine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words – it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost.
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Zhao, Y., Li, X., Lei, L., Chen, L., & Luo, Z. (2023). Permeability evolution mechanism and the optimum permeability determination of uranium leaching from low-permeability sandstone treated with low-frequency vibration. Journal of Rock Mechanics and Geotechnical Engineering, 15(10), 2597–2610.
Abstract: Low-frequency vibrations can effectively improve natural sandstone permeability, and higher vibration frequency is associated with larger permeability. However, the optimum permeability and permeability evolution mechanism for uranium leaching and the relationship between permeability and the change of chemical reactive rate affecting uranium leaching have not been determined. To solve the above problems, in this study, identical homogeneous sandstone samples were selected to simulate low-permeability sandstone; a permeability evolution model considering the combined action of vibration stress, pore water pressure, water flow impact force, and chemical erosion was established; and vibration leaching experiments were performed to test the model accuracy. Both the permeability and chemical reactions were found to simultaneously restrict U6+ leaching, and the vibration treatment increased the permeability, causing the U6+ leaching reaction to no longer be diffusion-constrained but to be primarily controlled by the reaction rate. Changes of the model calculation parameters were further analyzed to determine the permeability evolution mechanism under the influence of vibration and chemical erosion, to prove the correctness of the mechanism according to the experimental results, and to develop a new method for determining the optimum permeability in uranium leaching. The uranium leaching was found to primarily follow a process consisting of (1) a permeability control stage, (2) achieving the optimum permeability, (3) a chemical reactive rate control stage, and (4) a channel flow stage. The resolution of these problems is of great significance for facilitating the application and promotion of low-frequency vibration in the CO2 + O2 leaching process.
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