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Arya, S.; Kumar, A. |
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Title |
Evaluation of stormwater management approaches and challenges in urban flood control |
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Journal Article |
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Year |
2023 |
Publication |
Urban Climate |
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Volume |
51 |
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101643 |
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Keywords |
Flood risk, Green infrastructure (GI), Stormwater management, Stormwater modelling, Vulnerability assessment, Urban floods |
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Across the globe, the damage caused by urban floods has increased manifold. The unchecked development has encroached the natural drainage, and the conventional drainage systems are inadequate in handling the augmented hydrological response. To counter this, a variety of approaches with the ability to adjust within the constraints of complex environments by managing surface runoff are being widely investigated and applied worldwide. These can put the flood water to better use, and the ecological balance may get restored. This review discusses recent progress made in the area of Green Infrastructure (GI), modelling tools that help in stormwater management, vulnerability analysis and flood risk assessment. Different ways of handling the problem are summarized through an extensive literature survey. The gaps and barriers that impede the implementation of stormwater management solutions and strategies for further improvement have also been presented. A case study of Gurugram city, India depicting the challenges being faced by urban flooding and the possible solutions through an expert survey is also presented. |
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2212-0955 |
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THL @ christoph.kuells @ Arya2023101643 |
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224 |
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Bresinsky, L.; Kordilla, J.; Hector, T.; Engelhardt, I.; Livshitz, Y.; Sauter, M. |
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Title |
Managing climate change impacts on the Western Mountain Aquifer: Implications for Mediterranean karst groundwater resources |
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Journal Article |
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Year |
2023 |
Publication |
Journal of Hydrology X |
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Volume |
20 |
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100153 |
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Groundwater recharge, Storage, Hydrogeological droughts, Climate change effects, Groundwater management, Mitigation of climate change effects |
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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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2589-9155 |
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THL @ christoph.kuells @ Bresinsky2023100153 |
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223 |
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Rusli, S.R.; Weerts, A.H.; Mustafa, S.M.T.; Irawan, D.E.; Taufiq, A.; Bense, V.F. |
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Title |
Quantifying aquifer interaction using numerical groundwater flow model evaluated by environmental water tracer data: Application to the data-scarce area of the Bandung groundwater basin, West Java, Indonesia |
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Journal Article |
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Year |
2023 |
Publication |
Journal of Hydrology: Regional Studies |
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50 |
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Pages |
101585 |
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Keywords |
Aquifer interaction, Multi-layer groundwater abstraction, Environmental water tracers, Groundwater flow model, Bandung groundwater basin |
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Abstract |
Study Region: Bandung groundwater basin, Indonesia. Study focus: Groundwater abstraction of various magnitudes, pumped out from numerous depths in a multitude of layers of aquifers, stimulates different changes in hydraulic head distribution, including ones under vertical cross-sections. This generates groundwater flow in the vertical direction, where groundwater flows within its storage from the shallow to the underlying confined aquifers. In the Bandung groundwater basin, previous studies have identified such processes, but quantitative evaluations have never been conducted, with data scarcity mainly standing as one of the major challenges. In this study, we utilize the collated (1) environmental water tracer data, including major ion elements (Na+/K+, Ca2＋, Mg2+, Cl−, SO42−,HCO3−), stable isotope data (2H and δ18O), and groundwater age determination (14C), in conjunction with (2) groundwater flow modeling to quantify the aquifer interaction, driven mainly by the multi-layer groundwater abstraction in the Bandung groundwater basin, and demonstrate their correspondence. In addition, we also use the model to quantify the impact of multi-layer groundwater abstraction on the spatial distribution of the groundwater level changes. New hydrological insights for the region: In response to the limited calibration data availability, we expand the typical model calibration that makes use of the groundwater level observations, with in-situ measurement and a novel qualitative approach using the collated environmental water tracers (EWT) data for the model evaluation. The analysis in the study area using EWT data and quantitative methods of numerical groundwater flow modeling is found to collaborate with each other. Both methods show agreement in their assessment of (1) the groundwater recharge spatial distribution, (2) the regional groundwater flow direction, (3) the groundwater age estimates, and (4) the identification of aquifer interaction. On average, the downwelling to the deeper aquifer is quantified at 0.110 m/year, which stands out as a significant component compared to other groundwater fluxes in the system. We also determine the unconfined aquifer storage volume decrease, calculated from the change in the groundwater table, resulting in an average declining rate of 51 Mm3/year. This number shows that the upper aquifer storage is dwindling at a rate disproportionate to its groundwater abstraction, hugely influenced by losses to the deeper aquifer. The outflow to the deeper aquifer contributes to 60.3% of the total groundwater storage lost, despite representing only 32.3% of the total groundwater abstraction. This study shows the possibility of quantification of aquifer interaction and groundwater level change dynamics driven by multi-layer groundwater abstraction in a multi-layer hydrogeological setting, even in a data-scarce environment. Applying such methods can assist in deriving basin-scale groundwater policies and management strategies under the changing anthropogenic and climatic factors, thereby ensuring sustainable groundwater management. |
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2214-5818 |
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THL @ christoph.kuells @ Rusli2023101585 |
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222 |
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Author |
Aderemi, B.A.; Olwal, T.O.; Ndambuki, J.M.; Rwanga, S.S. |
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Title |
Groundwater levels forecasting using machine learning models: A case study of the groundwater region 10 at Karst Belt, South Africa |
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Journal Article |
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Year |
2023 |
Publication |
Systems and Soft Computing |
Abbreviated Journal |
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Volume |
5 |
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Pages |
200049 |
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Keywords |
Artificial intelligence, Forecasting model, Groundwater levels, Machine learning, Neural networks, Rainfall, Regression, Temperature, Time series |
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The crucial role which groundwater resource plays in our environment and the overall well-being of all living things can not be underestimated. Nonetheless, mismanagement of resources, over-exploitation, inadequate supply of surface water and pollution have led to severe drought and an overall drop in groundwater resources’ levels over the past decades. To address this, a groundwater flow model and several mathematical data-driven models have been developed for forecasting groundwater levels. However, there is a problem of unavailability and scarcity of the on-site input data needed by the data-driven models to forecast the groundwater level. Furthermore, as a result of the dynamics and stochastic characteristics of groundwater, there is a need for an appropriate, accurate and reliable forecasting model to solve these challenges. Over the years, the broad application of Machine Learning (ML) and Artificial Intelligence (AI) models are gaining attraction as an alternative solution for forecasting groundwater levels. Against this background, this article provides an overview of forecasting methods for predicting groundwater levels. Also, this article uses ML models such as Regressions Models, Deep Auto-Regressive models, and Nonlinear Autoregressive Neural Networks with External Input (NARX) to forecast groundwater levels using the groundwater region 10 at Karst belt in South Africa as a case study. This was done using Python Mx. Version 1.9.1., and MATLAB R2022a machine learning toolboxes. Moreover, the Coefficient of Determination (R2);, Root Mean Square Error (RMSE), Mutual Information gain, Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Mean Absolute Error (MAE), and the Mean Absolute Scaled Error (MASE)) models were the forecasting statistical performance metrics used to assess the predictive performance of these models. The results obtained showed that NARX and Support Vector Machine (SVM) have higher performance metrics and accuracy compared to other models used in this study. |
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2772-9419 |
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THL @ christoph.kuells @ Aderemi2023200049 |
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219 |
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Author |
Musy, S.; Purtschert, R. |
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Title |
Reviewing 39Ar and 37Ar underground production in shallow depths with implications for groundwater dating |
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Journal Article |
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Year |
2023 |
Publication |
Science of The Total Environment |
Abbreviated Journal |
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Volume |
884 |
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Pages |
163868 |
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Subsurface production, Argon-39, Argon-37, Muons, Isotope hydrology, Tracers |
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Argon-37 (37Ar) and Argon-39 (39Ar) are used for groundwater dating on timescales from weeks to centuries. For both isotopes, the quantification of underground sources is essential to accurately infer water residence times from sampled dissolved activities. Subsurface production resulting from interactions with neutrons from the natural radioactivity in rocks and with primary cosmogenic neutrons has been known for a long time. More recently, the capture of slow negative muons and reactions with muon-induced neutrons were documented for 39Ar subsurface production in the context of underground particle detectors (e.g. for Dark Matter research). However, the contribution from these particles was never considered for groundwater dating applications. Here, we reevaluate the importance of all potential depth-related production channels at depth ranges relevant for 39Ar groundwater dating [0 − 200 meters below the surface (m.b.s)]. The production of radioargon by muon-induced processes is considered in this depth range for the first time. The uncertainty on the total depth-dependent production rate is estimated with Monte Carlo simulations assuming a uniform distribution of the parameter uncertainties. This work aims to provide a comprehensive framework for interpreting 39Ar activities in terms of groundwater residence times and for exposure age dating of rocks. The production of 37Ar is also addressed since this isotope is relevant as a proxy for 39Ar production, for the timing of river-groundwater exchanges, and in the context of on-site inspections (OSI) within the verification framework of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). In this perspective, we provide an interactive web-based application for the calculation of 37Ar and 39Ar production rates in rocks. |
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0048-9697 |
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THL @ christoph.kuells @ Musy2023163868 |
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217 |
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Author |
Li, J.; Pang, Z.; Liu, Y.; Hu, S.; Jiang, W.; Tian, L.; Yang, G.; Jiang, Y.; Jiao, X.; Tian, J. |
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Title |
Changes in groundwater dynamics and geochemical evolution induced by drainage reorganization: Evidence from 81Kr and 36Cl dating of geothermal water in the Weihe Basin of China |
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Journal Article |
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2023 |
Publication |
Earth and Planetary Science Letters |
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623 |
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118425 |
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Kr dating, Cl dating, Geothermal water, Groundwater dynamics, Weihe basin |
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81Kr and 36Cl can both be used to date groundwater beyond the dating range of 14C. 81Kr usually provides reliable groundwater ages because it has uniform initial distribution and negligible subsurface generation, while 36Cl is commonly influenced by subsurface sources or “dead” chloride dissolution. Therefore, the combined use of 81Kr and 36Cl could provide clues on the evolution history of groundwater. In the present study, we performed 36Cl and 81Kr dating of geothermal water in Weihe Basin of China and interpreted the possible cause of disagreement. Two distinct water masses were identified with distinctive isotopic signals: groundwater with significant δ18O shifts (up to −2.0‰), dissolved dead Cl and ages < 1.0 Ma (Cluster A), and older water with little δ18O shifts, negligible dissolved Cl and ages >1.0 Ma (Cluster B). The results confirm the eastward flow path of Cluster B to the Ancient Sanmen Lake with an increasing trend of Cl concentration and age. Modern recharge from the mountains flows to the basin center with intense interaction between water and carbonate under respective reservoir temperatures (100 ∼ 130 °C). These waters flow through the saline stratum emerging from the spillover of the Ancient Sanmen Lake, resulting in higher dead Cl dissolution. A significant linear relationship is observed with the older end-member of ∼1.3Ma under the topographically-driven faster circulation effect. 81Kr ages seem to support the hypothesis that the birth of the modern Yellow River was at about 1.0–1.3 Ma. We inferred the drainage reorganization from the Ancient Sanmen Lake to the modern Yellow River since the Mid-Pleistocene Transition induced the change in groundwater dynamics as well as its chemical evolution. The excavation of the Ancient Sanmen Lake and the accentuated incision of the Weihe River induced groundwater gradient, and therefore the recharge from precipitation from both slopes of the Qinling Mountains in the south and the Beishan Mountains in the north. Our results highlight the effects of dead Cl on 36Cl dating and demonstrate the significant impact of catchment reorganization on groundwater dynamics and its chemistry. |
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0012-821x |
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THL @ christoph.kuells @ Li2023118425 |
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212 |
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Zeng, S.; Song, J.; Sun, B.; Wang, F.; Ye, W.; Shen, Y.; Li, H. |
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Title |
Seepage characteristics of the leaching solution during in situ leaching of uranium |
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Journal Article |
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Year |
2023 |
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Nuclear Engineering and Technology |
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55 |
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2 |
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566-574 |
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In situ leaching, Leaching solution viscosity, Seepage characteristics, Seepage pressure, Uranium-bearing sandstone |
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Investigating the seepage characteristics of the leaching solution in the ore-bearing layer during the in situ leaching process can be useful for designing the process parameters for the uranium mining well. We prepared leaching solutions of four different viscosities and conducted experiments using a self-developed multifunctional uranium ore seepage test device. The effects of different viscosities of leaching solutions on the seepage characteristics of uranium-bearing sandstones were examined using seepage mechanics, physicochemical seepage theory, and dissolution erosion mechanism. Results indicated that while the seepage characteristics of various viscosities of leaching solutions were the same in rock samples with similar internal pore architectures, there were regular differences between the saturated and the unsaturated stages. In addition, the time required for the specimen to reach saturation varied with the viscosity of the leaching solution. The higher the viscosity of the solution, the slower the seepage flow from the unsaturated stage to the saturated stage. Furthermore, during the saturation stage, the seepage pressure of a leaching solution with a high viscosity was greater than that of a leaching solution with a low viscosity. However, the permeability coefficient of the high viscosity leaching solution was less than that of a low viscosity leaching solution. |
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1738-5733 |
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THL @ christoph.kuells @ zeng_seepage_2023 |
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211 |
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Wang, B.; Luo, Y.; Qian, J.-zhong; Liu, J.-hui; Li, X.; Zhang, Y.-hong; Chen, Q.-qian; Li, L.-yao; Liang, D.-ye; Huang, J. |
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Machine learning–based optimal design of the in-situ leaching process parameter (ISLPP) for the acid in-situ leaching of uranium |
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Journal Article |
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2023 |
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Journal of Hydrology |
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626 |
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130234 |
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In-situ leaching, Injection rate design, Lixiviant concentration design, Machine learning, Simulation-optimisation, Uncertainty |
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The migration process of leached uranium in the in-situ leaching of uranium is considered a typical reactive transport problem. During this process, the lixiviant concentration and injection rate are important in-situ leaching process parameters (ISLPP) to efficiently recover uranium. However, several uncertain factors affect the outcomes of the ISLPP design. In addition, the repeated use of the reactive transport model (RTM) for investigating the acid in-situ leaching of uranium with the application of the Monte Carlo method leads to a substantial computational load. For this reason, a machine learning (ML)–based surrogate model was developed with the backpropagation neural network (BPNN) method to replace the RTM under the condition of uncertain parameters. Moreover, the simulated annealing optimisation model for ISLPP was created based on the proposed surrogate model. The optimal ISLPP was achieved that generated maximum profits from uranium recovery under different lixiviant prices, uranium prices and exploitation times. The optimal design framework of ISLPP based on the proposed ML algorithm was then applied in the Bayan-Uul sandstone-type uranium deposit in Inner Mongolia, China. From our analysis, it was demonstrated that the ML-based surrogate model exhibited great fitness with the RTM. The optimal results of the ISLPP indicated that the lixiviant concentration and injection rate could be adjusted based on the fluctuations in lixiviant price, uranium price and exploitation time. If the prices of sulphuric acid were high, a specific concentration of hydrogen peroxide could be injected into the injection well to promote the oxidation and dissolution of the uranium ore to increase the income from the uranium recovery. The optimisation model can also use the ISLPP scheme to boost the revenues from different lixiviant prices, uranium prices and exploitation times under the uncertainty of porosity, illustrating the applicability of the ML-based optimal design method of ISLPP in ISL mining. A general framework for developing surrogate models, as well as for conducting uncertainty analyses for a wide range of groundwater models was proposed here yielding valuable insights. |
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0022-1694 |
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THL @ christoph.kuells @ wang_machine_2023 |
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210 |
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Qiu, W.; Yang, Y.; Song, J.; Que, W.; Liu, Z.; Weng, H.; Wu, J.; Wu, J. |
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Title |
What chemical reaction dominates the CO2 and O2 in-situ uranium leaching?: Insights from a three-dimensional multicomponent reactive transport model at the field scale |
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Journal Article |
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2023 |
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Applied Geochemistry |
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148 |
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105522 |
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Carbonate minerals, In-situ leaching (ISL) of uranium, Pyrite oxidation, Reactive transport modeling (RTM) |
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The complex behavior of uranium in recovery is mostly driven by water-rock interactions following lixiviant injection into ore-bearing aquifers. Significant challenges exist in exploring the geochemical processes responsible for uranium release and mobilization. Herein this study provides an illustration of a ten-year field scale CO2 and O2 in-situ leaching (ISL) process at a typical sandstone-hosted uranium deposit in northern China. We also conducte a three-dimensional (3-D) multicomponent reactive transport model to assess the effects of potential chemical reactions on uranium recovery, in particular, to focus on the role of sulfide mineral pyrite (FeS2). Numerical simulations are performed considering three potential ISL reaction pathways to determine the relative contributions to uranium release, and the results indicate that bicarbonate promotes the oxidative dissolution of uranium-bearing minerals and further accelerates the uranium leaching in a neutral geochemical system. Moreover, the presence of FeS2 exerts a strong competitive role in the uranium-bearing mineral dissolution by increasing oxygen consumption, favoring the formation of iron oxyhydroxide, and therefore causing an associated decrease in uranium recovery rates. The simulation model demonstrates that dissolution of carbonate neutralizes acidic water generated from pyrite oxidation and aqueous CO2 dissociation. In addition, the cation concentrations (i.e., Ca and Mg) are increasing in the pregnant solutions, showing that the recycling of lixiviants and kinetic dissolution of carbonate generates a larger number of dissolved Ca and Mg and inevitably triggers the secondary dolomite mineral precipitation. The findings improve our fundamental understanding of the geochemical processes in a long-term uranium ISL system and provide important environmental implications for the optimal design of uranium recovery, remediation, and risk exposure assessment. |
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0883-2927 |
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THL @ christoph.kuells @ qiu_what_2023 |
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207 |
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Shayakhmetov, N.M.; Alibayeva, K.A.; Kaltayev, A.; Panfilov, I. |
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Title |
Enhancing uranium in-situ leaching efficiency through the well reverse technique: A study of the effects of reversal time on production efficiency and cost |
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Journal Article |
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Year |
2023 |
Publication |
Hydrometallurgy |
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Volume |
219 |
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Pages |
106086 |
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Keywords |
Economic evaluation, Hydrodynamic enhancement of mineral production, In-situ leaching, Mineral recovery, Optimal reversal time, Well reversing technique |
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Abstract |
In this study, the application of the Well Reversal Technique (WRT) and the impact of reversal time on the efficiency of uranium mining via In-Situ Leaching (ISL) were investigated. A prevalent issue in ISL mineral extraction is the formation of stagnant zones caused by limited access of the lixiviant, which leads to increased operating expenditures. The WRT, which involves altering the function of some wells from injection to production or vice versa, is a potential solution to this problem. The efficiency of WRT is heavily dependent on the well pattern and reversal time. Two commonly used well patterns in ISL are the 9-spot (row arrangement) and 7-spot (hexagonal arrangement). The objective of this study was to determine the optimal reversal time for a 9-spot well pattern through mathematical modeling of hydrodynamic and physico-chemical processes and subsequent economic assessment. A mathematical model of uranium extraction processes was developed using the principles of mass conservation, Darcy’s, and mass action laws. The results obtained for a 9-spot well pattern without reversal, with two reversal options, and a 7-spot scheme were analyzed comparatively. The 7-spot scheme without reversal was found to be the most effective of the options examined. The application of WRT on a 9-spot well pattern allows to enhance production efficiency to a level comparable to that of a 7-spot well pattern. Additionally, the effect of reversal time on recovery was studied based on two well reversal options. The results from calculation revealed that the optimal scenario was when the well reversal is conducted immediately after the time point at which the average concentration of the pregnant solution in the production wells reaches its peak value. The overall efficiency of WRT application was determined through economic calculations of capital (CAPEX) and operating (OPEX) expenditures. Based on economic calculations, it was determined that the utilization of WRT results in a 3–18% increase in mineral production efficiency for a 9-point scheme, depending on the chosen reversal method. |
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0304-386x |
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THL @ christoph.kuells @ shayakhmetov_enhancing_2023 |
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203 |
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