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Min, M., Chen, J., Wang, J., Wei, G., & Fayek, M. (2005). Mineral paragenesis and textures associated with sandstone-hosted roll-front uranium deposits, NW China. Ore Geology Reviews, 26(1), 51–69.
Abstract: We present a first paragenetic study of the Wuyier, Wuyisan, Wuyiyi and Shihongtan sandstone-hosted roll-front uranium deposits, northwest China. The mineralization is hosted by Lower–Middle Jurassic coarse- to medium-grained sandstones, which are dark-gray to black due to a mixture of ore minerals and carbonaceous debris. The sandstone is alluvial fan-braided river facies. Minerals associated with these deposits can be broadly categorized as detrital, authigenic, and ore-stage mineralization. Ore minerals consist of uraninite and coffinite. This is the first noted occurrence of coffinite in this type of deposit in China. Sulfide minerals associated with the uranium minerals are pyrite, marcasite, and less commonly, sphalerite and galena. The sulfide minerals are largely in textural equilibrium with the uranium minerals. However, these sulfide minerals occasionally appear to predate, as well as postdate, the uranium minerals. This implies that there are multiple generations of sulfides associated with these deposits. The ore minerals occur interstitially between fossilized wood cells in the sandstones as well as replace fossilized wood and biotite. The deposits are generally low-grade. Primary uranium minerals associated with the low-grade deposits are generally too small, ranging from 0.2 to 0.3 μm in diameter, to be observed by optical microscopy and are only observed by electron microscopy. Mineral paragenesis and textures indicate that these deposits formed under low temperature (30–50 °C) conditions.
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Uhrie, J. L., Drever, J. I., Colberg, P. J. S., & Nesbitt, C. C. (1996). In situ immobilization of heavy metals associated with uranium leach mines by bacterial sulfate reduction. Hydrometallurgy, 43(1), 231–239.
Abstract: Laboratory experiments with mixed populations of sulfate-reducing bactreria were shown to mediate the removal of milligrams/liter concentrations of uranium, selenium, arsenic and vanadium from aqueous solution via reduction, precipitation and adsorption. Results of laboratory experiments with active sulfidogenic biomass suggest that injection of sulfate and a source of carbon could enhance anaerobic microbial activity in and around uranium leach mines leading to in situ immobilization contaminating metals.
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Heaton, T. H. E. (1984). Sources of the nitrate in phreatic groundwater in the western Kalahari. Journal of Hydrology, 67(1), 249–259.
Abstract: Elevated levels of nitrate occur in phreatic groundwater in the western Kalahari, Namibia. Nitrate in water containing 0.4–3.1 meq NO−3l−1, of widespread occurrence, has δ15N values in the range +4.9 to +8.0‰, suggesting natural derivation from the soil. The sporadic occurrence of very high levels of nitrate (> 4 meq NO−3l−1), which has δ15N between +9.3 to +18.7‰, reflects pollution derived from animal waste. The importance of considering the possible isotopic effects of denitrification, and the significance of leaching in the nitrogen budget of the Kalahari soil, are also discussed.
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Heaton, T. H. E., Talma, A. S., & Vogel, J. C. (1983). Origin and history of nitrate in confined groundwater in the western Kalahari. Journal of Hydrology, 62(1), 243–262.
Abstract: Data are presented for nitrate, dinitrogen and argon concentrations and 15N14N ratios in groundwater, with radiocarbon ages up to 40,000 yr. for three confined sandstone aquifers in the western Kalahari of South West Africa/Namibia. The nitrate is probably generated within the soil of the recharge areas, and its production rate during the period 3000-40,000 B.P. has remained between 0.5 and 1.6 meq NO−3l−1 of recharge water, with ° 15N between + 4 and + 8‰. Variations in the amount of nitrate and of “excess air” in groundwater recharge are found, and can only reflect changes in the environmental conditions during recharge. They must therefore be caused by the climatic changes that have taken place during the past 25,000 yr.
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Rajfur, M., Kłos, A., & Wacławek, M. (2010). Sorption properties of algae Spirogyra sp. and their use for determination of heavy metal ions concentrations in surface water. Bioelectrochemistry, 80(1), 81–86.
Abstract: Kinetics of heavy-metal ions sorption by alga Spirogyra sp. was evaluated experimentally in the laboratory, using both the static and the dynamic approach. The metal ions – Mn2+, Cu2+, Zn2+ and Cd2+ – were sorbed from aqueous solutions of their salts. The static experiments showed that the sorption equilibria were attained in 30min, with 90-95% of metal ions sorbed in first 10min of each process. The sorption equilibria were approximated with the Langmuir isotherm model. The algae sorbed each heavy metal ions proportionally to the amount of this metal ions in solution. The experiments confirmed that after 30min of exposition to contaminated water, the concentration of heavy metal ions in the algae, which initially contained small amounts of these metal ions, increased proportionally to the concentration of metal ions in solution. The presented results can be used for elaboration of a method for classification of surface waters that complies with the legal regulations.
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Konapala, G., Mishra, A. K., Wada, Y., & Mann, M. E. (2020). Climate change will affect global water availability through compounding changes in seasonal precipitation and evaporation. Nature Communications, 11(1), 3044.
Abstract: Both seasonal and annual mean precipitation and evaporation influence patterns of water availability impacting society and ecosystems. Existing global climate studies rarely consider such patterns from non-parametric statistical standpoint. Here, we employ a non-parametric analysis framework to analyze seasonal hydroclimatic regimes by classifying global land regions into nine regimes using late 20th century precipitation means and seasonality. These regimes are used to assess implications for water availability due to concomitant changes in mean and seasonal precipitation and evaporation changes using CMIP5 model future climate projections. Out of 9 regimes, 4 show increased precipitation variation, while 5 show decreased evaporation variation coupled with increasing mean precipitation and evaporation. Increases in projected seasonal precipitation variation in already highly variable precipitation regimes gives rise to a pattern of “seasonally variable regimes becoming more variable”. Regimes with low seasonality in precipitation, instead, experience increased wet season precipitation.
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Illgen, M., & Ackermann, H. (2019). In S. Köster, M. Reese, & J. ’e Zuo (Eds.), Urban Flood Prevention: Technical and Institutional Aspects from Chinese and German Perspective (pp. 173–193). Cham: Springer International Publishing.
Abstract: Today’s cities face the challenge of climate change adaptation worldwide. In this context, prevention of damage caused by flash floods plays an important role. This requires a cooperative pluvial flood risk management approach, which includes planning, technical, and administrative measures and involves preliminary flood risk analyses. This article outlines the main components of this risk management approach, which has proven its effectiveness in Europe. The recommendations formulated for this purpose are applicable or adaptable to regions with other constraints, such as China, for example.
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Röttcher, K. (2018). In A. Michalke, M. Rambke, & S. Zeranski (Eds.), Risikomanagement und Nachhaltigkeit in der Wasserwirtschaft: Erfolgreiche Navigation durch die Komplexität und Dynamik des Risikos (pp. 165–174). Wiesbaden: Springer Fachmedien Wiesbaden.
Abstract: Im vorliegenden Beitrag werden beispielhaft unterschiedliche Ansätze des Risikomanagements und das Verständnis von Nachhaltigkeit in der Wasserwirtschaft dargelegt. Die Darstellung richtet sich insbesondere an Leser aus anderen Fachdisziplinen, wie das Rechts- und Finanzwesen, den Fahrzeug- und Maschinenbau oder auch die sozialen Berufe. Die Zusammenhänge werden überblicksartig mit einzelnen konkreten Beispielen dargestellt mit dem Fokus auf die grundsätzlichen Denk- und Vorgehensweisen.
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Stone, A. E. C., & Edmunds, W. M. (2014). Naturally-high nitrate in unsaturated zone sand dunes above the Stampriet Basin, Namibia. Journal of Arid Environments, 105, 41–51.
Abstract: Elevated groundwater nitrate levels are common in drylands, often in excess of WHO guidelines, with concern for human and animal health. In light of recent attempts to identify nitrate sources in the Kalahari this paper presents the first unsaturated zone (USZ) nitrate profiles and recharge rate estimates for the important transboundary Stampriet Basin, alongside the first rainfall chemistry records. Elevated subsurface nitrate reaches 100–250 and 250–525 mg/L NO3–N, with NO3–N/Cl of 4–12, indicating input above evapotranspiration. Chloride mass balance recharge rates range from 4 to 27 mm/y, indicating a vertical movement of these nitrate pulses toward the water table over multi-decadal timescales. These profiles are sampled from dune crests, away from high concentrations of animals and without termite mounds. Given low-density animal grazing is unlikely to contribute consistent spot-scale nitrate over decades, these profiles give an initial estimate of naturally-produced concentrations. This insight is important for the management of the Stampriet Basin and wider Kalahari groundwater. This study expands our knowledge about elevated nitrate in dryland USZs, demonstrating that it can occur as pulses, probably in response to transient vegetation cover and that it is not limited to long-residence time USZs with very limited downward moisture flux (recharge).
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Aderemi, B. A., Olwal, T. O., Ndambuki, J. M., & Rwanga, S. S. (2023). Groundwater levels forecasting using machine learning models: A case study of the groundwater region 10 at Karst Belt, South Africa. Systems and Soft Computing, 5, 200049.
Abstract: 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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