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Johnson, R. S. H., & Alila, Y. (2023). Nonstationary stochastic paired watershed approach: Investigating forest harvesting effects on floods in two large, nested, and snow-dominated watersheds in British Columbia, Canada. Journal of Hydrology, 625, 129970.
Abstract: Drawing on advances in nonstationary frequency analysis and the science of causation and attribution, this study employs a newly developed nonstationary stochastic paired watershed approach to determine the effect of forest harvesting on snowmelt-generated floods. Moreover, this study furthers the application of stochastic physics to evaluate the environmental controls and drivers of flood response. Physically-based climate and time-varying harvesting data are used as covariates to drive the nonstationary flood frequency distribution parameters to detect, attribute, and quantify the effect of harvesting on floods in the snow-dominated Deadman River (878 km2) and nested Joe Ross Creek (99 km2) watersheds. Harvesting only 21% of the watershed caused a 38% and 84% increase in the mean but no increase in variability around the mean of the frequency distribution in the Deadman River and Joe Ross Creek, respectively. Consequently, the 7-year, 20-year, 50-year, and 100-year flood events became approximately two, four, six, and ten times more frequent in both watersheds. An increase in the mean is posited to occur from an increase in moisture availability following harvest from suppressed snow interception and increased net radiation reaching the snowpack. Variability was not increased because snowmelt synchronization was inhibited by the buffering capacity of abundant lakes, evenly distributed aspects, and widespread spatial distribution of cutblocks in the watersheds, preventing any potential for harvesting to increase the efficiency of runoff delivery to the outlet. Consistent with similar recent studies, the effect of logging on floods is controlled not only by the harvest rate but most importantly the physiographic characteristics of the watershed and the spatial distribution of the cutblocks. Imposed by the probabilistic framework to understanding and predicting the relation between extremes and their environmental controls, commonly used in the general sciences but not forest hydrology, it is the inherent nature of snowmelt-driven flood regimes which cause even modest increases in magnitude, especially in the upper tail of the distribution, to translate into surprisingly large changes in frequency. Contrary to conventional wisdom, harvesting influenced small, medium, and very large flood events, and the sensitivity to harvest increased with increasing flood event size and watershed area.
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Wang, B., Luo, Y., Qian, J. -zhong, Liu, J. -hui, Li, X., Zhang, Y. -hong, et al. (2023). Machine learning–based optimal design of the in-situ leaching process parameter (ISLPP) for the acid in-situ leaching of uranium. Journal of Hydrology, 626, 130234.
Abstract: 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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Leeuwen, Z. R. van, Klaar, M. J., Smith, M. W., & Brown, L. E. (2024). Quantifying the natural flood management potential of leaky dams in upland catchments, Part II: Leaky dam impacts on flood peak magnitude. Journal of Hydrology, 628, 130449.
Abstract: Leaky dams are an increasingly popular natural flood management measure, yet their impacts on flood peak magnitude have not yet been empirically quantified for a range of event types and magnitudes, even at the stream scale. In this study, the novel application of a transfer function noise modelling approach to empirical Before-After-Control-Impact stage data from an upland catchment allowed leaky dam effectiveness in reducing flood peak magnitude to be quantified. Flood peak stage and discharge magnitude changes were assessed from empirical data for 50 single and multi-peaked high flow events with return periods ranging from less than one year to six years. Overall, event peak magnitude was significantly reduced following the installation of eight leaky dams on the impact stream. Effectiveness was highly variable, but on average, flood peak magnitude was reduced by 10% for events with a return period up to one year. Some of the variability was explained by the size of the event and whether it was a single or multi-peaked event. This finding emphasises the need to manage expectations by considering both a range of event magnitudes and types when designing or assessing leaky dam natural flood management schemes.
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Seidl, C., Wheeler, S. A., & Page, D. (2024). Understanding the global success criteria for managed aquifer recharge schemes. Journal of Hydrology, 628, 130469.
Abstract: Water availability and quality issues will only gain importance in the future, with climate change impacts putting increasing pressure on global water resources. Dealing with these challenges requires drawing on all available water management tools, including Managed Aquifer Recharge (MAR). Although MAR has seen increasing global implementation during the last half a century, it is still often overlooked as a management tool. While technical, bio-physical, and hydrogeological aspects of MAR are well researched, this cannot be said for socio-economic and other governance factors. Where information is available, this study seeks to understand the conditions necessary for MAR success. We apply fuzzy-set Qualitative Comparative Analysis on 313 world MAR applications, and also model separately for high- and low-middle-income countries. Results show that sophisticated hydrogeological site understanding and scheme operation is paramount for MAR success, as is utilizing natural water sources for high value end uses. Successful high-income country MAR schemes tend to be large and utilize natural water sources and sophisticated water injection and treatment methods to augment potable water supply; while successful low-middle-income country schemes are not large, older than 20 years, and use gravity infiltration methods and (limited) no water treatment. These findings will help inform the future suitability of MAR application design and its likely success within various contexts.
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Jana, A., Unni, A., Ravuru, S. S., Das, A., Das, D., Biswas, S., et al. (2022). In-situ polymerization into the basal spacing of LDH for selective and enhanced uranium adsorption: A case study with real life uranium alkaline leach liquor. Chemical Engineering Journal, 428, 131180.
Abstract: Uranium is used as a fuel for nuclear power plant and can be extracted from different ores, mainly acidic (silicious ore) and alkaline (carbonate ore). Recovery of uranium through acid leaching from silicious ore is well established, whereas, alkaline leaching from carbonate ore is challenging due to the excessive salinity of leach liquor and high concentration of carbonate, bicarbonate and sulphate. Herein, two monomers, acrylic acid (AA) and N, N-methylene bisacrylamide (BAM), selective towards uranyl were intercalated in-situ into the interlayer, followed by their polymerization and cross-linking to form novel polymer intercalated hybrid layered double hydroxide (LDH). The LDH acts as a backbone to overcome coiling and swelling of polymer and anchors them as free-standing. Various parameters, like, the type of metal ions, monomer ratio (AA: BAM) and metal ion ratio (M2+:M3+), were studied to determine the optimum conditions for effective intercalation and polymerization of monomers. Magnesium aluminum (MgAl) LDH with a cross-linked polymer having a monomer ratio of 3:2 (AA: BAM) as intercalating species showed maximum efficiency of uranyl adsorption (1456 mg/g at 30 °C) with highest capacity so far. The distribution coefficient (Kd, l/mg) in the order of 105 suggested that the adsorbent was highly selective for uranyl in the presence of different cations, anions and humic acid. The adsorbent extracts uranium effectively and selectively from a real-life alkaline leach liquor with an efficiency of 96% at 5 g/l dose. Uranium can be recovered from the adsorbent in the form of sodium di-uranate using 2(M) NaOH and was reused for eight cycles.
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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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Prusty, S., Somu, P., Sahoo, J. K., Panda, D., Sahoo, S. K., Sahoo, S. K., et al. (2022). Adsorptive sequestration of noxious uranium (VI) from water resources: A comprehensive review. Chemosphere, 308, 136278.
Abstract: Groundwater is usually utilized as a drinking water asset everywhere. Therefore, groundwater defilement by poisonous radioactive metals such as uranium (VI) is a major concern due to the increase in nuclear power plants as well as their by-products which are released into the watercourses. Waste Uranium (VI) can be regarded as a by-product of the enrichment method used to produce atomic energy, and the hazard associated with this is due to the uranium radioactivity causing toxicity. To manage these confronts, there are so many techniques that have been introduced but among those adsorptions is recognized as a straightforward, successful, and monetary innovation, which has gotten major interest nowadays, despite specific drawbacks regarding operational as well as functional applications. This review summarizes the various adsorbents such as Bio-adsorbent/green materials, metal oxide-based adsorbent, polymer based adsorbent, graphene oxide based adsorbent, and magnetic nanomaterials and discuss their synthesis methods. Furthermore, this paper emphasis on adsorption process by various adsorbents or modified forms under different physicochemical conditions. In addition to this adsorption mechanism of uranium (VI) onto different adsorbent is studied in this article. Finally, from the literature reviewed conclusion have been drawn and also proposed few future research suggestions.
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Jroundi, F., Descostes, M., Povedano-Priego, C., Sánchez-Castro, I., Suvannagan, V., Grizard, P., et al. (2020). Profiling native aquifer bacteria in a uranium roll-front deposit and their role in biogeochemical cycle dynamics: Insights regarding in situ recovery mining. Science of The Total Environment, 721, 137758.
Abstract: A uranium-mineralized sandy aquifer, planned for mining by means of uranium in situ recovery (U ISR), harbors a reservoir of bacterial life that may influence the biogeochemical cycles surrounding uranium roll-front deposits. Since microorganisms play an important role at all stages of U ISR, a better knowledge of the resident bacteria before any ISR actuations is essential to face environmental quality assessment. The focus here was on the characterization of bacteria residing in an aquifer surrounding a uranium roll-front deposit that forms part of an ISR facility project at Zoovch Ovoo (Mongolia). Water samples were collected following the natural redox zonation inherited in the native aquifer, including the mineralized orebody, as well as compartments located both upstream (oxidized waters) and downstream (reduced waters) of this area. An imposed chemical zonation for all sensitive redox elements through the roll-front system was observed. In addition, high-throughput sequencing data showed that the bacterial community structure was shaped by the redox gradient and oxygen availability. Several interesting bacteria were identified, including sulphate-reducing (e.g. Desulfovibrio, Nitrospira), iron-reducing (e.g. Gallionella, Sideroxydans), iron-oxidizing (e.g. Rhodobacter, Albidiferax, Ferribacterium), and nitrate-reducing bacteria (e.g. Pseudomonas, Aquabacterium), which may also be involved in metal reduction (e.g. Desulfovibrio, Ferribacterium, Pseudomonas, Albidiferax, Caulobacter, Zooglea). Canonical correspondence analysis (CCA) and co-occurrence patterns confirmed strong correlations among the bacterial genera, suggesting either shared/preferred environmental conditions or the performance of similar/complementary functions. As a whole, the bacterial community residing in each aquifer compartment would appear to define an ecologically functional ecosystem, containing suitable microorganisms (e.g. acidophilic bacteria) prone to promote the remediation of the acidified aquifer by natural attenuation. Assessing the composition and structure of the aquifer’s native bacteria is a prerequisite for understanding natural attenuation and predicting the role of bacterial input in improving ISR efficiency.
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Veerasamy, N., Kasar, S., Murugan, R., Inoue, K., Natarajan, T., Ramola, R. C., et al. (2023). 234U/238U disequilibrium and 235U/238U ratios measured using MC-ICP-MS in natural high background radiation area soils to understand the fate of uranium. Chemosphere, 323, 138217.
Abstract: The Chhatrapur-Gopalpur coastal area in Odisha, India is a well-known natural high background radiation (HBRA) area due to the abundance of monazite (a thorium bearing radioactive mineral) in beach sands and soils. Recent studies on Chhatrapur-Gopalpur HBRA groundwater have reported high concentrations of uranium and its decay products. Therefore, the soils of the Chhatrapur-Gopalpur HBRA are reasonably suspected as the sources of these high uranium concentrations in groundwater. In this report, first the uranium concentrations in soil samples were measured using inductively coupled plasma mass spectrometry (ICP-MS) and they were found to range from 0.61 ± 0.01 to 38.59 ± 0.16 mg kg−１. Next, the 234U/238U and 235U/238U isotope ratios were measured to establish a baseline for the first time in Chhatrapur-Gopalpur HBRA soil. Multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) was used for measurement of these isotope ratios. The 235U/238U ratio was observed to be the normal terrestrial value. The 234U/238U activity ratio, was calculated to understand the secular equilibrium between 234U and 238U in soil and it varied from 0.959 to 1.070. To understand the dynamics of uranium in HBRA soil, physico-chemical characteristics of soil were correlated with uranium isotope ratios and this correlation of 234U/238U activity ratio indicated the leaching of 234U from Odisha HBRA soil.
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Moreau, M., & Daughney, C. (2021). Defining natural baselines for rates of change in New Zealand’s groundwater quality: Dealing with incomplete or disparate datasets, accounting for impacted sites, and merging into state of the-environment reporting. Science of The Total Environment, 755, 143292.
Abstract: To effectively manage sustainably groundwater bodies, it is essential to establish what the naturally occurring ranges of chemical concentrations in groundwaters are and how they change over time. We defined baseline trends for New Zealand groundwaters using: 1) pattern recognition techniques to deal with inconsistent monitoring suites between the national (110 sites) and the denser regional network (\textgreater1000 sites), and 2) multivariate statistics to identify and remove impacted sites from the enhanced dataset. Rates of changes were calculated for 13 parameters between January 2005 and December 2014 at more than 1000 groundwater quality monitoring sites. The resulting dataset included 262 complete cases (CC), which was enhanced using Machine-Learning (ML) techniques to a total of 607 sites. Hierarchical cluster analysis was used to identify trend clusters that were consistent between the CC, ML-enhanced datasets and a 2006 study based on solely on the national network. The largest cluster (WR) consisted of low magnitude changes across all parameters and was attributed to water-rock interaction processes. The second largest cluster (I) exhibited fast changes particularly for parameters linked to human-induced impact. The third largest cluster (D) comprised decreases of all parameters and was associated with dilution processes. Trend clusters were further refined using groundwater quality state information, enabling the identification of impacted sites outside of Cluster I in the ML-enhanced and CC datasets. Corresponding trend baselines were subsequently derived at unimpacted sites using univariate quantile distribution (5th and 95th percentile thresholds). Finally, we developed classifications combining baselines (state and trend) and natural variability to enhance state of the environment reporting. This allowed the new identification of deteriorating trends at sites where groundwater quality state is not yet affected in addition to trend reversals. These classifications can be adapted to incorporate new knowledge or align with surface water quality reporting.
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