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Author Smedley, P.L.; Bearcock, J.M.; Ward, R.S.; Crewdson, E.; Bowes, M.J.; Darling, W.G.; Smith, A.C. url  openurl
  Title Monitoring of methane in groundwater from the Vale of Pickering, UK: Temporal variability and source discrimination Type Journal Article
  Year 2023 Publication Chemical Geology Abbreviated Journal  
  Volume (down) 636 Issue Pages 121640  
  Keywords Aquifer, Biogenic, Ethane, Hydrocarbons, Methane, Shale gas  
  Abstract Groundwater abstracted from aquifers in the Vale of Pickering, North Yorkshire, UK and monitored over the period 2015–2022, shows evidence of variable but commonly high concentrations of dissolved CH4. Sampled groundwater from the Jurassic organic-rich Kimmeridge Clay Formation (boreholes up to 180 m depth) has concentrations up to 57 mg/L, and concentrations up to 59 mg/L are found in groundwater from underlying confined Corallian Group limestone (borehole depths 50–227 m). The high concentrations are mainly from boreholes in the central parts of the vale. Small concentrations of ethane (C2H6, up to 800 μg/L) have been found in the Kimmeridge Clay and confined Corallian groundwaters, and of propane (C3H8, up to 160 μg/L) in deeper boreholes (110–180 m) from these formations. The concentrations are typically higher in groundwater from the deeper boreholes and vary with hydrostatic pressure, reflecting the pressure control on CH4 solubility. The occurrences contrast with groundwater from shallow Quaternary superficial deposits which have low CH4 concentrations (up to 0.39 mg/L), and with the unconfined and semi-confined sections of the Corallian aquifer (up to 0.7 mg/L) around the margins of the vale. Groundwater from the Quaternary, Kimmeridge Clay formations and to a small extent the confined Corallian aquifer, supports local private-water supplies, that from the peripheral unconfined sections of Corallian also supports public supply for towns and villages across the region. Dissolved methane/ethane (C1/C2) ratios and stable-isotopic compositions (δ13C-CH4, δ2H-CH4 and δ13C-CO2) suggest that the high-CH4 groundwater from both the Kimmeridge Clay and confined Corallian formations derives overwhelmingly from biogenic reactions, the methanogenesis pathway by CO2 reduction. A small minority of groundwater samples shows a more enriched δ13C-CH4 composition (−50 to −44 ‰) which has been interpreted as due to anaerobic or aerobic methylotrophic oxidation in situ or post-sampling oxidation, rather than derivation by a thermogenic route. Few of the existing groundwater sites are proximal to abandoned or disused conventional hydrocarbon wells that exist in the region, and little evidence has been found for an influence on groundwater dissolved gases from these sites. The Vale of Pickering has also been under recent consideration for development of an unconventional hydrocarbon (shale-gas) resource. In this context, the monitoring of dissolved gases has been an important step in establishing the high-CH4 baseline of groundwaters from Jurassic deposits in the region and in apportioning their sources and mechanisms of genesis.  
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  Series Volume Series Issue Edition  
  ISSN 0009-2541 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number THL @ christoph.kuells @ smedley_monitoring_2023 Serial 172  
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Author Leeuwen, Z.R. van; Klaar, M.J.; Smith, M.W.; Brown, L.E. url  openurl
  Title Quantifying the natural flood management potential of leaky dams in upland catchments, Part II: Leaky dam impacts on flood peak magnitude Type Journal Article
  Year 2024 Publication Journal of Hydrology Abbreviated Journal  
  Volume (down) 628 Issue Pages 130449  
  Keywords Nature based solutions, Large wood, Empirical, Hydrograph analysis, Ecosystem services, Transfer function noise model  
  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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  ISSN 0022-1694 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number THL @ christoph.kuells @ Vanleeuwen2024130449 Serial 228  
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Author Seidl, C.; Wheeler, S.A.; Page, D. url  openurl
  Title Understanding the global success criteria for managed aquifer recharge schemes Type Journal Article
  Year 2024 Publication Journal of Hydrology Abbreviated Journal  
  Volume (down) 628 Issue Pages 130469  
  Keywords Managed Aquifer Recharge (MAR), Fuzzy-set Qualitative Comparative Analysis, Water banking, Groundwater, Water management, Water storage  
  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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  ISSN 0022-1694 ISBN Medium  
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  Notes Approved no  
  Call Number THL @ christoph.kuells @ Seidl2024130469 Serial 273  
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Author 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. url  openurl
  Title Machine learning–based optimal design of the in-situ leaching process parameter (ISLPP) for the acid in-situ leaching of uranium Type Journal Article
  Year 2023 Publication Journal of Hydrology Abbreviated Journal  
  Volume (down) 626 Issue Pages 130234  
  Keywords In-situ leaching, Injection rate design, Lixiviant concentration design, Machine learning, Simulation-optimisation, Uncertainty  
  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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  ISSN 0022-1694 ISBN Medium  
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  Notes Approved no  
  Call Number THL @ christoph.kuells @ wang_machine_2023 Serial 210  
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Author Johnson, R.S.H.; Alila, Y. url  openurl
  Title Nonstationary stochastic paired watershed approach: Investigating forest harvesting effects on floods in two large, nested, and snow-dominated watersheds in British Columbia, Canada Type Journal Article
  Year 2023 Publication Journal of Hydrology Abbreviated Journal  
  Volume (down) 625 Issue Pages 129970  
  Keywords Probabilistic physics, Forest hydrology, Attribution science, Flood Frequency Analysis, Stochastic hydrology, Nonstationarity  
  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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  ISSN 0022-1694 ISBN Medium  
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  Notes Approved no  
  Call Number THL @ christoph.kuells @ Johnson2023129970 Serial 245  
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