Abstract: The uranium (U) concentrations and isotopic composition of waters and sediment cores were used to investigate the transport and accumulation of U in a water system (tailings pond, two lakes, and the Kalix River) receiving mine waters from the Kiruna mine. Concentrations of dissolved U decrease two orders of magnitude between the inflow of mine waters and in the Kalix River, while the concentration of the element bound to particulate matter increases, most likely due to sorption on iron‑manganese hydroxides and organic matter. The vertical distribution of U in the water column differs between two polluted lakes with a potential indication of dissolved U supply from sediment’s pore waters at anoxic conditions. Since the beginning of exposure in the 1950s, U concentrations in lake sediments have increased \textgreater20-fold, reaching concentrations above 50 μg g-1. The distribution of anthropogenic U between the lakes does not follow the distribution of other mine water contaminants, with a higher relative proportion of U accumulating in the sediments of the second lake. Concentrations of redox-sensitive elements in the sediment core as well as Fe isotopic composition were used to re-construct past redox-conditions potentially controlling early diagenesis of U in surface sediments. Two analytical techniques (ICP-SFMS and MC-ICP-MS) were used for the determination of U isotopic composition, providing an extra dimension in the understanding of processes in the system. The (234 U)/(238 U) activity ratio (AR) is rather uniform in the tailings pond but varies considerably in water and lake sediments providing a potential tracer for U transport from the Kiruna mine through the water system, and U immobilization in sediments. The U mass balance in the Rakkurijoki system as well as the amount of anthropogenic U accumulated in lake sediments were evaluated, indicating the immobilization in the two lakes of 170 kg and 285 kg U, respectively.

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.

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.

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.

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.