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Tisherman, R.A.; Rossi, R.J.; Shonkoff, S.B.C.; DiGiulio, D.C. |
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Title |
Groundwater uranium contamination from produced water disposal to unlined ponds in the San Joaquin Valley |
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Journal Article |
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Year |
2023 |
Publication |
Science of The Total Environment |
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904 |
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166937 |
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Groundwater, Oil & gas, Produced water, San Joaquin Valley, Uranium |
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In the southern San Joaquin Valley (SJV) of California, an agriculturally productive region that relies on groundwater for irrigation and domestic water supply, the infiltration of produced water from oil reservoirs is known to impact groundwater due to percolation from unlined disposal ponds. However, previously documented impacts almost exclusively focus on salinity, while contaminant loadings commonly associated with produced water (e.g., radionuclides) are poorly constrained. For example, the infiltration of bicarbonate-rich produced waters can react with sediment-bound uranium (U), leading to U mobilization and subsequent transport to nearby groundwater. Specifically, produced water infiltration poses a particular concern for SJV groundwater, as valley-fill sediments are well documented to be enriched in geogenic, reduced U. Here, we analyzed monitoring well data from two SJV produced water pond facilities to characterize U mobilization and subsequent groundwater contamination. Groundwater wells installed within 2 km of the facilities contained produced water and elevated levels of uranium. There are \textgreater400 produced water disposal pond facilities in the southern SJV. If our observations occur at even a fraction of these facilities, there is the potential for widespread U contamination in the groundwaters of one of the most productive agricultural regions in the world. |
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0048-9697 |
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THL @ christoph.kuells @ tisherman_groundwater_2023 |
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159 |
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Mathuthu, M.; Uushona, V.; Indongo, V. |
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Title |
Radiological safety of groundwater around a uranium mine in Namibia |
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Journal Article |
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Year |
2021 |
Publication |
Physics and Chemistry of the Earth, Parts A/B/C |
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122 |
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102915 |
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Groundwater, ICP-MS, Radiological hazard, Uranium mining |
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Uranium mining activities produce the main element used in nuclear energy production. However, it can also negatively affect the environment including groundwater by release of residues or effluent containing radioactive elements. The study investigated the concentration and radiological hazard of uranium in groundwater and seepage water from the tailings of a uranium mine in Namibia. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was used to assess the concentration of uranium in the groundwater and seepage water and the radiological hazards were determined. The radiological hazard indices Radium equivalent activity (Raeq), Absorbed dose (D), Annual Effective Dose equivalent (AEDE), External hazard index (Hex) and Internal hazard index (Hin) were determined and compared to limits recommended by United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). The calculated average value of D and Hin of groundwater is 108.11nGyh−1 and 1.26, respectively and are above the UNSCEAR values (55 nGyh−1 and 1). Further, the average values of Raeq, AEDE and Hex were below the recommended values. The isotopic ratio of uranium radionuclides in groundwater indicates that the uranium in the sampled groundwater is below 1 suggesting it is not natural uranium present but a possible contamination from the mine seepage. The radiological hazard parameters of the seepage water were above the recommended values and thus pose a radiation risk to human and environment. |
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1474-7065 |
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THL @ christoph.kuells @ mathuthu_radiological_2021 |
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160 |
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Kumar, V.; Setia, R.; Pandita, S.; Singh, S.; Mitran, T. |
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Title |
Assessment of U and As in groundwater of India: A meta-analysis |
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Journal Article |
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Year |
2022 |
Publication |
Chemosphere |
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303 |
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135199 |
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Arsenic, Geology, Groundwater, Health risk, Soil texture, Uranium |
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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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0045-6535 |
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THL @ christoph.kuells @ kumar_assessment_2022 |
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161 |
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Gómez, P.; Garralón, A.; Buil, B.; Turrero, M.J.; Sánchez, L.; Cruz, B. de la |
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Modeling of geochemical processes related to uranium mobilization in the groundwater of a uranium mine |
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Journal Article |
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2006 |
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Science of The Total Environment |
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366 |
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1 |
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295-309 |
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Geochemical modeling, Granite, Groundwater, Uranium mine, Uranium retention |
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This paper describes the processes leading to uranium distribution in the groundwater of five boreholes near a restored uranium mine (dug in granite), and the environmental impact of restoration work in the discharge area. The groundwater uranium content varied from \textless1 μg/L in reduced water far from the area of influence of the uranium ore-containing dyke, to 104 μg/L in a borehole hydraulically connected to the mine. These values, however, fail to reflect a chemical equilibrium between the water and the pure mineral phases. A model for the mobilization of uranium in this groundwater is therefore proposed. This involves the percolation of oxidized waters through the fractured granite, leading to the oxidation of pyrite and arsenopyrite and the precipitation of iron oxyhydroxides. This in turn leads to the dissolution of the primary pitchblende and, subsequently, the release of U(VI) species to the groundwater. These U(VI) species are retained by iron hydroxides. Secondary uranium species are eventually formed as reducing conditions are re-established due to water–rock interactions. |
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0048-9697 |
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THL @ christoph.kuells @ gomez_modeling_2006 |
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162 |
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Holmes, M.; Campbell, E.E.; Wit, M. de; Taylor, J.C. |
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Can diatoms be used as a biomonitoring tool for surface and groundwater?: Towards a baseline for Karoo water |
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2023 |
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South African Journal of Botany |
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161 |
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211-221 |
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Bioindicator, Diatom, Hydraulic fracturing, Karoo, Water quality |
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The environmental risks from shale gas extraction through the unconventional method of ‘fracking’ are considerable and impact on water supplies below and above ground. Since 2010 the recovery of natural shale gas through fracking has been proposed in parts of the fragile semi-arid ecosystems that make up the Karoo biome in South Africa. These unique ecosystems are heavily reliant on underground water, intermittent and ephemeral springs, which are at great risk of contamination by fracking processes. Diatoms are present in all water bodies and reflect aspects of the environment in which they are located. As the possibility of fracking has not been removed, the aim of the project was to determine if diatoms could be used for rapid biomonitoring of underground and surface waters in the Karoo. Over a period of 24 months, water samples and diatom species were collected simultaneously from 65 sites. A total of 388 diatom taxa were identified from 290 samples with seasonal and substrate variation affecting species composition but not the environmental information. Species diversity information, on the other hand, often varied significantly between substrates within a single sample. Analysis using CCA established that the diatom composition was affected by lithium, oxidized nitrogen, electrical conductivity, and sulphate levels in the sampled water. We conclude that changes in diatom community composition in the Karoo do reflect the water chemistry and could be useful as bioindicators. |
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0254-6299 |
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THL @ christoph.kuells @ holmes_can_2023 |
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163 |
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Moreau, M.; Daughney, C. |
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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 |
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Journal Article |
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2021 |
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Science of The Total Environment |
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755 |
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143292 |
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Baseline, Groundwater quality, Machine-learning, Monitoring, New Zealand, Trends |
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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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THL @ christoph.kuells @ moreau_defining_2021 |
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164 |
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Hofmann, H.; Pearce, J.K.; Hayes, P.; Golding, S.D.; Hall, N.; Baublys, K.A.; Raiber, M.; Suckow, A. |
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Multi-tracer approach to constrain groundwater flow and geochemical baseline assessments for CO2 sequestration in deep sedimentary basins |
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Journal Article |
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2023 |
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International Journal of Coal Geology |
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104438 |
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CO geological storage, Great Artesian Basin, Groundwater chemistry, Isotopic tracer, Surat Basin |
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Geological storage of gases will be necessary in the push to net zero and the energy transition to reduce carbon emissions to atmosphere. These include CO2 geological storage in suitable sandstone reservoirs. Understanding groundwater flow, connectivity and hydrogeochemical processes in aquifer and storage systems is vital to prevent risk and protect important water resources, such as the Great Artesian Basin. Here, we provide a ‘tool-box’ of geochemical assessment methods to provide information on flow patterns through the basin’s aquifers (changes in chemistry along flow path), stagnant versus flowing conditions (cosmogenic isotopes and noble gases), inter-aquifer connectivity and seal properties (major ions, Sr and stable isotopes), water quality (major ions and metals) and general assessments on residence times of groundwater (cosmogenic isotopes and noble gases). This information can be used with reservoir and groundwater models to inform on possible changes in the above-mentioned processes and serve as input parameters for CO2 injection impact modelling. We demonstrate the use and interpretation on an example of a potential CO2 storage geological sequestration site in the Surat Basin, part of the Great Artesian Basin, and the aquifers that overly the reservoir. The stable water isotopes are depleted compared to average rainfall and most likely indicate greater contributions from monsoonal rain events from the northern monsoonal troughs, where amount and rainout effects lead to the depletion rather than colder recharge climates. This is supported by the modern recharge temperatures from noble gases. Inter-aquifer mixing between the Precipice Sandstone reservoir and the Hutton Sandstone aquifer seems unlikely as the Sr isotope ratios are distinctly different suggesting that the Evergreen Formation is a seal in the locations sampled. Mixing, however, occurs on the edges of the basin, especially in the south-east and east where the Surat Basin transitions into the Clarence-Moreton Basin. Groundwater flow appears to be to the south in the Precipice Sandstone, with a component of flow east to the Clarence-Morton Basin. The cosmogenic isotopes and noble gases strongly indicate very long residence times of groundwater in the central south Precipice Sandstone around a proposed storage site. 14C values below analytical uncertainty, R36Cl ratios at secular equilibrium as well as high He concentrations and high 40Ar/36Ar ratios support the argument that groundwater flow in this area is extremely slow or groundwater is stagnant. The results of this study reflect the geological and hydrogeological complexities of sedimentary basins and that baseline studies, such as this one, are paramount for management strategies. |
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0166-5162 |
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THL @ christoph.kuells @ hofmann_multi-tracer_2023 |
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165 |
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Edmunds, W.M.; Shand, P.; Hart, P.; Ward, R.S. |
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The natural (baseline) quality of groundwater: a UK pilot study |
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2003 |
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Science of The Total Environment |
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310 |
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1 |
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25-35 |
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Baseline quality, Groundwater, Hydrogeochemistry, Monitoring, Water Policy |
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Knowledge of the natural baseline quality of groundwaters is an essential prerequisite for understanding pollution and for imposing regulatory limits. The natural baseline of groundwaters may show a range of concentrations depending on aquifer mineralogy, facies changes, flow paths and residence time. The geochemical controls on natural concentrations are discussed and an approach to defining baseline concentrations using geochemical and statistical tools is proposed. The approach is illustrated using a flowline from the Chalk aquifer in Berkshire, UK where aerobic and anaerobic sections of the aquifer are separately considered. The baseline concentrations for some elements are close to atmospheric values whereas others evolve through time-dependent water–rock interaction. Certain solutes (K, NH4+), often considered contaminants, reach naturally high concentrations due to geochemical controls; transition metal concentrations are generally low, although their concentrations may be modified by redox controls. It is recommended that the baseline approach be incorporated into future management strategies, notably monitoring. |
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THL @ christoph.kuells @ edmunds_natural_2003 |
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166 |
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Uddin, M.G.; Diganta, M.T.M.; Sajib, A.M.; Hasan, M.A.; Moniruzzaman, M.; Rahman, A.; Olbert, A.I. |
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Assessment of hydrogeochemistry in groundwater using water quality index model and indices approaches |
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2023 |
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Heliyon |
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9 |
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9 |
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19668 |
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CCME index, Groundwater quality, Hydrogeochemistry, Irrigation indices, Nuclear power plant, Water quality index |
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Groundwater resources around the world required periodic monitoring in order to ensure the safe and sustainable utilization for humans by keeping the good status of water quality. However, this could be a daunting task for developing countries due to the insufficient data in spatiotemporal resolution. Therefore, this research work aimed to assess groundwater quality in terms of drinking and irrigation purposes at the adjacent part of the Rooppur Nuclear Power Plant (RNPP) in Bangladesh. For the purposes of achieving the aim of this study, nine groundwater samples were collected seasonally (dry and wet season) and seventeen hydro-geochemical indicators were analyzed, including Temperature (Temp.), pH, electrical conductivity (EC), total dissolved solids (TDS), total alkalinity (TA), total hardness (TH), total organic carbon (TOC), bicarbonate (HCO3−), chloride (Cl−), phosphate (PO43−), sulfate (SO42−), nitrite (NO2−), nitrate (NO3−), sodium (Na+), potassium (K+), calcium (Ca2+) and magnesium (Mg2+). The present study utilized the Canadian Council of Ministers of the Environment water quality index (CCME-WQI) model to assess water quality for drinking purposes. In addition, nine indices including EC, TDS, TH, sodium adsorption ratio (SAR), percent sodium (Na%), permeability index (PI), Kelley’s ratio (KR), magnesium hazard ratio (MHR), soluble sodium percentage (SSP), and Residual sodium carbonate (RSC) were used in this research for assessing the water quality for irrigation purposes. The computed mean CCME-WQI score found higher during the dry season (ranges 48 to 74) than the wet season (ranges 40 to 65). Moreover, CCME-WQI model ranked groundwater quality between the “poor” and “marginal” categories during the wet season implying unsuitable water for human consumption. Like CCME-WQI model, majority of the irrigation index also demonstrated suitable water for crop cultivation during dry season. The findings of this research indicate that it requires additional care to improve the monitoring programme for protecting groundwater quality in the RNPP area. Insightful information from this study might be useful as baseline for national strategic planners in order to protect groundwater resources during the any emergencies associated with RNPP. |
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THL @ christoph.kuells @ uddin_assessment_2023 |
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167 |
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Singh, A.; Patel, S.; Bhadani, V.; Kumar, V.; Gaurav, K. |
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AutoML-GWL: Automated machine learning model for the prediction of groundwater level |
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Journal Article |
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2024 |
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Engineering Applications of Artificial Intelligence |
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127 |
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107405 |
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AutoML, Bayesian optimisation, Groundwater, Machine learning |
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Abstract |
Predicting groundwater levels is pivotal in curbing overexploitation and ensuring effective water resource governance. However, groundwater level prediction is intricate, driven by dynamic nonlinear factors. To comprehend the dynamic interaction among these drivers, leveraging machine learning models can provide valuable insights. The drastic increase in computational capabilities has catalysed a substantial surge in the utilisation of machine learning-based solutions for effective groundwater management. The performance of these models highly depends on the selection of hyperparameters. The optimisation of hyperparameters is a complex process that often requires application-specific expertise for a skillful prediction. To mitigate the challenge posed by hyperparameter tuning’s problem-specific nature, we present an innovative approach by introducing the automated machine learning (AutoML-GWL) framework. This framework is specifically designed for precise groundwater level mapping. It seamlessly integrates the selection of best machine learning model and adeptly fine-tunes its hyperparameters by using Bayesian optimisation. We used long time series (1997-2018) data of precipitation, temperature, evaporation, soil type, relative humidity, and lag of groundwater level as input features to train the AutoML-GWL model while considering the influence of Land Use Land Cover (LULC) as a contextual factor. Among these input features, the lag of groundwater level emerged as the most relevant input feature. Once the model is trained, it performs well over the unseen data with a strong correlation of coefficient (R = 0.90), low root mean square error (RMSE = 1.22), and minimal bias = 0.23. Further, we compared the performance of the proposed AutoML-GWL with sixteen benchmark algorithms comprising baseline and novel algorithms. The AutoML-GWL outperforms all the benchmark algorithms. Furthermore, the proposed algorithm ranked first in Friedman’s statistical test, confirming its reliability. Moreover, we conducted a spatial distribution and uncertainty analysis for the proposed algorithm. The outcomes of this analysis affirmed that the AutoML-GWL can effectively manage data with spatial variations and demonstrates remarkable stability when faced with small uncertainties in the input parameters. This study holds significant promise in revolutionising groundwater management practices by establishing an automated framework for simulating groundwater levels for sustainable water resource management. |
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0952-1976 |
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THL @ christoph.kuells @ singh_automl-gwl_2024 |
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168 |
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