Abstract: This study combines historical records of 14C and 3H in the atmosphere and soil with renewal rate and groundwater lumped parameter models to predict the abundance of 14C and 3H in groundwater over time. 624 groundwater samples from numerous studies, over four decades (1978–2019), in South Africa, Namibia, Botswana and Mozambique were collated to compare with predicted groundwater activities of 14C and 3H within the South African Development Community (SADC) region. Spatial datasets of carbonate bearing lithology, C3/C4 vegetation, summer/winter rainfall and coastal proximity were used to apply corrections to 14C and 3H data. Corrected values of 14C and 3H were compared with the theoretical abundance of these tracers, derived from the lumped parameter models, to estimate the general mean residence times and presence of groundwater mixing between modern recharge and older groundwaters. This study found that corrected values produced varying mean residence times derived from 14C ages (∼500–28500 years) and a wide range of potentially mixed waters within each aquifer system (0–100 % of tested wells) across the study area. The largest proportions of mixed groundwater, as well as the youngest mean residence times, were found in alluvial and primary fractured rock aquifers (e.g., western coast of South Africa and southern Mozambique). The smallest proportions of mixed groundwater were predicted in deep confined clay-rich aquifers as well as layered coal bearing carbonate sequences (e.g., Orapa, Malwewe and Serowe, Botswana). Insights into the proportions of mixed groundwater and mean residence times can help assess hydrological resilience on a regional scale. Such information is pertinent in promoting socio-economic development and increased water/food security in the SADC region. By understanding the resilience of groundwater resources, robust and informed strategies for water equality and GDP growth in the SADC region can be envisioned and implemented.

Abstract: It is proposed that a geothermal artesian karstic system at the central part of the Yarkon–Taninim aquifer creates the ‘Ayalon Saline Anomaly’ (ASA), whose mechanism has been under debate for several decades. A 4-year-long detailed groundwater monitoring was carried out at 68 new shallow boreholes in the Ayalon region, accompanied by a comprehensive survey of karstic voids. Results indicate the rising of warm-brackish groundwater through highly permeable swarms of karstic shafts, serving as an outflow of the artesian geothermal system. The ASA area contains ‘hot spots’, where groundwater contrasts with ‘normal’ water hundreds of meters away. The ASA temperature reaches 30°C (∼5°C warmer than its surroundings), chloride concentration reaches 528mg/l (50–100mg/l in the surrounding), H2S concentration reaches 5.6mg/l (zero all around) and pH value is 7.0 (compared with 7.8 around). Subsequently, the hydrothermal water flows laterally of at the watertable horizon through horizontal conduits, mixing with ‘normal’ fresh water which had circulated at shallow depth. Following rainy seasons, maximal watertable rise is observed in the ASA compared to its surroundings. Regional hydrogeology considerations suggest that the replenishment area for the ASA water is at the Samaria Mountains, east of the ASA. The water circulates to a great depth while flowing westward, and a cross-formational upward flow is then favored close the upper sub-aquifer’s confinement border.

Abstract: Concentrations of uranium (U) \textgreater30 µg/L in groundwater are relatively uncommon in drinking water in the United States but can be of concern in those areas where complex interactions of aquifer materials and anthropogenic alterations of the natural flow regime mobilize U. High concentrations (\textgreater30 µg/L) of U in the southeastern San Joaquin Valley, California, USA, have been detected in 24 percent of 257 domestic, irrigation, and public-supply wells sampled across an approximately 110,000 km2 area. In this study we evaluated mechanisms for mobilization of U in the San Joaquin Valley proposed in previous studies, confirming mobilization by HCO3 and refuting mobilization by NO3 and we refined our understanding of the geologic sources of U to the scale of individual alluvial fans. The location of high concentrations depends on the interactions of geological U sources from fluvial fans that originate in the Sierra Nevada to the east and seepage of irrigation water that contains high concentrations of HCO3 that leaches U from the sediments. In addition, interactions with PO4 from fertilized irrigated fields may sequester U in the aquifer. Principal component analysis of the data demonstrates that HCO3 and ions associated with high total dissolved solids in the aquifer and the percentage of agriculture near the well sampled are associated with high U concentrations. Nitrate concentrations do not appear to control release of U to the aquifer. Age dating of the groundwater and generally increasing U concentrations of the past 25 years in resampled wells where irrigation is prevalent suggests that high U concentrations are associated with younger water, indicating that irrigation of fields over the past 100 years has significantly contributed to increasing concentrations and mobilizing U. In some places, the groundwater is supersaturated with uranyl-containing minerals, as would be expected in roll front deposits. In general, the interaction of natural geological sources high in U, the anthropogenically driven addition of HCO3 and possibly phosphate fertilizer, control the location and concentration of U in each individual fluvial fan, but the addition of nitrate in fertilizer does not appear control the location of high U. These geochemical interactions are complex but can be used to determine controls on anomalously high U in alluvial aquifers.

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.

Abstract: Mitigation of localized pluvial flooding is one of the major resiliency goals in urban environments, and Green Stormwater Infrastructure (GSI) has the potential to deliver such an outcome. However, there is a lack of systematic approaches to prioritize investment in different candidate areas. This study provides a framework to identify vulnerable stormwater drainage inlets and their contributing areas, prioritize them, identify dominant factors in their selection, assess the potential of GSI in mitigating their overflows, and compare the impact and its cost to gray infrastructure upgrade alternatives. Using SWMM 5.1.013, decision trees, and a volumetric-based assessment of GSI overflow capture, we applied the framework to the City of Dallas, Texas, for three design storms with three GSI practices— bioretention cells, raingardens, and rainwater harvesting tanks. Results showed that there was a significant increase in the number of overflowing stormwater drainage inlets, referred to as hotspots, and their contributing subwatersheds, referred to as opportunity areas, with more intense storms especially in problematic watersheds. Also, prioritization results provided a series of maps to rank the opportunity areas based on overflow severity, recurrence of the overflows, and GSI availability. Moreover, classification results showed that inlet features, especially the inlet depth, were the dominant factors in the identification of the non-problematic inlets. Finally, the GSI impact assessment showed substantial overflow mitigation even at the “very high” severity levels when GSI is comprehensively deployed across opportunity areas. Despite gray infrastructure upgrades yielding higher reduction levels, their cost per cubic meter was higher than GSI. Therefore, a combination of GSI and gray results in maximum overflow reduction at a lower cost compared to common practices.