Thermal springs are widespread in the European Alps, with hundreds of geothermal sites known and exploited. The thermal circulation and fluid outflows were examined in the area around Bormio (Central Italian Alps), where ten geothermal springs discharge from dolomite bodies located close to the regional Zebrù thrust. Water is heated in deep circulation systems and upwells vigorously at a temperature of about 40 °C. Heat and fluid transport is explored by steady and transient three-dimensional finite-element simulations taking into account the effect of the last glaciation, which in the study area was recognized to end around 11,000–12,000 years ago. The full regional model (ca. 700 km²) is discretized with a highly refined triangular finite-element planar grid. Numerical simulations suggest a reactivation of the system following the end of the Last Glacial Maximum. Results correctly simulate the observed discharge rate of ca. 2,400 L/min and the spring temperatures after ca. 13,000 years from deglaciation, and show a complete cooling of the aquifer within a period of approximately 50,000 years. Groundwater flow and temperature patterns suggest that thermal water flows through a deep system crossing both sedimentary and metamorphic lithotypes along a fracture network associated with the thrust system. This example gives insights into the influences of deep alpine structures and glaciations on groundwater circulation that control the development of many hydrothermal systems not necessarily associated with convective heat flow.

High and variable levels of salinity were investigated in an intermittent stream in a high-rainfall area (∼800 mm/year) of the Mt. Lofty Ranges of South Australia. The groundwater system was found to have a local, upslope saline lens, referred to here as a groundwater salinity ‘hotspot’. Environmental tracer analyses (δ¹⁸O, δ²H, ⁸⁷/⁸⁶Sr, and major elements) of water from the intermittent stream, a nearby permanent stream, shallow and deep groundwater, and soil-water/runoff demonstrate seasonal groundwater input of very saline composition into the intermittent stream. This input results in large salinity increases of the stream water because the winter wet-season stream flow decreases during spring in this Mediterranean climate. Furthermore, strontium and water isotope analyses demonstrate: (1) the upslope-saline-groundwater zone (hotspot) mixes with the dominant groundwater system, (2) the intermittent-stream water is a mixture of soil-water/runoff and the upslope saline groundwater, and (3) the upslope-saline-groundwater zone results from the flushing of unsaturated-zone salts from the thick clayey regolith and soil which overlie the metamorphosed shale bedrock. The preferred theory on the origin of the upslope-saline-groundwater hotspot is land clearing of native deep-rooted woodland, followed by flushing of accumulated salts from the unsaturated zone due to increased recharge. This cause of elevated groundwater and surface-water salinity, if correct, could be widespread in Mt. Lofty Ranges areas, as well as other climatically and geologically similar areas with comparable hydrogeologic conditions.

One important tool for water resources management in arid and semi-arid areas is groundwater potential mapping. In this study, four data-mining models including K-nearest neighbor (KNN), linear discriminant analysis (LDA), multivariate adaptive regression splines (MARS), and quadric discriminant analysis (QDA) were used for groundwater potential mapping to get better and more accurate groundwater potential maps (GPMs). For this purpose, 14 groundwater influence factors were considered, such as altitude, slope angle, slope aspect, plan curvature, profile curvature, slope length, topographic wetness index (TWI), stream power index, distance from rivers, river density, distance from faults, fault density, land use, and lithology. From 842 springs in the study area, in the Khalkhal region of Iran, 70 % (589 springs) were considered for training and 30 % (253 springs) were used as a validation dataset. Then, KNN, LDA, MARS, and QDA models were applied in the R statistical software and the results were mapped as GPMs. Finally, the receiver operating characteristics (ROC) curve was implemented to evaluate the performance of the models. According to the results, the area under the curve of ROCs were calculated as 81.4, 80.5, 79.6, and 79.2 % for MARS, QDA, KNN, and LDA, respectively. So, it can be concluded that the performances of KNN and LDA were acceptable and the performances of MARS and QDA were excellent. Also, the results depicted high contribution of altitude, TWI, slope angle, and fault density, while plan curvature and land use were seen to be the least important factors.

Antibiotic-resistant (pathogenic and non-pathogenic) organisms and genes are now acknowledged as significant emerging aquatic contaminants with potentially adverse human and ecological health impacts, and thus require monitoring. This study is the first to investigate levels of resistance among Irish groundwater (private wells) samples; Escherichia coli isolates were examined against a panel of commonly prescribed human and veterinary therapeutic antibiotics, followed by determination of the causative factors of resistance. Overall, 42 confirmed E. coli isolates were recovered from a groundwater-sampling cohort. Resistance to the human panel of antibiotics was moderate; nine (21.4%) E. coli isolates demonstrated resistance to one or more human antibiotics. Conversely, extremely high levels of resistance to veterinary antibiotics were found, with all isolates presenting resistance to one or more veterinary antibiotics. Particularly high levels of resistance (93%) were found with respect to the aminoglycoside class of antibiotics. Results of statistical analysis indicate a significant association between the presence of human (multiple) antibiotic resistance (p = 0.002–0.011) and both septic tank density and the presence of vulnerable sub-populations (<5 years). For the veterinary antibiotics, results point to a significant relationship (p = <0.001) between livestock (cattle) density and the prevalence of multiple antibiotic resistant E. coli. Groundwater continues to be an important resource in Ireland, particularly in rural areas; thus, results of this preliminary study offer a valuable insight into the prevalence of antibiotic resistance in the hydrogeological environment and establish a need for further research with a larger geological diversity.

Stable isotopes of the water molecule (δ¹⁸O and δD) for groundwater, lake water, streams, and precipitation were coupled with physical flux measurements to investigate groundwater–lake interactions and to establish a water balance for a structurally complex lake. Georgetown Lake, a shallow high-latitude high-elevation lake, is located in southwestern Montana, USA. The lake is situated between two mountain ranges with highlands primarily to the east and south of the lake and a lower valley to the west. An annual water balance and (δ¹⁸O and δD) isotope balance were used to quantify annual groundwater inflows of 2.5 × 10⁷ m³/year and lake leakage outflows of 1.6 × 10⁷ m³/year. Roughly, 57% of total inflow to the lake is from groundwater, and 37% of total outflow at Georgetown Lake is groundwater. Stable isotopes of groundwater and springs around the lake and surrounding region show that the east side of the lake contains meteoric water recharged annually from higher mountain sources, and groundwater discharge to the lake occurs through this region. However, springs located in the lower western valley and some of the surrounding domestic wells west of the lake show isotopic enrichment indicative of strong to moderate evaporation similar to Georgetown Lake water. This indicates that some outflowing lake water recharges groundwater through the underlying west-dipping bedrock in the region.

Hydrologic budgets to determine groundwater availability are important tools for water-resource managers. One challenging component for developing hydrologic budgets is quantifying water use through time because historical and site-specific water-use data can be sparse or poorly documented. This research developed a groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010 that related county-level aggregated water-use data to site-specific well locations and aquifer units. A simple population-based linear model, constrained to 0 million liters per day in 1900, provided the best means to extrapolate groundwater-withdrawal rates pre-1950s when there was a paucity of water-use data. To disaggregate county-level data to individual wells across a regional aquifer system, a programmatic hierarchical process was developed, based on the level of confidence that a well pumped groundwater for a specific use during a specific year. Statistical models tested on a subset of the best-available site-specific water-use data provided a mechanism to bracket historic groundwater use, such that groundwater-withdrawal rates ranged, on average, plus or minus 38% from modeled values. Groundwater withdrawn for public supply and domestic use accounted for between 48 and 74% of total groundwater use since 1901, highlighting that groundwater provides an important drinking-water resource. The compilation, analysis, and spatial and temporal extrapolation of water-use data remain a challenging task for water scientists, but is of paramount importance to better quantify groundwater use and availability.

The water resources that supply most of the megacities in the world are under increased pressure because of land transformation, population growth, rapid urbanization, and climate-change impacts. Dhaka, in Bangladesh, is one of the largest of 22 growing megacities in the world, and it depends on mainly groundwater for all kinds of water needs. The regional groundwater-flow model MODFLOW-2005 was used to simulate the interaction between aquifers and rivers in steady-state and transient conditions during the period 1981–2013, to assess the impact of development and climate change on the regional groundwater resources. Detailed hydro-stratigraphic units are described according to 150 lithology logs, and a three-dimensional model of the upper 400 m of the Greater Dhaka area was constructed. The results explain how the total abstraction (2.9 million m³/d) in the Dhaka megacity, which has caused regional cones of depression, is balanced by recharge and induced river leakage. The simulated outcome shows the general trend of groundwater flow in the sedimentary Holocene aquifers under a variety of hydrogeological conditions, which will assist in the future development of a rational and sustainable management approach.

Hydrogeological models of mountain regions present the opportunity to understand the role of geological factors on groundwater resources. The effects of sedimentary facies and fracture distribution on groundwater flow and resource exploitation are studied in the ancient fan delta of Sant Llorenç de Munt (central Catalonia, Spain) by integrating geological field observations (using sequence stratigraphy methods) and hydrogeological data (pumping tests, hydrochemistry and environmental isotopes). A comprehensive analysis of data portrays the massif as a single unit, constituted by different compartments determined by specific layers and sets of fractures. Two distinct flow systems—local and regional—are identified based on pumping test analysis as well as hydrochemical and isotopic data. Drawdown curves derived from pumping tests indicate that the behavior of the saturated layers, whose main porosity is given by the fracture network, corresponds to a confined aquifer. Pumping tests also reflect a double porosity within the system and the occurrence of impervious boundaries that support a compartmentalized model for the whole aquifer system. Hydrochemical data and associated spatial evolution show the result of water–rock interaction along the flow lines. Concentration of magnesium, derived from dolomite dissolution, is a tracer of the flow-path along distinct stratigraphic units. Water stable isotopes indicate that evaporation (near a 5% loss) occurs in a thick unsaturated zone within the massif before infiltration reaches the water table. The hydrogeological analysis of this outcropping system provides a methodology for the conceptualization of groundwater flow in similar buried systems where logging and hydrogeological information are scarce.

The processes that affect water chemistry as the water flows from recharge areas through breccia-pipe uranium deposits in the Grand Canyon region of the southwestern United States are not well understood. Pigeon Spring had elevated uranium in 1982 (44 μg/L), compared to other perched springs (2.7–18 μg/L), prior to mining operations at the nearby Pigeon Mine. Perched groundwater springs in an area around the Pigeon Mine were sampled between 2009 and 2015 and compared with material from the Pigeon Mine to better understand the geochemistry and hydrology of the area. Two general groups of perched groundwater springs were identified from this study; one group is characterized by calcium sulfate type water, low uranium activity ratio ²³⁴U/²³⁸U (UAR) values, and a mixture of water with some component of modern water, and the other group by calcium-magnesium sulfate type water, higher UAR values, and radiocarbon ages indicating recharge on the order of several thousand years ago. Multivariate statistical principal components analysis of Pigeon Mine and spring samples indicate Cu, Pb, As, Mn, and Cd concentrations distinguished mining-related leachates from perched groundwater springs. The groundwater potentiometric surface indicates that perched groundwater at Pigeon Mine would likely flow toward the northwest away from Pigeon Spring. The geochemical analysis of the water, sediment and rock samples collected from the Snake Gulch area indicate that the elevated uranium at Pigeon Spring is likely related to a natural source of uranium upgradient from the spring and not likely related to the Pigeon Mine.

Artificial intelligence (AI) techniques have increasingly become efficient alternative modeling tools in the water resources field, particularly when the modeled process is influenced by complex and interrelated variables. In this study, two AI techniques—artificial neural networks (ANNs) and support vector machine (SVM)—were employed to achieve deeper understanding of the salinization process (represented by chloride concentration) in complex coastal aquifers influenced by various salinity sources. Both models were trained using 11 years of groundwater quality data from 22 municipal wells in Khan Younis Governorate, Gaza, Palestine. Both techniques showed satisfactory prediction performance, where the mean absolute percentage error (MAPE) and correlation coefficient (R) for the test data set were, respectively, about 4.5 and 99.8% for the ANNs model, and 4.6 and 99.7% for SVM model. The performances of the developed models were further noticeably improved through preprocessing the wells data set using a k-means clustering method, then conducting AI techniques separately for each cluster. The developed models with clustered data were associated with higher performance, easiness and simplicity. They can be employed as an analytical tool to investigate the influence of input variables on coastal aquifer salinity, which is of great importance for understanding salinization processes, leading to more effective water-resources-related planning and decision making.