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Groundwater is essential for drinking water and economic development, yet its availability and quality are threatened by climate change, pollution, and rising demand. Effective groundwater management relies on accurate numerical models for flow and contaminant transport. Traditional calibration techniques often struggle with the uncertainty and spatial variability inherent in hydrogeological data. Although geostatistical simulations can represent this variability, their computational complexity limits their use in large-scale models. To overcome these challenges, ensemble methods like the Ensemble Kalman Filter (EnKF) and Ensemble Smoother (ES) have been introduced for model updates using spatiotemporal data. However, they face limitations in high-dimensional systems with sparse observational data, common in hydrogeology. This paper introduces an innovative data assimilation method combining Well-by-Well (WbW) and observation Type-by-observation Type (TbT) techniques. This approach utilizes local analysis to effectively calibrate large, complex groundwater models with limited observations, resulting in a more stable and accurate calibration process. The method is tested on a synthetic 3D model and a real regional groundwater flow model, showing significant improvements in calibration and predictions. A 3D synthetic model of a coastal aquifer with saltwater intrusion was developed to evaluate the WbW & TbT updates within the Ensemble Smoother with Multiple Data Assimilation (ES-MDA 4x) method. The results indicate improved calibration and reduced errors in hydraulic head and salt concentration predictions. This study demonstrates the robustness of the WbW & TbT method in calibrating the Ville Mercier regional hydrogeological model, showcasing its potential for complex hydrogeological settings. By updating parameters locally around each observation well, the WbW & TbT method addresses high-dimensional challenges while preserving data amplitude and managing the complexity of regional hydrogeological systems. Results confirm that this method enhances the accuracy and reliability of groundwater flow models, making it a vital tool for resource management amid environmental challenges. [ABSTRACT FROM AUTHOR]

The present study focuses on a site contaminated with halogenated hydrocarbons, utilizing a detailed inventory of contamination data to achieve the precise characterization of groundwater pollution. Employing MOFLOW-2000 software, a groundwater flow model was established for the study area. In conjunction with MT3DMS, a predictive model was constructed to simulate and forecast the spatiotemporal distribution of contaminant migration and attenuation following site remediation. The simulation area was delineated based on geographical features, with the vertical simulation range of strata also determined. To establish a hydrogeological conceptual model for the target remediation site, comprehensive hydrogeological data were collected, encompassing geological structures, hydrological parameters, and rainfall information. Model calibration was based on the six layers of low-permeability aquifer intervals revealed by geological exploration wells MW1–5, as well as the distribution of groundwater-level contours and rainfall data. Based on data from September 2010, an initial three-dimensional model of tetrachloroethylene (PCE) distribution was generated. Subsequently, a solute transport model for PCE was established, incorporating various enhanced reductive dechlorination (ERD) remediation strategies applied at different times and locations. Calibration against actual monitoring data revealed the presence of unmonitored dense non-aqueous phase liquids (DNAPLs) at the site, contributing to the continuous release and elevation of PCE concentrations. By accounting for DNAPL release, the calibrated transport and attenuation model closely matched observed concentration decay patterns, effectively capturing the actual dynamics of contaminant transport and attenuation within the groundwater system. The modeling approach proposed in this study provides important support for contamination remediation and attenuation at the current site, and it is also applicable to simulating and predicting pollution scenarios at similar sites. [ABSTRACT FROM AUTHOR]

Selecting representative groundwater monitoring wells in polluted areas is crucial to comprehensively assess groundwater pollution, thereby ensuring effective groundwater remediation. However, numerous factors can affect the effectiveness of groundwater monitoring well network optimizations. A local sensitivity analysis method was used in this study to analyze the hydrogeological parameters of a simulation groundwater solute transport model. The results showed a strong effect of longitudinal dispersion and transverse dispersion on the output results of the simulation model, and a good fit between the backpropagation neural network (BPNN)-based alternative model's results and those obtained using the solute transport simulation model, accurately reflecting the input and output relationship of the simulation model. The optimized groundwater monitoring layout scheme consisted of four groundwater monitoring wells, namely no. 7, no. 16, no. 23, and no. 24. These wells resulted in a groundwater fluoride pollution rate of 98.44%, which was substantially higher than that obtained using the random layout scheme. In addition, statistical analysis of the fluoride groundwater pollution results obtained using the Monte Carlo random simulation highlighted continuous and high groundwater fluoride levels in the second and third pollution sources and their downstream groundwater. Therefore, more attention should be devoted to these sources to ensure the effective remediation of groundwater pollution in the study area. [ABSTRACT FROM AUTHOR]

The Arborea plain in Sardinia (Italy) is classified as a nitrate vulnerable zone (NVZ). In the present study, the individual work steps that are necessary to progress from the existing 3D hydrogeological model to a 3D numerical groundwater model using the interactive finite-element simulation system FEFLOW 7.4 are shown. The results of the transient flow model highlight the influence of the drainage network on the overall groundwater management: the total water volume drained by the ditches accounted for approximately 58% of the annual outflow volume. The numerical transport simulations conducted from 2012 to 2020 using hypothetical field-based nitrate input scenarios globally underestimated the high concentrations that were observed in the NVZ. However, as observed in the field, the computed nitrate concentrations in December 2020 still varied strongly in space, from several mg L−1 to several hundreds of mg L−1. The origin of these remaining local hotspots is not yet known. The modeling of rainfall fluctuations under the influence of climate change revealed a general long-term decline in the groundwater level of several tens of centimeters in the long term and, in conjunction with a zero-nitrate scenario, led to a significant decrease in nitrate pollution. Although hotspots were attenuated, the concentrations at several monitoring wells still exceeded the limit value of 50 mg L−1. [ABSTRACT FROM AUTHOR]

In order to predict the ground settlement in a scientific, intuitive, and simple way, based on the theory of Bio-consolidation, a three-dimensional fluid-solid coupled numerical calculation programme FGS-3D for ground settlement was compiled by using the Fortran 95 language, and a front-end operation platform was developed by using Microsoft VisualBasic, so that a three-dimensional variable-parameter fully coupled viscoelastic-plastic model of ground settlement was constructed using the city of Yancheng as an example, and the development of ground settlement and horizontal displacement changes from 2021 to 2030 were predicted. The results show that the three-dimensional fully coupled finite-element numerical model of building load, groundwater seepage, and soil deformation established by the above computer development program can directly create a hydrogeological conceptual model of groundwater mining and predict ground settlement, so as to achieve the visualisation of the three-dimensional seepage of groundwater and the fully coupled simulation of ground subsidence in the whole process of groundwater mining. Under the joint action of construction load and groundwater mining, the water level of the aquifer in Yancheng City rises by 1.26 m on average in the main groundwater mining area of the group III pressurised aquifer, forming two smaller landing funnels, and the lowest water level of the two landing funnels is −15 m. [ABSTRACT FROM AUTHOR]

North Florida's karst springs are among the largest and most abundant in the world. Despite relatively stable spring discharges, flow reversals can episodically occur in some springs when river waters backflow into the aquifer during flood events. Reversals are normal features of the springs along the Suwanee River, but the changing incidence of these reversals in response to anthropogenic activities or climate change remains unclear and the mechanisms responsible for these reversals remain poorly described. Here we develop a reduced‐complexity hydrogeological model of the Suwannee River catchment to explore conditions needed to induce spring flow reversals. Our model demonstrates that reversals require two conditions: (a) a hydrogeological setting that combines an upstream catchment with rapid hydrological responses to meteorological drivers, which freely drains to a downstream catchment containing the karst aquifer (i.e., the spring‐fed river segment); and (b) meteorological conditions that create sufficient temporal variability in recharge. Given both conditions, recharge events can propagate from the upstream catchment and fill the downstream river segment faster than it can drain, causing river stage to rise above the aquifer head, resulting in temporary spring flow reversal (or bank storage). Our model accurately predicts significant post‐flood increases in spring flow as bank storage recedes, and using measured electrical conductivity at a major river‐adjacent spring we also quantify the enhancement of limestone dissolution (cave enlargement) due to reversal events. A comprehensive assessment of the incidence and duration of reversal events shows a predominant influence of climate and vegetation changes over that of groundwater pumping. Plain Language Summary: North Florida's karst springs are among the largest and most abundant in the world. Spring flow is very stable and usually into the main river, but reversals of flow direction may occur temporarily, such that water from the river enters the subsurface through the springs. This is a natural feature, but its causes and future behavior under climate change and human activities are poorly understood. In this work, we develop a simple model of the Suwannee River catchment that describes spring flow and reversals, showing that reversals require both appropriate geological as well as meteorological conditions. We also show that spring flow reversals contribute significantly to the limestone cave enlargement near the river, and that the future characteristics of reversal events are most dependent on climate and vegetation changes. Key Points: A reduced‐complexity model explains flow reversals in Florida karst springs due to fast discharge response from upstream surficial aquiferThe occurrence of reversals requires a certain hydrogeological setting and sufficient temporal variability in aquifer rechargeThe model also quantifies enhanced limestone dissolution rates (cave enlargement) near the river due to flow reversals [ABSTRACT FROM AUTHOR]

Introduction: Geological models provide a critical foundation for hydrogeological models and significantly influence the spatial distribution of key hydraulic parameters such as hydraulic conductivity, transmissivity, or porosity. The conventional modeling workflow involves a hierarchical approach that simulates three levels: stratigraphical units, lithologies, and finally properties. Although lithological descriptions are often available in the data (boreholes), the same is not true for unit descriptions, leading to potential inconsistencies in the modeling process. Methodology: To address this challenge, a geostatistical learning approach is presented, which aims to predict stratigraphical units at boreholes where this information is lacking, primarily using lithological logs as input. Various standard machine learning algorithms have been compared and evaluated to identify the most effective ones. The outputs of these algorithms are then processed and utilized to simulate the stratigraphy in boreholes using a sequential approach. Subsequently, these boreholes contribute to the construction of stochastic geological models, which are then compared with models generated without the inclusion of these supplementary boreholes. Results: This method is useful for reducing uncertainty at certain locations and for mitigating inconsistencies between units and lithologies. Conclusion: This approach maximizes the use of available data and contributes to more robust hydrogeological models. [ABSTRACT FROM AUTHOR]

Groundwater level tidal analysis is a powerful technique to monitor aquifer's permeability and hence its change over time. Earthquakes are known to affect aquifer's properties, in their vicinity through static stress changes but also further away through dynamic stresses. Most often changes are in the form of permeability increases, but sometimes decreases; the changes can be either permanent or transient. These observations are relatively well documented but the physical processes behind these changes are not well understood. By combining solid‐earth and barometric tidal groundwater level responses in a borehole in a coherent poroelastic theoretical framework, and a bi‐layer hydrogeological model, we recover a 15 years‐long time series evolution of aquifer transmissivity and shear modulus. This study showcases the full potential of the tidal analysis method, coupling pore pressure diffusion and rock deformation, at the frontier of hydrogeology and rock physics. This unprecedented measurement of permeability and shear modulus evolution by tidal analysis reveals, during interseismic period, high sensitivity of this shallow aquifer to effective stress, and thus to pore pressure. Thanks to additional finite element simulation of seismic wave propagation, we explore the different mechanisms affecting permeability and shear modulus in the studied fractured andesite aquifer. This study confirms the predominant role of seismic dynamic stresses, and more precisely of dynamic shear stresses, in the change of permeability following an earthquake. Plain Language Summary: Tidal oscillations of groundwater level, observable in boreholes all around the world, are information‐rich signals for hydrogeologist to infer the properties of surrounding aquifers, and how they evolve over time. Most importantly, it allows to monitor aquifer permeability and how it evolves under the influence of earthquakes, especially through static stresses changes or seismic wave propagation. Here we push the limits of what tidal analysis can reveal by also retrieving the shear modulus of the studied aquifer. This new observable, combined with the computation of regional earthquakes stresses, allows us to understand better how aquifer properties are modified by earthquakes. The analysis reveals first that dynamic shear stresses are the most probable cause of permeability changes, and second that the sensitivity of our fractured aquifer permeability to pore pressure is high. Key Points: The 15‐years' time series of permeability and shear modulus of the aquifer is deduced from the analysis of solid earth and barometric tidesCo‐seismic irreversible changes of fractured aquifer permeability are induced by earthquakes dynamic shear stressesInterseismic permeability variations of the aquifer are controlled by pore pressure, that is, the hydraulic head [ABSTRACT FROM AUTHOR]

Water‐table maps are fundamental to hydrogeological studies and a manual, hand‐drawn method is still commonly used to produce them. Despite this, the accuracy and variability of such maps have received little attention in international literature. In a unique experiment, 63 groundwater professionals drew water‐table equipotential contours based on the same dataset of point measurements and were asked to infer flow directions and predict groundwater elevations at predefined locations. The root mean squared error (RMSE) for the average map calibration data was 10.5 m, which is accuracy comparable to numerical groundwater models. This study confirmed that to produce hand‐drawn water‐table maps, practitioners seek to not only fit the spatial data, but also to conform to their own cognitive model of hydrogeological concepts and processes. The calibration accuracy increased with experience; from a RMSE of 13.3 m for practitioners with 0–3 years of experience to a RMSE of 9.2 m for those with four or more years. Despite considerable variability in the style of the hand‐drawn water‐table maps, the maps were consistent in their representation of the dominant regional groundwater flow directions. There was less consensus, however, in predicting the direction of surface water‐groundwater interaction for a stream reach. Hand‐drawn water‐table mapping remains useful and valid, especially as a starting point for hydrogeological conceptualization, yet further work is required to resolve issues around transparency, repeatability, and reproducibility. [ABSTRACT FROM AUTHOR]

The soil–water characteristic curve (SWCC) is an important parameter of unsaturated soil, and almost all the engineering characteristics of unsaturated soil are more or less related to the SWCC. The SWCC contains important information for geotechnical engineering, water engineering, hydrogeology modelling and climate modelling. It is noted that the experimental measurement of SWCC is costly and time consuming, which limits the implementation of principles of unsaturated soil mechanics in practical engineering. The indirect method, which estimates the SWCC from the index properties of soil, can provide the SWCC with the errors which are within tolerance in practical engineering. In addition, the indirect method can determine SWCC very fast and almost with no cost. In this paper, the domestic sandy soils are selected and the index properties of those sands are used to correlate the SWCC fitting parameters. Consequently, mathematical equations are proposed to estimate SWCC from index properties of domestic sands. The proposed models are trained from 44 sets of experimental data and verified with another independent 8 sets of experimental data from published literature. It is observed that the results from the proposed model agree well with the experimental data from literature. [ABSTRACT FROM AUTHOR]

Karst terrains can undergo geotechnical issues like subsidence and collapse, occurring both naturally and anthropogenically. The municipality of Sete Lagoas, in the State of Minas Gerais, Brazil, is notable for overexploiting a karst aquifer, resulting in adverse effects such as drying lakes and geotechnical problems. This study aims to assess the progression of geotechnical risk areas in the central urban area from 1940 to 2020 and simulate future scenarios until 2100. To achieve this, historical hydraulic head data, a three-dimensional geological model, and a karst geotechnical risk matrix were used to develop a calibrated FEFLOW numerical model. Results show that before the installation of the first pumping well in 1942, the natural groundwater flow direction was primarily northeast. However, in the 1980s, a cone of depression emerged in the city, creating a zone of influence (ZOI) with a surface area of around 30 km2. Between 1940 and 2020, twenty geotechnical collapse events occurred in defined risk zones, often in regions where limestone outcrops or is mantled in association with the ZOI. In future scenarios, if the 2020 total annual groundwater pumping rate (Q = 145,000 m3/d) remains constant until 2100, the geotechnical risk zones will continue expanding laterally. To establish a sustainable risk state, a 40% decrease in the pumping rate (Q = 85,500 m3/d) is necessary. [ABSTRACT FROM AUTHOR]

Geological information is required to parameterize hydrogeological properties in groundwater flow models. Our aim was to provide a hydrogeological model for the island of Norderney, Northwest Germany and the surrounding Wadden Sea for this purpose. The model focuses on Holocene, Pleistocene and Pliocene deposits which are the most relevant to groundwater flow in and around the island's freshwater lens. For these geological units, borehole data was available that allowed us to distinguish between sediments acting as aquifers and aquitards. Conceptual units were derived that comprise the most common stratigraphic and petrographic features into discrete entities. The borehole data was supplemented by maps of the pre‐Holocene surface as well as data from an existing stratigraphic model for deeper geological units. The model was developed and created using the open‐source geological modelling software GemPy. The resulting model contains major hydrogeological units that can be assumed continuous over a larger extent of the model area based on the available data. From the deeper geology, a possible range of locations of the aquifer base below Norderney was extracted. By integrating borehole data, existing geological models and geological interpretations available in the literature, this dataset complements the so far mainly cross‐sectional and partial descriptions of the hydrogeology below Norderney. [ABSTRACT FROM AUTHOR]

The paper discusses the possibility of using groundwater as a source of water supply for Mykolaiv during emergencies or military operations. A hydrogeological model of the Mykolaiv groundwater field was developed to investigate the water exchange pattern and sources of operational groundwater reserves in the Upper Sarmatian aquifer, which is a primary source of drinking groundwater in the Mykolaiv area. The influence of various factors on water-bearing capacity of the Upper Sarmatian sediments was assessed, including the vulnerability of the fresh groundwater to the intrusion of brackish water from the Bug Estuary. The study also examined the feasibility of operating the aquifer under forced conditions, depending on the duration of emergency periods or military operations. [ABSTRACT FROM AUTHOR]

Coastal aquifers play an important role in marine ecosystems by providing high fluxes of nutrients and solutes via submarine groundwater discharge pathways. The physical and chemical characterization of these dynamic systems is foundational to understanding the extent and magnitude of hydrogeologic processes and their subsequent contributions to the marine environment. We describe a km‐scale experimental field site located in a glaciofluvial delta entering Kachemak Bay, Alaska. Our characterization applies geophysical (ERT and HVSR), hydrogeologic (grain size analyses, slug tests and tidal response analyses) and geochemical (major ions and stable water isotopes) methods to describe the complexity of coastal aquifers in proglacial environments currently experiencing rapid transformations. The hydrogeologic and geophysical techniques revealed thick (20–84 m) sediments dominated by sands and gravels and delineated zones of freshwater, brackish water and saltwater at both high and low tides within the subterranean estuary. Estimates of hydraulic conductivities via multiple approaches ranged from 2 to 250 m d−1, with means across the four methods within the same order of magnitude. Tidal response analyses highlighted a coastal aquifer in strong connection with the sea as evidenced by clear spring‐ and neap‐tidal signals within a proximal piezometric hydrograph. Geochemical sampling revealed coastal groundwaters as substantially enriched in solutes compared to proximal river samples with limited variability across seasons. A clear connection between the Wosnesenski River and the adjacent aquifer was also observed, with concentrated recharge from the river corridor during the meltwater season. This combination of approaches provides the basis for a conceptual model for coastal aquifer systems within the Gulf of Alaska and an upscaled mean daily yield of freshwater and solutes from the delta subsurface. Our findings are critical for subsequent numerical simulations of groundwater flow, tidal pumping and chemical reactions and transport in these understudied environments. This approach may be applied for low‐cost, large‐scale hydrogeologic investigations in coastal areas and may be particularly useful for remote sites where access and mobility are challenging. [ABSTRACT FROM AUTHOR]

The main objective of this research was to develop a geological and geophysical modeling to infer the geometry and thickness in the sedimentary sequence of the middle basin of the Bogotá River with emphasis on the Guadalupe Group, reconstructing the stratigraphic sequence, structural setting, hydrogeological modeling, and potential geothermal uses. Various geophysical methods were applied, including vertical electrical soundings (VES), and magneto telluric soundings (MT-VES), whose results were complemented with the interpretation of seismic lines, regional and local gravity anomaly maps, and borehole data, among others, which allowed to model the subsurface from the surface to depths beyond 3000 meters, with emphasis on the interval between 500m to 1000m depth. Integrated models were developed from interpretations of electrical resistivity data, gravity and magnetic data, reflection seismic and borehole data. Based on the results, potential deep aquifers have been proposed to be confirmed by drilling. These deep aquifers can contribute to satisfy the need for water, which historically has been explored and overexploited from shallower aquifers in this sector of the basin. A recommendation was also made to consider the potential of low enthalpy thermal energy for agro-industrial purposes associated with groundwater's temperature at the depth of this research. As a result, the modeled sedimentary sequence is characterized by a thick quaternary overburden overlying an intensively folded and faulted Neogene, Paleogene, and upper Cretaceous formations, mainly composed of siltstone, sandstones, and shale sequences of fluvial and marine environment, including facies of marine regressions and transgressions near the coastline. The penetration obtained allows establishing a high hydrogeological potential in the first 2000m depth, especially associated with the Guadalupe group, where the Labor and Tierna and Arenisca Dura formations have the highest hydrogeological potential. In addition, the preliminary estimation of thermal gradients suggest that low enthalpy geothermal energy potential is feasible to be used for the agro-industrial demand of energy of the study area. [ABSTRACT FROM AUTHOR]

Modeling surface water quality has become crucial in providing better strategies for managing surface water resources, and adequate findings need accurate and geographically dispersed data. Hydrogeological modeling of these data sets is possible using empirically-based models. The other statistical models are also an alternative approach. In this study, a process with maximum probability is considered with the help of machine learning tools (MLT) to have optimized and valid output. The proposed method combines remote sensing and geographic information systems (RS and GIS) and MLT, which are appropriate for the predicament of neither small, large scale, nor long-term simulations. MLT methods such as VAR and ARIMA are developed in the Python programming with Jupyter notebook and tested according to the data in the spatial prediction for surface water quality parameters such as Tr, pH, Ec, TDS, AL, Ca++, NO−3, So, Cl, F−, Fe, and Mg2+ in the Krishna District, Andhra Pradesh, India—lower delta part. The delta with susceptible zones was identified using RS and GIS as those areas are prone to direct exposure to surface water contaminants from aquaculture, agricultural runoff, small- and medium-scale businesses, and household trash. Achieving effective surface water management for this ecosystem is critical for regional water management. The geographical information about the concentrations acquired via the RS and GIS was compared to the statistical modeling findings and verified using real-time measurements. MLT modeling seems more realistic than the experimental setting; data from the previous 20 years (2000–2020) were used for modeling, and the predicted values presented in the paper are predicted for the year 2021. The computed R2 value of ranges between 0.75 and 0.96% is recorded with ARIMA, and VAR posted range between 0.56 and 0.75% with the trained and tested data. The findings show the potential for MLT of geographically dispersed hydrogeological data to be used for pollution-free surface water management. From the surface water management perspective, combining RS and GIS and MLT offers an alternate data analysis approach for obtaining quick results utilizing a less laborious process that produces acceptable results. [ABSTRACT FROM AUTHOR]

This study presents the development of a comprehensive three-dimensional groundwater flow model for the Erbil Basin utilizing the Groundwater Modeling System (GMS). The Erbil Basin, situated in the Kurdistan Region of Iraq, is a vital water resource area facing increasing water demands and environmental challenges. The three-dimensional nature of the groundwater flow system is crucial for accurately understanding and managing water resources in the basin. The modeling process involved data collection, geological and hydrogeological characterization, conceptual model development, and numerical simulation using GMS software MODFLOW 2000 package. Various parameters such as hydraulic conductivity, recharge rates, and boundary conditions were integrated into the model to represent the complex hydrogeological conditions of the basin. Model calibration was performed by comparing simulated groundwater levels with observed data from monitoring wells across the basin, using the automatic calibration method of automated Parameter Estimation (PEST). Pilot points were applied to adjust the hydraulic conductivity in the model area spatially. Sensitivity analysis was conducted to assess the influence of key parameters on model predictions and to identify areas of uncertainty. The developed three-dimensional groundwater flow model provides valuable insights into the dynamics of groundwater flow, recharge-discharge mechanisms, and potential impacts of future scenarios such as climate change and water resource management strategies. It serves as a useful tool for decision-makers, water resource managers, and researchers to evaluate different management scenarios and formulate sustainable groundwater management policies for the Erbil Basin. In conclusion, this study demonstrates the effectiveness of using GMS for developing three-dimensional groundwater flow models in complex hydrogeological settings like the Erbil Basin, contributing to improved understanding and management of groundwater resources in the region. [ABSTRACT FROM AUTHOR]

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Non‐perennial streams play a crucial role in ecological communities and the hydrological cycle. However, the key parameters and processes involved in stream intermittency remain poorly understood. While climatic conditions, geology and land use are well identified, the assessment and modelling of groundwater controls on streamflow intermittence remain a challenge. In this study, we explore new opportunities to calibrate process‐based 3D groundwater flow models designed to simulate hydrographic network dynamics in groundwater‐fed headwaters. Streamflow measurements and stream network maps are considered together to constrain the effective hydraulic properties of the aquifer in hydrogeological models. The simulations were then validated using visual observations of water presence/absence, provided by a national monitoring network in France (ONDE). We tested the methodology on two pilot unconfined shallow crystalline aquifer catchments, the Canut and Nançon catchments (Brittany, France). We found that both streamflow and stream network expansion/contraction dynamics are required to calibrate models that simultaneously estimate hydraulic conductivity K$$ K $$ and porosity Φ$$ \varPhi $$ with low uncertainties. The calibration allowed good prediction of stream intermittency, both in terms of flow and spatial extent. For the two catchments studied, Canut and Nançon, the hydraulic conductivity is close reaching 1.5 × 10−5 m/s and 4.5 × 10−5 m/s, respectively. However, they differ more in their storage capacity, with porosity estimated at 0.1% and 2.2%, respectively. Lower storage capacity leads to higher groundwater level fluctuations, shorter aquifer response times, an increase in the proportion of intermittent streams and a reduction in perennial flow. This new modelling framework for predicting headwater streamflow intermittence can be deployed to improve our understanding of groundwater controls in different geomorphological, geological and climatic contexts. It will benefit from advances in remote sensing and crowdsourcing approaches that generate new observational data products with high spatial and temporal resolution. [ABSTRACT FROM AUTHOR]

Groundwater is essential for drinking water and economic development, yet its availability and quality are threatened by climate change, pollution, and rising demand. Effective groundwater management relies on accurate numerical models for flow and contaminant transport. Traditional calibration techniques often struggle with the uncertainty and spatial variability inherent in hydrogeological data. Although geostatistical simulations can represent this variability, their computational complexity limits their use in large-scale models. To overcome these challenges, ensemble methods like the Ensemble Kalman Filter (EnKF) and Ensemble Smoother (ES) have been introduced for model updates using spatiotemporal data. However, they face limitations in high-dimensional systems with sparse observational data, common in hydrogeology. This paper introduces an innovative data assimilation method combining Well-by-Well (WbW) and observation Type-by-observation Type (TbT) techniques. This approach utilizes local analysis to effectively calibrate large, complex groundwater models with limited observations, resulting in a more stable and accurate calibration process. The method is tested on a synthetic 3D model and a real regional groundwater flow model, showing significant improvements in calibration and predictions. A 3D synthetic model of a coastal aquifer with saltwater intrusion was developed to evaluate the WbW & TbT updates within the Ensemble Smoother with Multiple Data Assimilation (ES-MDA 4x) method. The results indicate improved calibration and reduced errors in hydraulic head and salt concentration predictions. This study demonstrates the robustness of the WbW & TbT method in calibrating the Ville Mercier regional hydrogeological model, showcasing its potential for complex hydrogeological settings. By updating parameters locally around each observation well, the WbW & TbT method addresses high-dimensional challenges while preserving data amplitude and managing the complexity of regional hydrogeological systems. Results confirm that this method enhances the accuracy and reliability of groundwater flow models, making it a vital tool for resource management amid environmental challenges.

Since 2013, 34 surveys of surface and ground waters within and outside the former Hg-mine of Abbadia San Salvatore (Italy), which is currently under remediation, were performed for determining Hg, As, Sb, and main and minor solutes. The water quality is rather poor since most waters show relatively high Hg concentrations (up to 695 µg/L). Differently, As and Sb only overcome the Italian law thresholds in a few sites. A high geochemical variability was observed for most groundwaters without any clear relationship between wet and dry periods. The main source of chalcophile elements is likely related to: (i) the interaction between meteoric waters and soils contaminated by the previous production of mercury; or (ii) the interaction between meteoric waters and the anthropic filling material of a former paleo-valley near the furnaces edifices. While the remediation is expected to be concluded in 2025, the aquifer contamination still remains a problem. Our investigation, including geochemical/hydrogeological modeling, is prodromal to future activities aimed at reducing the Hg content. Currently, the construction of a hydraulic barrier is apparently the most suitable solution to minimize the interaction processes between water–rock and man-made material, which are responsible for the 10-year concentration variability. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Peshawar Basin is a part of the lower Himalayas that contains an enormous amount of groundwater storage. The evaluation of groundwater potential in the southern Peshawar district was done using well logging, lithostratigraphic properties, and combined hydrogeological and geophysical techniques. A total of 13 Vertical Electrical Sounding (VES) profiles were utilised to assess potential groundwater zones for surface resistivity studies. The aquifer system was delineated by comparing the data from five boreholes with the VES findings. An exploration of super-saturated groundwater potential was conducted, utilising parameters such as transmissivity (T), hydraulic conductivity (K), storativity, and the Dar Zarrouk analysis. The Dar Zarrouk analysis yielded average values of transverse resistance (TR), longitudinal conductance (S), and anisotropy (λ), which were determined to be 8069.12, 0.51, and 0.561, respectively. Similarly, average values of transmissivity (T), hydraulic conductivity (K), and storativity were obtained, resulting in 28.67, 0.24, and 0.000177, respectively. The saturated confined layer, characterized by highly saturated zones, was identified to begin at a depth of approximately 119 m and extend down to the lower boundary of the aquifer. The examined aquifer is composed of clay, sand, gravel, boulders, and loose layers of lacustrine mud that are interlayered to form an unconsolidated groundwater aquifer system. The aquifers in the region are highly developed and consisted of unconfined, semi-confined, and confined aquifer systems. As a result, it is possible to use the aquifer for groundwater development in the study area because of its low -to-medium discharge. [ABSTRACT FROM AUTHOR]

Groundwater resources in Morocco often face sustainability challenges due to increased exploitation and climate change. Specifically, the Al-Haouz-Mejjate groundwater in the Marrakesh region is faced with overexploitation and insufficient recharge. However, the complex subsurface geometries hamper hydrogeological modeling, characterization, and effective management. Reliably estimating aquifer substrate topography is critical for groundwater models but is challenged by limited direct measurements. This study develops nonlinear machine learning models to infer substrate depths by fusing sparse borehole logs with regional geospatial data. A Gaussian process regression approach provided robust holistic mapping, leveraging flexibility, and uncertainty quantification. Supplementary neural network architectures focus on isolating specific variable relationships, like surface elevation–substrate. Model accuracy exceeded 0.8 R-squared against validation boreholes. Spatial visualizations confirmed consistency across landscape transects. Elevation and piezometric data proved most predictive, though multivariate inputs were required for the lowest errors. The results highlight the power of statistical learning to extract meaningful patterns from disparate hydrological data. However, model opacity and the need for broader training datasets remain barriers. Overall, the work demonstrates advanced machine learning as a promising avenue for illuminating complex aquifer geometries essential for sustainability. Hybrid approaches that use both data-driven and physics-based methods can help solve long-standing problems with hydrogeological characterization. [ABSTRACT FROM AUTHOR]

Hydrogeological models require reliable uncertainty intervals that honestly reflect the total uncertainties of model predictions. The operation of a conventional Bayesian framework only produces realistic (interpretable in the context of the natural system) inference results if the model structure matches the data‐generating process, that is, applying Bayes' theorem implicitly assumes the underlying model to be true. With an imperfect model, we may obtain a too‐narrow‐for‐its‐bias uncertainty interval when conditioning on a long time‐series of calibration data, because the assumption of a quasi‐true model becomes too strict. To overcome the problem of overconfident posteriors, we propose a non‐parametric Bayesian method, called Tau‐averaging method: it applies Bayesian analysis on sliding time windows along the data time series for calibration. Thus, it obtains so‐called transitional posteriors per time window. Then, we average these into a wider predictive posterior. With the proposed routine, we explicitly capture the time‐varying impact of model error on prediction uncertainty. The length of the calibration window is optimized to maximize goal‐oriented statistical skill scores for predictive coverage. Our method loosens the perfect‐model‐assumption by conditioning only on small windows of the data set at a time, that is, it assumes that "the model is sufficient to follow the system dynamics for a smaller duration." We test our method on two cases of soil moisture modeling and show how it improves predictive coverage as compared to the conventional Bayesian approach. Our findings demonstrate that the proposed method convincingly overcomes the overconfidence drawback of Bayesian inference under model misspecification and long calibration time‐series. Plain Language Summary: Mathematical models mimic environmental systems to match what we see, and to predict what will happen. Unfortunately, such models are always simplifications of reality, balancing their complexity between manageability and accuracy. Consequently, interpreting model‐based conclusions requires caution. Assume a model has ten adjustable parameters to make it match with a system. The best‐possible achievable fit to observations is imperfect. Yet, statistical tools indicate we knew these parameters perfectly well after adjustment, especially when adjusting on long data series. Then, we might start believing that this model's adjusted predictions are perfect. We call this "overconfidence." Ways to overcome overconfidence include extending models by statistical components, making them predict intervals and probabilities rather than exact numbers. However, adjusting these additional statistical components has been difficult to date. In our new approach, we force the model only to match short time windows of the data, and move this window through the whole data set. As we use little data per window, we reduce the overconfidence effect. Instead, the model adjusts parameters and predicts outputs differently in each window. To make predictions, we combine the outputs into a more robust result, such that the testing data fall inside the intervals generated by our method. Key Points: We propose a data‐driven Bayesian method to obtain realistic uncertainty estimates despite model errorsOur method builds on a statistically rigorous, time‐windowed Bayesian framework without prior assumptions about error sources or patternsThe method is confirmed to provide realistic predictive coverage with two synthetic test cases and a real‐world lysimeter case study [ABSTRACT FROM AUTHOR]

This paper presents the verification results of an experimental site that employed a particle tracking algorithm to assess the transport of tracers through the composite formation of gravel and Cholan in northwest Taiwan. A suitable hydrogeological conceptual model that describes the flow characteristics of the gravel formation and Cholan formation is essential to evaluate groundwater flow and management at this site. Continuous porous medium (CPM) can be easily applied in the gravel formation, while the Cholan formation, characterized by argillaceous sandstone, is commonly treated as a porous medium. However, this study obtains its fracture distribution through geological surveys, and the key fracture parameters are also collected, analyzed, and incorporated into the model. Four hydrogeological conceptual models, including CPM, discrete fracture network (DFN), equivalent continuous porous medium (ECPM), and hybrid DFN/ECPM, are generated for this complex formation. This study combines the conceptual models of the gravel and Cholan formation into four cases to describe the characteristics of the composite formation. The groundwater flow field of four cases is simulated, and the particle tracking method is employed to model the tracer transport. Simulation results from the four hybrid models all yielded a breakthrough curve (BTC) for the first 15 h, indicating that the tracer arrived at the designated outlet within this timeframe and primarily flowed through the gravel formation, while long-time particle tracking revealed a possible flow path through the Cholan formation after 15 h. The breakthrough curve of the four cases shows that the ECPM model is more suitable for representing the heterogeneity of the Cholan formation than the common CPM model. This study provides a suitable numerical algorithm of the conceptual model of the Cholan formation based on strong evidence by considering different models and comparing them with in situ tracer tests. [ABSTRACT FROM AUTHOR]

We present a new computationally efficient methodology to estimate the probability of rainfall-induced slope failure based on mechanical probabilistic slope stability analyses coupled with a hydrogeological model of the upslope area. The model accounts for: (1) uncertainty of geotechnical and hydrogeological parameters; (2) rainfall precipitation recorded over a period of time; and (3) the effect of upslope topography. The methodology provides two key outputs: (1) time-varying conditional probability of slope failure; and (2) an estimate of the absolute frequency of slope failure over any time period of interest. The methodology consists of the following steps: first, characterising the uncertainty of the slope geomaterial strength parameters; second, performing limit equilibrium method stability analyses for the realisations of the geomaterial strength parameters required to calculate the slope probability of failure by a Monte Carlo Simulation. The stability analyses are performed for various phreatic surface heights. These phreatic surfaces are then matched to a phreatic surface time series obtained from the 1D Hillslope-Storage Boussinesq model run for the upslope area to generate Factor of Safety (FoS) time series. A time-varying conditional probability of failure and an absolute frequency of slope failure can then be estimated from these FoS time series. We demonstrate this methodology on a road slope cutting in Nepal where geotechnical tests are not readily conducted. We believe this methodology improves the reliability of slope safety estimates where site investigation is not possible. Also, the methodology enables practitioners to avoid making unrealistic assumptions on the hydrological input. Finally, we find that the time-varying failure probability shows marked variations over time as a result of the monsoon wet–dry weather. Highlights: Probabilistic slope stability analyses are coupled with a hydrogeological hillslope model to estimate the probability and frequency of rainfall-induced slope failure. The model accounts for the uncertainty about rainfall using a time-dependent method, and for uncertainty relative to the geomaterial properties. The model is tested on a road cut slope in Nepal (mountainous area subject to a monsoon season) finding that the cut slope will fail every other year. Time-varying failure probability shows marked variations over time as a result of the monsoon wet–dry weather. The findings indicate that it is important to use a time-dependent system to represent rainfall variability for slope failure probability analysis. [ABSTRACT FROM AUTHOR]

The karst aquifer located in the Environmental Protection Area of Lagoa Santa, Minas Gerais, Brazil, exhibits the characteristic morphological features of an evolved karst environment, including large caves, sinkholes, and copious springs. Understanding the hydrogeological characteristics of karst aquifers is crucial for effective management of public resources and prevention of contamination, as these aquifers are highly vulnerable, making it essential to identify and mitigate potential risks. Given the ongoing economic and population growth in this region, the assessment of the hydrogeological parameters that control the dynamics of local flow becomes relevant for the proper evaluation of hydrogeological models and the management of water resources. Four classical pumping test analysis methods were compared to quantify the flow and storativity of the aquifer: Theis (1935), Neuman (1972), Moench (1984), and Agarwal (1980). In addition, indirect estimation methods based on the identification of capture zones and the analysis of recession curves of water courses were employed, since these approaches are cheaper and easier to apply in areas with low information. The statistical analysis of the results suggests that classical solutions can be applied to the karst aquifer to estimate hydrogeological parameters, apart from the Storage Coefficient obtained using the Neuman method. In general, the indirect estimation methods tend to produce values that are consistent with those obtained through direct methods, albeit with some reservations. The transmissivity values obtained from the pumping tests were approximately 3.0 x 10-4 m²/s, while the storage coefficient is estimated to be around 3.7 x 10-3. The indirect estimation methods yield transmissivity values of about 1.8 x 10-4 m²/s using the capture zone method, and storage coefficient values of 4.0 x 10-3 and 3.9 x 10-2 using recession curve analysis. [ABSTRACT FROM AUTHOR]

Copyright of Hydrogeology Journal is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of offshore freshened groundwater (OFG) is gaining importance due to population growth and environmental pressure on coastal water resources. Marine controlled source electromagnetic (CSEM) methods can effectively map the spatial extent of OFG systems using electrical resistivity as a proxy. Integrating these resistivity models with sub‐surface properties, such as host‐rock porosity, allows for estimates of pore‐water salinity. However, evaluating the uncertainty in pore‐water salinity using resistivity models obtained from deterministic inversion approaches presents challenges, as they provide only one best‐fit model, with no associated estimate of uncertainty. To address this limitation, we employ trans‐dimensional Markov‐Chain Monte‐Carlo inversion on marine time‐domain CSEM data, acquired in the Canterbury Bight, New Zealand. We integrate resistivity posterior probability distributions with borehole and seismic reflection data to estimate pore‐water salinity with corresponding uncertainty estimates. The results highlight a low‐salinity groundwater body in the center of the survey area, hosted by consecutive silty‐ and fine‐sand layers approximately 20–60 km from the coast. The posterior probability distribution of resistivity models indicates freshening of the OFG body toward the shoreline within a permeable, coarse‐sand layer 40–150 m beneath the seafloor, suggesting an active connection between the OFG body and the terrestrial groundwater system. The approach demonstrates how Bayesian inversion constrains the uncertainties in resistivity models and subsequently in pore‐water salinity estimates. Our findings highlight the potential of Bayesian inversion to enhance our understanding of OFG systems and provide uncertainty constraints for hydrogeological modeling, thereby contributing to sustainable water resource development. Plain Language Summary: Geophysical methods that measure the electromagnetic properties of the Earth are effective in investigating freshwater sources beneath the seafloor. By combining the geophysical and geological information, we can better assess the quality of this groundwater. In this study, we develop a workflow that uses statistical methods to integrate electromagnetic observations with borehole and acoustic measurements along the eastern coast of the South Island of New Zealand. We aim to improve our understanding of the groundwater quality beneath the seafloor. Our research confirms the presence of freshened groundwater within the sandy seafloor up to 60 km from the coastline. Importantly, our observations indicate that the groundwater quality increases toward the coast. These findings are significant as they enhance the hydrogeological modeling of the groundwater system and suggest its potential as a source of freshwater. Key Points: A Bayesian workflow is employed to evaluate uncertainty in pore‐water salinity estimatesOffshore groundwater in Canterbury Bight stores freshened pore‐water in fine‐grained sediments, likely extending from the onshore aquiferCorrelation between pore‐water salinities and seismic‐derived stratigraphy provides boundary conditions for hydrogeological modeling [ABSTRACT FROM AUTHOR]

The development of the oil industry is accompanied by a technogenic impact on the environment. According to various estimates, annual losses of hydrocarbons can reach 15% of the produced volumes at the transportation stage alone. These losses are accompanied by the formation of more than 510 million tons of contaminated soil. Emergency situations, which are difficult to predict, may arise at oil production and oil refining enterprises. That situations also lead to environmental pollution. The remediation of groundwater from dissolved petroleum products is one of the difficult tasks. There are two main approaches to remediation of oil pollution: ex situ, i.e. at special sites, and in situ, i.e. at the site of contamination. Using in situ techniques can be significantly cheaper and more effective. The applying of in situ techniques should be based on a well-developed strategy for implementing environmental protection measures. Mathematical modeling allows one to reliably determine and justify hydrogeological studies and to obtain parameters for the development of designed solutions. This article studies the possibility of mathematical modeling methods applying for the biotechnological process of groundwater remediation used a dosed supply of oxygen into a contaminated aquifer.The results of field observations and model data were compared. During the research, it was established that the developed geomigration model, which uses a package of instantaneous aerobic degradation of hydrocarbons, adequately describes the dynamics of pollutant reduction in groundwater when compared with field measurements. To assess the effectiveness of the measures taken, forecast calculations were additionally performed on the model with different numbers of treatment wells and the distance between them. The data obtained allowed us to conclude that the development of mathematical modeling at the preliminary stage makes it possible to select the most optimal scheme for groundwater treatment even before the construction of the technological complex, which can significantly reduce costs when implementing such projects.

In this work, we study the calibration of the parameters of a hydrogeological watershed model by comparing a 1D+2D approach that combines unsaturated 1D columns and a saturated 2D model, with a full 3D approach. In a first step, a heterogeneous permeability field is estimated by an inversion procedure for each model (2D saturated and 3D unsaturated). The fields obtained are similar but the calculation time is obviously much higher in the case of the 3D model: the 2D model seems therefore sufficient and more efficient to evaluate permeability fields using piezometric measurements in the case of vertically homogeneous aquifers. The second step focuses on the calibration of the hydraulic parameters by adjusting the hydraulic heights either derived from a 1D+2D reference model at several fictitious points distributed over the entire domain, or measured in a dozen real piezometers. Both approaches provide a good fit to the piezometric measurements, but the parameter values differ significantly: the van Genuchten alpha coefficient is unrealistic in the 1D+2D approach, reflecting a poorer consideration of the modeling unsaturated zone, while the porosity value is higher in the 3D approach, which can probably be remedied by developing a more suitable cost function. [ABSTRACT FROM AUTHOR]

This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km 2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km 2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment. [ABSTRACT FROM AUTHOR]

The presence of high concentrations of geogenic arsenic (As) in groundwater poses a serious threat to the health of millions of individuals globally. This paper examines the research progress of groundwater with high concentrations of geogenic As through a comprehensive literature review and analysis, covering distribution, health risks, in situ remediation, regulatory technologies, and development trends, to establish a reference for future research. The global distribution of geogenic high-As groundwater is mainly in inland basins and river deltas of countries in South Asia, East Asia, and South America. High-As risk areas can be modeled using hydrogeologic data and field measurements. This modeling approach allows for assessing and measuring potential areas of high-As groundwater. In order to provide safe drinking water promptly and effectively to areas affected by high-As groundwater, in situ rapid detection and remediation techniques have been given significant attention. This paper introduces household- or community-scale As removal technologies, including flocculant–disinfectant, bucket treatment units, use of activated alumina, use of nano zero-valent iron, aquifer iron coating technology, and bioremediation, summarizing the basic mechanisms of arsenic removal for each technology. Guaranteeing the sustainability of site-scale remediation technologies, reasonable aquifer management, and exploring alternative water sources are crucial for combating high-As groundwater contamination. Future studies should aim to elucidate the mechanisms of As's coexistence with other pollutants in groundwater, effectively treating As-containing wastes or sludge produced during the treatment process and exploring better treatment options. [ABSTRACT FROM AUTHOR]

Altered crystalline catchments are complex to study and model, as they present multi‐scale properties that control their hydrogeological behaviour and that are difficult to capture through a single geophysical imaging technique. Several volumes of interest must be sampled in order that both small‐scale (porosity, layering) and large‐scale (bedrock, weathering, faults) heterogeneities can be captured. We propose a geoelectrical model of the Strengbach catchment (Vosges Mountains, France), aiming at identifying the weathered structures and hydrogeological functioning of the aquifer. This is achieved through electrical resistivity tomography (ERT) and Controlled‐Source Audio‐Magnetotelluric (CSAMT) measurements and the use of appropriate measurement set‐ups. Meters‐scale shallow contrasts in the top soil, catchment‐scale shallow contrasts (top 30 m), and large‐scale vertical contrasts (up to 150 m) were resolved through this methodology. A structural interpretation is proposed, based on information provided by borehole measurements (gamma ray, optical images), analysis of sampled waters, and geological mapping. The limits at depth of the weathered and fractured granite, not detected by ERT, are detected by CSAMT. The analysis showed that the weathering state of the granite controls, at first order, the electrical resistivity signal. Shallow geoelectrical signal (first 30 m) is particularly driven by surface conductivity and hence by the clay content, whereas deep geoelectrical signal may arise from both the ionic content of pore waters and the clay content. A structural model is proposed and discussed. Geoelectrical contrasts revealed several qualities of weathered saprolite between the northern and the southern slopes. The inferred structural model and the distribution of weathered and unweathered crystalline units are considered for their respective effect on the hydrogeology, leading to the proposition of a new hydrogeological conceptual model of the catchment. [ABSTRACT FROM AUTHOR]

Tropical volcanic islands are biodiversity hotspots where the Critical Zone (CZ) still remains poorly studied. In such steep topographic environments associated with extreme climatic events (cyclones), deployment and maintenance of monitoring equipment is highly challenging. While a few Critical Zone Observatories (CZOS) are located in tropical volcanic regions, none of them includes a Tropical Montane Cloud Forest (TMCF) at the watershed scale. We present here the dataset of the first observatory from the French network of critical zone observatories (OZCAR) located in an insular tropical and volcanic context, integrating a 'Tropical Montane Cloud Forest': The ERORUN‐STAFOR observatory. This collaborative observatory is located in the northern part of La Réunion island (Indian Ocean) within the 45.0 km2 watershed of Rivière des Pluies (i.e., Rainfall river) which hosts the TMCF of Plaines des Fougères, one of the best preserved natural habitats in La Réunion Island. Since 2014, the ERORUN‐STAFOR monitoring in collaboration with local partners collected a multidisciplinary dataset with a constant improvement of the instrumentation over time. At the watershed scale and in its vicinity, the ERORUN‐STAFOR observatory includes 10 measurement stations covering the upstream, midstream and downstream part of the watershed. The stations record a total of 48 different variables through continuous (sensors) or periodic (sampling) monitoring. The dataset consists of continuous time series variables related to (i) meteorology, including precipitation, air temperature, relative humidity, wind speed and direction, net radiation, atmospheric pressure, cloud water flux, irradiance, leaf wetness and soil temperature, (ii) hydrology, including water level and temperature, discharge and electrical conductivity (EC) of stream, (iii) hydrogeology, including (ground)water level, water temperature and EC in two piezometers and one horizontally drilled groundwater gallery completed by soil moisture measurements under the canopy. The dataset is completed by periodic time series variables related to (iv) hydrogeochemistry, including field parameters and water analysis results. The periodic sampling survey provides chemical and isotopic compositions of rainfall, groundwater, and stream water at different locations of this watershed. The ERORUN‐STAFOR monitoring dataset extends from 2014 to 2022 with an acquisition frequency from 10 min to hourly for the sensor variables and from weekly to monthly frequency for the sampling. Despite the frequent maintenance of the monitoring sites, several data gaps exist due to the remote location of some sites and instrument destruction by cyclones. Preliminary results show that the Rivière des Pluies watershed is characterized by high annual precipitation (>3000 mm y−1) and a fast hydrologic response to precipitation (≈2 h basin lag time). The long‐term evolution of the deep groundwater recharge is mainly driven by the occurrence of cyclone events with a seasonal groundwater response. The water chemical results support existing hydrogeological conceptual models suggesting a deep infiltration of the upstream infiltrated rainfall. The TMCF of Plaine des Fougères shows a high water storage capacity (>2000% for the Bryophytes) that makes this one a significant input of water to groundwater recharge which still needs to be quantified. This observatory is a unique research site in an insular volcanic tropical environment offering three windows of observation for the study of critical zone processes through upstream‐midstream‐downstream measurements sites. This high‐resolution dataset is valuable to assess the response of volcanic tropical watersheds and aquifers at both event and long‐term scales (i.e., global change). It will also provide insights in the hydrogeological conceptual model of volcanic islands, including the significant role of the TMCFs in the recharge processes as well as the watershed hydrosedimentary responses to extreme climatic events and their respective evolution under changing climatic conditions. All data sets are available at https://doi.org/10.5281/zenodo.7983138. [ABSTRACT FROM AUTHOR]

The application of machine learning (ML) including deep learning models in hydrogeology to model and predict groundwater level in monitoring wells has gained some traction in recent years. Currently, the dominant model class is the so-called single-well model, where one model is trained for each well separately. However, recent developments in neighbouring disciplines including hydrology (rainfall–runoff modelling) have shown that global models, being able to incorporate data of several wells, may have advantages. These models are often called "entity-aware models", as they usually rely on static data to differentiate the entities, i.e. groundwater wells in hydrogeology or catchments in surface hydrology. We test two kinds of static information to characterize the groundwater wells in a global, entity-aware deep learning model set-up: first, environmental features that are continuously available and thus theoretically enable spatial generalization (regionalization), and second, time-series features that are derived from the past time series at the respective well. Moreover, we test random integer features as entity information for comparison. We use a published dataset of 108 groundwater wells in Germany, and evaluate the performance of the models in terms of Nash–Sutcliffe efficiency (NSE) in an in-sample and an out-of-sample setting, representing temporal and spatial generalization. Our results show that entity-aware models work well with a mean performance of NSE >0.8 in an in-sample setting, thus being comparable to, or even outperforming, single-well models. However, they do not generalize well spatially in an out-of-sample setting (mean NSE <0.7 , i.e. lower than a global model without entity information). Strikingly, all model variants, regardless of the type of static features used, basically perform equally well both in- and out-of-sample. The conclusion is that the model in fact does not show entity awareness, but uses static features merely as unique identifiers, raising the research question of how to properly establish entity awareness in deep learning models. Potential future avenues lie in bigger datasets, as the relatively small number of wells in the dataset might not be enough to take full advantage of global models. Also, more research is needed to find meaningful static features for ML in hydrogeology. [ABSTRACT FROM AUTHOR]

A key issue in the legal case before the International Court of Justice between Bolivia and Chile concerned artificial channels in the headwater wetlands of the Silala River in Bolivia, and their impact on the river and groundwater flow rates across the international border into Chile. In pleadings before the Court, Bolivia had claimed up to 40% changes in river flow, whereas Chile had maintained that these were much smaller. This paper reviews construction of a numerical groundwater model to quantify this impact, based on the hydrogeological conceptual model presented earlier in this volume. The groundwater model domain covers the Silala River topographical catchment, plus three adjacent closed (endorheic) topographical catchments to the northeast, which together form the groundwater catchment of the Silala River. The geometry was based on a 3D geological model, constructed based on knowledge gained from several geological mapping investigations. Surface water flows were simulated within a margin of error less than the range of uncertainty associated with the flow measurements. The resulting calibrated groundwater model was used to simulate scenarios corresponding to (a) the removal of channels in the Bolivian wetlands and (b) backfilling of the channels and a small increase in ground elevation (postulated by Bolivia due to long term peat accumulation). The results of these scenarios indicate that the measures would result in a small reduction to the surface water flow over the border to Chile; for Scenario A less than 1% change in surface flows, and for Scenario B less than 3%. This article is categorized under:Human Water > Rights to WaterScience of Water > Hydrological ProcessesHuman Water > Water Governance [ABSTRACT FROM AUTHOR]

This article reviews hydrogeological studies carried out between 2016 and 2018 in the Silala River basin, a catchment shared by Chile and Bolivia. These were conducted in the context of the Case Concerning the Status and Use of the Waters of the Silala River, submitted to the International Court of Justice in 2016, and contributed to multidisciplinary science to demonstrate that this system is an international watercourse. In 2016, the hydrogeological understanding of the Silala River basin was poor. The studies reviewed here filled many knowledge gaps, providing a solid hydrogeological baseline, and establishing new monitoring infrastructure to collect relevant aquifer data. The most important hydrogeological units were identified as the fluvial deposits, alluvial deposits, and the Cabana ignimbrite. The latter is highly heterogeneous, weathered and fractured, and exhibits a high permeability. It is the most important unit in terms of productivity, and is the major regional aquifer providing spring flows to Bolivian wetlands and groundwater flow across the international border. The studies provided a preliminary understanding of the main aquifers in Chile and their properties, which underpinned the development of a robust hydrogeological conceptual model of the system, reviewed elsewhere in this special issue. Subsequent refinements are also summarized. This work confirmed that both surface water and groundwater flows from Bolivia to Chile, and thus confirms the status of the Silala River as an international watercourse and provided the basis for a basin‐scale groundwater numerical model, used to investigate the impact of wetland channelization on surface water/groundwater partitioning. This article is categorized under:Science of Water > Hydrological Processes [ABSTRACT FROM AUTHOR]

This article reviews a hydro‐chemical and isotopic study aiming to provide information about groundwater‐surface water interactions in the Silala River, a transboundary basin shared between Chile and Bolivia. The chemical and isotopic data show: The springs located in the northern section of the lower course of the Silala River and the Cajones springs in Bolivia have similar characteristics and represent a shallow flow system fed by local recharge. In contrast, the springs located in the higher and southern sections of the lower course of the river have similar characteristics than the Orientales springs located in the higher part of river basin indicating these springs are associated with a high‐altitude recharge area. The river in the upper course in Chile has similar chemical and isotopic characteristics to the springs already mentioned, indicating most of the river flow comes from the high part of the basin in Bolivia. The groundwater shows different chemical characteristics, similar depleted isotopic values, and much lower 14C values (including Orientales groundwater) than the upper springs and river, providing the first evidence that both systems are not connected in the Chilean section of the river and the springs system is part of a perched aquifer confirmed by visual field observations. These data support a conceptual model which includes an interaction between a perched aquifer, probably in alluvial deposits on the flanks of the volcanoes, and the river as result of a complex system of fractures present in the near‐surface levels of Silala Ignimbrite. This study provides valuable information for modeling of hydrological and hydrogeological data in the study area. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > Water Quality [ABSTRACT FROM AUTHOR]

From 1999 a dispute between Bolivia and Chile concerning the status and use of the Silala River developed. In 2016 it was taken before the International Court of Justice. Over time, a key disagreement between the parties emerged, concerning artificial channels in the headwater wetlands of the Silala River in Bolivia and their impact on the river and groundwater discharge from Bolivia to Chile. To quantify this, a numerical groundwater model was developed by Chile, requiring a hydrogeological conceptual model of the Silala River Basin, reviewed here. This focussed on understanding the groundwater system and its interactions with the Silala River. The data and information used to gain this understanding included geological mapping, drilling, satellite imagery interpretation, geophysical surveys, hydrogeochemical analyses, groundwater level monitoring, surface flow monitoring, and groundwater pumping tests. These were focussed along the course of the river and wetlands. A three‐dimensional geological model of the Silala Basin was based on these investigations. The groundwater model area covers the topographic catchment, plus three adjacent closed (endorheic) topographical catchments to the northeast, which together form the groundwater catchment of the Silala River. The main deep regional aquifer is found in ignimbrite pyroclastic rocks and an interbedded alluvial deposit, but secondary perched aquifers on the flanks of the Silala River ravine contribute to the complexity. Although uncertainty remains, the hydrogeological conceptual model describes the main observed features of the system in a scientifically sound and coherent manner, with appropriate detail to support a credible numerical model. This article is categorized under:Science of Water > Hydrological ProcessesEngineering Water > Sustainable Engineering of Water [ABSTRACT FROM AUTHOR]

The Silala River basin is located in a remote area in the Andes Mountain range, where hydro‐meteorological and hydrogeological data are scarce. Consequently, the hydrological functioning of this river system was not well understood. Due to a dispute between Chile and Bolivia over the status and use of the waters of the Silala River, Chile requested the International Court of Justice to adjudge the Silala River system to be an international watercourse. To support the case, scientific studies were carried out in both countries to fill hydrological and hydrogeological knowledge gaps. This article reviews the Silala River basin topographic characterization, historical water use, and the dominant hydrological processes, and briefly summarizes an enhanced monitoring programme, reported in more detail elsewhere in this Special Issue. The longitudinal topographic profile and river slope show that Silala fluvial system is an exorheic watershed; waters from the Cajones and Orientals wetlands in Bolivia, the two headwater sources of the Silala fluvial system, naturally flow from Bolivia to Chile, demonstrating that the Silala River system is indeed an international watercourse. New hydro‐meteorological, hydrological and hydrogeological measurement stations were installed in both countries and provided improved process insights and spatiotemporal coverage within the basin. These new observations helped to populate hydraulic, hydrological, and hydrogeological models, aimed to improve understanding of the functioning of the system, including the effects of historical disturbance due to channelization of the Bolivian wetlands. This article is categorized under:Science of Water > Hydrological ProcessesHuman Water > Rights to Water [ABSTRACT FROM AUTHOR]

The first hydrogeological mapping of Ischia Island at the 1:10,000 scale is presented and discussed. The 'Map of the geohydrologic units of Ischia Island' and the accompanying hydrostratigraphic sequence at a basin scale are based on the most recent geological maps and data from the CAR.G Project, and on new volcanological and hydrogeological surveys and studies. Data sources include the database stored by the INGV, Sezione di Napoli, Osservatorio Vesuviano and field investigations, including a survey of the springs and thermo-mineral springs which has been neglected up to now. In total 130 volcanostratigraphic units and 18 geohydrologic units were recognized; the distribution of fumaroles sites was enhanced, and 60 springs/thermal springs were identified/rediscovered. The proposed hydrogeological map provides an overview of the volcano-tectonic evolution of Ischia Island and upgrades the hydrogeological model, becoming a catalyst for the effort to acquire better data and to manage natural both resources and risks. [ABSTRACT FROM AUTHOR]