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The study aims to simulate the stage-wise, year-wise mine seepage predictions and the corresponding impact on the groundwater regime (drawdown and heads) in accordance with the approved mine plan for certain coal mines in Central India. To that end, the optimized and efficient watershed area of 997.61 km2 has been delineated by using ArcGIS software and was synthesized in a finite difference numerical model with the concept of 21 layers (multi-layered aquifer system) encompassing six working mines. Initially, the groundwater-flow model was constructed for the simulation of groundwater conditions during May 2022 which shows a good model fit of the observed and simulated water levels, with the majority of the data lying close to the 1:1 line as indicated by an RMS value of less than 5 m. Then, the zone budget of different forecast scenarios reveals that the inflows into the various mine excavation area are: 13,733 (Gevra OC), 12,732 (Kusmunda OC), 8569 (Dipka OC), 8308 (Surakchar UG), 8018 (Manikpur OC), and 7511 (Balgi UG) m3/day. The zone of influence defined by zero drawdown extends up to 1.22 km to the NW of Kusmunda OCP, 2 km to the east of Dipka OCP, and 1.25 km to the SW from the quarry surface boundary of Gevra OCP and is negligible, i.e. up to < 0.5 km, in the western side with the predicted drawdown of 10 m within the project lease area. However, the progressive recovery of water levels will start in accordance with the closure of mines and the cone of depressions due to mine dewatering tend to vanish by 2050. The simulations suggest that mining activities have impacted neither the flow system of the Hasdeo River (effluent stream) nor the aquifers that are interacting with the river, as the river has not contributed any groundwater flows in to these mining areas. [ABSTRACT FROM AUTHOR]

Offshore freshened groundwater (OFG) represents a significant, yet underexplored, component of the global freshwater system as it is found across various continental margins. In this study, a 3-D geological and groundwater model was developed for the Canterbury Plains and Bight (New Zealand) to assess the role of present-day onshore recharge in the emplacement of OFG. Topographic and bathymetric, seismic reflection and well data have been integrated to construct an onshore-offshore geological model. The facies property distribution and associated hydrodynamic parameters were determined using stochastic modelling techniques. The geological reconstruction was imported within a variable density groundwater model. Simulations, under transient regime, were run until equilibrium conditions between the involved aquifer portion and the adjacent ocean have been reached. Our results show that the geological model accurately captures the stratigraphic and sedimentary features of the area, and that onshore recharge at present contributes to OFG emplacement up to 15 km from the coast, which is equivalent to 25% of its maximum extent. Onshore recharge during sea-level lowstands is therefore the dominant OFG emplacement mechanism in the Canterbury Bight. [ABSTRACT FROM AUTHOR]

The industrial evaporation ponds of the Dead Sea Works are located in the Dead Sea rift valley, Israel. To prevent brine leakage, the ponds were sealed by 40‐m deep impermeable dikes, except in the Ye'elim alluvial fan, at the northwest corner, where the leakage continues. The average leakage at present is approximately 100 million cubic meters per year, a significant portion of which discharges via a spring located approximately 0.5 km north of the ponds' embankment; the rest flows into the Dead Sea underground. We hypothesized two main reasons for the increase in leakage over time: the dropping level of the Dead Sea, which increases the hydraulic gradient, and the diameter expansion of the subsurface karst network of fast‐flowing conduits. The brine in the evaporation ponds is warmer than the ground in the summer, colder in the winter. Therefore, the brine leaking within the karst conduits warms and cools, respectively, the surrounding porous medium, as detected by field monitoring. One of the conduits was also detected through a geoelectrical survey. In addition, we identified an increased brine‐leakage rate in the winter. We propose that this results from temporal changes in the diameter of the conduits due to the infiltration of low‐salinity water entering the network. The diluted water dissolves the salt and causes the conduits to expand. Using a numerical model that solves the coupled groundwater flow and heat transport equations, we were able to reproduce all of these field observations and validate the suggested explanations. [ABSTRACT FROM AUTHOR]

The Red river delta plain (RRDP), the second largest delta in Vietnam, is situated in the northern region of the country and spans an area of 21,260 km² and supports a population of over 22.9 million inhabitants. Groundwater extraction primarily occurs from quaternary sedimentary aquifers, with a total discharge of approximately 1.5 million m3/day. However, certain localities, such as Hanoi and Nam Dinh, have exhibited signs of over-exploitation, leading to associated issues such as depletion, land subsidence, saltwater intrusion, and water pollution. Groundwater recharge in the study area primarily originates from various sources including rainfall, irrigation, wastewater, and the river system. The objective of this study is to evaluate the contribution of groundwater recharge to groundwater exploitation reserves within the Red river delta. To achieve this, a three-dimensional (3D) model employing the MODFLOW code was developed and refined through the comparison of modelled and actual groundwater levels within the surveillance network. The refined model’s budget analysis indicated that the recharge of quaternary aquifers by means of rainfall, irrigation, and effluent occurs year-round, with the peak recharge happening during the monsoon season (approximately 68% of rainfall) and the nadir during the arid season (approximately 10% of rainfall). Throughout the monsoon period, the river system predominantly replenishes the quaternary aquifers, contributing approximately 9.51-17.36% to the overall water balance of the aquifers. The influx from fractured aquifers at the fringe of the plain to the quaternary aquifers remains consistently minimal year-round.

The Ecosystem Services Approach (ESA) is an effective tool for evaluating humans-nature relationships, but publications on the use of ES to assess groundwater ecosystem services (GWES) are scarce. This work presents a practical example of how to apply the ESA to support groundwater dependent ecosystems (GDE) and aquifer management, using groundwater numerical modelling as assessment tool. It was performed in the NAIAD Horizon 2020 project to assess current status and potential future evolution of two GWES of the Medina del Campo Groundwater Body (Spain): the Provisioning Service Groundwater Used for Non-Drinking Purposes (APS_GUNDP), focusing on irrigation water supply, and the Regulating and Maintaining Service Regulation of Baseline Flows and Extreme Events (ARMS_RBFEE), focusing on GDE.The numerical modeling was done with MODFLOW 2005 and ModelMuse. The present-day status of APS-GUNDP was evaluated analyzing the piezometric trends from 1950 to 2018, while the ARMS_RBFEE was assessed comparing GDE areas in 2018 to those in 1956. The future evolution of both GWES until 2350 was predicted as piezometric level changes and flooded land surface under different precipitation and groundwater management scenarios.Intensive groundwater exploitation in the past led to drying GDE and boost different groundwater management measures. But natural conditions are not restored any scenario by year 2350, due to ongoing adjustment of the aquifer water balance. This work demonstrates how to use ESA to assess management actions to recover GWES.

The national-scale British Groundwater Model (BGWM) is implemented to simulate groundwater dynamics and budgets in Great Britain. Notwithstanding the challenges of integrating a very large amount of data, finding a trade-off between computational efficiency and realism, performing automatic calibration, and addressing multiple sources of structural and parameter uncertainty, a quantitative–qualitive evaluation approach showed that the BGWM provides a reasonably accurate digital representation of groundwater systems and processes at a national scale. In this work, the model was applied to understand the variability of budget components across multiple spatial and temporal scales. Comparisons showed regional differences linked to lithological and climatic factors, which in turn can be associated with more or less groundwater resilience to extreme climatic events. There is confidence that the current and future versions of the BGWM can become valuable tools for effective water resources management and adaptation strategies under future climatic and population changes. [ABSTRACT FROM AUTHOR]

Small island countries like Vanuatu are facing the brunt of climate change, sea level rise (SLR), tropical cyclones, and limited or declining access to freshwater. The Tagabe coastal aquifer in Port Vila (the capital of Vanuatu) shows the presence of salinity, indicating saltwater intrusion (SWI). This study aims to develop and evaluate effective SWI management strategies for Tagabe coastal aquifer. To manage SWI, the numerical simulation model for the study area was developed using the SEAWAT code. The flow model was developed using MODFLOW and the transport model was developed using MT3DMS. Whereby SEAWAT solved flow and transport equations simultaneously. The model was calibrated, and different scenarios were evaluated for the management of SWI. The SLR was also considered in the model simulations. The results indicated that increased population, pumping rates, and SLR affect the SWI rates. To manage the SWI, we introduced hydraulic barriers like barrier wells and injection wells which effectively managed SWI in Tagabe coastal aquifer. The results from this study are significantly important whereby, the water managers, site owners, and governing bodies can use the management strategies presented in this study to create policies and regulations for managing SWI rates in Port Vila. Additionally, the water industry, private businesses, and investors who wish to extract groundwater from the Tagabe can use this study as a reference for daily or yearly freshwater production rates without the risk of SWI. [ABSTRACT FROM AUTHOR]

This paper presents an approach to estimate the effects of a managed recharge experiment in a multilayer aquifer characterized by the presence of perched water tables in the Medina del Campo groundwater body, Douro basin, central Spain. A numerical model was developed to evaluate the effect of artificial recharge on the shallow sector of a regional‐scale aquifer and on formerly active wetlands. The model was developed in the Visual MODFLOW Pro v.2011.1 environment in order to represent and analyse the regional impact of this artificial recharge event. Results suggest that the assumption of a single perched system may prove useful in regional contexts where data is limited. From a study site perspective, managed recharge is observed to increase shallow storage along the riverbanks, which is considered valuable for environmental purposes. However, downstream wetlands are unlikely to experience a significant recovery. Furthermore, only a small percentage of artificial recharge is expected to reach the deep regional aquifer. This method can be exported to settings characterized by the presence of perched aquifers and associated groundwater dependent ecosystems. [ABSTRACT FROM AUTHOR]

Results from numerical simulations play a vital role in the decision process of everyday groundwater management. However, these simulations can be time-consuming for large-scale investigations, and it can be necessary to apply approximate methods instead.This study investigates the abilities of a neural network to replicate simulated drawdown from groundwater abstraction in a numerical groundwater model of the Egebjerg catchment, Denmark. We follow a generalised methodology that uses the information within the deterministic numerical model to create a training set for the neural network to learn from and extend the method to work in a 3D Danish groundwater model case. We compare the abilities of the trained neural network with the results of conventional computations in terms of speed and accuracy and argue that this approach has the potential to improve decision support for decision-makers within groundwater management.

West Africa is subject to climatic variability with a long period of drought during the 1970s–1990s whose impact on groundwater remains poorly studied. This work focuses on the Kou basin in Burkina Faso, which holds a large groundwater resource resulting in exceptional springs. This resource shows signs of depletion that raise a critical question: What is the share of climate and that of withdrawals in the depletion of the resource? To answer this question, we used a hydrogeological model calibrated in steady state and in transient regime (monthly time step 1995–2014; annual time step 1961–2014). The results showed that pumping has a significant impact on the resource, especially in the vicinity of the pumping areas, and caused approximately 30% of the observed decrease in spring discharge. Drought periods and consecutive years without recharge also led to a decrease in groundwater levels. Thus, precipitation deficits and variability, combined with increasing pumping, have endangered the resource.

In Burkina Faso, human activities around water points in rural areas affect groundwater resources, which become unfit for consumption. Nearly 33.5% of boreholes are subject to point source pollution. The assessment of the evolution of such pollution should be monitored to assess groundwater quality. In addition, withdrawals for irrigation alone are estimated at 85%, i.e. 46% of the water demand, heightening the deterioration in quality while creating depression zones further leading to an increase in recharge. It is therefore critical to understand the evolution and fate of the transfer of pollutants in such environments. In this study, we aimed to model the transfer of pollutant and predict the future state of pollution using the MT3D-USGS Groundwater Solute Transport Simulator code through the Groundwater Modelling Software (GMS) over the period 2012–2062 (50 years). A mathematical model is further developed through inferential statistics and used as a surrogate model for comparison. The results showed that deterioration in water quality was more attributable to withdrawals, especially for Cyanide (Cn) and Arsenic (As). A rather slow degradation is reported for Lead (Pb), which extends over 22 km, and Fluoride (F), which extends from 4 to 10 km due to localized recharge. A faster degradation for Cn over a distance of 2–16 km and as from 3 to 11 km is also observed because of the geological setting of the subsoil. These results might assist decision-makers for the quantitative and qualitative management of groundwater resources, and the management of the basement aquifer in the area through the establishment of protection zones.

AbstractGroundwater is the primary source of water supply in Ethiopia. The study area was challenged due to increasing water demand, uneven water resource distribution, and noticeable changes in groundwater levels. The study focused on the examining of existing abstraction and future water demand scenarios on groundwater balance in the Weyib watershed using the WetSpass-M and MODFLOW-2005 models. The input datasets, such as aquifer properties, observed groundwater heads, hydrogeology, groundwater recharge, the Digital Elevation Model (DEM), and hydrological data were used. Datasets were prepared to better represent subsurface hydrology and its future demand effects evaluated using calibrated steady-state numerical groundwater modeling. The WetSpass-M and MODFLOW-2005 models depicted good performances during the simulations of groundwater recharge and groundwater budget under existing abstractions and estimated demand scenarios, respectively. The mean annual groundwater recharge estimated was 177.66 mm/year. The existing groundwater abstraction was 34,686.39, estimated short-term and long-term water demand scenarios were 72,113.61 and 93,795.57 m3/day, respectively. The upstream area has the highest groundwater head and recharge, while decreasing as it approaches the Weyib watershed outlet. During the outflow groundwater budget, the groundwater abstractions increased as expenses of river leakage and head dept. bounds increased. Moreover, the increasing groundwater withdrawal would reduce groundwater heads, and the estimated future water demand scenarios would substantially impact the groundwater budget, which would also have an impact on the watershed hydrology and ecosystem.

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.)

Study Region: The study region is the northwest region of Bangladesh Study Focus: The study focuses on developing an improved understanding of groundwater balance and long-term groundwater storage trends in the districts of northwest Bangladesh. We used MODFLOW-2005 to construct two groundwater models of northwest Bangladesh, which differed in the conceptual representation of groundwater recharge to investigate groundwater balance and storage trends. One approach was based on estimating gross recharge and the other on estimating net recharge by ignoring direct use of groundwater by vegetation. The two models were calibrated by fitting to observed groundwater levels, with a probabilistic method using PEST-IES, resulting in 500 realisations of comparable goodness of fit for each model. New Hydrological Insights for the Region: The two modelling approaches provided plausible range of groundwater storage decline in the northwest region with long-term average between − 1.1 mm/y and − 5.3 mm/y. In the southern parts of the region groundwater storage is declining with highest rates of − 12.5 mm/y, − 10.6 mm/y and − 8.9 mm/y respectively in Nawabganj, Naogaon and Rajshahi respectively. Groundwater use appears to be unsustainable in this area. The northern part receives greater rainfall, and groundwater storage is declining less. Furthermore, the recharge rates are less than the potential rates. In this part of the region, some further development of groundwater use may be sustainable.

Groundwater is the primary source of water supply in Ethiopia. The study area was challenged due to increasing water demand, uneven water resource distribution, and noticeable changes in groundwater levels. The study focused on the examining of existing abstraction and future water demand scenarios on groundwater balance in the Weyib watershed using the WetSpass-M and MODFLOW-2005 models. The input datasets, such as aquifer properties, observed groundwater heads, hydrogeology, groundwater recharge, the Digital Elevation Model (DEM), and hydrological data were used. Datasets were prepared to better represent subsurface hydrology and its future demand effects evaluated using calibrated steady-state numerical groundwater modeling. The WetSpass-M and MODFLOW-2005 models depicted good performances during the simulations of groundwater recharge and groundwater budget under existing abstractions and estimated demand scenarios, respectively. The mean annual groundwater recharge estimated was 177.66 mm/year. The existing groundwater abstraction was 34,686.39, estimated short-term and long-term water demand scenarios were 72,113.61 and 93,795.57 m3/day, respectively. The upstream area has the highest groundwater head and recharge, while decreasing as it approaches the Weyib watershed outlet. During the outflow groundwater budget, the groundwater abstractions increased as expenses of river leakage and head dept. bounds increased. Moreover, the increasing groundwater withdrawal would reduce groundwater heads, and the estimated future water demand scenarios would substantially impact the groundwater budget, which would also have an impact on the watershed hydrology and ecosystem. [ABSTRACT FROM AUTHOR]

A laboratory installation designed for simulating groundwater flow in homogeneous and isotropic unconfined aquifers between two rivers or parallel channels is described in this paper. The laboratory installation allows to visualize and to study the behaviour of the phreatic surface, to determine the saturated hydraulic conductivity, and to compare experimental data with analytical and numerical solutions of partial differential equation describing the groundwater flow in steady-state and transient conditions. The installation is simple to use and has been proven to be robust and useful in improving scientific knowledge on modelling principles of groundwater flow in saturated porous media. [ABSTRACT FROM AUTHOR]

Worldwide, coastal aquifers have been heavily exploited by socio economic activities for several decades, and climate change and sea level rise have also been threatening coastal aquifers. The authorities and policymakers have been advised to find the solutions in order to achieve sustainable water resources management. The southern part of Po delta, Italy is a low-lying coastal area also experiencing tectonic activity. Along with low-lying topography, unstable shore line and sea level, the groundwater is heavily exploited by this deltaic multilayered system of aquifers. Hence, a multilayer three-dimensional model of this aquifer system has allowed for the investigation of the response of aquifer to natural and anthropogenic exploitation. The present work regards the conceptualization of the multilayer aquifer system using lithological cross-sections, surface water features, and appropriate boundary conditions and the steady-state flow modelling. The spatially distributed elevations of the groundwater table and piezometric head from the different aquifers have been calibrated. The values of model error statistics at a satisfactory range, such as R-squared, mean error, root-mean-squared error and model efficiency, confirm that the developed model is reliable, and calibration is obtained with good match between observed and simulated data. The developed model can be used as a decision-making tool for the authorities and policymakers in order to plan for sustainable water management. [ABSTRACT FROM AUTHOR]

Groundwater (GW) flooding mechanisms differ from river flooding, both spatially and temporally, and preventative methods against groundwater flooding must take this into account. Although groundwater flooding caused by a rise of river water seldom occurs, it can occasionally become severe and last for a long time if the river is significantly flooded. In the southwest portion of the research domain, Friedrichshafen, Germany, with a few urban communities, the level of the groundwater table was discovered to be roughly 1 m below the surface. In the study region, it is typical for the bottom level of the foundation of a single-story building to extend up to a depth of about 1.5 m. Therefore, flood mitigation methods are taken into account for the southwest portion of the study region. In this study, FEFLOW is used to explore the preventative methods for groundwater flooding caused by river water increase in urban settings, the spread of contamination, and the strategizing of effective mitigation solutions for flooding. The installation of a pumping well, drainage, and a barrier in the affected area are three different flood control strategies that are taken into consideration for the study area. Pumping well installation, reducing up to 1.5 m of hydraulic head, was found to be the most effective flood control measure locally in a small region. By contrast, removing groundwater by building drainage and barriers was shown to be ineffective for lowering the groundwater table over an extended region, and was significantly more expensive than the installation of wells. Additionally, when river flooding is taken into account, compared to the default scenario where no intake of water from the river is included along the western border of the study area, it was discovered that the spread of pollution (nitrate concentration) is significantly greater.

Groundwater (GW) flooding mechanisms differ from river flooding, both spatially and temporally, and preventative methods against groundwater flooding must take this into account. Although groundwater flooding caused by a rise of river water seldom occurs, it can occasionally become severe and last for a long time if the river is significantly flooded. In the southwest portion of the research domain, Friedrichshafen, Germany, with a few urban communities, the level of the groundwater table was discovered to be roughly 1 m below the surface. In the study region, it is typical for the bottom level of the foundation of a single-story building to extend up to a depth of about 1.5 m. Therefore, flood mitigation methods are taken into account for the southwest portion of the study region. In this study, FEFLOW is used to explore the preventative methods for groundwater flooding caused by river water increase in urban settings, the spread of contamination, and the strategizing of effective mitigation solutions for flooding. The installation of a pumping well, drainage, and a barrier in the affected area are three different flood control strategies that are taken into consideration for the study area. Pumping well installation, reducing up to 1.5 m of hydraulic head, was found to be the most effective flood control measure locally in a small region. By contrast, removing groundwater by building drainage and barriers was shown to be ineffective for lowering the groundwater table over an extended region, and was significantly more expensive than the installation of wells. Additionally, when river flooding is taken into account, compared to the default scenario where no intake of water from the river is included along the western border of the study area, it was discovered that the spread of pollution (nitrate concentration) is significantly greater. [ABSTRACT FROM AUTHOR]

Polluted groundwater discharge at a chlorinated solvent contaminated site in Hagfors, Sweden, is affecting a nearby stream flowing through a sparsely populated area. Because of difficulties related to source zone remediation, decision makers recently changed the short-term site management objective to mitigating discharge of polluted groundwater to the stream. To help formulating targeted remediation strategies pertaining to the new objective, we developed a groundwater numerical decision-support model. To facilitate reproducibility, the modelling workflow was scripted. The model was designed to quantify and reduce the uncertainty of surface water-groundwater (SW-GW) exchange fluxes for the studied period (2016–2020) through the use of history-matching. In addition to classical observations, thermal anomalies detected in fiber optic distributed temperature sensing (FO-DTS) measurements were used to inform the model of groundwater discharge. After assessing SW-GW exchange fluxes, we used measurements of surface water chemistry to provide a probabilistic estimation of mass influx and spatio-temporal distributions of contaminated groundwater discharge. Results show 1) SW-GW exchange fluxes are likely to be significantly larger than previously estimated, and 2) prior estimations of mass influx are located near the center of the posterior probability distribution. Based on this, we recommend decision makers to focus remediation action on specific segments of the stream.

Barbados is heavily reliant on groundwater resources for its potable water supply, with over 80% of the island's water sourced from aquifers. The ability to meet demand will become even more challenging due to the continuing climate crisis. The consequences of climate change within the Caribbean region include sea level rise, as well as hydrometeorological effects such as increased rainfall intensity, and declines in average annual rainfall. Scientifically sound approaches are becoming increasingly important to understand projected changes in supply and demand while concurrently minimizing deleterious impacts on the island's aquifers. Therefore, the objective of this paper is to develop a physics-based groundwater model and surrogate models using machine learning (ML), which provide decision support to assist with groundwater resources management in Barbados. Results from the study show that a single continuum conceptualization is adequate for representing the island's hydrogeology as demonstrated by a root mean squared error and mean absolute error of 2.7 m and 2.08 m between the model and observed steady-state hydraulic head. In addition, we show that data-driven surrogates using deep neural networks, elastic networks, and generative adversarial networks are capable of approximating the physics-based model with a high degree of accuracy as shown by R-squared values of 0.96, 0.95, and 0.95, respectively. The framework and tools developed are a critical step towards a digital twin that provides stakeholders with a quantitative tool for optimal management of groundwater under a changing climate in Barbados. These outputs will provide sound evidence-based solutions to aid long-term economic and social development on the island. [ABSTRACT FROM AUTHOR]

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• Physics-model-derived causal priors can be embedded into deep neural networks. • Metformin sandy column transport experiment results were used as seed data. • Impact from underexplored parameters (F, α and L) was estimated for the first time. • Metformin has long-range transport potential in groundwater. • Presented an AI-for-Science paradigm using both domain priors and data-driven methods. This study introduces a novel approach to transport modelling by integrating experimentally derived causal priors into neural networks. We illustrate this paradigm using a case study of metformin, a ubiquitous pharmaceutical emerging pollutant, and its transport behaviour in sandy media. Specifically, data from metformin's sandy column transport experiment was used to estimate unobservable parameters through a physics-based model Hydrus-1D, followed by a data augmentation to produce a more comprehensive dataset. A causal graph incorporating key variables was constructed, aiding in identifying impactful variables and estimating their causal dynamics or "causal prior." The causal priors extracted from the augmented dataset included underexplored system parameters such as the type-1 sorption fraction F , first-order reaction rate coefficient α , and transport system scale. Their moderate impact on the transport process has been quantitatively evaluated (normalized causal effect 0.0423, -0.1447 and -0.0351, respectively) with adequate confounders considered for the first time. The prior was later embedded into multilayer neural networks via two methods: causal weight initialization and causal prior regularization. Based on the results from AutoML hyperparameter tuning experiments, using two embedding methods simultaneously emerged as a more advantageous practice since our proposed causal weight initialization technique can enhance model stability, particularly when used in conjunction with causal prior regularization. amongst those experiments utilizing both techniques, the R-squared values peaked at 0.881. This study demonstrates a balanced approach between expert knowledge and data-driven methods, providing enhanced interpretability in black-box models such as neural networks for environmental modelling. [Display omitted] [ABSTRACT FROM AUTHOR]

Introduction: Pressure on groundwater resources is increasing rapidly by population growth and climate change effects. Thus, it is urgent to quantify their availability and determine their dynamics at a global scale to assess the impacts of climate change or anthropogenically induced pressure, and to support water management strategies. In this context, regional hydrogeological numerical models become essential to simulate the behavior of groundwater resources. However, the construction of global hydrogeological models faces a lot of challenges that affect their accuracy.Methods: In this work, using the German portion of the Upper Danube Basin (∼43,000 km2) we outline common challenges encountered in parameterizing a regional-scale groundwater model, and provide an innovative approach to efficiently tackle such challenges. The hydrogeological model of the Danube consists of the groundwater finite element code OpenGeoSys forced by the groundwater recharge of the surface hydrological model mHM.Results: The main novelties of the suggested approach are 1) the use of spectral analyses of the river baseflow and a steady state calibration taking as reference the topography to constraint the hydraulic parameters and facilitate the calibration process, and 2) the calibration of the hydraulic parameters for a transient state model by considering parameters derived from the piezometric head evolution.Discussion/conclusion: The results show that the proposed methodology is useful to build a reliable large-scale groundwater model. Finally, the suggested approach is compared with the standard one used by other authors for the construction of global models. The comparison shows that the proposed approach allows for obtaining more reliable results, especially in mountainous areas.

Quantification of long-term hydrologic change in groundwater often requires the comparison of states pre- and post-change. The assessment of these changes in ungauged catchments using numerical models and other quantitative methods is particularly difficult from a conceptual point of view and due to parameter non-uniqueness and associated uncertainty of quantitative frameworks. In these contexts, the use of data assimilation, sensitivity analysis and uncertainty quantification techniques are critical to maximize the use of available data both in terms of conceptualization and quantification. This paper summarizes findings of a study undertaken in the Lake Muir-Unicup Natural Diversity Recovery Catchment (MUNDRC), a small-scale endorheic basin located in southwestern Australia that has been subject to a systematic decline in rainfall rates since 1970s. A combination of data assimilation techniques was applied to conceptual and numerical frameworks in order to understand and quantify impacts of rainfall decline on the catchment using a variety of metrics involving groundwater and lake levels, as well as fluxes between these compartments and mass balance components. Conceptualization was facilitated with the use of a novel data-driven method relating rainfall and groundwater responses running backwards in time, allowing the establishment of the likely baseline conditions prior to rainfall decline, estimation of net recharge rates and providing initial heads for the forward numerical modelling. Numerical model parameter and predictive uncertainties associated with data gaps were then minimized and quantified utilizing an Iterative Ensemble Smoother algorithm, while further refinement of conceptual model was made possible following results from sensitivity analysis, where major parameter controls on groundwater levels and other predictions of interest were quantified. The combination of methods can be considered as a template for other long-term catchment modelling studies that seek to constrain uncertainty in situations with sparse data availability.

The problem of identifying an unknown pollution source in polluted aquifers, based on known contaminant concentrations measurement in the studied areas, is part of the broader group of issues, called inverse problems. This paper investigates the feasibility of using Artificial Neural Networks (ANNs) for solving the inverse problem of locating in time and space the source of a contamination event in a homogeneous and isotropic two dimensional domain. ANNs are trained in order to implement an input-output relationship which associates the position. Once the output of the system is known, the input is reconstructed by inverting the trained ANNs. The approach is applied for studying a theoretical test case where the inverse problem is solved on the basis of measurements of contaminant concentrations in monitoring wells located in the studied area. Groundwater pollution sources are characterized by varying spatial location and duration of activity. To identify these unknown pollution sources, concentration measurements data of monitoring wells are used. If concentration observations are missing over a length of time after an unknown source has become active, it is more difficult to correctly identify the unknown pollution source. In this work, a missing data scenario has been taken into consideration. In particular, a case where only one measurement has been made after the pollutant source interrupted its activity has been considered.

The delineation of protection zones for groundwater intakes is a difficult task resulting from the significant variability of regional and local environmental conditions. Different methods are used, both simple (analytical or graphic), giving estimated results, and the most reliable, but also the most time-consuming ones, based on numerical groundwater flow models. An alternative method for the delineation of protection zones is the analytical elements method (AEM), which gives solutions like those obtained using FDM/FEM modelling methods with a relatively low degree of complexity. The estimated ranges of protection zones obtained with the use of four methods are presented for the selected test area (groundwater intake around Olesno). Results obtained with the use of the FDM model were taken as reference and CFR and SimpleWHPA were used as simplified methods. Comparative studies indicate that the results obtained by the CFR method differ significantly from the results of other methods, and their reliability is low. The results of the SimpleWHPA method are satisfactory, given the relative simplicity of the method. On the other hand, the results obtained with the AEM are close to the results obtained with the FDM treated as a reference. Considering that AEM is less time-consuming than FDM (which requires the most effort for proper model preparation), the use of AEM in the practice of protection zone delineation seems to be an interesting alternative. [ABSTRACT FROM AUTHOR]

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This paper concerns a stepwise modelling procedure for groundwater flow simulation in a folded and faulted, multilayer carbonate aquifer, which constitutes a source of good quality water for human consumption in the Apennine Range in Central Italy. A perennial river acts as the main natural drain for groundwater while sustaining valuable water-related ecosystems. The spatial distribution of recharge was estimated using the Thornthwaite–Mather method on 60 years of climate data. The system was conceptualized as three main aquifers separated by two locally discontinuous aquitards. Three numerical models were implemented by gradually adding complexity to the model grid: single layer (2D), three layers (quasi-3D) and five layers (fully 3D), using an equivalent porous medium approach, in order to find the best solution with a parsimonious model setting. To overcome dry-cell problems in the fully 3D model, the Newton–Raphson formulation for MODFLOW-2005 was invoked. The calibration results show that a fully 3D model was required to match the observed distribution of aquifer outflow to the river baseflow. The numerical model demonstrated the major impact of folded and faulted geological structures on controlling the flow dynamics in terms of flow direction, water heads and the spatial distribution of the outflows to the river and springs. [ABSTRACT FROM AUTHOR]

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Groundwater depletion poses a major threat to global groundwater resources with increasing trends due to natural and anthropogenic activities. This study presents a surface-groundwater framework for water resources modelling of ill-posed problems in hydrogeologically data-scarce areas. The proposed framework is based on the application of a conceptual water balance model and composed of surface hydrological (UTHBAL) and groundwater flow simulation with the integration of a Newton formulation of the MODFLOW-2005 code (MODFLOW-NWT) and PEST suite modules. The groundwater simulation includes a preprocessor tool for automated calibration and a post-processor tool for automated validation. The methodology was applied to a rural region of Central Greece, Lake Karla Basin, which is degraded due to groundwater resources overexploitation to cover irrigation water demands. The aquifer is modelled focusing on a precise simulation–validation procedure of the conceptual model. The groundwater model was calibrated with the calibration preprocessor tool for spatially distributed hydraulic conductivity with the pilot points method. The calibration process achieved satisfactory results as validated by the post-process analysis of observed and simulated water levels. The findings for the groundwater budget indicate that the groundwater system is still under intense pressure even though farming activity in recent years has turned to less water-intensive crops. HIGHLIGHT My research deals with the pilot points method on groundwater modelling in an area with scarce hydrogeologic data.;

Worldwide, coastal aquifers have been heavily exploited by socio economic activities for several decades, and climate change and sea level rise have also been threatening coastal aquifers. The authorities and policymakers have been advised to find the solutions in order to achieve sustainable water resources management. The southern part of Po delta, Italy is a low-lying coastal area also experiencing tectonic activity. Along with low-lying topography, unstable shore line and sea level, the groundwater is heavily exploited by this deltaic multilayered system of aquifers. Hence, a multilayer three-dimensional model of this aquifer system has allowed for the investigation of the response of aquifer to natural and anthropogenic exploitation. The present work regards the conceptualization of the multilayer aquifer system using lithological cross-sections, surface water features, and appropriate boundary conditions and the steady-state flow modelling. The spatially distributed elevations of the groundwater table and piezometric head from the different aquifers have been calibrated. The values of model error statistics at a satisfactory range, such as R-squared, mean error, root-mean-squared error and model efficiency, confirm that the developed model is reliable, and calibration is obtained with good match between observed and simulated data. The developed model can be used as a decision-making tool for the authorities and policymakers in order to plan for sustainable water management.

The present study employs a mathematical method, i.e. Particle Filter (PF), to accurately estimate the parameters of three standard aquifers. The method is linked to a new developed numerical method, i.e. meshless local Petrov-Galerkin based on the moving kriging method (PF-MLPG-MK), to determine the aquifer parameters such as hydraulic conductivity coefficient, transmissivity coefficient, and storage coefficient or specific yield appropriately. For this purpose, a set of particles scattered in the state space. Each particle has two features: location and weight. Particles with greater weight values have the closer location to the estimation. Weight values which are assigned to each particle is computed based on the maximum likelihood function. This function is calculated in MLPG-MK simulation model. Overall, by linking particle filter model to the accurate simulation model, an efficient estimation method for aquifer parameters is obtained. This model applied to three standard aquifers. In the first standard aquifer, the estimated parameters of hydraulic conductivity and specific yield were 30.21 and 0.143, respectively. However, the exact values are 30 and 0.15. Also, in the second standard aquifer, the predicted transmissivity and storage coefficients were 99.7038 and 0.001057 whereas their true values are 100 and 0.001. In the third aquifer, the exact value of six parameters were achieved. The sensitivity analysis of the number of particles was carried out. Results revealed that with increasing the particles more accuracy will be achieved. 60, 80 and 100 particles were considered in the model. Results for 100 particles showed more accuracy.

The purpose of this study was to improve the optimization model for predicting more parameters in more difficult conditions (more grid cell numbers and high time interval numbers) than other studies in groundwater flow modelling. Also, the model needs fewer observation numbers for estimating parameters than other studies. In the present study, an optimization model based on model calibration was developed to estimate simultaneously four groundwater flow parameters – hydraulic conductivity, transmissivity, storage coefficient and leakance. The modified clonal selection algorithm, a class of artificial immune systems, was used as a heuristic optimization method. In order to simulate the groundwater flow, MODFLOW was used in conjunction with the model in MATLAB. The input files for MODFLOW were obtained by GMS groundwater simulator. The model was applied to two different hypothetical groundwater systems (two- and three-dimensional) under transient conditions to evaluate its performance. The results showed that the model was feasible for groundwater flow modelling and it could determine the groundwater flow parameters successfully with less observations and more grid cell numbers than the other studies. HIGHLIGHTS The optimization model was improved for determining groundwater model parameters.; The model can estimate more parameters in more difficult conditions (more grid cell numbers and high time interval numbers) than other studies.; The model needs to less observation numbers for estimating parameters than other studies.;

Although traditional physical models have been used to analyse groundwater systems, the emergence of novel machine learning models can improve the accuracy of the predictions. Deep learning has been prominent in environmental and climate change problems. In this paper, we present a framework for utilising deep learning models to predict groundwater levels based on nearby streamflow and rainfall data. We address the missing data problem using a Bayesian linear regression model within the deep learning framework. Our deep learning framework utilises models such as long-short term memory (LSTM) networks and convolutional neural networks (CNN) for multi-step ahead time series prediction. We examine the fluctuations in groundwater levels at various boreholes located near Middle Creek in New South Wales, Australia. We use the National Collaborative Research Infrastructure Strategy (NCRIS) groundwater database and utilise Bayesian linear regression to impute missing data. We investigate the accuracy of the selected models for individual and regional basins and univariate and multivariate strategies. Our results show that the LSTM-based regional model with multivariate strategy using rainfall data provided the best accuracy. • We predict groundwater levels based on stream flow and rainfall data. • Our framework uses Bayesian data imputation and deep learning for multi-step prediction. • We examine the groundwater fluctuations at various boreholes located in Australia. • Results show a fine-tuned regional model with rainfall data yielded the best accuracy. • We find that LSTM models outperformed CNNs using the multivariate approach. [ABSTRACT FROM AUTHOR]

Groundwater resources have been extensively exploited in many areas around the globe for providing good quality water for drinking and other purposes. Groundwater flow models have been widely used as management, evaluation and prediction tools on many occasions, however, in the case of karstic aquifers, the use of modelling tools is often a task with increased complexity. In the light of this constrain, a new methodology for implementing field data into mathematical models developed for simulating flow in karstic aquifers is presented. The aim is to combine an existing groundwater flow model, field data and the MODFLOW CFP code to develop a model that adequately simulates the hydrological processes in the karstic aquifer. Results show that MODFLOW CFP can be used to model areas where karstic aquifers are developed, providing decisive information about hydrological processes taking place in these aquifers. • A new methodology is developed for combining field data and modelling applications. • Application of the method provides improved results compared to traditional models. • Sensitive parameters for MODFLOW CFP models are highlighted. [ABSTRACT FROM AUTHOR]

Water stress conditions associated with population growth, climate change, and groundwater contamination, represent a significant challenge for all stakeholders in the water sector. Increasing the resilience of Water Supply Systems (WSSs) becomes of fundamental importance: along with an adequate level of service, sustainability targets must be ensured. A long-term management strategy is strictly connected to a holistic approach, based on analyses at different scales. To this end, both groundwater modeling tools and water management models, with different spatial and temporal scales, are routinely and independently employed. Here, we propose a coupled approach combining: i) groundwater models (MODFLOW) to investigate different stress scenarios, involving climate change and anthropic activities; ii) water management models (Aquator), to assess the water resources availability and the best long-term management strategy for large-scale WSS. The management models are implemented starting from input and output flows derived by groundwater models: this leads to establish a comprehensive framework usually not defined in management models and including a quantitative characterization of the aquifer. The proposed methodology, general and applicable to any study area, is here implemented to the WSS of Reggio Emilia Province, and its main groundwater resource, the Enza aquifer, considering three different stress scenarios for groundwater models (BAU, ST1, and ST2), and for management strategies (BAU, BAURV2, ST2). Among the key results, we observe that coupling the two model types: i) allows evaluating water resources availability in connection with management rules; ii) leads to examining more realistic operation choices; iii) permits planning of infrastructures at basin scale. [ABSTRACT FROM AUTHOR]