Search Results (185)

The sustainable management of global groundwater resources is increasingly challenged by climatic uncertainty and escalating anthropogenic stress. Thus, there is a need for simulation tools that are more robust and flexible. This systematic review addresses the integration of two dominant modeling paradigms: the physically grounded Modular Finite-Difference Flow (MODFLOW) model and the data-agile Artificial Neural Network (ANN). While the MODFLOW model provides deep process-based understanding, it is often limited by extensive data requirements and computational intensity. In contrast, an ANN offers remarkable predictive accuracy and computational efficiency, particularly in complex, non-linear systems, but traditionally lacks physical interpretability. This review synthesizes existing research to present a functional classification framework for MODFLOW–ANN integration, providing a systematic analysis of the literature within this structure. Our analysis of the literature, sourced from Scopus, Web of Science, and Google Scholar reveals a clear trend of the strategic integration of these models, representing a new trend in hydrogeological simulation. The literature reveals a classification framework that categorizes the primary integration strategies into three distinct approaches: (1) training an ANN on MODFLOW model outputs to create computationally efficient surrogate models; (2) using an ANN to estimate physical parameters for improved MODFLOW model calibration; and (3) applying ANNs as post-processors to correct systematic errors in MODFLOW model simulations. Our analysis reveals that these hybrid methods consistently outperform standalone approaches by leveraging ANNs for computational acceleration through surrogate modeling, for enhanced model calibration via intelligent parameter estimation, and for improved accuracy through systematic error correction. Full article

The Nanmiao Emergency Groundwater Source Area, rich in H₂SiO₃, serves as a strategic freshwater reserve zone in western Jiangxi Province. However, the mechanisms underlying groundwater formation in this area remain unclear. This study applied a combination of statistical analysis, isotopic tracing, and hydrochemical modeling to reveal the hydrochemical characteristics and origins of groundwater in the region. The results indicate that Na⁺ and Ca²⁺ dominate the cations, while HCO₃⁻ and Cl⁻ dominate the anions. Groundwater from descending springs is characterized by low mineralization and weak acidity, with hydrochemical types of primarily HCO₃–Na·Mg and HCO₃–Mg·Na·Ca. Groundwater from boreholes is weakly mineralized and neutral, with dominant hydrochemical types of HCO₃–Ca·Na and HCO₃–Ca·Na·Mg, suggesting a deep circulation hydrogeochemical process. Hydrogen and oxygen isotope analysis indicates that atmospheric precipitation is the primary recharge source. The chemical composition of groundwater is mainly controlled by rock weathering, silicate mineral dissolution, and cation exchange processes. During groundwater flowing, water and rock interactions, such as leaching, cation exchange, and mixing, occur. This study identifies the recharge sources and circulation mechanisms of regional groundwater, offering valuable insights for the sustainable development and protection of the emergency water source area. Full article

A deep interaction between groundwater and surface hydrology characterizes karst environments. These settings feature closed depressions, whose hydrological role varies depending on whether they have genetic and hydraulic relationships with overland–subsurface flow (epigenic) or deep groundwater circulation (hypogenic). Epigenic dolines and poljes are among the diagnostic landforms of karst terrains. In this study, we applied a hydrological criterion to map closed depressions—including dolines—across the Alburni karst massif, in southern Italy. A GIS-based, semi-automatic approach was employed, combining the sink-filling method (applied to a 5 m DEM) with the visual interpretation of various informative layers. This process produced a raster representing the location and depth of karst closed depressions. This raster was then used to automatically delineate endorheic areas using classic GIS tools. The resulting map reveals a thousand dolines and hundreds of adjacent endorheic areas. Endorheic areas form a complex mosaic across the massif, a feature that had been poorly emphasized in previous works. The main morphometric features of the dolines and endorheic areas were statistically analyzed and compared with the structural characteristics of the massif. The results of the proposed mapping approach provide valuable insights for groundwater management, karst area protection, recharge modeling, and tracer test planning. Full article

The main goal of our work was to evaluate approaches for modeling lateral outflow from shallow unconfined aquifers in a one-dimensional model of vertical variably-saturated flow. The HYDRUS-1D model was modified by implementing formulas representing lateral flow in an aquifer, with linear or quadratic drainage functions describing the relationship between groundwater head and flux. The results obtained by the modified HYDRUS-1D model were compared to the reference simulations with HydroGeoSphere (HGS), with explicit representation of 2D flow in unsaturated and saturated zones in a vertical cross-section of a strip aquifer, including evapotranspiration and plant water uptake. Four series of simulations were conducted for sand and loamy sand soil profiles with deep (6 m) and shallow (2 m) water tables. The results indicate that both linear and quadratic drainage functions can effectively capture groundwater table fluctuations and soil water dynamics. HYDRUS-1D demonstrates notable accuracy in simulating transient fluctuations but shows higher variability near the surface. The study concludes that both quadratic and linear drainage boundary conditions can effectively represent horizontal aquifer flow in 1D models, enhancing the ability of such models to simulate groundwater table fluctuations. Full article

Cylindrical retaining structures are widely adopted in intercity railway tunnel engineering due to their exceptional load-bearing performance, no need for internal support, and efficient utilization of concrete compressive strength. Measured deformation data not only comprehensively reflect the influence of construction and hydrogeological conditions but also directly and clearly indicate the safety and stability status of structure. Therefore, based on two geometrically similar cylindrical shield tunnel shafts in Shenzhen, the surface deformation, structure deformation, and changes in groundwater outside the shafts during excavation were analyzed, and the deformation characteristics under the soil–rock composite stratum were summarized. Results indicate that the uneven distribution of surface surcharge and groundwater level are key factors causing differential deformations. The maximum horizontal deformation of the shafts wall is less than 0.05% of the current excavation depth (H), occurring primarily in two zones: from H − 20 m to H + 20 m and in the shallow 0–10 m range. Vertical deformations at the wall top are mostly within ±0.2% H. Localized groundwater leakage in joints may lead to groundwater redistribution and seepage-induced fine particle migration, exacerbating uneven deformations. Timely grouting when leakage occurs and selecting joints with superior waterproof sealing performance are essential measures to ensure effective sealing. Compared with general polygonal foundation pits, cylindrical retaining structures can achieve low environmental disturbances while possessing high structural stability. Full article

Globally, groundwater resources are experiencing a decline in hydraulic heads resulting from the dual effects of urbanization and climate change, highlighting the need for integrated and sustainable water resources management. Urban development in the cities of Kansai region, western Japan, presents a significant challenge to the sustainability of groundwater resources. This study aims to assess the combined influence of urbanization and climate change on the groundwater resources of the Nara Basin using MODFLOW 6 for two distinct periods: The Pre-Urbanization Period (PreUP: 1980–1988), and the Post-Urbanization Period (PostUP, 2000–2008) with an emphasis on spatiotemporal distribution of recharge in a multi-layer aquifer system. Simulated hydraulic heads were evaluated under three different recharge scenarios: uniformly, spatiotemporally and spatially distributed. The uniform recharge scenario both overestimates and underestimates hydraulic heads, while the spatially distributed scenario produced a simulated heads distribution similar to the spatiotemporally distributed recharge scenario, underscoring the importance of incorporating spatiotemporal variability in recharge input for accurate groundwater flow simulation. Moreover, our results highlight the relevance of spatial distribution of recharge input than temporal distribution. Our findings indicate a significant decrease in hydraulic heads of approximately 5 m from the PreUP to PostUP in the unconfined aquifer, primarily driven by changes in land use and climate. In contrast, the average head decline in deep confined aquifers is about 4 m and is mainly influenced by long-term climatic variations. The impervious land use types experienced more decline in hydraulic heads than the permeable areas under changing climate because of the impedance to infiltration and percolation exacerbating the climate variability effect. These changes in hydraulic heads were particularly evident in the interactions between surface and groundwater. The cumulative volume of groundwater discharge to the river decreased by 27%, while the river seepage into the aquifer increased by 16%. Sustainable groundwater resources management under conditions of urbanization and climate change necessitates a holistic and integrated approach. Full article

The distribution of fresh and salty groundwater is a critical factor affecting the coastal wetlands. However, the dynamics of groundwater flow and salinity in river deltas remain unclear due to complex hydrological settings and impacts of human activities. The uniqueness of the Yellow River Delta (YRD) lies in its relatively short formation time, the frequent salinization and freshening alternation associated with changes in the course of the Yellow River, and the extensive impacts of oil production and underground brine extraction. This study employed a detailed hydrogeological modeling approach to investigate groundwater flow and the impacts of oil field brine leakage in the YRD. To characterize the heterogeneity of the aquifer, a sediment texture model was constructed based on a geotechnical borehole database for the top 30 m of the YRD. A detailed variable-density groundwater model was then constructed to simulate the salinity distribution in the predevelopment period and disturbance by brine extraction in the past decades. Probabilistic particle tracking simulation was implemented to assess the alterations in groundwater flow resulting from brine resource development and evaluate the potential risk of salinity contamination from oil well fields. Simulations show that the limited extraction of brine groundwater has significantly altered the hydraulic gradient and groundwater flow pattern accounting for the less permeable sediments in the delta. The vertical gradient increased by brine pumping has mitigated the salinization process of the shallow groundwater which supports the coastal wetlands. The low groundwater velocity and long travel time suggest that the peak salinity concentration would be greatly reduced, reaching the deep aquifers accounting for dispersion and dilution. Further detailed investigation of the complex groundwater salinization process in the YRD is necessary, as well as its association with alternations in the hydraulic gradient by brine extraction and water injection/production in the oilfield. Full article

Aquifer health assessment is essential for sustainable groundwater management, particularly in semi-arid regions with challenging geological conditions. This study presents a novel methodology for assessing aquifer health in the Barakar River Basin, a hard-rock terrain, by integrating tree-based classification, deep learning, and the Soil and Water Assessment Tool (SWAT) model. Employing Random Forest, Decision Tree, and Convolutional Neural Network (CNN) models, the research examines 20 influential factors, including hydrological, water quality, and socioeconomic variables, to classify aquifer health into four categories: Good, Moderately Good, Semi-Critical, and Critical. The CNN model exhibited the highest predictive accuracy, identifying 33% of the basin as having good aquifer health, while Random Forest assessed 27% as Critical heath. Pearson correlation analysis of CNN-predicted aquifer health indicates that groundwater recharge (r = 0.52), return flow (r = 0.50), and groundwater fluctuation (r = 0.48) are the most influential positive factors. Validation results showed that the CNN model performed strongly, with a precision of 0.957, Area Under the Curve–Receiver Operating Characteristic (AUC-ROC) of 0.95, and F1 score of 0.828, underscoring its reliability and robustness. Geophysical Electrical Resistivity Tomography (ERT) field surveys validated these classifications, particularly in high- and low-aquifer health zones. This study enhances understanding of aquifer dynamics and presents a robust methodology with broader applicability for sustainable groundwater management worldwide. Full article

The northern Yucatán Peninsula hosts a complex karstic environment shaped by carbonate platform development and the Chicxulub impact event, making subsurface characterization crucial for geological and hydrogeological studies. This work aimed to resolve the shallow crustal structure and identify major tectonic features that influence karst processes and groundwater dynamics. We applied a rapid 3D gravity inversion method, linear back projection (LBP), to Bouguer anomaly data, combined with Euler deconvolution to map shallow and deep fault systems. The inversion produced a high-resolution density model down to 12.8 km depth, revealing key geological structures. Multilevel thresholding delineated significant low-density basins, notably the Chicxulub crater, as well as buried sedimentary basins. Euler solutions identified fault networks that coincide with areas of intense karstification, particularly in the eastern peninsula. Results highlight the interplay between impact-related tectonics and karst evolution, influencing groundwater flow paths and recharge zones. This study demonstrates the effectiveness of gravity inversion and Euler deconvolution for regional crustal imaging in carbonate platforms and emphasizes the need for further local-scale surveys to investigate coastal aquifer vulnerability and saltwater intrusion processes. Full article

Deep borehole heat exchangers (DBHEs) have been widely used for extracting geothermal energy in China. However, the application of this technology in an open well with high temperature remains unknown. In this paper, the thermal performance of a DBHE installed in a groundwater-filled hot dry rock (HDR) well in the Gonghe Basin of Qinghai Province in China was investigated. A U-shaped pipe subjected to a hydraulic pressure of 30 MPa and a temperature of 180 °C was tested successfully. Severe heat loss was detected during the test, which might have been due to the pipe not being well-insulated. To better understand the performance of DBHEs, a numerical model was developed. The results indicate that the pipe’s thermal performance increased by 247% using insulation with a 15 mm layer thickness and a thermal conductivity of 0.042 W/m·K. Thermal performance was significantly improved by increasing the fluid flow rate and pipe diameter. Among the different pipe configurations, double U-shaped buried pipes can achieve the highest performance. The heat-specific rate can reach up to 341.33 W/m with a double U-shaped pipe with a diameter of 63 mm. The second highest rate can be achieved with a coaxial pipe, while single U-shaped pipes have the lowest one. Full article

Sustainable groundwater resource management necessitates dependable and precise predictions of groundwater head fields under fluctuating climatic conditions. The substitution of original simulation models with efficient surrogates presents a challenge in simultaneously accounting for correlations among multiple time series outputs and maintaining overall prediction accuracy. This study develops a novel surrogate modelling approach, DSCNN-GRU, incorporating a deep separable convolutional neural network (DSCNN) and a gated recurrent unit (GRU), to efficiently capture temporal and spatial variations in groundwater head fields from transient groundwater flow models using input hydraulic conductivity field data. The applicability and performance of the proposed method are evaluated for predicting groundwater head fields in a practical research area under three scenarios with different hydraulic conductivity fields. The performance of the DSCNN-GRU model is compared to the traditional convolutional neural network (CNN), CNN-LSTM, and DSCNN-LSTM models to further test its applicability. The numerical study demonstrates that optimizing hyperparameters can result in reasonably accurate performance of the proposed model, and the “simplest” DSCNN-GRU outperforms CNN, CNN-LSTM, and DSCNN-LSTM in both prediction accuracy and time-to-solution. Full article

This study combines field experiments and numerical analysis using the HYDRUS model to investigate the impact of water table depths on evaporation processes in semi-arid regions with shallow groundwater. Two lysimeters with different water table depths were set up in the Ordos Basin, Northwest China, and instrumented with multi-depth soil moisture and temperature sensors. The experimental data were used to calibrate and validate numerical models that simulated both non-isothermal and isothermal flows. The results reveal that groundwater levels significantly influence the evaporation rate, dictating the position of the evaporation front and zero-flux plane. Isothermal models underestimated cumulative evaporation by 14.7% and 44.2% for the shallow and deep-water table lysimeters, respectively, while non-isothermal models produced more accurate results with 0.95% overestimation and 5.2% underestimation. The study demonstrates that incorporating both water and heat transport into numerical models enhances the accuracy of evaporation estimates under varying groundwater conditions. Furthermore, the findings show that when the evaporation front occurs near the surface, liquid water flux dominates, whereas water vapor flux plays a crucial role when the evaporation front is located below the surface. These results offer valuable insights for refining water management strategies and models in agricultural and ecological systems of semi-arid areas, underscoring the critical role of considering soil moisture and temperature dynamics, along with groundwater levels, in accurately quantifying evaporation for improved resource management. Full article

Prioritizing agricultural land use is a significant challenge for sustainable development in the rapidly urbanizing, semi-arid riverine basins of South Asia, especially under climate variability and water scarcity. This study introduces a systematic framework combining remote sensing and geospatial data with the Soil and Water Assessment Tool (SWAT) model, morphometric analysis, and VIKOR-based Multi-Criteria Decision Analysis (MCDA) to effectively identify Agricultural Land Prioritization (AgLP) areas in the Upper Kansai Basin, India, while reducing the environmental impact, in line with Sustainable Development Goals (SDGs). The SWAT model simulation reveals varied hydrological patterns, with basin water yields from 965.9 to 1012.9 mm and a substantial baseflow (~64% of total flow), emphasizing essential groundwater–surface water interactions for sustainable agriculture. However, the discrepancy between percolation (47% of precipitation) and deep recharge (2% of precipitation) signals potential long-term groundwater challenges. VIKOR analysis offers a robust prioritization framework, ranking SW4 as the most suitable (Qi = 0.003) for balanced hydrological and morphometric features, in agreement with the SWAT outcomes. SW4 and SW5 display optimal agricultural conditions due to stable terrain, effective water retention, and favorable morphometric traits (drainage density 3.0–3.15 km/km²; ruggedness 0.3–0.4). Conversely, SW2, with high drainage density (5.33 km/km²) and ruggedness (2.0), shows low suitability, indicating risks of erosion and poor water retention. This integrated AgLP framework advances sustainable agricultural development and supports SDGs, including SDG 2 (Zero Hunger), SDG 6 (Clean Water), SDG 13 (Climate Action), and SDG 15 (Life on Land). Incorporating hydrological dynamics, land use, soil properties, and climate variables, this approach offers a precise assessment of agricultural suitability to address global sustainability challenges in vulnerable riverine basins of developing nations. Full article

Dual isotopes of sulfate (δ³⁴S_SO4 and δ¹⁸O_SO4), along with isotopes in water and trace elements of geothermal waters, are systematically investigated to quantitatively elucidate sulfate sources and oxygen and sulfur isotopic behaviors during deep groundwater circulation and to constrain reservoir temperatures in the Jimo nonvolcanic geothermal system on the eastern coast of China. The results show that δ³⁴S_SO4 and δ¹⁸O_SO4 values in geothermal waters ranged from −21.0 to 5.7‰ and from 1.1 to 8.8‰, respectively. An increase in SO₄ concentrations (140–796 mg/L) with a systematic decrease in δ³⁴S_SO4 and δ¹⁸O_SO4 values was observed along the flow path from the central to eastern and western parts. The sulfate in the Middle Group was predominantly from atmospheric deposition, with sulfide oxidation contributions of <27%. In contrast, 80–85% of SO₄ in the Eastern Group is derived from pyrite oxidation. In the Western Group, the oxidation of multiple metal sulfides contributed 43–66% of SO₄. Sulfate oxidation and mixing of shallow groundwater caused reservoir temperatures to be underestimated by 9 ± 6–14 ± 16% using silica and K-Mg geothermometers but overestimated by up to 52–62% using sulfate–water oxygen isotope geothermometers. The estimated average target reservoir temperature was 144 ± 8 °C, with geothermal waters circulating to depths of 3.6–4.6 km. This study offers new insights into the significant impact of sulfate-related processes on geothermometric estimates, a factor often overlooked when using aqueous geothermometers. It also provides valuable guidance for accurately estimating target geothermal reservoir temperatures and advancing exploration in nonvolcanic geothermal systems. Full article

This study analyzes the evolution of surface water and groundwater temperatures at various depths in the sand-dune ponds of Doñana National Park (southern Spain) over eight hydrometeorological years (2016–2024). This research aims to characterize the water temperature regime, identify water temperature trends, and analyze patterns in groundwater flow dynamics. The results indicate that, in a recent dry–warm period (2020–2023), coinciding with a notable decrease in precipitation and an increase in the average air temperature in the area, there was an increase in the annual mean temperature of pond water and in shallow piezometers (~15 m depth). However, in deep piezometers, a decrease in water temperature was recorded during the dry–warm period, along with a reduction in temperature variability. A phase shift has also been observed between groundwater temperature extremes and air temperature variations, with the magnitude of this shift depending on sensor depth. These findings enable the analysis of the sensitivity of these wetlands to global environmental change and contribute to the characterization of recharge and discharge flows in the aquifer, both at local and regional scales, allowing for the evaluation of flow variability in hydrological years with below-average precipitation and above-average air temperature and shallow groundwater temperature. Full article