Groundwater depletion in hard rock terrains necessitates scientifically validated approaches for identifying suitable aquifer replenishment sites. This study integrates geophysical resistivity surveys with geospatial multi criteria analysis to delineate recharge potential zones in the Kiliyar Sub-Basin of the Palar River Basin, Tamil Nadu. Seven thematic layers, geomorphology, land use/land cover (LULC), lineament density, drainage density, slope, resistivity layer properties, and depth were generated using Landsat ETM+, SRTM DEM, and 32 Vertical Electrical Sounding (VES) points. These parameters are converted to raster format and assigned rank and weights then computed from the Normalized Weight Method (NWM). All the layers have been integrated to generate final layer to assess the artificial recharge structures in the Kiliyar Sub-Basin. The final output zones are classified into five suitability categories: least suitable (5.66%), poorly suitable (22.91%), moderately suitable (29.25%), highly suitable (30.19%), and very highly suitable (12%), and the resulting recharge zonation map groups the basin into the same five classes from least to very highly suitable. The study area boundaries and drainage framework provide important spatial context for interpreting recharge behavior. This aquifer replenishment zone map will be useful for extraction and management of groundwater in the study area. Keywords: Aquifer Replenishment, GIS, Resistivity Survey, Multi-criteria Analysis, Kiliyar Sub-Basin, Remote Sensing

Integration of major ions and multiple isotopes to identify circulation and hydrochemical process of limestone groundwater in the Huainan coalfield, China.

Hybrid data-driven framework for interpretable prediction of nitrate and sulfate risks in coastal aquifers.

The Tipan River, a tributary of Son River in Madhya Pradesh, India, is characterized by diverse geomorphic features such as pediment-pediplain complexes, low to moderately dissected hills, and an intricate river network. The soil of region ranges from clayey to loamy, underlain by geological formations including basalt, granite gneiss, limestone, and fine-grained sandstone. To address urgent need for sustainable groundwater management, this study integrates the Analytical Hierarchy Process (AHP) with Geographic Information System (GIS) tools to delineate groundwater potential zones (GWPZs). Eight hydrological parameters - rainfall, geology, geomorphology, soil, land use/land cover (LULC), slope, drainage density, and lineament density—were selected based on their relevance to groundwater occurrence and recharge. These were weighted through AHP using Saaty's 1–9 scale, with consistency verified (CI = 0.055, CR = 0.039). A weighted overlay analysis in ArcGIS Pro produced a GWPZ map, classifying basin into four classes: Poor (3.58%), Moderate (20.62%), Good (47.59%), and Very Good (28.21%). High groundwater potential was found in areas with gentle slopes, loamy soils, pediment-pediplain features, and high rainfall. The map's accuracy was validated using Receiver Operating Characteristic (ROC). Area Under Curve (AUC) value of 0.789, indicates strong predictive performance. Sensitivity analysis through the map removal method highlighted geology, geomorphology, and soil as the most influential parameters, while LULC showed minimal impact. This AHP-GIS approach offers a robust and replicable framework for groundwater assessment, supporting sustainable water resource planning in Tipan River Basin. Keywords: Tipan River Basin, Analytical Hierarchy Process, Geographic Information System, Groundwater Potential Zones, Sensitivity Analysis

Managing coastal aquifer salinity risks: Strategies for balance, recharge, and crop adaptation.

Understanding the influence of landcover on spring dynamics and evaporation, in Himalayan region, using stable isotope and discharge.

Integrating nitrate isotopes and organic contaminants of emerging concern to improve untreated wastewater tracing in urban groundwater.

Groundwater is absolutely vital for sustaining over 80% of agricultural irrigation in India, underscoring its critical importance in food production. However, ensuring groundwater sustainability remains a pressing challenge, particularly in regions with hard rock, such as the Deccan basalts. Formed millions of years ago through volcanic eruptions, this terrain is characterized by complex geological formations with variable basaltic layer thicknesses, classified into two types: 'simple' and 'compound'. Effective groundwater management in such settings requires integrated hydrogeological studies that rely on rainfall patterns, geological structures, and hydrographic data. To address these challenges, innovative approaches, such as BoreCharger, have been introduced. BoreCharger technology involves detailed hydrogeological investigations and perforation of borewell casings to enable recharge of deeper aquifers with freshwater from unconfined aquifers. This process enhances groundwater availability, improves quality, and revitalizes low-yielding or failing borewells, paving the way for sustainable water management. The present study, conducted at Khalad, Purandar, Maharashtra, demonstrates the positive outcomes of the BoreCharger application. Results show that BoreCharger-equipped borewells consistently sustain water levels until late March, ensuring a reliable supply for both agriculture and drinking purposes. Water quality has also shown significant improvement, with no adverse effects observed on groundwater levels or in nearby wells and water bodies. BoreCharger emerges as a powerful solution to combat the challenge of groundwater sustainability in basaltic terrains. Its ability to enhance both quantity and quality of groundwater highlights its potential for wider application beyond the study area. Keywords: Artificial Recharge, BoreCharger, Impact, Water Level, Khalad Area, Pune District

AI-enhanced groundwater management platform: A network-driven approach for simulation

Groundwater in coastal areas is susceptible to salinization by the inland migration of seawater, driven primarily by excessive abstraction, reduced recharge, and hydrogeological imbalances of natural origin. This study evaluates the extent of seawater intrusion regarding the selected coastal belt using hydro-chemical indicators, geospatial analysis, and graphical interpretation. The quality data related to major cations (Ca²⁺, Mg²⁺, Na⁺, K⁺) and major anions (Cl⁻, HCO₃⁻, CO₃²⁻, SO₄²⁻) of groundwater were collected from the Central Ground Water Board, Government of India, with geographical coordinates. The sampling locations within a 40 km buffer from the coastline were considered for intrusion assessment. The chemical concentrations were converted into milliequivalents per liter (meq/L), and diagnostic ratios like Ca/Mg, Na/Cl, Cl/ (HCO₃⁻ + SO₄²⁻), Cl/ (HCO₃ + CO₃), and the Base Exchange Index (BEX) were computed to identify marine influence on groundwater. These indices provided a strong and multi-parameter method of intrusion detection. A Piper diagram, developed using RockWorks17 software facilitated visualization of hydro-chemical facies with clear distinctions between freshwater, mixed water, and saline water types. Sites affected by intrusion showed typical signatures like a decrease in the Na/Cl ratios, increases in the chloride-alkalinity ratios, negative BEX values, and shifts toward Na–Cl facies. Spatial mapping was carried out to demonstrate the geographical distribution of intrusion-impacted zones using ArcGIS. The intrusion map showed that areas near the coastline and low-lying coastal plains are highly affected, while inland areas are generally less affected. The present study of an integrated hydro-chemical, RockWorks17 based facies analysis and GIS-based approach has evolved into an effective framework for the identification of seawater intrusion and facilitates sustainable management of groundwater in vulnerable coastal aquifers.

ABSTRACT The Aksum district in northern Ethiopia is well-known for its water scarcity, where the water demand exceeds the available supply due to rapid urbanization, population, and economic growth. Groundwater serves as a vital freshwater source in this semi-arid region. However, its quality for drinking and irrigation consumption remains underexplored. This study examines the hydrogeochemical properties of the groundwater of the area, characterized by diverse geological formations. Eighteen groundwater samples were collected and analyzed for physicochemical properties in accordance with American Public Health Association (APHA) standards, using Atomic Absorption Spectrometry and Ultraviolet Spectrometry. The hydrogeochemical parameters were compared with the Ethiopian and World Health Organization (WHO) standards established for drinking and agricultural water. The results revealed that of the groundwater samples were unsuitable for drinking water purposes, largely due to high levels of calcium, potassium, total dissolved solids, electrical conductivity, bicarbonates, and total hardness, particularly in areas underlain by the mudstone units. These physicochemical parameters of some groundwater samples exceeded acceptable limits for drinking water, calling for physicochemical treatment before consumption. Groundwater quality indices such as sodium percentage (%Na), sodium absorption ratio (SAR), Kelly’s Ratio (KR), permeability index (PI), Potential salinity (PS), and residual sodium bicarbonate (RSBC) were evaluated to assess their suitability for irrigation uses. Findings of these indices indicate that the groundwater in the area is generally suitable for irrigation purposes and poses minimal risk. However, few samples surpassed the standards for use, suggesting that proper management of it is still essential to avoid potential problems associated with salinity. The predominant groundwater type identified was Ca-Mg-Na-HCO3, influenced by weathering processes and water-rock interactions. Therefore, this investigation underscores the urgent need for effective groundwater management strategies to address quality issues and promote sustainable use for drinking purposes, especially.

The study's location in a semi-arid climate is impacted by drought cycles, which cause groundwater levels to decline. Groundwater overextraction by agricultural and industrial activities has contributed to minimizing the groundwater storage in the area of interest. Over eight years, 88 pairs of descending Sentinel-1 SAR scenes, supplemented with DInSAR analysis, were employed to track land surface deformation. The Bazian sub-basin, which is characterized by unconsolidated clay-rich deposits, is considered the optimum site for such a kind of study. Vertical subsidence maps were created to delineate areas with high and low-risk zones of land subsidence. According to the results, land subsidence reached in 2017 and 2023 at a maximum of 16 cm, while in 2019, it was at its lowest of 8 cm. The groundwater discharge map shows that areas with high discharge rates are strongly related to zones of high land subsidence, and vice versa. This spatial association indicates that one of the main causes of ground deformation in the sub-basin is excessive groundwater withdrawal, especially in industrial and irrigated agricultural areas. These findings highlight the urgent need for sustainable groundwater management to mitigate subsidence hazard and put a suitable plan for water policies in the region.

This study investigates groundwater flow reversal and fault-induced aquifer segmentation in the Zazari–Cheimaditida lake system of Northern Greece, a tectonically active basin impacted by extensive lignite mining. Using long-term piezometric data, elevation measurements, and hydrogeological cross-sections, we assess flow regimes, drawdown patterns, and the hydraulic role of fault structures. A major cone of depression (>40 m) has formed around the Amyntaio Lignite Mine, reversing regional groundwater flow toward the excavation void. Fault zones function either as barriers or conduits, as quantified through a newly proposed Tectonic Influence Index (TII). Results reveal a dual aquifer system: a shallow, seasonally artesian phreatic aquifer connected to Lake Zazari, and a deeper, confined aquifer hydraulically decoupled from surface waters. These findings highlight the strong influence of structural segmentation on groundwater dynamics in post-mining environments. The study proposes a conceptual hydrostructural model to guide adaptive groundwater management in fault-controlled basins. The framework supports efforts to maintain aquifer sustainability during the transition from lignite-based energy, especially under evolving climate and land-use conditions. The approach presented here is transferable to other tectonically segmented mining basins undergoing ecological and policy-driven restoration.

The Hailiutu River Basin in northern China represents a semi-arid area where groundwater-dependent ecosystems (GDEs) play a critical role in maintaining regional vegetation structure and ecological stability. This study investigated the spatiotemporal dynamics of GDEs and their relationship with water conditions using trend analysis, partial correlation, and Random Forest models over the period of 2002–2022. The results show that vegetation activity (NDVI) increased at a rate of 0.0052/yr in GDEs. Precipitation exhibited a basin-wide upward trend of 0.735 mm/yr, while SPEI increased at 0.0207/yr. In contrast, groundwater storage declined markedly at −11.19 mm/yr, highlighting a persistent reduction in water availability that poses a significant risk to the stability of GDEs. Both partial correlation analysis and the random forest model consistently showed strong ecohydrological interactions between vegetation and groundwater. Vegetation dynamics are primarily driven by groundwater availability, especially in groundwater-dependent ecosystems. Conversely, groundwater variations are most strongly influenced by vegetation. The results indicate that precipitation and the standardized precipitation–evapotranspiration index (SPEI) are the primary positive drivers of interannual NDVI variability, whereas groundwater plays a critical role in sustaining GDEs. Field observations of key species confirm the dependence of GDEs on groundwater, and vegetation dynamics are regulated by climate and groundwater; however, ongoing groundwater decline may threaten ecosystem stability. These findings demonstrate that vegetation transpiration exerts the dominant influence on groundwater variations, while groundwater simultaneously constrains vegetation growth, particularly in areas where declining groundwater storage anomalies (GWSAs) coincide with reduced NDVI. The results emphasize that continuous groundwater depletion threatens vegetation–groundwater sustainability, highlighting the need for balanced groundwater and vegetation management in arid regions.

Abstract The characterization of coastal aquifers is critical for managing freshwater resources threatened by urbanization, agriculture, and climate change. Traditional geophysical techniques, such as electrical resistivity tomography (ERT) and seismic refraction tomography (SRT), provide insights into subsurface structures but can be limited by resolution and interpretational ambiguities. This study introduces a novel approach that combines ERT, SRT and time-domain induced polarization (TDIP) data in a petrophysical framework, including both a direct transformation model (N3PM) and a comprehensive petrophysical joint inversion (PJI) scheme. By integrating these complementary datasets, our method enhances the high-resolution imaging of coastal aquifers, enabling more accurate identification of the water table level, porosity, and salinization. We tested this approach on a synthetic example and two field sites in the Pontina Plain, Italy. R, where results demonstrated that N3PM allows for a fast petrophysical screening where prior knowledge is available and the contribution of surface conduction is properly acknowledged, whilst the joint inversion, particularly with the inclusion of TDIP, ensured the reliable characterization of aquifer layers, capturing fine-grained and saline-impacted zones. This approach advances the non-invasive, quantitative assessment of aquifers, offering a valuable tool for groundwater management in coastal regions.

Groundwater is an important resource for agriculture and drinking water worldwide. However, the over exploitation in agriculture has resulted in a significant decline in quality and quantity. Sustainable groundwater management has become essential, requiring efficient planning and micro-level resource utilization. Geoinformatics, encompassing Remote Sensing (RS) and Geographic Information Systems (GIS), has appeared as a prominent tool in hydrology and water resource development. These technologies enable the rapid assessment and mapping of groundwater potential zones and suitable sites for artificial recharge structures, utilizing different thematic layers, including geomorphology, slope, geology, soil type, land use/land cover, lineament density, and drainage. This review compiles recent advancements in identifying artificial groundwater recharge zones using geoinformatics and highlights methodologies as the Multi-Criteria Decision Making (MCDM), fuzzy logicand Analytic Hierarchy Process (AHP). The paper aims to support the development of cost-effective, efficient groundwater recharge strategies and contribute to sustainable aquifer management, especially during non-rainfall periods.

Accurate prediction of groundwater levels (GWL) is critical for sustainable utilization and scientific management of groundwater resources. However, precise forecasting of GWL fluctuations faces significant challenges due to the complex nonlinear coupling effects of hydrogeological conditions and hydro-meteorological factors. In recent years, research on GWL prediction based on deep learning models has become a cutting-edge topic in the field of hydrogeology. This study focused on Jinan City, China, and constructed a novel hybrid deep learning model that integrates graph neural networks to capture spatial relationships and recurrent neural networks to model temporal dynamics, effectively learning the complex spatio-temporal patterns in the data, namely the Spatio-Temporal Graph Prediction Model (STGPM). Our approach uniquely captures both hydrological connectivity between monitoring wells and multi-scale temporal dependencies, overcoming key limitations of conventional time-series models. Comparative experiments demonstrate that STGPM outperforms the benchmark models on the test set, achieving the lowest prediction errors (MAE = 0.039, RMSE = 0.052) and the highest coefficient of determination (R2=0.988). Notably, for the monitoring well data not involved in model training, the STGPM still maintains excellent predictive accuracy (MAE = 0.062, RMSE = 0.087, R2=0.980), demonstrating the model's strong generalization ability to unmonitored locations. This study provides water resource managers with a reliable decision-support tool for sustainable groundwater management and spring conservation strategies. The proposed methodological framework also offers a transferable solution for addressing various environmental forecasting challenges characterized by spatial heterogeneity.

Groundwater in Bangladesh exhibits significant spatial and temporal variability, driven by monsoon recharge, lithologic heterogeneity, and human extraction. Integrating long-term monitoring data with recent field and Geographic Information Systems analyses (2021–2023), this study quantifies groundwater responses across northwestern and west-central Bangladesh. Seasonal drawdowns in solar irrigation pump (SIP) wells averaged 4.38 ± 1.74 m, followed by full post-monsoon recovery, confirming a recharge–discharge balance. The Theis analytical model, applied with a pumping rate of 2,500 m3/day (representing the upper operational range of SIPs), an average aquifer material transmissivity of 1,800 m2/day, and a storage coefficient of 0.1, predicted maximum drawdowns of 0.68 m at a distance of 10 m from the pumping wells—well below the 5 m critical threshold for maintaining domestic water-supply sustainability. Data also reveal that transmissivity and storage coefficients vary by up to two orders of magnitude among physiographic regions, emphasizing the need for site-specific management. The relatively high transmissivity and storage coefficients of the aquifer materials enable the functioning of the Bengal Water Machine, in which irrigation-induced recharge enhances groundwater storage and helps maintain stable water levels. By applying the United States Geological Survey’s safe-yield concept alongside the Mandel–Shiftan sustainability framework, this study demonstrates that current SIP groundwater withdrawals remain well within sustainable limits. These findings support regionally adaptive groundwater governance that aligns pumping rates with recharge capacity. Such alignment is essential for maintaining irrigation viability and food security under changing climatic and hydrologic conditions. Overall, the results emphasize the importance of region-specific management strategies rather than generalized depletion narratives.

Groundwater in arid regions such as Northwestern Rajasthan of India is under increasing pressure due to climatic extremes, excessive extraction, and contamination from both geogenic and anthropogenic sources. This study assesses the seasonal dynamics of groundwater quality in Bikaner, focusing on fluoride and nitrate contamination and their implications for drinking suitability and public health. Twenty samples were collected from tube wells during the monsoon (2019) and pre-monsoon (2020) periods and analysed for a suite of physicochemical parameters following standard protocols. Water usability was gauged using several parameters including pH, electrical conductivity, total hardness, total dissolved solids, and ions such as calcium, magnesium, potassium, sodium, bicarbonate, carbonate, chloride, fluoride, nitrate and sulphate, while overall quality was synthesized using the Water Quality Index (WQI). Spatial patterns of contamination were visualized through geostatistical mapping, and hydrochemical facies were interpreted via Piper diagrams. Results revealed that over 65% of pre-monsoon samples surpassed WQI thresholds for safe use, signalling deteriorating groundwater quality. Elevated concentrations of fluoride (up to 5 mg/L) and nitrate (up to 320 mg/L) were commonly detected, with several areas falling into unsuitable categories for drinking. A health risk assessment using the Hazard Index framework found that all demographic groups especially infants were exposed to non-carcinogenic risk, with HI values reaching beyond 12 in critical zones. These findings underscore the urgent need for localized groundwater management strategies in the arid regions where seasonal fluctuations and geogenic factors are intensifying fluoride and nitrate contamination. The spatial clustering of high-risk zones especially in central and southeastern areas suggests persistent vulnerability requiring targeted mitigation. Prioritizing seasonal monitoring, fluoride and nitrate treatment technologies, and community-level interventions to mitigate health hazards and secure water resilience in ecologically fragile region of northwestern Rajasthan.

Abstract. Groundwater is vital for agricultural, domestic, and industrial use, particularly in semi-arid regions like Pune district, Maharashtra, India. Increasing water demand and irregular rainfall patterns resulting in water stress areas have made the identification of groundwater potential zones (GWPZs) essential for sustainable resource planning. This study aims to use the Multi-Influencing Factor (MIF) technique integrated with Remote Sensing (RS) and Geographic Information System (GIS) tools to delineate GWPZs, and statistical validation using Receiver Operating Characteristic (ROC) curve analysis. Eleven thematic layers- lithology, geomorphology, slope, elevation, rainfall, land use/land cover (LULC), soil, drainage density, lineament density, topographic wetness index (TWI), and static water level- were selected based on their influence on groundwater occurrence. Each thematic layer was assigned ranks and weights reflecting their hydrogeological relevance. These were integrated using a weighted overlay to derive the Groundwater Potential Zones, categorised into Excellent, Good, Moderate and Low. Model validation using yield data showed a good correlation, with an area under the ROC curve (AUC) value of 0.709, confirming the predictive accuracy. The study found that excellent potential zones are primarily located in the western parts of the district. The majority of areas fall under the good and moderate category. The MIF method and GIS and ROC validation provide a practical and reproducible framework for evaluating groundwater potential. The findings are a valuable tool for planners, facilitating sustainable groundwater planning and management in the Pune district and similar regions.