Groundwater Potential Zones Research Articles

Identification of groundwater recharge potential zone using geospatial approaches and multi criteria decision models in Udham Singh Nagar district, Uttarakhand, India

Groundwater is a valuable natural resource, which is extensively used in agricultural, industrial as well as daily activities of human beings. It is an essential source of freshwater need of half of the world’s population. In this study Remote Sensing (RS) and Geographic Information Systems (GIS), along with Multi criteria decision models were used. The Analytical Hierarchy Process (AHP) was used to determine the weights of various themes and their classes in the study to identify the groundwater recharge zones in Udham Singh Nagar district. Nine thematic maps/layers were created using GIS methods and employed for the demarcation of groundwater potential zone (GWPZ). It was concluded that around 82% of the area is very suitable (very good and good) for ground water recharge, which suggests that there is a significant amount of potential for artificial recharge systems to be implemented. This can help to augment the natural recharge process, improve water quality, and reduce the strain on existing water sources. Whereas only 18% (very poor and poor) of the area has low potential to groundwater recharge is still important to consider, as it may require different approaches or strategies to improve its suitability. Validation shows that, wells data; (n=38) have water level <5 mbgl (83%), whereas only (n=8) have water less >5 mbgl (17%). This area could be prioritized for more extensive data collection or monitoring to better understand its hydrogeological characteristics. The findings will indeed be helpful for decision-makers in selecting suitable locations for groundwater recharge structures.

Analytical Hierarchy process and geospatial techniques for Delineation of Groundwater potential zones in Bundelkhand Craton Region, India

Analytical Hierarchy process and geospatial techniques for Delineation of Groundwater potential zones in Bundelkhand Craton Region, India

Hydrogeological Resolution Using Composite Geophysical Methods: A Case Study of Inland Salinity in Part of Agra, Uttar Pradesh India

ABSTRACT This manuscript is an attempt at utilizing a combination of varied Geophysical methods (n = 4) – Vertical Electrical Sounding (VES), Electrical Resistivity Tomography (ERT), Time Domain Electromagnetic (TEM), and Borehole logging for finer resolution of potential fresh groundwater and saline groundwater aquifer zones in marginal alluvial plains of Agra district, Uttar Pradesh state. A conceptual model of sub-surface aquifer disposition displaying zones of fresh and saline groundwater zones was prepared using an interpreted and processed multi-parameter dataset. A positive correlation was found between TEM (44.6 m), Well log data (43.0 m), VES data (47.2), and ERT data (45.0 m) demarcating the boundary up to which fresh groundwater potential lies from the ground surface. Conventional methods rely on resistivity values to identify groundwater potential zones, and a rough estimation of salinity can be carried out. Instead of the conventional VES method, the combination of aforesaid methods results in finer resolution and easier demarcation of fresh groundwater zones from those of saline zones. This method can be successfully reproduced to demarcate the extent of saline water ingress in coastal areas and finding freshwater lenses within inland saline aquifers.

Evaluation of groundwater quality potential zones using AHP and WIOA models in Shopian District, Jammu and Kashmir, India: A GIS

Groundwater is an important natural resource stored in aquifers beneath the earth's surface. The hilly district of Shopian in Jammu and Kashmir serves as a study area due to its present and future groundwater needs. This study aims to assess the groundwater potential zones (GWPZ) in Shopian District using the analytical hierarchy process (AHP) and weighted index overlay analysis (WIOA). The AHP approach attempted to assign weights to specific groundwater recharge characteristics. The various thematic maps, including rainfall, land cover and usage, slope, drainage density, geomorphology, soil, and geology, were integrated using overlay analysis to create a comprehensive GWPZ map. Geographic information system (GIS) and remote sensing (RS) tools were utilized to indicate the potential groundwater existence in the studied area. Four zones were created from the GWPZ: very poor, poor, good, and very good. The analysis showed that the very poor GWPZ is around 35.12 sq km, the poor zone is roughly 166.89 sq km, the excellent zone is approximately 340 sq km, and the very good zone is approximately 66.13 sq km. The present study reveals significant perspectives for organizing and effectively restocking groundwater locations within the district. It intends to safeguard the sustainability of groundwater resources for future generations by promoting their successful development and management.

Identification of groundwater potential zone and Water harvesting Structures using remote sensing and GIS technique in Chilapura Watershed, Davangere district, Karnataka state.

Identification of groundwater potential zone and Water harvesting Structures using remote sensing and GIS technique in Chilapura Watershed, Davangere district, Karnataka state.

Delineation of Groundwater Storage and Recharge Potential Zones Using Multi-Influencing Factors (MIF) Method: Application in Synclinal Coastal Basin of Essaouira (Western High Atlas of Morocco)

Unpredictable rainfall caused by climate change and pollution directly impacts groundwater demand, making the exploitation of groundwater reserves necessary. To achieve this, a study in the synclinal basin of Essaouira (Western High Atlas) used GIS, remote sensing, and the Multi-Influencing Factors (MIF) method, to identify areas ideal for the installation of productive wells. An overlay analysis created a groundwater potential zone (GWPZ) map, showing 30% of the basin with high potential, 51% with moderate potential, and 19% with low to very low potential. The groundwater potential zone map was validated using geophysical surveys, piezometric data, and well water levels, showing a 69.3% prediction accuracy with the ROC curve.

Application of remote sensing and electrical resistivity technique for delineating groundwater potential in North Western Nigeria

Improving the living condition of residents of Palladan and Basawa community requires access to drinking water. The main objectives of this paper are to identify suitable groundwater zones for productive drilling and to assess groundwater mineralization in the coastal aquifers of the study area. Geographic Information Systems (GIS) and Analytical Hierarchy Process (AHP) were used in the methodology to generate the groundwater potential map. Slope, landcover/land use, lineament density, rainfall, soil cover and drainage density were taken into account to characterize the groundwater potential zones. Weights were assigned to the various parameters and their characteristics according to their impact on groundwater recharge. The groundwater potential map was classified into five zones namely: poor, fair, moderate, good, excellent. Based on the lineament density map, the distribution of these lineaments reveals the degree of porosity or permeability in each area and, consequently, its groundwater potential. Aeromagnetic data filtering permits the construction of a structural map that illustrates various geophysical lineaments that are known to be fault systems in the research area. These faults are the main routes via which groundwater seeps into the subsurface and granitoid-type magnetic rocks intrude into the basement. The research region is badly fractured/failed and made up of four lithologic units, including the aquifer layer (clayey sands in the cracked basement) with thicknesses varying from 12–55 m, according to the vertical electrical sounding (VES) applications. According to geoelectric cross-sections, the subsurface structures are made of granitic rocks that are surrounded by normal faults that trend both NW and NE. It is believed that groundwater flows into the hard rock aquifers in the studied locations through these notable geological features, such as faults and fractures. Two phenomena are responsible for the mineralization of water: a process of interaction between water and rock; and a process of salinization resulting from natural phenomena or anthropic activities. The present study could guide hydrogeological investigations and groundwater resource management planning in the study area.

A Multi-criterian Approach to Identify Groundwater Potential Zones in the Subarnarekha River Basin Using Integrated Analytical Hierarchy Process and Geospatial Technology

The intense extraction of groundwater and changing climate patterns have strained global groundwater supplies. As the demand for drinkable water rises worldwide, assessing groundwater availability and aquifer output becomes increasingly important. Geographic information systems (GIS) are being used more frequently for groundwater exploration due to their speed and provision of preliminary data. This study focuses on mapping groundwater availability in a minor tropical river basin in India, using a combination of GIS and the analytical hierarchy process (AHP). Ten thematic layers were generated and analyzed, including Geology, Geomorphology, Land use and land cover (LULC), Lineament density, Drainage density, Rainfall, Soil type, Slope, Topographic Wetness Index ( TWI), and curvature to delineate groundwater potential zones. AHP was employed to assign weights to each category based on their water retention properties. The resulting map was validated against existing groundwater data, demonstrating an accuracy of approximately 85%. The groundwater potential zones were classified as high, moderate, and, low. The moderate potential zone covered 59% of the basin, while the low and high potential zones constituted 29% and 11% respectively. High and low potential regions were limited to small sections of the basin. In conclusion, this research successfully mapped the groundwater availability in the Rarhu River watershed using GIS and AHP. The findings highlight the distribution of different groundwater potential zones, providing valuable information for sustainable water resource management in the area.

Delineation of fresh groundwater potentiality zones in saline coastal aquifers, Southwest Bangladesh using remote sensing and GIS approaches.

Bay of Bengal in southern Bangladesh is a major source of water from coastal aquifers, but prone to contamination by seawater intrusion,making climate-vulnerable populations and economies unfit for potable, agricultural water, adopting crops, etc. The study area located in Khulna district lies in the southwestern coast of the country is among the most vulnerable due to its salinity issues. Therefore, this study identified fresh groundwater potential zones in the southwestern coastal zones of the country suited for community usage helping coastal peoples meet their demands. This study focused on twelve thematic layers employing remote sensing and GIS with analytical hierarchy process. Here, groundwater salinity is 84% brackish to saline over 70% of the region [electric conductivity: 295-16,295 micro-Siemens/cm]. However, groundwater chloride in 88% signifies a slightly to medium salty zone. The annual average rainfall reduced surface water infiltration in 75% of the area with little to very slightly soil salinity. The fresh groundwater resource zone has classified based on its potentiality as: very high (0.52%)-for drinking, agricultural irrigation, or industrial work; high (25%)-marginal salinity suitable for agricultural or industrial uses; low (11%)-low salinity, but usable for high salt tolerant crops in irrigation; and very low (64%)-very high groundwater salinity, and not suitable for human consumption and community uses. Finally, this study will help develop sustainable groundwater resources in the coastal region and a fresh groundwater supply plan in saline-prone areas.

Sustainable Water Resource Planning for Alanda Micro Watershed Using Geospatial Techniques

Groundwater is a vital natural resource, especially in areas lacking surface water bodies. About one-third of the global population relies on it for drinking, irrigation and industrial purposes. However, excessive and unregulated exploitation has led to a rapid decline in water tables, emphasizing the need for sustainable groundwater management. The Alanda micro watershed in Barshitakli Taluka, Akola District, Maharashtra, spans 11.39 km², with a sub-humid climate and uneven monsoon rainfall averaging 780 mm. The region faces high water stress in summer, with dried bore wells and farmers relying on rain and groundwater for irrigation. The water resource development plan for Alanda micro watersheds integrates GIS, remote sensing and AHP to identify groundwater potential zones. The Alanda micro watershed soil and water conservation plans were developed using GIS, remote sensing and the AHP method. Thematic maps were overlaid in ArcGIS, applying weighted factors from a pairwise comparison matrix to identify groundwater potential zones. These zones, categorised as high, moderate and low potential, highlight that the largest area has moderate potential, suggesting good opportunities for conservation measures. The survey of the study area identified existing soil and water conservation structures, including 3 farm ponds, 1 check dam and a contour bund. Additional recommendations include 5 farm ponds, 4 check dams, contour trenches and bunding measures, along with agronomic practices for effective surface and groundwater management.

Comprehensive groundwater potential mapping in Nagaland, India using integrated geo-spatial techniques

Groundwater is essential for a sustainable future, yet identifying potential groundwater zones remains challenging in regions with varied hydro-geological conditions. Nagaland is a state in north-eastern India characterized by diverse terrain, complex geological formations, and seasonal variations in rainfall. The objective of the present study is to evaluate groundwater potential zones in Nagaland using an integrated Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) methodology, resulting in the first comprehensive map addressing the region's diverse hydro-geological conditions. Several attributes like geomorphology, geology, slope, soil, rainfall, drainage density, and Land use/Land cover (LU/LC) were generated from available data resources like Landsat 8 and Sentinel-2 satellite imageries, the Geological Survey of India (GSI), Environmental Systems Research Institute (ESRI), the Food and Agriculture Organization (FAO), and the Climatic Research Unit (CRU). These datasets are extracted using the Arc-GIS (Arc-GIS Desktop 10.8.1), with weights assigned according to Saaty's scale, and subsequently normalized through the AHP. The findings reveal that 14% (2240km2) of the state has very good groundwater potential, 42% (6720 km2) is classified as good, 9% (1440 km2) as moderate, 27% (4320 km2) as poor, and 8% (1280 km2) as very poor. These insights are significant for regions like Mokokchung, Longleng, and Wokha, which require urgent intervention. Conversely, the study identifies Dimapur and Chumoukedima as areas with significant groundwater potential, capable of meeting rising water demands. The validation of these results using well discharge data from 12 monitoring wells supports these findings.

Geospatial and geo-electrical assessment of groundwater vulnerability and potential in parts of Cross River, Southern Nigeria

Assessing groundwater vulnerability and potential is essential for sustainable management. This study evaluates these factors in southern Cross River, Nigeria, using geospatial and geo-electrical methods, including Vertical Electrical Sounding (VES), Geographic Information Systems (GIS), and Remote Sensing (RS). Twenty VES surveys were performed, revealing aquifer resistivity from 5.12 to 506.00 Ω/m, thickness from 6.60 to 34.30 m, and depth from 18.60 to 68.00 m. Rainfall was the most significant factor (38 %) affecting groundwater potential, followed by geology (24 %), slope (13 %), drainage density (8 %), land use/cover (6 %), lineament density (5 %), and soil type (3 %). With a Consistency Ratio (CR) of 0.043884, data consistency was high. Groundwater potential zoning (GWPZ) maps categorized the area into low, moderate, good, and excellent zones, highlighting high potential in western areas with high lineament density and moderate slopes. This research demonstrates the effectiveness of integrating geospatial and geo-electrical techniques for groundwater assessment.

Geographical Information System for Groundwater Potential Zoning in a Peninsular Region of Bihar

Background: Exponential growth in population and over-exploitation has created groundwater stress situation in several regions globally. The peninsular area spread in the Bhagalpur and Khagaria districts of Bihar (India) is rich in groundwater, but decrease in groundwater level has been observed in the last decade. Methods: In this study, groundwater potential zones have been delineated using remote sensing and geographic information system (GIS) based AHP. The occurrence of groundwater in the study area is mainly affected by following factors- geomorphology, lithology, lineaments, drainage, soil, annual rainfall, slope, land use land cover and fluctuations in groundwater level. Above factors were considered as themes and were prioritized over each-other using the Analytic Hierarchy Process and merged in a GIS environment to delineate the groundwater potential zones. Result: Four different zones of groundwater potential- low, moderate, high and very high have been observed in the study area. The moderate and high groundwater potential zones cover 44% and 55%, respectively. The delineated potential zones have also been validated using the groundwater levels of the pre- and post-monsoon seasons, which match well. The areas at higher elevations were in the moderate potential zones.

An Assessment of Groundwater Potential for Water Supply in Misau and Dambam Local Government Areas of Bauchi State, Nigeria

This study aimed at assessing groundwater potential in Misau and Dambam areas of Bauchi State, Nigeria. Vertical Electrical Sounding (VES) survey was also conducted to carry out the study. Five thematic maps were generated for weighted overlay. Descriptive statistics was used to analysed data on water supply situation, aquifer parameters were analysed using standard table where porosity and permeability were calculated. The VES data was analysed using ipi2win, thematic maps were produced through overlay analysis using extension of ArcGIS 10.4. VES result reveals the existence of about three to four geologic layers in the study area which constitute the topsoil, weathered rock, weathered/fractured rock, fractured basement, and fresh basement rock. Nine out of the thirteen soundings conducted were found to be of good in nature while the only non-promising aquifers were found in Jalam Kukadi, Hardawa PHC, Bada Koshi, Dambam A Bam. Five groundwater potential zones were determined which are very low 354 km2 (15%), low 393 km2 (15%), moderate 416 km2 (20%), high 436 km2 (25%), and very high 497 km2 (25%). Drainage is the most important factor affecting groundwater occurrence with 25% which is the highest followed by geology with 22%. It can be concluded that 50% of the study area was characterized under high, and very high groundwater potential. It is recommended that areas with poor groundwater potentials government and non-governmental organizations should provide them with an alternative source of water to aid them during periods of difficulties.

Evaluating groundwater potential in water-deficit laterite zones of Eastern India using RS and GIS techniques, combining an analytical hierarchical process for sustainable water resources management

Sustainable groundwater management in water-deficit, laterite-dominated regions need urgent planning, which involve accurate identification of groundwater potential zones (GWPZs). While unsustainable water extraction has exacerbated groundwater availability in laterite zones, laterite is globally known for its limited groundwater potential but has received relatively little research attention. Therefore, the present study aims to examine the role of laterite formation on groundwater potentiality and its relationship with the stage of groundwater development in Paschim Medinipur district of West Bengal in eastern India. This study integrated cost-effective and efficient time-saving tools like remote sensing, and GIS and to produce thematic map layers for overlay analysis and analytical hierarchy process (AHP) to delineate the GWPZs precisely using n = 10 parameters, while a consistency check was performed prior to the integration of these parameters to ensure low subjectivity in the GWPZ. The three identified GWPZ classes cover 30% of ‘good’, 44% of ‘moderate’ and 26% of ‘poor’ zones. The yield data and water level fluctuation analysis revealed that 70% and 60% match the delineated GWPZs. The cross-validation with the receiver operating characteristic curve also demonstrated good (75.1%) prediction accuracy. We found that hydrogeological factors like laterite formations witness around 80% of moderate to poor GWPZ, while poor GWPZ covers half of the laterite belt. However, flood plains and valley fill deposits in the lateritic parts demonstrate moderate to good GWPZ, suggesting laterite formation at variable depths that control groundwater recharge potential. The laterite regions with lower groundwater recharge potential have experienced a 17% increase in water extraction compared to non-laterite areas. Whereas four blocks within the district are partly overlapped with laterite formations and poor GWPZ, which encounter high stages of groundwater development (70–90%), leading to semi-critical to critical conditions. It is attributed to anthropogenic perturbations and hydrogeological conditions, which need urgent planning to ensure sustainable groundwater usage.

Groundwater potential mapping in arid and semi-arid regions of kurdistan region of Iraq: A geoinformatics-based machine learning approach

Groundwater (GW) is a crucial and increasingly scarce natural resource, that is affected by climate change and mismanagement. To manage GW resources effectively, it is crucial to accurately identify GW potential zones (GWPZs) using modern techniques. This study aimed to employ and assess geoinformatics-based machine learning (ML) models to delineate GWPZs in the Akre district, Kurdistan region of Iraq. Six nonparametric ML models were used: a support vector machine (SVM), k-nearest neighbours (KNN), decision tree (DT), random forest (RF), gradient boost DT (GBDT), and extreme gradient boosting (XGBoost). These models were trained on diverse GWPZ-favourable influencing factors, encompassing topographic, hydrological, geological, and environmental aspects. The findings of this study revealed that the XGBoost model outperformed the other nonparametric models in terms of best-fit performance and accuracy in generating a GW potential map (GWPM), achieving a R2 of 0.88, a root mean square error (RMSE) of 11.348, and a mean absolute error (MAE) of 6.623. Notably, over half of the study area (53%) was categorised as having high or very high GWPZs, primarily in the low-lying Rovia Plain. The study identified rainfall, elevation, lineament density (LD), drainage density (Dd), topographic wetness index (TWI), and slope as the most significant factors influencing GWPZ modelling. This study provides a comprehensive framework for GW resource management, ecological conservation, and urban development planning. These insights are crucial for stakeholders, policymakers, and local authorities in strategic resource planning and environmental stewardship.

Application of machine learning and fuzzy AHP for identification of suitable groundwater potential zones using field based hydrogeophysical and soil hydraulic factors in a complex hydrogeological terrain

The eastern section of West Bengal grapples with limited surface water availability in its hard rock terrain, compounded by a semi-arid climate, variable rainfall, and a plateau topography, prompting communities to adapt groundwater water-use practices, leading to unsustainable extraction and misuse. Thus, the novel objective of the present research was to produce groundwater potential maps by comparing machine learning techniques with a Fuzzy MCDM model using specific field-based conditioning factors. In the first step, 285 wells were identified, of which 70 percent were used for training and 30 percent for the validation of the models. Secondly, field-based conditioning factors including, longitudinal conductance (SC), longitudinal resistance (ρl), transverse resistance (TR), coefficient of electrical anisotropy (λ), resistivity of formation (ρm), fracture porosity (φf), reflection coefficients (r), hydraulic conductivity (K), transmissivity(Tr), bulk density, porosity, permeability, soil moisture content and water holding capacity were used to analyze the association between these conditioning factors and groundwater occurrences. In the following steps, the XGBoost, Random Forest, and Naïve Bayes models were executed using the training dataset, and factor weights were calculated using Fuzzy Analytical Hierarchy Process of Extent analysis method. To validate and compare the performance of four models, ROC curves, AUCs, MCAs, and correlation plots were used. In general, all four models were successful in evaluating the potential of groundwater occurrences. The predictive capability of the XGBoost techniques with the highest AUC values (0.79) and the highest correlation value (0.78) is superior to those of other machine learning and MCDM models. Geophysical survey revealed that transmissivity and hydraulic conductivity of the aquifer of the river basin range from 1.55 to 440.11 m/day and 10.15–2253 m2/day, indicating a moderate to good hydrodynamic potential. Planners and engineers can use such groundwater potential maps to manage water resources effectively.

GIS-Based Analytical Hierarchy Process for Identifying Groundwater Potential Zones in Punjab, Pakistan

The quality and level of groundwater tables have rapidly declined because of intensive pumping in Punjab (Pakistan). For sustainable groundwater supplies, there is a need for better management practices. So, the identification of potential groundwater recharge zones is crucial for developing effective management systems. The current research is based on integrating seven contributing factors, including geology, soil map, land cover/land use, lineament density, drainage density, slope, and rainfall to categorize the area into various groundwater recharge potential zones using remote sensing, geographic information system (GIS), and analytical hierarchical process (AHP) for Punjab, Pakistan. The weights (for various thematic layers) and rating values (for sub-classes) in the overlay analysis were assigned for thematic layers and then modified and normalized using the AHP. The result indicates that about 17.88% of the area falls under the category of very high groundwater potential zones (GWPZs). It was found that only 12.27% of the area falls under the category of very low GWPZs. The results showed that spatial technologies like remote sensing and geographic information system (GIS), when combined with AHP technique, provide a robust platform for studying GWPZs. This will help the public and government sectors to understand the potential zone for sustainable groundwater management.

Delineating groundwater potential zones using integrated remote sensing and GIS in Lahore, Pakistan.

Groundwater depletion and water scarcity are pressing issues in water-limited regions worldwide, including Pakistan, where it ranks as the third-largest user of groundwater. Lahore, Pakistan, grapples with severe groundwater depletion due to factors like population growth and increased agricultural land use. This study aims to address the lack of comprehensive groundwater availability data in Lahore's semi-arid region by employing GIS techniques and remote sensing data. Various parameters, including Land Use and Land Cover (LULC), Rainfall, Drainage Density(DD), Water Depth, Soil Type, Slope, Population Density, Road Density, Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-Up Index (NDBI), Moisture Stress Index (MSI), Water Vegetation Water Index (WVWI), and Land Surface Temperature (LST), are considered. Thematic layers of these parameters are assigned different weights based on previous literature, reclassified, and superimposed in weighted overlay tool to develop a groundwater potential zones index map for Lahore. The groundwater recharge potential zones are categorized into five classes: Extremely Bad, Bad, Mediocre, Good, and Extremely Good. The groundwater potential zone index (GWPZI) map of Lahore reveals that the majority falls within the Bad to Mediocre recharge potential zones, covering 33% and 28% of the total land area in Lahore, respectively. Additionally, 14% of the total area falls under the category of Extremely Bad recharge potential zones, while Good to Extremely Good areas cover 19% and 6%, respectively. By providing policymakers and water supply authorities with valuable insights, this study underscores the significance of GIS techniques in groundwater management. Implementing the findings can aid in addressing Lahore's groundwater challenges and formulating sustainable water management strategies for the city's future.

Application of bagging and boosting ensemble machine learning techniques for groundwater potential mapping in a drought-prone agriculture region of eastern India

Groundwater is a primary source of drinking water for billions worldwide. It plays a crucial role in irrigation, domestic, and industrial uses, and significantly contributes to drought resilience in various regions. However, excessive groundwater discharge has left many areas vulnerable to potable water shortages. Therefore, assessing groundwater potential zones (GWPZ) is essential for implementing sustainable management practices to ensure the availability of groundwater for present and future generations. This study aims to delineate areas with high groundwater potential in the Bankura district of West Bengal using four machine learning methods: Random Forest (RF), Adaptive Boosting (AdaBoost), Extreme Gradient Boosting (XGBoost), and Voting Ensemble (VE). The models used 161 data points, comprising 70% of the training dataset, to identify significant correlations between the presence and absence of groundwater in the region. Among the methods, Random Forest (RF) and Extreme Gradient Boosting (XGBoost) proved to be the most effective in mapping groundwater potential, suggesting their applicability in other regions with similar hydrogeological conditions. The performance metrics for RF are very good with a precision of 0.919, recall of 0.971, F1-score of 0.944, and accuracy of 0.943. This indicates a strong capability to accurately predict groundwater zones with minimal false positives and negatives. Adaptive Boosting (AdaBoost) demonstrated comparable performance across all metrics (precision: 0.919, recall: 0.971, F1-score: 0.944, accuracy: 0.943), highlighting its effectiveness in predicting groundwater potential areas accurately; whereas, Extreme Gradient Boosting (XGBoost) outperformed the other models slightly, with higher values in all metrics: precision (0.944), recall (0.971), F1-score (0.958), and accuracy (0.957), suggesting a more refined model performance. The Voting Ensemble (VE) approach also showed enhanced performance, mirroring XGBoost's metrics (precision: 0.944, recall: 0.971, F1-score: 0.958, accuracy: 0.957). This indicates that combining the strengths of individual models leads to better predictions. The groundwater potentiality zoning across the Bankura district varied significantly, with areas of very low potentiality accounting for 41.81% and very high potentiality at 24.35%. The uncertainty in predictions ranged from 0.0 to 0.75 across the study area, reflecting the variability in groundwater availability and the need for targeted management strategies.In summary, this study highlights the critical need for assessing and managing groundwater resources effectively using advanced machine learning techniques. The findings provide a foundation for better groundwater management practices, ensuring sustainable use and conservation in Bankura district and beyond.