Groundwater Potential Map Research Articles

An integrated geospatial and analytical hierarchy process approach for sustainable water management in the Amravati District, India

Abstract Groundwater is crucial for agriculture, domestic use, and industry. This study represents groundwater potential zones in the Amravati district, Maharashtra, India, using the analytical hierarchy process (AHP) and multi-influencing factor (MIF) techniques. These techniques are employed for a detailed spatial analysis, which is essential for sustainable groundwater management. The study integrates data layers including lithology, geomorphology, land use/land cover, drainage density, lineament density, rainfall, soil, elevation, and slope to evaluate the groundwater potential. The resulting groundwater potential map classifies the area into five categories: poor, fair, moderate, good, and excellent based on groundwater availability. The study reveals that 9% of the area has poor groundwater potential, 37% fair, 28% moderate, 13% good, and 13% excellent. This map is instrumental for stakeholders and policymakers, as it aids in resource allocation and the formulation of sustainable groundwater management strategies. Through the application of AHP and MIF techniques, this study effectively maps the groundwater potential, providing an essential tool for evidence-based decision-making for water resource management in the Amravati district.

Identification of Deep and Shallow Groundwater Potential Zones using GIS Techniques; Case Study: Monaragala District, Sri Lanka

One of the most crucial steps in the management of groundwater sources sustainably is the delineation of the zones with potential for groundwater. However, in addition to taking a lot of time and money, groundwater investigations can be difficult and complex in many locations. To get sufficient results, it needed to demarcate shallow and deep groundwater potentiality separately. Sri Lankan districts have various problems due to a lack of water. With population growth and urbanization, surface water is insufficient to meet the water requirement. This study focused on groundwater potential mapping in Monaragala district covered with the total are 5708 km2 in Sri Lanka. The fuzzy overlay and weighted overlay method integrated with GIS were mainly used to determine potential zones for deep and shallow groundwater. The final results from the two overlaying methods were compared to identify most accurate locations. Six parameters, namely aquifer type, soil depth, soil group, rainfall, proximity to surface water bodies, and slope, were evaluated for the shallow groundwater studies. Proximity to lineament, geology and shallow groundwater parameters were assessed for profound groundwater potentiality. The final output resulting maps were categorized into five main categories such as extremely low, low, moderate, high and extremely high by considering obtained potential values. The deep groundwater potential map demonstrates that the high groundwater potential areas are located around the lineaments, prominently areas having mountain ranges. Therefore the effect of the lineament is very high for deep groundwater availability. High shallow groundwater potential areas are located in smaller regions from Katharagama, Thanamalwila and Siyambalanduwa. Obtained results were validated using existing 220 tube well data and 100 dug well data. 
 Keywords: Fuzzy overlay, Geology, GIS, Groundwater, Weighted overlay

Aquifers Recharge Potentiality Evaluation using Bivariate and Multivariate Statistical Analysis: A Case Study in Malwathu Oya River Basin

An aquifer is a body of porous rock or sediment saturated with groundwater that plays a vital role in the hydrological cycle. Due to rapid population growth and urbanization, these valuable resources face threats like climate changes, pollution, and over-exploitation. Overdraft, where extraction exceeds recharge, can lead to groundwater depletion. Although Sri Lanka is not considered a water- scarce country, it faces rising water demands due to rapid population growth. Especially in dry zones, groundwater is crucial for drinking and agriculture; unauthorized agro-wells exacerbate groundwater issues. Therefore, this research aims to assess groundwater recharge potential zones in Malwathu Oya river basin using Bivariate and Multivariate statistical analysis. Comparing these techniques will lead to the precise identification of potential recharge areas. And this study primarily focuses on the implementation of GIS to find solutions for this kind of challenge without performing field investigations. Therefore, eight conditioning factors; water level, electrical conductivity, lithology, soil, slope, lineament density, drainage density and land use were selected as groundwater recharge influencing factors. The well inventory database consisted of 380 well locations and, out of these, 70% was considered as the training dataset, and the remaining 30% was taken as the testing data set. Groundwater recharge potential maps (GRP) were developed in ArcGIS 10.8, based on the results obtained from Frequency Ratio (FR), Logistic Regression (LR) and their ensemble method. For testing the accuracy of the FR model, test well locations were cross tabulated with the GRP map, and the highest well percentage was achieved in high groundwater recharge potential zone (37.39%). In the LR model, cross-tabulation results showed that 62.61% of testing wells were in the very high potential zones. The ensemble method of FR and LR revealed that 53.04% of test wells fall into the very high potential class. Hence, it can be assumed that LR predictions are more reliable than the FR model. To further validate the LR model and ensemble model, Receiver Operating Characteristics curve method was used. The Area Under the Curve (AUC) values for Success rate curve (SRC) and prediction rate curve (PRC) in LR method were 63% and 57% respectively. In ensemble method, the AUC values for SRC and PRC were 89% and 75%. These results indicate that the LR model is relatively poor estimator, whereas FR and LR ensemble method is relatively good estimator to evaluate groundwater recharge potential in Mulwathu Oya river basin.
 
 Keywords: Area under curve, Frequency ratio, GIS, Groundwater recharge, Logistic regression

Cost-Effective Groundwater Potential Mapping by Integrating Multiple Remote Sensing Data and the Index–Overlay Method

The Choushui River groundwater basin (CRGB) in Yunlin County, Taiwan, is a significant groundwater source for the western part of the region. However, increasing groundwater demand and human activities have triggered a potential crisis due to overexploitation. Therefore, groundwater potential zone (GWPZ) maps are crucial for mapping groundwater resources and water resource management. This study employs the normalized index–overlay method and fuzzy extended analytical hierarchy process (FE-AHP) to map GWPZs cost-effectively. The methodology objectively incorporates weightings from various thematic layers by normalizing and correlating parameters with observed groundwater availability (GA). Site-specific observations, including aquifer thickness, depth to the groundwater level, and porosity, inform GA calculations. Seven comprehensive layers derived from remote sensing (RS) data are processed to obtain weightings and ratings for the groundwater potential index (GWPI) in the CRGB. Selected parameters are categorized into hydrological processes, human interventions, geological, and surface profiles. Hydrological processes include precipitation, modified normalized difference water index (MNDWI), and drainage density. Human interventions consist of the enhanced vegetation index (EVI) and normalized difference building index (NDBI). Surface profiles encompass the terrain ruggedness index (TRI) and slope, enhancing the study’s multi-criteria approach. The observed GA validates the GWPZ accuracy, classifying zones into five categories. According to the GWPI of FE-AHP, about 59.56% of the CRGB area can be categorized as “moderate” to “very good” potential groundwater recharge zones. Pearson’s correlation coefficient between GWPI and GA, based on FE-AHP, outperforms the conventional AHP. This RS-based approach efficiently evaluates GA in aquifers with limited wells, highlighting crucial zones in CRGB’s proximal-fan and southeastern mid-fan for informed groundwater management strategies.

Assessment of groundwater potential and determination of influencing factors using remote sensing and machine learning algorithms: A study of Nainital district of Uttarakhand state, India

Exponential increase in population, rapid urbanization and industrialization have increased the demand of water globally. Groundwater is an important resource in hilly and mountainous regions during dry spells. Thus, identifying prospective groundwater zones is crucial for conserving and managing groundwater. The study makes an attempt to assess groundwater potential in the Nainital district of a hill state in India. Random forest, multi-layer perceptron, M5P and REPTree algorithms were used for preparing groundwater potential maps. Sensitivity analysis was carried out to examine the influence of site-specific parameters on groundwater potential. Each model was evaluated through performance successors and receiver operating characteristic curve (ROC) for its effectiveness in groundwater potential assessment. Multi-layer perceptron was found best fit model for groundwater potential assessment. Largest area was found under high to very high groundwater potential zones in the plain area of the district (48 %), followed by very low to low in the hilly area (46 %) and moderate in the transition zone (7 %). Rainfall, lineament density and drainage density were found significant factors for influencing groundwater potential. The methodology adopted in this study has proved effective in groundwater potential assessment. The other geographical regions may find this methodology useful for groundwater management.

Geospatial and geophysical insights for groundwater potential zones mapping and aquifer evaluation at Wadi Abu Marzouk in El-Nagila, Egypt

This study employs an integration of remote sensing, geographic information systems (GIS), and geophysical techniques to delineate groundwater potential zones (GWPZ). This multidisciplinary approach significantly enhances the precision and reliability of groundwater potential zone mapping. Eight criteria were introduced into the analytic hierarchy process (AHP) to identify GWPZs in Wadi Abu Marzouk by applying a weighted overlay analysis of all criteria layers. The criteria weights were derived by using a pairwise-comparison technique, while the accuracy of the weightage process was calculated by the consistency ratio as 0.06. As revealed in the GWPZ analysis, the northern and northwestern regions have the highest groundwater potentiality. Thirty-five vertical electrical soundings (VES) and four electrical resistivity tomography (ERT) profiles were measured across the study area. The interpretation of geophysical data revealed the presence of a water-bearing layer at depths varying between 27 and 51 m from the ground surface. Its resistivity values indicate the existence of freshwater in the northern and northwestern parts, which highly matches the GWPZ analysis results. However, the southern parts of the area are dominated by saltwater. The integration between geospatial techniques, geophysics, and hydrogeology forms a robust scientific approach, with invaluable insights for sustainable water resource management.

MaxEnt machine learning model predicts high groundwater potential areas in a fractured volcanic aquifer system

Groundwater constitutes a vital resource for public water supply, and thus, it is imperative to recognize the areas of highest potential for increasing availability. The present study employs the MaxEnt model to discern the most favorable areas for locating high-yield wells in Caxias do Sul, Rio Grande do Sul, southern Brazil, where the Serra Geral Aquifer System, a fractured volcanic aquifer, emerges. This aquifer system is characterized by its heterogeneous, discontinuous, and highly anisotropic nature. A dataset comprising 83 wells with high flow rates (≥10 m³/h) was selected from the municipal registry of deep tubular wells, along with 14 factors that influence groundwater occurrence (specific capacity, transmissivity, altitude, slope, horizontal curvature, vertical curvature, relief dissection index, drainage density, distance to drainage, topographic wetness index, distance to lineament, lineament density, precipitation, and soil hydrological group). The model output was a Groundwater Potential Map, which stochastically expresses the probability of obtaining flow rates ≥10 m³/h. The map was validated through cross-validation, resulting in an average accuracy of 65.14%, and by the Receiver Operating Characteristic analysis, resulting in an Area Under the Curve value of 0.911, indicating satisfactory validation. While the MaxEnt model is widely used in ecology to model species distribution, its application in groundwater prediction remains limited, particularly in fractured aquifers associated with volcanic rocks. Apart from optimizing the use of groundwater resources, this study also enhances the understanding of natural phenomena in this type of aquifer.

Groundwater delineation for sustainable improvement and development aided by GIS, AHP, and MIF techniques

Exploration of groundwater is an integral part of viable resource growth for society, economy, and irrigation. However, uncontrolled utilization is mainly reported in urban and industries due to the increasing demand for water in semi-arid and arid regions of the world. In the background, groundwater demarcation for potential areas is vital in meeting necessary demand. The current study applied an integrated method comprising the analytical hierarchy process (AHP), multiple influence factors (MIF), combined with a linear regression curve and observatory well data for groundwater prospects mapping. Thematic maps such as flow direction, flow accumulation, elevation map, land use land cover, slope, soil texture, hill shade, geomorphology, normalized vegetation index, and groundwater depth map were generated utilizing remote sensing techniques. The relative weight of each parameter was estimated and then assigned to major and minor parameters. Potential zones for groundwater were classified into five classes, namely very good, good, moderate, poor, and very poor, based on AHP and MIF methods. A spatially explicit sensitivity and uncertainty analysis method to a GIS-based multi-criteria groundwater potential zone model is presented in this research. The study addressed a flaw in the way groundwater potential mapping results are typically presented in GIS-based multi-criteria decision analysis studies, where discrete class outputs are used without any assessment of their certainty with respect to variations in criteria weighting, which is one of the main contributors to output uncertainty. The study region is categorized based on inferred results as very poor, poor, marginal, and very good in potential ground quality 3.04 km2 is considered extremely poor, 3.33 km2 is considered poor, 64.42 km2 is considered very good, and 85.84 km2 is considered marginal zones, which shows reliable and potential implementation. The outcomes of AHP and MIF were validated by linear regression curve and actual water table in a study area. The study results help to formulate the potential demarcation of groundwater zones for future sustainable planning and development of groundwater sources. This study may be helpful to provide a cost-effective solution to water resources crises. The current study finding may be helpful for decision-makers and administrative professionals for sustainable management of groundwater resources for present and future demands.

Modeling of geophysical derived parameters for groundwater potential zonation using GIS-based multi-criteria conceptual model

This study modeled geophysical derived parameters and multi-critically synthesized their themes based on geospatial and analytical hierarchy processes (AHP) approaches for groundwater potentiality prediction mapping. These methodologies were investigated in a typical hard rock geologic terrain, southwestern, Nigeria. Considering the spatially acquired 96 vertical electrical sounding (VES) data in the area, geoelectric sections revealing five subsurface layers including the topsoil, laterite, weathered layer, fractured basement and fresh basement rock were produced mindful of the 2-D resistivity structure subsurface imaging data interpreted results. The correlative results of the 2-D resistivity structure images and VES data interpretation results delineated major low resistivity vertical discontinuity typical of fractured zones characterized with width range of 25–40 m, while the depth vary from about 40 to > 60 m. Themes of groundwater potential conditioning factors (GPCFs), namely: regolith, bedrock relief, hydraulic head, coefficient of anisotropy, aquifer resistivity and aquifer thickness were prepared from the re-analyzed hydrogeological and geophysical data. The produced themes were appropriately weighted in the context of AHP data mining technique. The groundwater potential prediction index (GPPI) mathematical modeling equation for the area was established via applying the weight linear average algorithm involving the AHP weightage results. The synthesized results of the applied GPPI model equation on the GPCFs’ hydrogeologic themes give GPPI values in the range 1.59–3.65 for the study area. The geospatial modeling of the GPPI estimated values result produced groundwater potential prediction index map for the area. The produced GPPI model map zoned the area into low (1.59–2.30), medium (2.30–2.61), medium–high (2.61–3.02) and high (3.02–3.65) groundwater potential classes. The area analysis of the GPPI map indicates that more than 70% of the study area has ‘low to medium groundwater potential. The GPPI map result verification using reacting operating characteristics technique results gave 86% and 81% success and prediction rates, respectively. The findings of this study are useful to water managers and decision-makers for locating appropriate positions of new productive wells in the study area and other areas with similar geologic settings.

Mapping Groundwater Potential (GWP) in the Al-Ahsa Oasis, Eastern Saudi Arabia Using Data-Driven GIS Techniques

Searching for new sources of water is becoming one of the most important aspects of scientific research, especially in areas prone to drought, like Saudi Arabia. The study aim was to delineate groundwater potential zones within the Oasis of Al-Ahsa, in Saudi Arabia’s eastern region, and to identify the optimum factors that control the availability of groundwater zones. This was achieved through examining the effect of ten environmental variables on groundwater recharge, namely: slope, topographic wetness index (TWI), land cover (LC), elevation, lineament density (Ld), drainage density (Dd), rainfall, geology, and soil texture. The variables were prepared from a variety of data sources, including spatial data (i.e., DEM and Landsat-8 image), in addition to other complementing data sources for appropriate parameters extraction. Two weighted overlay methods were used, namely the simple additive weight (SAW) as well as the optimum index factor (OIF) in order to categorize the optimal set of parameters for computing GWP and identifying its zones. Two GWP maps were obtained and validated through comparison with the locations of existing wells at GWP zones. The study findings have assured the cogency of the SAW map, where it was found that nearly 45–48% of the resultant zones were characterized as in the “moderate” class, whereas around 21–37% of the entire zones area were classified within the “high” class. The soil texture parameter was determined as being the most influencing parameter for GWP mapping followed by the “geology” parameter; however, the “lineament density” (Ld) was the least important factor. Furthermore, the OIF method has facilitated the identification of the optimal parameter combination for delineating groundwater potential (GWP) zones, which included “Ld”, “land cover”, and “TWI”. The study findings and methodology can serve as a potential model for other similar regions, supporting sustainable water resource management locally as well as globally.

Groundwater potential zone mapping using GIS and Remote Sensing based models for sustainable groundwater management

The present research is conducted in the southern region of Khyber Pakhtunkhwa, Pakistan, to identify groundwater potential zones (GWPZ). We used three models including Weight of Evidence (WOE), Frequency Ratio (FR), and Information Value (IV) with twelve parameters (elevation, slope, aspect, curvature, drainage network, LULC, precipitation, geology, Lineament, NDVI, road, and soil texture, that have been prepared and integrated into ArcGIS 10.8. The reliability of the applied models’ results was validated using Area Under the Receiver Operating Characteristics (AUROC). The GWPZ were reclassified into five classes, i.e. very low, low, medium, high, and very high zone. The area occupied by mentioned classes using WOE are very low (10.14%), low (19.58%), medium (26.75%), high (27.10%), very high (16.40%), while using FR are very low (20.93%), low (32.38%), medium (18.92%), high (13.13%), very high (14.61%) and using IV are very low (14.41%), low (17.17%), medium (29.01%), high (25.85%), and very High (13.53%). The Success Rate Curve of WOE, FR, and IV were 0.86, 0.91, and 0.87, while the Predicted Rate Curve values were 0.89, 0.93, and 0.90, respectively. The results revealed that all applied statistical models performed very well to delineate GWPZ. However, use of the FR technique is strongly encouraged to evaluate the GWPZ, and its findings are especially useful for managing groundwater resources in urban planning. Our approaches for assessing the GWPZ mapping can be applied in any region with similar scenarios and are recommended as a helpful tool for policymakers to manage groundwater.

ANALYSIS OF SPATIAL RELATIONSHIP BETWEEN GROUNDWATER POTENTIAL ZONES AND BOREHOLE YIELDS IN OKENE LOCAL GOVERNMENT AREA, KOGI STATE, NIGERIA

The quantity of water that can be extracted from a borehole is directly related to the groundwater potential of an area among other things. Boreholes drilled in areas of low groundwater potential have every tendency to fail. There have been reported cases of borehole failures in Okene Local Government Area of Kogi state. This study therefore aimed at analyzing the potentiality of groundwater and the spatial relationship between borehole yield and groundwater potential zones in the area. Various data which include Sentinel 2 satellite image, Digital Elevation Model, geological map, rainfall data and borehole yield data were analyzed to produce various zones of groundwater potential, and validated using existing borehole yields and the relationship was tested using Pearson correlation. The result of this study reveals that the low potential zone covers 33.2%; moderate potential zone occupies 44.9% which cuts across the whole of Okene LGA and the high potential zone covers 21.9% mainly found around the western part of the area. The Pearson moment correlation analysis result revealed a strong positive correlation (R) value of 0.919. The correlation value shows that there is a strong positive relationship between the existing borehole yields in the study area and the groundwater potentiality map produced from the analysis. The study concluded that there is a strong positive relationship between the existing borehole yields and the groundwater potential zones in Okene Local Government Area.

Investigating machine learning and ensemble learning models in groundwater potential mapping in arid region: case study from Tan-Tan water-scarce region, Morocco

Groundwater resource management in arid regions has a critical importance for sustaining human activities and ecological systems. Accurate mapping of groundwater potential plays a vital role in effective water resource planning. This study investigates the effectiveness of machine learning models, including Random Forest (RF), Adaboost, K-Nearest Neighbors (KNN), and Gaussian Process in groundwater potential mapping (GWPM) in the Tan-Tan arid region, Morocco. Fourteen groundwater conditional factors were considered following multicollinearity test, including topographical, hydrological, climatic, and geological factors. Additionally, point data with 174 sites indicative of groundwater occurrences were incorporated. The groundwater inventory data underwent random partitioning into training and testing datasets at three different ratios: 55/45%, 65/35%, and 75/25%. Ultimately, a comprehensive ranking of the 13 models, encompassing both individual and ensemble models, was determined using the prioritization rank technique. The results revealed that ensemble learning (EL) models, particularly RF and Adaboost (RF-Adaboost), outperformed individual models in groundwater potential mapping. Based on accuracy assessment using the validation dataset, the RF-Adaboost EL results yielded an Area Under the Receiver Operating characteristic Curve (AUROC) and Overall Accuracy (OA) of 94.02 and 94%, respectively. Ensemble models have been effectively applied to integrate 14 factors, capturing their intricate interrelationships, and thereby enhancing the accuracy and robustness of groundwater prediction in the Tan-Tan water-scarce region. Among the natural factors, the current study identified lithology, structural elements (such as faults and tectonic lineaments), and land use as significant contributors to groundwater potential. However, the critical characteristics of the study area showing a coastal position as well as a low background in groundwater prospectivity (low borehole points) are challenging in GWPM. The findings highlight the importance of the significant factors in assessing and managing groundwater resources in arid regions. Moreover, this study makes a contribution to the management of groundwater resources by demonstrating the effectiveness of ensemble learning algorithms in the groundwater potential mapping (GWPM) in arid regions.

Groundwater potentiality mapping: A case study in Baba and Sidri watersheds, South Sinai, Egypt

Groundwater potential zone (GWPZ) mapping is a multi-parameters approach that can assess the groundwater potentiality in mountainous terrain and coastal areas. This approach utilizes the geomorphology, lithology, rainfall, structure lineaments density, drainage density and slope which are the major effective factors controlling the groundwater potentiality. Primarily, these factors are prepared in the form of thematic layers using GIS technique, and then assigned different weights for these thematic layers using Analytical Hierarchy Process (AHP) technique to explore the GWPZ. This GWPZ is generated by the linear weighted sequence of all the prepared thematic layers. The moderate GWPZ (41.8%) sites are located in the main Wadi channels and alluvial fan at western portion; whereas, the high GWPZ (29.8%) concentrates in Homaier depression at the eastern region. Vertical electrical soundings (VES) and time-domain electromagnetic soundings (TEM) measurements have been achieved at high GWPZ to estimate depth and thickness of both saturated and unsaturated areas with water. This geophysical investigation has been done to confirm and support the effectiveness of applied factors of GWPZ mapping. The findings of these measurements are validated by standardizing the measured electrical resistivity values with the sequential layering layout and data records for five wells drilled at the locations of the geophysical soundings. VES and TEM data show the existence of moderately thick adjacent aquifers, covered with a dry area of different thicknesses (18–50 m). The aquifer units with thickness ranging from 43 to 71 m has resistivity values of 22–50 Ω m which is an indicator of freshwater content.

Delineation of Saline/Fresh Water Interface and Mapping Ground-water Potential Zones using Spatial Resistivity Models in Bichpuri Block Agra, District UP, India

Abstract Pin-pointing freshwater within saline formations is of utmost importance as filtration and alternate means of public water supply are responsible for high expenditure. Vertical Electrical Sounding (VES) (n=49) was conducted at various locations in the Bichpuri block, Agra district. In this study for VES, the Schlumberger configuration was used. VES data were reconciled with the borehole well log, and drill sample cuttings were utilized to understand sub-surface configuration. Reconciled VES data displayed variation in resistivity layer parameters, i.e., layer thickness & true resistivity of sub-surface. True resistivity spatial models were developed at 25m intervals from the ground surface down to the depth of 150m, based on geo-electric parameters. Resistivity models reveal that freshwater is limited to 55m depth, beyond which groundwater is saline to brackish. The basement was encountered at a depth of 120m and further extended up to 150m. A groundwater potential map was prepared using GIS and divided into 3 categories – good, moderate, and poor. Major habitations of the study area lie in poor groundwater potential zone, which is a cause of concern with the intent on future development. Similar studies can be extended to areas with saline groundwater for mapping freshwater zones.

Multi-criteria groundwater potential zonation using GIS-based fuzzified AHP: Case study of Ondo metropolis Southwestern Nigeria

The study utilized the fuzzy analytical hierarchical process (F-AHP) in the multicriteria decision analysis of seven important hydrogeologic parameters associated with groundwater potentiality/yield. The purpose was to develop groundwater potential map using groundwater potential index values (GWPIV) for Ondo metropolis, Southwestern Nigeria. The hydrogeologic parameters were prioritize and assigned different weights hierarchically according to their level of importance using F-AHP, as aquifer layer thickness (0.05), aquifer layer resistivity (0.04), overburden thickness (0.12), transverse resistance (0.18), transmissivity (0.32), coefficient of anisotropy (0.25), and formation factor (0.03). From regional perspective, based on drainage basin, and river network, the region was categorized to be of low/moderate groundwater yield, with moderate to high flow connectivity. The higher and lower elevations are generally remarkable in the northern and southern areas respectively, hence possibility of movement of water towards the southern part with the northern forming the watershed. Furthermore, the longitudinal unit conductance recorded regional average value of 1.168, while 1.20, 1.16, and 1.10 were recorded for granite, gneiss and migmatite, which suggests moderate vulnerability to contamination. The average values recorded for overburden thickness, hydraulic conductivity, transmissivity, transverse resistance, formation factor, coefficient of anisotropy, fracture contrast, and reflection coefficient are 22.5 m, 0.33 m/d, 5.56 m2/d, 4966 ohm-m2, 2.42, 1.17, 15.3, and 0.66 respectively. The water table aquifer and the fractured basement are the major water bearing units in the area; while the geological units showed overlapping hydrogeologic properties. The obtained GWPIV ranged from 1.21 to 3.55 with regional average of 1.86, suggesting a moderate potential. Nevertheless, the southern part showed more propensity/yield than the northern area. The study showed the importance of geospatial mapping technique, involving fuzzy analytical hierarchical process, in groundwater evaluation, as it was able to solve and obtain different hydrogeological parameters, which were integrated to prioritize and define the area's groundwater prolificacy for the purpose of improving, expanding, and management of the existing water scheme in the study area.

Modeling and Mapping of Groundwater Potential Zones of the Shewasoor Sub-Basin Using Analytical Hierarchy Process, RS and GIS Techniques in Kirkuk, Northeastern Iraq

Groundwater is considered one of the most vital natural resources for sustaining life. The demand for water in the Shewasoor sub-basin is constantly increasing due to formidable population growth and the development of human activities. Besides, groundwater is scarce due to climatic changes in arid and semi-arid. This study aims to determine spatial distribution of groundwater potential in the Shewasoor sub-basin. This study relied on seven layers (geology, slope, elevation, lineament, drainage density, soil, and land use/land covers) using geographic information systems, remote sensing, and applying the analytical hierarchy process method after determining the weights for each parameter by a multi-criteria decision analysis; to model the groundwater potential map in the Shewasoor sub-basin. The result appeared as a map of groundwater potential categorized into five zones. The majority of the sub-basin (61.8 km2) falls under a very high-high groundwater potential zone, which distributes over an area of elevations, drainage density, and slopes low of the Bai-Hassan Formation; from the center towards the north of the sub-basin. The moderate groundwater potential zone (47.6 km2) mainly encompasses an area of elevations and slopes moderate to the Bai-Hassan formation. About 49.6 km2 is a very low to low groundwater potential zone, mainly found over the area of the elevations and slopes high within the Mukdadiyah Formation east of the sub-basin; in addition to, low groundwater potential within the Bai-Hassan Formation in the south, west, and some part center of the sub-basin due of the elevations and slopes high.

Geospatial Mapping of Groundwater Potentiality in Sooriyawewa Divisional Secretariat Division by Utilizing GIS

The dry zone of Sri Lanka is affected by drought conditions owing to a lack of rainfall. Hence, mapping the distribution of groundwater potential zones is vital for water management. The Hambantota district, which is in the dry zone is a severely afflicted area due to lack of rainfall, and Sooriyawewa divisional secretariat area faces water scarcity. Therefore, this study aims to map groundwater potentiality in the Sooriyawewa divisional secretariat division using a geographical information system. For this study, spatial interpolation techniques, weighted overlay analysis, georeferencing, and digitizing methods were used. In this study, the annual average rainfall, geology, geomorphology, drainage density, lineament density, land use land cover, slope, and soil maps were prepared, and integrating those maps, the final groundwater potential zones map was prepared by using ArcMap 10.5 software. The study found that there were no high-potential groundwater zones in the Sooriyawewa divisional secretariat division and it already consists of low and moderate ranges. Therefore, the final groundwater potential zone map was categorized as very low, low, and moderate. The Percentages of area Coverage according to classes as, very low 2%, low 91%, and moderate 7%. This study can be highly helpful in identifying the groundwater potential zones in the Sooriyawewa divisional secretariat division and in preventing water scarcity because identified groundwater potential zones can be used for effective water management and provide essential information to responsible authorities for decision-making. Furthermore, the identified potential zones can be used for rainwater harvesting and can be used properly for future consumption.

Geophysical Approach for Groundwater Resource Assessment: A Case Study of Oda Community Akure, Southwestern Nigeria

The geophysical investigation for groundwater was carried out at Oda town, Akure south local government area of Ondo State. Fourteen (14) points were sounded using a Schlumberger array with AB/2 of 80 m and the resulting geoelectric parameters were used in the estimation of the aquifer layer parameters of the subsurface. The first layer resistivity value ranges from 29 to 164 Ωm and thickness ranges from 0.6 to 2.5 m. The second layer has a resistivity value ranging from 21-1361 Ωm with a thickness ranging from 1.5 m to 14.6 m. The third layer resistivity value is from 68 to 297 Ωm with thickness ranging from 4 m to 12.4 m. The fourth layer which is the deepest layer has a resistivity value ranging from 180 to 4364 Ωm with depth ranging from 4 m to 19.5 m. The parameters interpreted from the geoelectric data were used to generate the aquifer thickness and resistivity maps, with bedrock relief which were combined to produce the groundwater potential map of the area. These maps were used to characterise the study area into low to high groundwater potential zones. The southwestern and eastern parts were identified as productive groundwater potential zones. The result was validated by taking water column depth from eight existing hand-dug wells. A significant correlation was obtained between the groundwater potential model and the well water column. The surveyed area is generally suitable for hand-dug well aside from the north-eastern part where groundwater potential is low and water volume is observed.

Groundwater resource exploration and mapping methods: a review

Groundwater, a vital resource for various human activities and ecosystems, necessitates efficient management and sustainable utilisation. Groundwater potential zone mapping plays a pivotal role in identifying areas where groundwater resources are abundant, thereby aiding decision makers in optimal resource allocation. This review paper presents an in-depth analysis of diverse methods employed for groundwater potential zone mapping, offering a comprehensive overview of their strengths, weaknesses and recent advancements. The review covers traditional methods rooted in hydrogeological principles, as well as modern techniques that harness the power of geospatial technologies and machine learning. Furthermore, the paper explores the integration of remote sensing and geographic information systems for spatial data analysis, emphasising their role in enhancing the accuracy of potential zone mapping. In the context of recent advancements, the review sheds light on the emergence of hybrid methods that combine the strengths of multiple approaches, resulting in improved prediction accuracy and robustness. Challenges associated with each method, such as data quality, model complexity and interpretability, are critically examined, providing insights into the potential limitations and avenues for improvement. The review also emphasises the importance of validation and uncertainty assessment, ensuring the reliability of potential zone mapping results. Finally, this review paper serves as a comprehensive guide for researchers, practitioners and policymakers engaged in groundwater resource management. By offering a holistic understanding of the diverse methods available for groundwater potential zone mapping, this paper contributes to informed decision making and the advancement of sustainable groundwater-management practices.