Groundwater Potential Zone Map Research Articles

Estimating groundwater resources in an equatorial forested basin using geographic information system and remote sensing techniques (case of Nyong, South Cameroon)

ABSTRACT This article aims to produce a groundwater potential zone (GWPZ) map of the Nyong basin using an integrated analytical hierarchy process driven in a geographic information system (GIS) environment. For this, seven parameters (rainfall, geology, slopes, drainage density, land use and land cover, lineament density, and soil) known to influence the availability of groundwater were considered. The results obtained show that the Eastern part of the basin holds the largest quantities of groundwater. The produced map shows that this region includes high and very high GWPZs (yield > 6 l/s). It is essentially characterized by abundant rainfall (on average 135–136 and 131–134 mm), low slopes, significant drainage and lineament densities, and significant forest cover. On the other hand, the opposite region (west), which includes the low and very low GWPZs, is characterized by less abundant precipitation (on average 121–125 and 125–128 mm), significant slopes, lower drainage and lineament densities, and greater impervious areas. With a success rate of 80%, confidence deserves to be placed in the GWPZs map produced. It can be considered in water supply projects in this basin. Such work has never been done in this basin before.

Groundwater potential zone mapping of middle Andaman using multi-criteria decision-making and support vector machine

Groundwater is a vital resource crucial to human survival worldwide and plays a significant role in addressing climate change. The multi-criteria decision method and support vector machine technique were used to demarcate the groundwater potential zones (GWPZ) of Middle Andaman. A total of 11 factors including geology, geomorphology, LULC map, lineament density, distance from Active Fault, groundwater level, distance from the sea, slope, drainage density, distance from major earthquakes, and distance from epicenter hotspots were used to calculate GWPZ. Spatially distributed maps/thematic layers of all of the above factors were generated using remotely sensed data as well as ground data. Each factor was assigned weights based on preceding global and regional research and the influence of each layer on groundwater. Finally, all thematic layers were used for multi-criteria decision analysis to create a map depicting the GWPZ of Middle Andaman. A support vector machine (SVM) tool was used to demarcate the potential zone based on the signature obtained from overlay analysis. The resulting map was divided into four categories: very high, high, low, and very low groundwater potential zones. SVM classification result showed that most of Middle Andaman's areas come under the low to very low GWPZ (63.4%), followed by high GWPZ (27%), and 10.6% of very high GWPZ. SVM classification resulted in overall accuracy, kappa coefficient, and the area in the ROC curve of 91.66%, 0.87, and 0.64 respectively. The analysis revealed a correlation between each factor and the Multi-Criteria Decision Method (MCDM) and Support Vector Machine (SVM), indicating that the majority of geological and geomorphological features are linked to lower groundwater potential. Further, the result was compared with groundwater fluctuation data of the middle Andaman. Finally, this study provides an expedient approach to delineating the GWPZ for practical management and use of the area's groundwater resources to maintain the island's sustainability.

Mapping of groundwater potential zones of Khordha District using GIS and AHP approaches

The most dependable source of fresh water is groundwater. Groundwater supplies are severely threatened by a number of factors, including urbanization, industrialization, and population growth. The amount, quality and variables affecting groundwater supplies are significantly impacted by climate variability. The fall in groundwater levels is often exacerbated by poor quality surface water resources and unreliable monsoons. Therefore, in order to supplement the groundwater supply, it is important to locate and define the groundwater potential zone (GPZ). The analysis is conducted for the Khordha district, where groundwater rather is a primary source for agricultural uses. In order to determine the possible groundwater zones, many factors, including geomorphology, geology, elevation, slope, precipitation, soil type, soil texture, drainage density (DD), lineament density (LD), Land use/Land cover (LULC), and lineament density (LD), are constructed as separate layers in the geographical information system (GIS) backdrop. The multi-criteria decision-making technique and the Analytic Hierarchy Process (AHP), which enable pairwise evaluation of criteria impacting the potential zone, were utilized to establish the weights for the different layers and after that, the weighted overlay analysis (WOA) tool in ArcGIS10.8 was used to produce the final groundwater potential map. The output map of specified region was delineated into five new classes-very good, good, moderate, poor, and very poor of which 12% (325.1745 km2) falls under ‘very low’, 22% (603.9765 km2) under ‘low’, 26% (700.7715 km2) under ‘moderate’, 26% (694.2591 km2) under ‘high’, 14% (376.7553 km2) under ‘very high’. Approximately 1395 km2 area concerning 52% of study region, falls under ‘high’ and ‘very high’ categories of GPZ. Validation of the generated GPWZ map was done with data acquired from Central groundwater board. The accuracy assessment was done by kappa coefficient error matrix, and based on overall accuracy, the obtained map was 81.538% accurate to field value. As dependable results were produced with the proposed methodology, future management plans incorporating natural and artificial recharge practices can be created in these locations with effectiveness.

Delineation of Groundwater Potential Zones Using Remote Sensing and Gis Techniques of Phewa Watershed (Nepal)

Groundwater is the primary source of water in the study region, both for domestic and agricultural needs. The main objective of this research is to identify the groundwater potential zones via remote sensing (RS) and Geographic information system (GIS), which is essential in evaluating, preserving, and monitoring various groundwater-related development programs. Man-made pressures include over-exploitation of groundwater and climate changes have led to a strain on groundwater resources. As the use of consumable water increases for human consumption, agriculture, industrial growth, municipal, and pharmaceutical needs to evaluate the groundwater potential and aquifer productivity also increase. Groundwater inspections have been historically done by field survey method, which is inefficient or not practical in terms of time and resources. Arc GIS software is utilized to manipulate datasets. The LULC map of the study area will be developed using Landsat 8 satellite data. A soil map and rainfall map will be created using the data sources from USGS, a Parent soil map will creates using the data from NARC and slope map, lineament density and drainage density from ASTER from earth data. Seven thematic maps will be applied, each with appropriate weight and rank assigned based on its characteristics and connection with groundwater. All the thematic layers combine into a GIS domain, and weight values are put to the attribute table for each polygon. The groundwater potential zone map will be classified into different zones, i.e., very poor, poor, moderate, good, and very good. These results will help hydrogeologists, decision-makers, planners, and local authorities formulate better groundwater resource planning in the Phewa watershed area.

Assessment of groundwater potential zone mapping for semi-arid environment areas using AHP and MIF techniques

AbstractGroundwater resources are essential for drinking water, irrigation, and the economy mainly in semiarid environments where rainfall is limited. Currently, unpredictable rainfall due to climate change and pollution on the Earth’s surface directly affects groundwater resources. In this area, most people depend on groundwater resources for irrigation and drinking purposes, and every summer, most of the area depends on groundwater in a semiarid environment. Hence, we selected two popular methods, the analytical hierarchy process (AHP) and multiple influence factor (MIF) methods, which can be applied to map groundwater potential zones. Nine thematic layers, such as land use and land cover (LULC), geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps, were selected for this study using remote sensing and geographic information system (GIS) techniques. These layers are integrated in ArcGIS 10.5 software with the help of the AHP and MIF methods. The map of the groundwater potential zones in the study area revealed four classes, i.e., poor, moderate, good, and very good, based on the AHP and MF methods. The groundwater potential zone area is 241.50 (ha) Poor, 285.64 (ha) moderate, 408.31 (ha) good, and 92.75 (ha) very good using the AHP method. Similarly, the MIF method revealed that the groundwater potential classes were divided into four classes: 351.29 (ha) poor, 511.18 (ha), moderate, 123.95 (ha) good, and 41.78 (ha) very good. The results were compared to determine which methods are best for planning water and land resource development in specific areas that have basaltic rock and drought conditions. Both groundwater potential zone maps were validated with water yield data. The receiver operating characteristic (ROC) curve and area under the curve (AUC) model results are found to be 0.80 (good) and 0.93 (excellent) using the MIF and AHP methods, respectively; hence, the AHP method is best for delineation of groundwater potential zone maps and groundwater resource planning. The present study’s framework and the results will be valuable for improving the efficiency of irrigation, conserving rainwater and maintaining the ecosystem in India.

Demarcation of groundwater potential zones in Ponnai sub-basin, Southern India using remote sensing, GIS and fuzzy-AHP approaches

ABSTRACT Groundwater is an essential source for household, irrigation and industry needs. The amount of groundwater and its quality are rapidly declining because of urbanization and industrialization. Groundwater resources in hard rock regions should be handled properly to maximize their utilization. This work aims to demarcate the Groundwater Potential Zones (GWPZ) in a part of the Palar River Basin (Ponnai sub-basin) by combining Remote Sensing (RS), Geographic Information System (GIS) and Fuzzy-Analytical Hierarchy Process (FAHP). The factors which influence the groundwater like geology, land use/land cover (LULC), geomorphology, slope, soil, rainfall, lineament density (LD), drainage density (DD), normalized difference vegetation index (NDVI), topographic wetness index (TWI) and topographic position index (TPI) are considered for mapping of GWPZ. The weightage is allocated to these parameters on the basis of the FAHP technique and the obtained groundwater potential map was classified as, very poor (13.5%), poor (21.76%), moderate (31.5%), good (20.66%) and very good (8.54%). The GWPZ map was validated with the actual well yield of the Ponnai sub-basin. The research work will serve as a guideline for the effective use of groundwater and long-term sustainable management of the aquifer in the Ponnai sub-basin.

Empowered machine learning algorithm to identify sustainable groundwater potential zone map in Jashore District, Bangladesh

Groundwater is a crucial natural resource that supplies potable water to the local population in Jashore, Bangladesh. In recent years, the district has experienced groundwater scarcity during the summer season, significantly affecting both domestic and agricultural usage, thereby impacting the local populace. However, accurately assessing its availability and quality remains a challenge. Our objective was to identify groundwater prospect zones in Jashore and provide valuable insights for management and decision-making through Explainable Artificial Intelligence (XAI). This study used 15 groundwater conditioning factors for potential zone mapping. The k-Nearest Neighbors (KNN), Neural Networks (NNET), Gradient Boosting Machines (GBM), Random Forest (RF), and Support Vector Machines (SVM) models were applied to assess groundwater suitability, resulting in the identification of five distinct areas with different levels of potential. The areas with very low suitability covered 39.37, 14.95, 107.23, 291.59, and 300.24 km2, while areas with very high suitability covered 1255.61, 969.49, 1221.99, 1958.85, and 1211.03 km2, respectively. Notably, the RF and NNET models exhibited higher accuracy, with Area Under Curve (AUC) values of 90%. The KNN, GBM, and SVM models achieved AUC values of 85%, 86%, and 88% respectively. The study reveals that the northeastern region has the greatest groundwater potential, while the southern and southwestern regions have lower capacities. The researcher's also utilized Partial Dependence Plots (PDP) technique, to analyze parameter behavior in predicting groundwater suitability. This approach provided valuable insights into the impact of various factors on groundwater potential, aiding management decisions. The study findings inform to policymakers and water resource managers in Jashore, enabling sustainable groundwater management by identifying high-potential areas. This knowledge optimizes resource allocation, ensuring sufficient supply for sustainable development.

Mapping of Groundwater Potential Zones in the Kuzhithuraiyar Sub Basin of Kodayar River, Kanniyakumari District, Tamilnadu: Using Analytic Hierarchy Process (AHP) and GIS


 
 
 Groundwater plays a very important role for all living beings. It is decisive to have a scientific understanding of groundwater management since, with careful use and replenishment, groundwater may help solve issues. The distribution of groundwater tables, slope, land-form, drainage pattern, lithology, topography, geological structure, fracturing density, opening and connectivity of fractures, secondary porosity, and landuse landcover all affect the occurrence and efficiency of groundwater in an aquifer system. An essential tool for assessing, tracking and protecting groundwater resources is the integration of geospatial techniques such as Remote Sensing and Geographic Information System for the identification of groundwater potential zones. This study aims to find the groundwater potential zones using Analytical Hierarchy Process (AHP) and managing the resources by creating different thematic layers such as rainfall, geology, geomorphology, drainage density, soil, slope, lineament and landuse landcover (LULC) of the Kuzhithuraiyar sub basin of the Kodayar river in Tamilnadu using the application of geospatial technologies. The thematic maps for all the thematic layers have been prepared using tools such as Interpolation, contour lines, Classification in ArcGIS 10.8. Theme weight and class rank were assigned to different thematic layers in weighed overlay analysis. The results were validated through field work and groundwater potential map was created. The groundwater potential zonation mapping was done by the overlay analysis in ArcGIS 10.8 software. The obtained map was classified into four categories namely very high groundwater potential zone, high groundwater potential zone, medium groundwater potential zone and low groundwater potential zone. The North Eastern part of the basin is considered as low groundwater potential zone while the Southern portion has high groundwater potentiality. The low groundwater potential zone covers an area of 10.58 sq.km and high groundwater potential zone covers an area of about 388.37sq.km.This study will be helpful for useful groundwater management for different tenacities.
 
 

Mapping coastal groundwater potential zones using remote sensing based AHP model in Al Qunfudhah region along Red Sea, Saudi Arabia

Due to the increases in agriculture and industry sector as well as high population, lack of water is becoming a major problem in the Middle East especially in arid regions. Saudi Arabia needs more groundwater research and explorations because of its higher water use and no source of freshwater. Assessing groundwater zonation in semi-arid locations is essential due to the significant degree of variation in groundwater depth, aquifer features, topographical characteristics, and insufficient precipitation. Mapping prospective groundwater zones in Al Qunfudhah region of southwestern Saudi Arabia has utilized the capability of the multi-criteria decision approaches (MCDA), and the Geographic information system (GIS). We have used the analytical hierarchy process (AHP) as one of the MCDA that is applied to achieve the objective of the current study by integrating twelve controlling factors. These factors are represented by the thematic layers; slope, precipitation, soil type, land use/cover (LULC), drainage density (DD), normalized difference vegetation index (NDVI), curvature, topographic position index (TPI), Terrain Ruggedness Index (TRI), drainage density (DD), and Lineament Density (LD). These thematic layers are combined with GIS to delineate the zones of groundwater potentialities. All factors were classified and weighted according to their importance and its effect on groundwater zones. Their normalized weights were evaluated using a pairwise comparison matrix. The present study shows that the groundwater potential zones (GWPZs) map is represented by five groups ranging between a very high zone with an area of 23781.06 Km2 that represents 4.04 % of the studied area, and a very poor GWPZ with an area of 182944.4 Km2 that represents 31.09 % of the studied area. The AHP model suggests that lineament density, slope, and drainage density are more important for determining the groundwater potentiality than other physiographic factors. The study's findings will be helpful in developing practical strategies for the region's groundwater supply. This analysis shows how the methodology may be used to study a broad coastal groundwater basin. The current study will give the decision makers to select suitable sites with a high groundwater potential.

Mapping of groundwater potential zones in a drought prone Marathwada Region using frequency ratio and statistical index methods, India

Groundwater potential investigation is one of the most significant and crucial aspects in arid and semi-arid regions like Marathwada. Marathwada is often susceptible to water scarcity and drought due to monsoon variability. Therefore, it is indispensable to identify groundwater potential zones (GWPZs) to meet human needs. The present research used the frequency ratio (FR) and statistical index (SI) models to recognize the GWPZs in the region. Accordingly, eight factors such as geomorphology, elevation, slope, geology, drainage density, rainfall, soil types, and land use/land cover applied to delineate GWPZ in the Marathwada region. About 309 wells in the study area were randomly subset into training (70%) and testing (30%) datasets. The GWPZ maps were classified into the five zones of groundwater potential (very low, low, moderate, high, and very high). The FR showed about 53% areas having the very high potentiality of groundwater, whereas 11% area comes under a low potentiality of groundwater. However, SI model showed 65% areas having very high potential of groundwater, while 8% areas fall in a category of medium potentiality of groundwater. The most substantial GWPZ observed in central eastern part of the region with low elevation and slope, pediment pediplain complex areas with high rainfall covered with Chromic Vertisols (Vc) soil. The results of the receiver operating characteristic (ROC) and the area under the curve (AUC) revealed that the performance of the SI model (AUC = 75.14%) is better than the FR model (61.20%). Therefore, the SI model is most suitable to identity and map the GWPZs in the study region. The outcomes derived from this model are appropriate for groundwater resources management and planning in the semi-arid Marathwada region.

Optimizing urban water sustainability: Integrating deep learning, genetic algorithm, and CMIP6 GCM for groundwater potential zone prediction within a social-ecological-technological framework

This study presents a novel approach to groundwater resource assessment and drought vulnerability, achieved through integrating cutting-edge deep-learning algorithms into a comprehensive framework. In regions susceptible to drought, ensuring groundwater availability is of paramount importance. Addressing this critical need, our research employs an ensemble of advanced algorithms, including long short-term memory, convolutional neural network, deep neural network, and recurrent neural network. These algorithms are further enhanced through optimization using a genetic algorithm to map groundwater potential zones (GWPZ). Leveraging model validation based on the area under the receiver operating characteristic curve (AUCROC), the long short-term memory-genetic algorithm model emerges as the superior algorithm, boasting the highest values of AUCROC: 0.995 for training and 0.996 for testing). Utilizing this optimized model, this study developed the GWPZ map, subsequently overlaying it with established drought maps developed by the Bangladesh Agricultural Research Council across distinct periods—Pre-Kharif, Kharif, and Rabi. The derived baseline GWPZ spatial distribution revealed five categories—very low (34.99%), low (27.67%), moderate (13.26%), high (11.71%), and very high (12.37%)—and their intersection with drought-prone regions, indicative of probabilities of drought occurrence ranging from very severe to low (15.14% to 24.69%). Moreover, employing the best-predicted model, this study projected future GWPZ for 2050 and 2100 using the coupled model intercomparison project 6 general circulation model data under the ambit of three distinct shared socioeconomic pathways (SSPs): SSP1-2.6, SSP2-4.5, and SSP5-8.5. Our findings suggested a contraction in the groundwater potential area by the end of the twenty-first century (2100). This pioneering integration sheds light on the intricate relationship between groundwater availability and drought susceptibility, furnishing invaluable insights for formulating targeted water resource management strategies. By amalgamating advanced computational techniques with geospatial analyses, this research contributes to a more comprehensive grasp of water resource dynamics within the context of escalating climate challenges. Consequently, it offers a foundation for informed decision-making and implementing sustainable water management practices in regions grappling with the dual challenges of groundwater scarcity and recurrent droughts.

Mapping groundwater potential zone in the subarnarekha basin, India, using a novel hybrid multi-criteria approach in Google earth Engine

Assessing groundwater potential for sustainable resource management is critically important. In addressing this concern, this study aims to advance the field by developing an innovative approach for Groundwater potential zone (GWPZ) mapping using advanced techniques, such as FuzzyAHP, FuzzyDEMATEL, and Logistic regression (LR) models. GWPZ was carried out by integrating various primary factors, such as hydrologic, soil permeability, morphometric, terrain distribution, and anthropogenic influences, incorporating twenty-seven individual criteria using multi-criteria decision models along with a hybrid approach for the Subarnarekha River basin, India, in Google earth engine (GEE). The predictive capability of the model was evaluated using a Multi-Collinearity test (VIF <10.0), followed by applying a random forest model, considering the weighted impact of the five primary factors. The hybrid model for GWPZ classification showed that 21.97 % (4256.3 km2) of the area exhibited very high potential, while 11.37 % (2202.1 km2) indicated very low potential for GW in this area. Validation of the groundwater level data from 72 observation wells, performed by the Area under receiver operating characteristic (AUROC) curve technique, yielded values ranging between 75 % and 78 % for different models, underscoring the robust predictability of GWPZ. The hybrid and LR-FuzzyAHP models demonstrated remarkable effectiveness in GWPZ mapping, indicating that the downstream and southern regions boast substantial groundwater potential attributed to alluvial soil and favorable recharge conditions. Conversely, the central part grapples with a scarcity of groundwater. It holds the potential to assist planners and managers in formulating strategies for managing groundwater levels and alleviating the impacts of future droughts.

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.

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.

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.

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.

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.

Unveiling groundwater potential zones as catalyst for multidimensional poverty reduction using analytical hierarchical process and geospatial decision support systems (S-DSS) approach in the semiarid region, Jigawa, Nigeria

Integrating agricultural production with the identification and use of groundwater resources has been shown to reduce multidimensional poverty in semi-arid regions. Poverty reduction and socioeconomic growth depend on sustainable water supply, especially in developing countries with limited rainy seasons. Poverty eradication is a top priority among the 17 Sustainable Development Goals (SDGs), and its reduction in the 21st century has led to significant advances in research. This study used remote sensing, geographic information system (GIS), and geospatial decision support system (S-DSS) approaches to uncover potential groundwater zones. The Analytic Hierarchy Process (AHP) integrates geospatial data to create a groundwater potential zone map and suggests the best land requirements for groundwater abstraction for poverty alleviation programs. The groundwater potential zone maps indicate that the majority of the region was in the high-potential zone, covering 59.75% of the total area, followed by a moderate-potential zone at 23.21%, an extremely high-potential zone at 14.6%, a low-potential zone at 2.44%, and an extremely low-potential zone at 0%. In addition, the study emphasizes the need for alternative water sources and infrastructure development in dry seasons in areas with fewer drainage systems and proposes measures such as rainwater harvesting structures and small reservoirs. Diversifying income sources by promoting alternative livelihoods can help reduce poverty and vulnerability to fluctuations in agricultural productivity. The integration of socioeconomic data into the S-DSS framework will provide a comprehensive understanding of the complex relationship between groundwater resources, poverty, and socioeconomic development, enabling informed decision-making in water resource management for poverty reduction initiatives and the achievement of the 2030 Agenda for Sustainable Development Goals.

A triangulation approach for groundwater potential evaluation using geospatial technology and multi-criteria decision analysis (MCDA) in Edo State, Nigeria

The quality and availability of groundwater resources are under extreme pressure as a result of growing urbanisation and population. The creation of lithological, structural, and geomorphological maps is made easier by satellite-based remote sensing data, notably at a regional level. This study uses the analytical hierarchical process (AHP) and geoinformatics-based approaches to facilitate and analyse different layers of geographically influencing data to define groundwater potential zones (GWPZ) in Edo State, Nigeria. The generated GWPZ map was created by selecting and weighting eleven precisely defined variables (including rainfall, lineament density, geomorphology, slopes, drainage density, soil type, landuse/landcover, proximity to surface water bodies, geology, a digital elevation model, and land surface temperature) based on their effect on groundwater availability. The zones of groundwater potential were developed using a GIS that incorporated the regulating variables. Depending on the degree of groundwater accessibility within each, this was grouped into four classifications (high, moderate, low, and very low). Low to moderate levels were seen across the study area, with high GWPZ representing 18% (3135.0294 km2) of the total area but only found in the Edo-central and isolated portions of the Edo-south. However, a very small fraction (3%) of very low GWPZ was found in the study's northern region. The exactitude of the established GWPZ map was determined to be 81.25% utilising well yield data (m3/d) from sixteen strategically selected boreholes in the study location, which were used to validate the GWPZ map. The research has shown that the criteria that have been observed are what govern the asymmetric distribution of these groundwater potential zones. The study will aid in the creation and governance of groundwater sources by improving recharge techniques, particularly in very low and low groundwater potential zones.