Groundwater Potential Zones Research Articles

GIS-based delineation of potential recharge zones of groundwater and its validation with actual recharge in the Nangasai River Basin of Eastern India

GIS-based delineation of potential recharge zones of groundwater and its validation with actual recharge in the Nangasai River Basin of Eastern India

Assessment of groundwater potential zones using GIS-based multicriteria decision analysis: a case study on Enemor and Ener Woreda, Central Ethiopia Region

ABSTRACT Groundwater is one of the most important contributors to fresh water for humankind in the world. The knowledge of groundwater distribution can play a significant role in the planning and implementation of groundwater management strategies. The major aim of this study was to assess the groundwater potential zone using geographic information system (GIS)-based multicriteria decision analysis in the Enemor and Ener Woreda, Ethiopia. The factors considered in this study are rainfall, geology, slope, drainage density, land use/land cover (LULC), lineament density, and soil type. As a result of the analytic hierarchy process (AHP), it was determined that rainfall and geology are the most influencing factors based on their scoring higher weights. The groundwater potential zone of the study area was categorized into five classes, namely, very low, low, moderate, high, and very high. On analysis, most portions of the study area are found to be under the moderate situation, which covers around 540.23 km2 (65.6%) of the study area, whereas very low, low, high, and very high potentiality classes cover 0.002, 10.99, 21.93, and 0.55% of the area, respectively. Approximately 92% of the observed boreholes agreed with the developed map. Finally, the output of this study is important to regional as well as local policymakers for the exploitation of groundwater or management purposes.

Integrating remote sensing, GIS-based, and AHP techniques to delineate groundwater potential zones in the Moulouya Basin, North-East Morocco

Groundwater is a valuable shared resource in the Moulouya Basin, but it has been in decline due to recent years of low rainfall and rapid population growth. To support socio-economic development, there is increased demand for this precious resource. This paper presents a standard methodology for delimiting potential groundwater zones using geographic information systems (GIS), an integrated analytical hierarchy process (AHP), and remote sensing techniques. Seven parameters that monitor the presence and mobility of groundwater, including drainage density, lithology, slope, precipitation, land use/land cover, distance to river, and lineament density, were incorporated into a raster data model using ArcGIS software. AHP-based expert knowledge was used to prepare a groundwater potential index and assign weights to the thematic layers. The study classified the area into five zones of varying groundwater potential: very high (26%), high (51%), moderate (13%), poor (9%), and very poor (1%). The accuracy of the model was validated by comparing the Groundwater Potential Zones map with data from 96 wells and boreholes across the basin. The validity of the results was confirmed by comparing them with the specific yield of the aquifer in the study area, yielding a high correlation coefficient (R2) of 0.79. The analysis revealed that 89.5% of the boreholes were situated in the high and very high potential zones, demonstrating the reliability and robustness of the employed approach. These findings can aid decision-making and planning for sustainable groundwater use in the water-stressed region.

GIS-based groundwater potential zonation and assessment of groundwater quality and suitability for drinking and irrigation purposes in the Shanmughanadhi river basin, south India

To develop a specific watershed scenario, the quantity and quality of groundwater resources must be assessed and monitored locally. In the present study, an attempt has been made to identify possible groundwater potential zones, determine the quality of groundwater resources in this region, and evaluate their suitability for drinking and irrigation purposes. This goal has been achieved with the combined use of the weighted index overlay analysis (WIOA), groundwater quality index (GWQI), Remote Sensing (RS), and Geographic Information System (GIS) techniques. The proposed study area, Shanmuganadhi, is marked with superior rainfall, oscillating temperature, and runoff with litho-units encompassing charnockite (CHK) and hornblende biotite gneiss (HBG). Over-abstraction of groundwater and intensive agricultural practices have resulted in declining and degrading water quantity and quality in this area. The resulting integrated thematic map has been classified into five groundwater potential zones, namely poor, low, moderate, high, and very high, covering 3.2, 45.49, 15.3, 27.9, and 8.1% area, respectively. Sixty groundwater samples were collected during the pre-monsoon (PRM) and analyzed for major Physico-chemical parameters. From the water quality index assessment, over 28.0% of the samples fall within the “excellent,” 8.0% “good” and 4.0% “poor” in CHK, followed by 5.71% “excellent,” 48.57% “good,” 37.14% “poor,” 5.71% “very poor” and 2.87% “unsuitable” for drinking purposes in HBG terrain of this region. Irrigation indices also demonstrated that most of the groundwater samples in the CHK and HBG exposed zones exhibited good classes for irrigation purposes, as evidenced by the SAR and %Na+. The outcome, which shows the research area's groundwater potential zones, is beneficial for improved groundwater resource planning and management. It is concluded that for larger-scale groundwater-quality investigation and assessment, the groundwater quality index-making approach (GWQI) is more practical and dependable. Water planners and decision-makers may find it helpful in effectively controlling and monitoring groundwater quality at the basin or watershed scale. Reducing urban land use and natural runoff from farms can help prevent water contamination in some regions. To ensure the safe use of groundwater, long-term monitoring of these groundwater was suggested.

Identification of groundwater potential zones of Alappuzha (Kerala) in South India integrating AHP and GIS

Identification of groundwater potential zones of Alappuzha (Kerala) in South India integrating AHP and GIS

Future groundwater potential mapping using machine learning algorithms and climate change scenarios in Bangladesh

The aim of the study was to estimate future groundwater potential zones based on machine learning algorithms and climate change scenarios. Fourteen parameters (i.e., curvature, drainage density, slope, roughness, rainfall, temperature, relative humidity, lineament density, land use and land cover, general soil types, geology, geomorphology, topographic position index (TPI), topographic wetness index (TWI)) were used in developing machine learning algorithms. Three machine learning algorithms (i.e., artificial neural network (ANN), logistic model tree (LMT), and logistic regression (LR)) were applied to identify groundwater potential zones. The best-fit model was selected based on the ROC curve. Representative concentration pathways (RCP) of 2.5, 4.5, 6.0, and 8.5 climate scenarios of precipitation were used for modeling future climate change. Finally, future groundwater potential zones were identified for 2025, 2030, 2035, and 2040 based on the best machine learning model and future RCP models. According to findings, ANN shows better accuracy than the other two models (AUC: 0.875). The ANN model predicted that 23.10 percent of the land was in very high groundwater potential zones, whereas 33.50 percent was in extremely high groundwater potential zones. The study forecasts precipitation values under different climate change scenarios (RCP2.6, RCP4.5, RCP6, and RCP8.5) for 2025, 2030, 2035, and 2040 using an ANN model and shows spatial distribution maps for each scenario. Finally, sixteen scenarios were generated for future groundwater potential zones. Government officials may utilize the study’s results to inform evidence-based choices on water management and planning at the national level.

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 recharge potential zone modeling in the Wadi Al-Lith Basin, Saudi Arabia

The management of groundwater resources is crucial in arid and semi-arid regions such as Al-Lith Basin, and therefore, the identification of suitable areas for groundwater recharge is important in solving the problem of water scarcity and ensuring the long-term sustainability of aquifers. In this study, the Analytic Hierarchy Process (AHP) technique, in conjunction with GIS, was applied to locate potential zones for groundwater recharge in the Al-Lith basin. The research methodology includes collecting the essential data, including lineament density, slope, rainfall, drainage density, LU/LC, soil, elevation, and TWI. AHP is used to assign relative weights to different qualities, considering their significance in influencing groundwater recharge. The ArcGIS was employed to process and analyze the weighted layers, which resulted in the creation of a comprehensive map illustrating the potential for groundwater recharge. The study results suggested that the Al-Lith Subbasin has several zones that exhibit different levels of groundwater recharge capability. The results obtained from this study indicated that 12.83% of the basin area has significant groundwater recharge potential zones (GWPZ), ranging from high to very high levels. The groundwater recharge potential zones in the basin are categorized as very poor to poor, covering 19.4% of the area, while the moderate groundwater recharge potential zones represent 67.77% of the basin area. The groundwater protection zones were validated using 19 wells distributed across the basin. The validation findings indicate there is an overlap between the GWPZ classes and the wells in the specified location. Overall, the findings of this study can enhance groundwater resource management and inform policy development for targeted interventions aimed at enhancing groundwater recharge.

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.

Geospatial Assessment of Potential Groundwater Zones Within Igede Ekiti, Ekiti State, Nigeria

Groundwater happens to be an accessible and renewable source of water, and so has to be monitored. A Multi-criteria Decision approach was utilized which allows for data fusion of various thematic criteria using the Analytical Hierarchical approach to assign weight to the selected criteria peculiar to Igede-Ekiti, of Irepodun/Ifelodun Local Government Area. The study aims to carry out a geospatial assessment of the groundwater potential zone within Igede Ekiti, Ekiti state. Geology, Rainfall, Digital Elevation Model, Land Use land cover, Nominal difference in water Index (NDWI), Slope and Lineament density were selected to depict the potential groundwater zones, of which geospatial assessments were carried out. Selected groundwater sources in the form of boreholes and well were afterwards used to ground truth and depict the distribution of groundwater sources within the study area. The ArcMap software’s weight overlay Analysis was used to present the output in the form of a Potential Groundwater zones (PGWZ) map, with the Groundwater sources, wells and boreholes, indicating that they were well dispersed within the study area, but more densely situated around the built-up class of the study area. The results indicate that high PGWZ was more prevalent than the other classes, as the classes were distributed into very high, high and low PGWZ. The very high PGWZ covered 7%, the high PGWZ 55% and the Low PGWZ, 38%. The study can be used for further physical planning and decision-making for policymakers. Further research into the Spatio-temporal behaviour of groundwater potential is recommended.

Remote sensing and geospatial approach: Optimizing groundwater exploration in semi-arid region, Nepal

Groundwater is the fundamental component of the hydrological system that acts as a major factor in comprehensions of the physical processes in both the land surface and the atmosphere. Determining groundwater, which directly affects the agricultural productivity of semi-arid mountainous regions, is crucial. Mountain ecosystems, once abundant with flowing water, now face immense pressure from a changing climate, evident in the drying of springs and the diminishing flow of groundwater. Ensuring a steady flow of water, fair access to it, and responsible use are the cornerstones of a secure future for mountain communities. This study aims to assess the groundwater potential zones using remote sensing and a geospatial approach in the Mustang Valley's rural municipalities (Thasang and Gharapjhong). Nine factors were assigned to assess the groundwater potential map: slope, drainage density, lineament density, geology, soil, land use/land cover, rainfall, aspect, and soil moisture. The Bayesian weights of evidence model was used to delineate the groundwater potential zone. The study categorized groundwater potential across the region, creating five zones: very high, high, moderate, low, and very low. These zones covered 0.6 %, 12.4 %, 51.2 %, 35.5 %, and 0.3 % of the study area. The accuracy of the groundwater potential map was assessed by comparing its predictions with the actual locations of springs, using the area under the curve metric. The receiver operating characteristics curve analysis yielded an area under the curve of 0.7226, indicating a 72.26 % accuracy in predicting the presence of groundwater. The findings of this paper contribute to a better understanding of groundwater potential zones, which can support policymakers and planners for hydrological, meteorological, and crop planning applications in this climatically vulnerable region.

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.

Appraisal of lacustrine aquifer’s groundwater potentiality and its hydrogeological modelling in southeastern Peshawar, Pakistan: implications for environmental geology, and geotechnical engineering

The Peshawar Basin is a part of the lower Himalayas that contains an enormous amount of groundwater storage. The evaluation of groundwater potential in the southern Peshawar district was done using well logging, lithostratigraphic properties, and combined hydrogeological and geophysical techniques. A total of 13 Vertical Electrical Sounding (VES) profiles were utilised to assess potential groundwater zones for surface resistivity studies. The aquifer system was delineated by comparing the data from five boreholes with the VES findings. An exploration of super-saturated groundwater potential was conducted, utilising parameters such as transmissivity (T), hydraulic conductivity (K), storativity, and the Dar Zarrouk analysis. The Dar Zarrouk analysis yielded average values of transverse resistance (TR), longitudinal conductance (S), and anisotropy (λ), which were determined to be 8069.12, 0.51, and 0.561, respectively. Similarly, average values of transmissivity (T), hydraulic conductivity (K), and storativity were obtained, resulting in 28.67, 0.24, and 0.000177, respectively. The saturated confined layer, characterized by highly saturated zones, was identified to begin at a depth of approximately 119 m and extend down to the lower boundary of the aquifer. The examined aquifer is composed of clay, sand, gravel, boulders, and loose layers of lacustrine mud that are interlayered to form an unconsolidated groundwater aquifer system. The aquifers in the region are highly developed and consisted of unconfined, semi-confined, and confined aquifer systems. As a result, it is possible to use the aquifer for groundwater development in the study area because of its low -to-medium discharge.

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.

PROTECTIVE CAPACITY ASSESSMENT OF A SHALLOW AQUIFERAT THE EASTERN PART OF ADO-EKITI, SOUTHWESTERN NIGERIA

Vertical Electrical Soundings (VES) survey has been undertaken at the eastern part of Ado-Ekiti, southwestern Nigeria to assessthe aquifer protective capacity of the overburden units of the area. The Schlumberger electrode array was adopted with a maximumcurrent electrode spread (AB) of 300 m.Thirty-six(36) VES points wasoccupied and processed through a partial curve matching technique and 1-D forward modelingcomputer-assistedsoftware.The interpretation revealed H, A, KH and HA-type curves and threemajor geoelectric layers overlying the resistive basement. The groundwater potential and overburden protective capacity maps were prepared. The groundwater in the area was categorized into high, medium and low groundwater potential zones. About 80% of thestudy area falls within the moderate/low groundwater potential zone while the remaining 20% constituted the high groundwater potential zone (Agric Olope area). Hence, thegroundwater potential rating of other areas is considered to be low. The values of longitudinal conductance (ranging from 0.01 to 2.01 mhos) of the area enabled the overburden units to be rated into good, moderate and weakprotective capacity. About 75% of the area falls within the good/moderate rating while 25% constitutes the weak/poorprotective capacity rating (Agric Olope area), suggesting that the groundwater around Agric Olope isvulnerable to contamination.

Groundwater Potential Zone Assessment Using Remote Sensing, Geographical Information System (GIS), and Analytical Hierarchy Process (AHP) Techniques in Fogera Woreda, South Gondar Zone, Ethiopia

The study was conducted to know the groundwater potential zones in Fogera Woreda, south Gondar zone, Ethiopia. Through the utilization of the analytical hierarchy process (AHP), remote sensing, and geographic information system (GIS), the study identified groundwater potential zones. Ten thematic layers were analyzed to delineate the groundwater potential zones, including land use and land cover (LULC), topographic wetness index (TWI), drainage density, lineament density, geology, slope, rainfall, elevation, and soil texture. By determining the relative importance of each thematic layer through AHP and combining all thematic layers through overlay analysis in a GIS environment, the study revealed a spatial variation in the distribution of groundwater potential zones. The results showed that excellent groundwater potentials cover 2.02% of the study area, moderate groundwater potentials cover 45.54%, poor groundwater potentials cover 51.2%, and extremely poor groundwater potentials cover 1.24% of the study area. The study provides valuable information that can be used for decision-making processes and the development of appropriate groundwater management strategies in the region.

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.

Groundwater Potency Analysis Using Remote Sensing and Analytical Hierarchy Process To Overcome Drought In Rembang Regency, Indonesia

Water is an indispensable need for all living beings, including humans, who require this vital resource for consumption, bathing, and agricultural irrigation. One of the sources of clean water is groundwater, which meets 80% of the drinking needs. However, only 82.1% of the population in Central Java has access to clean water, while the remaining 17.9% have limited accessibility. This condition was caused by the prevalence of droughts, particularly in Rembang Regency, indicating that several efforts are needed to overcome this problem. Therefore, this study aims to analyze the groundwater potential in Rembang Regency using remote sensing and Analytical Hierarchy Process (AHP) methods. The remote sensing technique was used to determine the lithology, hydrogeology, lineament density, slope, rainfall, vegetation cover, and land use of the area, while the AHP method was utilized to assess groundwater potential. The results showed that the hydrogeology parameter had the greatest influence with a weight of 21.8%, followed by lithology (15.8%), rainfall (15.1%), vegetation cover (13.5%), land use (10.9%), lineament density (14%), and slope (9.4%). These findings were then validated with existing points of interest, including dug wells, deep wells, and reservoirs. The analysis results showed that the study area can be divided into 4 zones based on the groundwater potential, namely very low (1.2 – 2.24), low (2.24 – 3.48), moderate (3.48 – 4.72), and high (4.72 – 5.96) with areas of 0.19 km2, 234.8 km2,173.4 km2, and 51.9 km2, respectively. Furthermore, based on the validation, 90 out of 108 (83%) interest points were in line with the groundwater potential map zones.

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.