Lineament Density Research Articles

Strategic assessment of groundwater potential zones: a hybrid geospatial approach

Groundwater aquifers constitute the primary water supply for populations in arid regions, exemplified by the Goharkooh Plain in Iran's driest drainage basin, where conditions of high evapotranspiration and low precipitation prevail. With the escalating demand for water resources, driven mainly by agricultural expansion, the strategic management of groundwater assets has become increasingly critical. This study focuses on delineating groundwater potential zones (GWPZs) through an integrated approach combining multi-criteria decision analysis and geospatial tools. Based on an extensive literature review, nine thematic layers were selected and developed: lithology, geology, drainage density, slope gradient, elevation, vegetation cover, lineament density, land use, and precipitation. These criteria were initially weighted using the analytical hierarchical process (AHP) and subsequently integrated via weighted overlay analysis. In this research, the strategic selection of thematic layers for assessing groundwater potential in arid regions has been identified as an innovative approach that could significantly advance studies in similar settings. The analysis revealed that approximately 60% of the study area, primarily in the southwestern parts, exhibited moderate to very high groundwater potential. This potential is primarily attributed to the presence of alluvial deposits, low drainage density, and favorable slope and elevation conditions. Applying the receiver operating characteristic (ROC) curve yields an area under the curve (AUC) of 81.5%, indicating a relatively high level of predictive accuracy. These findings demonstrate the efficacy of this integrated approach, suggesting its broader applicability in regions with analogous groundwater challenges and management needs.

Characterization of problematic subsurface soils in Eha-Amufu using integrated investigation approach: implications for earth works

Mapping of the subsurface is a vital procedure during construction. It enhances hazard zonation, planning and protection of engineering structures. The present study centres on an area susceptible to foundation instability and building collapse in Enugu State, southeastern Nigeria. The study followed an integrated research method by employing a geotechnical approach and geophysical surveys such as electrical resistivity and remote sensing performed using Landsat, Aeromagnetic and shuttle radar topography mission (SRTM) images. Geotechnical data revealed that the subsurface comprised soils with higher fines (69%) than coarse (31%) grain sizes, high liquid limit (27–76%), plasticity index (9–46%), natural moisture content (6.0–14.8%) as well as low specific gravity (2.49–2.67) and coefficient of permeability (2.27 × 10–8–1.81 × 10–4 cm/s). Shear strength parameters- cohesion (13–35 kPa) and internal friction angle (9–21°) were low to moderate as well as the coefficient of consolidation (0.04–3.84 m2/mN) and coefficient of volume compressibility (0.05–0.29 m2/year). These properties are reminiscent of silty-clay soil of high plasticity and compressibility. The low soil resistivity with values ranging between 10 and 170 Ωm and aeromagnetic signal strength of 8.74 × 10–5 nT/km confirmed the silty-clay classification. The moderate to high lineament density determined from the remote sensing methods indicates the influx of moisture from higher surrounding grounds into the area to initiate high groundwater regime and flooding as observed in the fieldwork, which consequently triggers the activity of clay minerals present in the clay.

Exploring groundwater patterns in Souss-Massa Mountainous Basin, Morocco: A fusion of fractal analysis and machine learning techniques on gravity data

Groundwater potential in Morocco’s Souss-Massa mountainous basin (SMMB) is being identified using geospatial tools and geological data. We deployed four mathematical models, namely Data-Driven Multi-index Overlay (DMIO), Geometric Average (GA), Support Vector Machine (SVM), and Logistic Regression (LR), to establish data-driven patterns among the nine influencing factors, primarily drainage density, permeability, slope, distance to rivers, elevation, lineament density, distance to lineaments, intersection node density, and rainfall. Based on the Concentration-Area (C-A) fractal approach, the findings of the four models were developed and classified into five levels of potentiality ranging from very low to very high. The regions designated as having high and very high potentialities for the DMIO, GA, SVM, and LR models, respectively, account for 22.44 %, 9.80 %, 19.36 %, and 26.77 % of the overall basin. We validated the models by calculating each model's area under the ROC curve (AUC). The estimated AUC values are more than 70 %, suggesting the model performs well. The four models' performance was compared, revealing that the SVM model outperforms the others. Gravimetric data shows that possible groundwater zones closely coincide with gravimetric lineaments. The findings of this study can provide valuable insights to decision-makers, allowing them to improve decision-making processes and develop holistic groundwater resource management in the Souss-Massa mountainous basin (SMMB).

Securing water for arid regions: Rainwater harvesting and sustainable groundwater management using remote sensing and GIS techniques

Arid regions experience climatic stress under climate change: increased drought frequency coupled with intensified storm events. This disruption and lack of precipitation patterns leads to water scarcity and hinders the achievement of sustainable development goals. Egypt drainage basin exhibiting the greatest suitability for the implementation of rainwater harvesting (RWH) strategies. To facilitate the development of sustainable water resource management practices in the region, this study uses a multi-criteria methodology to delineate optimal zones for RWH within the Wadi Safaga. Integration of radar and optical remote sensing data obtained from Sentinel-1&2, Landsat-8, ALOS/PALSAR, and Sentinel-1 Interferometric SAR with climatic Tropical Rainfall Measuring Mission (TRMM), hydrological, and geological datasets emphasizes the hydrologic characteristics of the catchments. Additionally, the analysis of rainfall intensity patterns within the basin was undertaken. Thirteen factors are used in the predicted model including elevation, slope, curvature, depression, lithology, radar, InSAR CCD, drainage density (Dd), distance to river (DR), vegetation, topographic wetness index (TWI), rainfall, and lineament density. A knowledge-driven Geographic Information System (GIS) methodology, including weighted factors based on the Analytical Hierarchy Process (AHP), was implemented to delineate plausible areas for RWH and groundwater potential zones (GWPZs). The resultant map categorized the basin into five GWPZ classes: very low (14%), low (28%), moderate (27%), high (21%), and very high (10%). Furthermore, the study identified optimal locations for constructing reservoirs to store harvested rainwater and provide protection for downstream mining, industrial, and tourism activities. In conclusion, the obtained information is crucial for planners and decision-makers to implement sustainable water resource management strategies within the Wadi Safaga basin.

Mineralogy and rare earth elements spatial distribution in the carboniferous rocks of the eastern El Galala El Bahariya, Egypt

The Carboniferous rocks in the eastern part of El Galala El Bahariya were investigated using integrated field and laboratory techniques to determine their mineralogy, rare earth elements (REEs) distribution, and structural lineament density. The succession is mainly composed of argillaceous and minor arenaceous rocks, exhibiting variations in lithology across the study area. The essential minerals of these rocks are quartz, kaolinite, and illite. The accessory minerals include microcline, gypsum, anhydrite, halite, barite, hematite, pyrite, anatase and gibbsite, in addition to, the radioactive and REEs-bearing minerals such as uranophane, xenotime, monazite, and zircon. These minerals are reported in the rocks of the study area for the first time. The types, forms, habits, and modes of occurrence of the recorded minerals indicate multiple origins: allogenic–authigenic, and primary-secondary. REEs in the rocks exhibit enriched patterns with a negative Eu anomaly, likely due to low plagioclase content or and/or Eu removal by alteration processes. The distribution of REEs is influenced by textural attributes, with finer sediments in the southern part showing higher REEs content, ascribed to the high clay content and presence of gibbsite. The preferential mobility of LREEs is evident, explaining elevated LREEs/HREEs ratios in the rocks. Utilizing remote sensing techniques, lithological units and alteration zones were determined using decorrelation stretch and band ratio methods. The structural features, identified by Laplacian filter and edge enhancement, revealed the presence of NW–SE, N–S, and NE–SW faults that structurally regulate alteration zones and REEs distribution. These alteration zones are associated with clay minerals, REEs concentrations, and high lineament structure density. Spatial distribution maps highlight higher REEs concentrations in the southern part of the study area. These findings were validated using various analytical methods, including mineralogical and geochemical investigations, main component analysis, minimum noise fraction, decorrelation stretch, and spectral reflectance studies. They provide new insights into the REEs potential of the Carboniferous rocks and heighten our understanding of REEs genesis and distribution in the region.

Improving groundwater vulnerability assessment in structurally controlled hard rock aquifer: insight from lineament density and land use/land cover pattern.

A comprehensive seasonal assessment of groundwater vulnerability was conducted in the weathered hard rock aquifer of the upper Swarnrekha watershed in Ranchi district, India. Lineament density (Ld) and land use/land cover (LULC) were integrated into the conventional DRASTIC and Pesticide DRASTIC (P-DRASTIC) models and were extensively compared with six modified models, viz. DRASTIC-Ld, DRASTIC-Lu, DRASTIC-LdLu, P-DRASTIC-Ld, P-DRASTIC-Lu, and P-DRASTIC-LdLu, to identify the most optimal model for vulnerability mapping in hard rock terrain of the region. Findings were geochemically validated using NO3- concentrations of 68 wells during pre-monsoon (Pre-M) and post-monsoon (Post-M) 2022. Irrespective of the applied model, groundwater vulnerability shows significant seasonal variation, with > 45% of the region classified as high to very high vulnerability in the pre-M, increasing to ̴67% in post-M season, highlighting the importance of seasonal vulnerability assessments. Agriculture and industries' dominant southern region showed higher vulnerability, followed by regions with high Ld and thin weathered zone. Incorporating Ld and LULC parameters into DRASTIC-LdLu and P-DRASTIC-LdLu models increases the 'Very High' vulnerability zones to 17.4% and 17.6% for pre-M and 29.4% and 27.9% for post-M, respectively. Similarly, 'High' vulnerable zones increase from 32.5% and 25% in pre-M to 33.8% and 35.3% in post-M for respective models. Model output comparisons suggest that modified DRASTIC-LdLu and P-DRASTIC-LdLu perform better, with accurate estimations of 83.8% and 89.7% for pre-M and post-M, respectively. However, results of geochemical validation suggest that among all the applied modified models, DRASTIC-LdLu performs best, with accurate estimations of 34.4% and 20.6% for pre-M and post-M, respectively.

Groundwater Recharge Potential Index and artificial groundwater recharge in the alluvial soils of the middle Ganga Basin

Recent studies prove the faster depletion of groundwater is a cause of concern in the middle Ganga basin. Most of the groundwater-related studies in the middle Ganga basin deal with groundwater levels and quality aspects. The past studies on groundwater potential are confined to arid and humid zones of India, which leaves ample space for semi-humid to semi-arid, frost-prone, and alluvial region. The basin has alluvial soil due to sediments deposited by the river Ganga. In this study, eight thematic maps were prepared for the assessment of the groundwater recharge potential. These maps are; rainfall, geomorphology, slope, drainage density, lineament density, lithology, Land Use/Land Cover (LULC), and Groundwater Fluctuation (GWF). The weighted overlay of these thematic maps gave the Groundwater Recharge Potential Zone (GWRPZ) map representing the spatial variation of the Groundwater Recharge Potential Index (GWRPI) in the basin, whose value varies from 0.071 to 0.309. A total of 92 artificial groundwater recharge sites have been identified using specialized GIS processes taking into account stream network. The Analytic Hierarchy Process (AHP) based weights classification offers a robust framework for prioritizing and understanding the relative significance of factors affecting groundwater recharge. Alluvial soils are capable of holding large amount of water, and are overlaid by large aquifers. A large number of wells and tube wells have led to the over-extraction of groundwater in the region. This is the reason of the study being carried out despite being a region infested with large aquifers.

Leveraging Artificial Neural Networks for Robust Landslide Susceptibility Mapping: A Geospatial Modeling Approach in the Ecologically Sensitive Nilgiri District, Tamil Nadu

Landslides pose a significant threat to the lives and livelihoods of marginalised communities residing in rural areas and the delicate ecological balance of the environment. Implementing advanced technologies is crucial for improving hazard risk assessment and enhancing preparedness measures in regions characterised by diverse topography and complex geological formations. Geospatial applications and modelling techniques have emerged as indispensable in mitigating landslide risks, particularly in environmentally sensitive areas. This study presents a comprehensive approach to landslide susceptibility mapping in the Nilgiri District of Tamil Nadu, India, leveraging the power of Artificial Neural Networks (ANNs) and integrating multi-dimensional geospatial datasets. Integrating ANN-based modelling and geospatial techniques offers significant advantages in terms of statistical robustness, reproducibility, and the ability to analyse the complex interplay of factors influencing landslide hazards quantitatively. The methodology involves rigorous pre-processing and integrating spatial data, including landslide event occurrences as the dependent variable and ten independent parameters influencing landslide susceptibility. These parameters encompass elevation, slope aspect, slope degree, distance to roads, land use patterns, geomorphology, lithology, drainage density, lineament density, and rainfall distribution. Feature extraction and selection techniques are employed to effectively model the complex interactions between these factors and landslide occurrences. This process identifies the most relevant variables influencing landslide susceptibility, enhancing the model's predictive capabilities. The state-of-the-art ANNs are trained using historical landslide occurrence data and the selected influencing factors, enabling the development of a robust and accurate landslide susceptibility model. The performance of the developed model is rigorously evaluated using a comprehensive suite of metrics, including accuracy, precision, and the Area under the Receiver Operating Characteristic (ROC) curve. Preliminary results indicate that the ANN-based landslide susceptibility model outperforms traditional zonation methods, demonstrating higher accuracy and reliability in predicting landslide-prone areas. The resulting Landslide Susceptibility Map (LSM) categorises the study area into five distinct hazard zones, ranging from very high (664.1 km2), high (598.9 km2), moderate (639.7 km2), low (478.9 km2) and to very low (170.9 km2) . Notably, the eastern and central regions of the district emerge as particularly vulnerable to landslide occurrences. The study's findings have far-reaching implications for disaster risk reduction efforts, land-use planning, and sustainable development strategies in the ecologically sensitive Nilgiri District and beyond.

Delineation of the Groundwater Potential Zones using Integrated Geospatial Techniques and Multi-criteria Decision Approach in the Cretaceous Lower Benue and Niger Delta Basins of Abia State, Southern Nigeria

Delineation of the groundwater potential zones in the Cretaceous Lower Benue and Niger Delta basins of Abia state, Nigeria with geographic information system (GIS) / remote sensing (RS) multi-criteria decision approach (MCDA) considered the significant hydrogeomorphological factors affecting the availability of groundwater resources. The factors (geology, rainfall, slope, drainage density, lineament density, soil type, and land use land cover) were ranked using the analytical hierarchical process, a multi-criteria decision-making tool. The integration of the factors into a geographic information system (GIS) and weighted overlay analysis were then carried out using ArcGIS software. The result indicates 31.5% of zones of high to very high groundwater occurrence are in the southern section, and 41.6% of poor to very poor zones in the northern section. While the moderate zones make up the 26.8% of the study area. The study demonstrates that the groundwater occurrence in the study area is primarily controlled by the interactive impact of geology, rainfall, and slope factors, thus revealing the causes of the incessant random borehole failures in the moderate zones. Thus, the groundwater resources can be sustainably exploited, developed, and managed with the help of the map produced from the resulting demarcation of groundwater potential zones in the study.

Delineation of the Groundwater Potential Zones using Integrated Geospatial Techniques and Multi-criteria Decision Approach in the Cretaceous Lower Benue and Niger Delta Basins of Abia State, Southern Nigeria

Delineation of the groundwater potential zones in the Cretaceous Lower Benue and Niger Delta basins of Abia state, Nigeria with geographic information system (GIS) / remote sensing (RS) multi-criteria decision approach (MCDA) considered the significant hydrogeomorphological factors affecting the availability of groundwater resources. The factors (geology, rainfall, slope, drainage density, lineament density, soil type, and land use land cover) were ranked using the analytical hierarchical process, a multi-criteria decision-making tool. The integration of the factors into a geographic information system (GIS) and weighted overlay analysis were then carried out using ArcGIS software. The result indicates 31.5% of zones of high to very high groundwater occurrence are in the southern section, and 41.6% of poor to very poor zones in the northern section. While the moderate zones make up the 26.8% of the study area. The study demonstrates that the groundwater occurrence in the study area is primarily controlled by the interactive impact of geology, rainfall, and slope factors, thus revealing the causes of the incessant random borehole failures in the moderate zones. Thus, the groundwater resources can be sustainably exploited, developed, and managed with the help of the map produced from the resulting demarcation of groundwater potential zones in the study.

Integration of geospatial-based algorithms for groundwater potential characterization in Keiskamma Catchment of South Africa

Groundwater supports over 2.4 billion people across the globe and is critical to food security. The spatial dynamics of groundwater vary from place to place. The irregularity of groundwater resource exploitation is recognized in drought-prone areas, putting pressure on the resource. Hence, accurate groundwater potential characterization is critical for sustainable development and management of groundwater, particularly in drought-prone environments. Therefore, this study aimed at utilizing remote sensing satellite data and geospatial-based (analytical hierarchy process (AHP) and frequency ratio (FR)) algorithms to characterize groundwater potential zones (GWPZs) in the Keiskamma Catchment of South Africa. Seven (7) selected factors, including geology, soil type, slope, rainfall, drainage density, lineament density, and land use land cover, were assigned weights based on the AHP and FR algorithms. The validation results showed that the FR model performed better than the AHP, with the area under curve (AUC) accuracies of 62% and 50%, respectively. Based on the findings of this study, we infer that FR is more reliable than AHP when characterizing GWPZ. Lastly, GWPZ maps produced will be beneficial for improving efficient planning, management strategies, and decision-making.

Geographical Information System, Remote Sensing and Multi Influencing Factors Techniques for Delineation of Groundwater Potential Zones in District Charsadda, Khyber Pakhtunkhwa, Pakistan

The effective harvesting of groundwater and its sustainable management is possible with the proper identification of zones on its potential basis. For this purpose, geographical information system (GIS) and Remote Sensing (RS) data approaches were combined and used for the investigation, preservation, and evaluation of groundwater supply. This study aimed to assess groundwater delineation and availability-based potential of groundwater area in Charsadda District, KPK, Pakistan, by applying the approach of RS, GIS, and multi-influencing factors (MIF). For this purpose, digital elevation model (DEM), shuttle radar topographic mission (SRTM), and sentinel 2 satellite images were employed to produce numerous thematic layers, i.e., land use land cover (LULC), drainage density, lineament density, geology, slope soil, and rainfall as MIF in this study. After assigning a fixed score and weight to each thematic layer (MIF techniques), then an analyzed spatial layer was combined with a weighted overlay using ArcGIS software (ArcMap 10.5) and finally potential area for groundwater was defined. The obtained potential area of groundwater was categorized spatially as, very high, high, moderate, and low zones which depict most of the area is covered with moderate (547.66 km2) to high (306.7 Km2), as well as, high highest groundwater potential in 7 km2. The results of this study and the approach will be applicable and insightful for regional and extensive levels of developmental planning and harvesting of groundwater resources.

Modeling of groundwater productivity in the Alfred Nzo District, South Africa, using relative frequency ratio and Shannon entropy models

Study regionAlfred Nzo District, Eastern Cape Province, South Africa. Study focusThe study aimed to identify groundwater potential zones in the Alfred Nzo District using advanced geographic information systems and remote sensing applications by integrating relative frequency ratio (RF) with predictor rate and Shannon entropy (SE) models. Seven influential factors that are thought to control groundwater availability in the Alfred Nzo District were considered to identify groundwater potential zones. These factors are drainage density, lineament density, rainfall, slope, land use and land cover, lithology, and soil class. The factors were weighted in the RF and SE approaches. About 70 % of boreholes were used as training datasets, and 30 % were used for validation. Groundwater potential zones were delineated by integrating all these factors and their corresponding weights in ArcGIS software. The accuracy of each model was evaluated using receiver operating characteristic curve and area under curve techniques. New hydrological insights for the regionFive groundwater potential zones were found in the research area, which includes very poor, poor, moderate, good, and very good, by RF and SE models. The results of the models revealed that the SE model, with a success rate of 79.80 %, performed better than the RF, with a success rate of 75.10 %. The results of this research could be helpful in adequately managing groundwater resources in the research area.

Combination of remote sensing, GIS, AHP techniques and geophysical data to delineate groundwater potential zones in the Shiriya River Basin, South India

Shiriya River Basin (SRB) of Kasaragod district, Kerala, is one of the minor river basins that faces acute water shortage soon after the rainy season. Increasing the aquifer productivity of the SRB is the need of the hour. The present study is performed to determine the groundwater potential zones (GWPZ) of the SRB through Weighted Overlay Analysis. Different thematic layers (Geomorphology, Geology, Lineament density, Slope, Drainage density, LULC, and Soil) were prepared. Based on Saaty's scale, the rank and weightage assigned to each thematic layer and their respective features were standardized through the AHP techniques. Subsequently, GIS-based Weighted Overlay Analysis generated the ultimate GWPZ map, dividing SRB into 3 potential zones (poor, moderate, and good). To validate the GWPZ and understand the geoelectric characteristics of the SRB, 50 Schlumberger VES were performed and analyzed. Depth to water level data is also used to validate the GWPZ. The VES data indicated three distinct geoelectric layers, the topsoil, laterite, and weathered/fractured basement, overlying the resistive basement. In the SRB second layer (laterite) and, in some regions, the third layer (fractured charnockite) functions as an aquifer. The presence of groundwater potential region is indicated by resistivity values ranging from 50 to 200 ohm-m. The combination of surface and subsurface indicators of GWPZ will be much more reliable in locating the site for sustainable groundwater exploration and management of SRB groundwater resources.

GIS-based multi-criteria decision making for delineation of potential groundwater recharge zones for sustainable resource management in the Eastern Mediterranean: a case study

In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km2 (10.87%); low, 52.45 km2 (26.65%); moderate, 65.64 km2 (33.35%); high, 40.45 km2 (20.55%) and very high, 16.90 km2 (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.

GIS-based multi-criteria decision models for barite exploration in Nigeria’s Benue Trough

Spatial predictive mapping using geographic information system (GIS) is considered an invaluable tool for reconnaissance-scale exploration of mineral resources. In this study, geospatial data on geophysics, remote sensing, and structural and lithological attributes were systematically integrated to prospect barite potential zones within the Mid-Nigerian Benue Trough (MBT). Correlation attribute evaluation was used to establish the relationship between mineral deposit occurrences and geospatial data, while data integration was implemented using the Multi-Objective Optimization by Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Additive Ratio Assessment (ARAS) multi-criteria models. Here we show that the correlation attribute evaluation suggests that barite occurrences displayed a strong correlation with spatial data on lineament density, ferric iron alteration, and potassium to thorium (K/Th) ratio, whereas a weak correlation was observed with spatial data on the first vertical derivative (FVD), proximity to the host rock, and ferrous iron alteration. Here we report that the quantitative estimation of predictive models indicated that very high predictive zones for barite occurrences accounted for 19% of all the models. The accuracy assessment using Receiver Operating Characteristic (ROC)/Area Under the Curve (AUC) showed prediction levels above 78% for all models. The effectiveness of the spatial application of multi-criteria decision models makes them a reliable tool for barite exploration within the Mid-Nigerian Benue Trough (MBT) and other geologically similar environments.

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.

Spatial modelling of present and future groundwater potentials in Nigeria; towards a sustainable water demand and supply

The development of water resources in Nigeria has not risen alongside population increase. Although groundwater is the available source of water at all locations in Nigeria, groundwater aquifer is becoming deeper due to increased groundwater harvest, especially in urban areas. There is a need for continuous groundwater modelling using geological, climatic, environmental data, and spatial tools especially under climate change and intense landcover conversions. The Spatial Multi-Criteria Analysis (SMCA) was adopted in this study to model the current groundwater potential in Nigeria. The multi-criteria analysis tool in ArcGIS was explored to overlay the nine factor maps to model historic and futuristic groundwater potentials. Our groundwater factor maps show an interesting pattern across Nigeria, the southern parts show more potential considering suitability factors like; surface water density, rainfall, temperature, soil, land cover and elevation in the region. Whereas the upland regions even with higher rainfall and lower temperatures suitable for groundwater recharge, are disadvantaged by geomorphological factors. Northern part of Nigeria shows high potentials, considering the geology, soil, lineament density and slope, but disadvantaged by other factors like lower rainfall and higher temperatures. This informed the final groundwater potential maps; results for the historic potential revealed that, no location in Nigeria has optimal (9–10), very poor or no (1–2) groundwater potential. The results further revealed that areas with higher groundwater potentials are largely within the corridors of major rivers in Nigeria (Niger and Benue), covering about 17.6% of the Nigerian landmass, while 2.6%, 33.7, 44% and 2.2% are occupy areas with very low, low, moderate and very high groundwater potentials respectively. Further analysis highlighs locations of concern due to climatic and environmental changes. Interestingly, our groundwater projection results show a persistent increase in groundwater potential from 2021 to 2100 if current landuses and environmental factors are maintained, and if the projected increase in rainfall is true. Despite these groundwater potentials, the recent issues of shallow aquifers have been cautioned by scientists, especially due to groundwater uncertainties in Nigeria especially with intense landcover conversions, combined with accelerated water demands due to increase in population, and incessant groundwater extractions. Therefore, there is a need to seek caution in the pattern of unregulated and incessant groundwater harvest in Nigeria and we recommend frequent updates of the groundwater potential using geospatial tools to inform governing policies on a centralised consolidated sustainable water supply in Nigeria.

Use of remote sensing, spatial and geophysical modeling, and real recharging capabilities to identify suitable areas for groundwater exploitation in dry coastal areas

Accurate identification of groundwater potential areas in arid regions is an important task for groundwater management and sustainability. As a result, this study used the innovative integration of remote sensing (RS), geographic information system (GIS), watershed modeling system (WMS), geophysical survey, and water mass balance equation to identify potential groundwater areas in the W. Dara, Eastern Desert, Egypt. A weighted spatial probability model (WSPM) of groundwater potential based on eight regulatory factors was implemented within ArcGIS software. Drainage density (DD), precipitation (P), net groundwater recharge (NGR), terrain slope (TS), lineament density (LD), lithologic group (LG), water quality (TDS), and depth to groundwater level (DGW) are the aspects considered. The Analytical hierarchy process (AHP) method was used to assign weights to these parameters, and their accuracy was estimated using the consistency ratio (CR). The resulting groundwater potential map classified W. Dara study area into five categories, ranging from very low to very high potential. A geophysical survey, in the form of Vertical Electrical Sounding (VES) and Transient Electromagnetic (TEM), was conducted along W. Dara to validate the results of the WSPM, which identified areas of high groundwater potential. The 1D inversion of VES/TEM shows that the central and western parts of W. Dara are considered the most promising areas for groundwater occurrence, and are located in areas of high and very high potential classes derived from WSPM. Moreover, the results of VES and TEM surveys showed that the proposed aquifers (Nubian Sandstone, Miocene, and Quaternary) in the study area are horizontally and vertically connected through a set of normal faults traversing NW-SE. Ten sites have been proposed for drilling additional exploitative wells in W. Dara area based on the WSPM and geophysical survey with the aim of sustainable development. Thus, the integrated techniques applied in this study proved effective in accurately determining the development strategy for arid and semi-arid coastal areas, especially those that suffer from scarcity of rainfall and increased agricultural reclamation requirements in remote areas.

Contribution of GIS and remote sensing in evaluating groundwater potential zoning in Mbandjock

ABSTRACT Geographical information systems present today an undisputed advantage for the management of natural resources to facilitate their management. As a matter of fact, this study aims to evaluate the water potential in the water tables of Mbandjock using the multivariable analytical hierarchy process method applied on GIS. To do so, we first determined the different contributing variables: in this study, we use drainage density, rainfall distribution, soil geology, variation in slopes, soil type, land use, and lineament density. Once the different factors were mapped and reclassified, which led us to the second part of this work, where it was a question of overlaying these different variables by associating each variable with a weight value proportional to its importance in relation to other variables. This led to the production of a distribution map of groundwater potential.