{"paper_id":"4892da39-fbec-4e6d-bc0e-e171bbf60e7a","body_text":"Evaluation of Groundwater Resources Using Remote Sensing and Gis Techniques Within Kwara State University, Malete, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of Groundwater Resources Using Remote Sensing and Gis Techniques Within Kwara State University, Malete, Nigeria Jimoh Ajadi, Mosunrat Yusuf, Gabriel Efomeh Omolaiye, Sodiq Bamidele Adam, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6458804/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract This study combined remote sensing and GIS techniques to evaluate the groundwater potential zones at Kwara State University (KWASU) by assessing groundwater resources using the Analytical Hierarchy Process (AHP). This involved integrating and overlaying thematic layers through the weight overlay analysis tool to assign weights and rank these layers based on their characteristics or influence on groundwater potential and recharge within the institution. The thematic layers used included rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament, and lineament density, all significantly impacting groundwater distribution. The results revealed that Kwara State University is situated in an area with higher rainfall of approximately 1430 mm, a flat-gentle slope gradient, and an elevation of less than 300 m, with land use/land cover comprising crops, trees, and rangeland, alongside a dendritic drainage network pattern, very good to good drainage density, and low lineament density. The Analytical Hierarchy Process evaluated and categorised Kwara State University as an excellent to good groundwater potential zone, indicating that the delineation of groundwater resources is reliable. This study provides insights for future groundwater management planning and further recommends fieldwork studies to achieve detailed groundwater potential mapping within Kwara State University. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Highlights Kwara State University is located within a region with annual rainfall of 1430mm, a flat-gentle slope gradient, elevation of less than 300m, comprising crops, trees, built-up and rangeland, dendritic drainage network pattern, very good drainage density and low lineament density. KWASU area has excellent-good groundwater potential zones and geophysical field studies are recommended for accurate groundwater potential mapping. 1.0 Introduction Groundwater represents a significant resource for socio-economic development, particularly in regions where surface water availability is erratic and insufficient [1, 2]. It is vital in all parts of the world as it is essential for both human and industrial use [3 - 6]. However, rapid population growth, industrialization, agricultural expansion, and climate variability have increased pressure on groundwater resources, necessitating systematic exploration and sustainable management strategies [7 - 10]. Kwara State University (KWASU), located in Nigeria’s North Central region, relies primarily on groundwater to satisfy its institutional and community needs. In understanding the groundwater resource within the region, the lack of a spatially explicit groundwater potential map hinders efficient resource allocation and long-term planning. Over the years, Remote Sensing and Geographic Information Systems (GIS) have emerged as powerful tools in groundwater studies, providing spatially distributed data that enhances the accuracy and efficiency of hydrogeological investigations [1, 11, 12]. These techniques offer significant advantages over conventional hydrogeological methods by enabling rapid assessment, cost-effectiveness, and large-scale mapping of groundwater potential zones [13]. Thus, the integration of Remote Sensing and Geographic Information Systems serves as a means to combine multiple datasets, including geological, hydrological, and topographical information, to delineate groundwater potential zones with high precision [3, 14 - 16]. Kwara State University (KWASU) is situated in a region experiencing increasing water demand due to the growing population of its students and urban expansion. Although limited studies have been conducted to assess the groundwater potential in this area using modern geospatial techniques, traditional methods of groundwater exploration, such as drilling and geophysical surveys, are often time-consuming, expensive, and spatially restricted [17 - 19]. Therefore, using RS and GIS techniques for hydrogeological mapping provides a cost-effective and systematic way to identify and evaluate groundwater potential zones, which is essential for understanding the hydrogeological characteristics of KWASU and its surroundings, thereby supporting sustainable water resource planning and management. Furthermore, it is crucial to recognise that several factors influence groundwater potential, including lithology, lineament density, drainage patterns, slope, soil type, land use/land cover (LULC), and rainfall distribution [11, 13, 20, 21]. By analysing these factors, remote sensing and GIS data can define groundwater potential zones and assess aquifer characteristics with greater precision [18, 22, 23]. Additionally, this approach not only improves the accuracy of groundwater resource evaluation but also facilitates informed decision-making for sustainable water resource management, which is vital for addressing water supply challenges and ensuring the long-term sustainability of available resources [7, 14, 16, 24 - 26]. The outcomes of this research have significant implications for sustainable water resource management in KWASU and its surrounding areas. By evaluating groundwater resources, this study aims to generate essential thematic maps to analyse and assess groundwater availability. It will also provide actionable insights for optimizing borehole siting, reducing infrastructure costs, and mitigating risks associated with groundwater overexploitation. The findings will contribute to the broader field of hydrogeology by demonstrating the effectiveness of remote sensing and GIS in groundwater assessment and management. Ultimately, this research will support informed decision-making for water resource development in KWASU and similar regions facing challenges related to water scarcity. 2.0 Description and Geology of Study Area Kwara State University (KWASU) is a public institution established in 2009, located in Malete, Moro Local Government Area, Kwara State, Nigeria, serving as a hub for academic excellence and research. The university lies between latitude [8.704445; 8.684772; 8.723889; 8.743056]° N and longitude [4.451389; 4.493333; 4.510556; 4.470278]° E within a semi-urban area characterized by a mix of residential, agricultural, and academic land use, featuring a tropical climate marked by distinct wet and dry seasons. Figure 1 shows the map of Kwara State University within Nigeria, and Figure 2 presents the geological map of Kwara State University within Malete and its environment. The terrain is generally undulating, with gentle slopes and isolated hills that influence drainage patterns. The rainy season in Kwara State University and its surroundings begins at the end of March and spans until early September, while the dry season lasts from October to early March, with temperatures fluctuating between 25 °C and 30 °C during the wet season [27]. The dry season temperature ranges from 33 °C to 34 o C, experiencing intense heat during the dry months, while annual rainfall ranges from 1000 mm to 1500 mm in Kwara State [27, 28]. KWASU lies within the Basement Complex of southwestern Nigeria, primarily composed of Precambrian crystalline rocks, and it is underlain by lithological units such as migmatitic gneiss, porphyritic granite and quartzite [29, 30]. The rocks in the study area reflect significant geological events linked to the Liberian, Eburnean and Pan-African orogenies, occurring approximately 2500 Ma, 2000 Ma, and 500 Ma, respectively, and are associated with the formation of migmatites, quartzites and Pan-African granites [31, 32]. The Groundwater occurrence in this region is controlled by weathering and fracturing, with aquifers developing in secondary porosities created by these processes. The part of the research area exhibits good aquifer characteristics, particularly within the quartzitic layers, indicating potential for groundwater resources [30]. The weathered overburden varies in thickness, typically between a few meters and over 20 meters, influencing groundwater accumulation and movement. Understanding the geological and structural framework of KWASU is important for effective groundwater exploration and sustainable management. 3.0 Materials Used and Methodology 3.1 Material Used Figure 3 shows a process chart for the research approach employed in this study. The materials utilized include high-resolution Landsat 8 satellite imagery for land use/land cover (LULC) mapping, as well as Shuttle Radar Topography Mission (SRTM) digital elevation models (DEMs) to extract elevation, slope, and drainage patterns. The Landsat imagery and SRTM DEM were acquired from the United States Geological Survey (USGS) website (http://www.earthexplorer.usgs.gov/). Specialized software such as ArcGIS facilitates the spatial analysis and integration of these diverse datasets. 3.2 Methodology This study integrates remote sensing and GIS techniques to evaluate groundwater resources at Kwara State University, Malete. The methodology is structured around a multi-criteria decision analysis framework, employing the Analytical Hierarchy Process (AHP) to assign weights to various hydrogeological factors such as rainfall, lineament and lineament density, drainage network and drainage density, slope, elevation, and land use/land cover. The process begins with data acquisition and preprocessing, followed by the generation of thematic layers that represent each groundwater controlling factor, as shown in Figure 3. 3.2.1 Analytical Hierarchy Process (AHP) The Analytical Hierarchy Process (AHP) is employed as a multi-criteria decision analysis technique to systematically assign weights to various thematic layers based on their influence on groundwater potential [49, 50]. A pairwise comparison matrix is constructed, and consistency ratio calculations are performed to ensure logical consistency in weight assignments. The weighted overlay method in GIS is then used to integrate the ranked factors such as lineament density, slope, LULC, rainfall and drainage density into a composite groundwater potential map as indicated using equation 1 below [33 - 35]. The AHP approach enhances the objectivity and reliability of groundwater potential zone evaluation and delineation, which provide a robust framework for decision-making in sustainable groundwater resource management [2]. These layers are then integrated using weighted overlay analysis within the GIS environment to produce a comprehensive groundwater potential map, in which findings are presented in a detailed spatial delineation of high, moderate and low groundwater potential zones within Kwara State University. In addition, the groundwater potential index (GWPI) was estimated from the integration of the total normalized weights for the layers using Equation 1. 𝐺𝑊𝑃𝐼 = 𝐴𝑅𝑤𝐴𝑅𝑤𝑖 + 𝐿𝑈𝐿𝐶𝑤𝐿𝑈𝐿𝐶𝑤𝑖 + 𝑆𝑤𝑆𝑤𝑖 + E𝑤E𝑤𝑖 + 𝐷𝑤𝐷𝑤𝑖 + 𝐷𝑑𝑤𝐷𝑑𝑤𝑖 + 𝐿𝑤𝐿𝑤𝑖 + 𝐿d𝑤𝐿d𝑤𝑖 - Eqn. 1 In which are represented as Annual rainfall (AR), Land Use/Land Cover (LULC), Slope (S), Elevation (E), Drainage Network (D), Drainage Density (Dd), Lineament (L), Lineament density (Ld), and w is the normalized weight of the thematic layer; and wi is the normalized weight of sub-layer classes that is used in evaluation of the groundwater potential zones. 4.0 Results and Discussion 4.1 Results Analysis 4.1.1 Rainfall Rainfall is the primary source of groundwater recharge and is essential in the delineation of groundwater potential zones [36, 37]. (Rahman et al., 2022; Sresto et al., 2021). The spatial and temporal distribution of rainfall is analysed using meteorological data obtained from weather stations and satellite-derived precipitation datasets (TRMM and local gauge data of 2021). A rainfall distribution map is generated in GIS to assess variations across the study area, as shown in Fig. 4. Regions receiving higher rainfall are more likely to have greater groundwater recharge potential, especially when combined with favourable geomorphological and soil conditions [37, 38]. This parameter is integrated with other thematic layers to refine the groundwater potential assessment. As shown in Fig. 4, the average annual rainfall around the study area ranges from 1318mm to 1430mm and this is classified as a high variation of rainfall region. Based on the maximum and minimum values, the rainfall map is classified into low, moderate and high, in which Kwara State University is located within a higher rainfall potential of approximately 1430 mm, which serves as a good indicator of potential area for groundwater . 4.1.2 Land Use/Land Cover (LULC ) Land use and land cover play a significant role in groundwater recharge and its impact on the hydrological cycle directly by affecting surface permeability, runoff and evaporation rates [39, 40]. LULC classification is carried out using remote sensing data, which is analysed in GIS to categorize different land cover types such as forests, agricultural lands, built-up areas, and water bodies. Vegetated and agricultural areas generally enhance infiltration and groundwater recharge, whereas impervious surfaces like urban settlements reduce percolation and increase runoff [36]. Integrating LULC analysis helps in assessing the impact of anthropogenic activities on groundwater availability and potential. The land-use/land-cover (LULC) map of KWASU is characterized into five classes: water bodies, trees, built-up, crop and rangeland (Fig. 5). The research area is located within the classes of crops, trees, built-up and rangeland, with no indication of water bodies; this limits the distribution of water body reservoirs over the study area. However, as Land Use/Land Cover is the essential factor that controls groundwater infiltration, runoff and recharge, KWASU indicate moderate weightage due to the presence of trees and crops, which help in reducing the speed of water flow and increase the rate of infiltration . 4.1.3 Elevation and Slope Slope is a critical topographical parameter influencing surface runoff and groundwater recharge. Steep slopes promote surface runoff, reducing the opportunity for infiltration, whereas gentle slopes favour water percolation and recharge [41]. The slope map was generated using a DEM in GIS, where the gradient of the terrain is classified into various categories. Areas with lower slopes are considered more favourable for groundwater accumulation [41]. The spatial analysis of slope in relation to other hydrogeological factors aids in refining the groundwater potential zones within the study area. The elevation and slope of a location are thought to be regulating elements that influence the amount of erosion and weathering processes inside it. Fig. 6 depicts elevation levels ranging from 100 m to 400 m, with Kwara State University's elevation level of 300 m indicating a reasonable rate of groundwater potential . Moreover, the degree of slope as shown in Figure 7 is grouped into flat, gentle, moderate, steep and very steep. As a gentle slope is classified as “good” for groundwater recharge and flat terrain is of most favourable for infiltration, KWASU is located within the group of flat and gentle slope, which indicate potential for a high level of groundwater, as there will be a very low level of runoff . The combination of elevation and slope map analysis shows a moderate weight of groundwater potential. 4.1.4 Drainage Network and Drainage Density Drainage density is defined as the total length of streams per unit area that is an important hydrological parameter that affects groundwater recharge [42]. Areas with low drainage density are often associated with high infiltration rates and good groundwater potential, whereas high drainage density areas indicate increased surface runoff and lower recharge capabilities [43]. A drainage network map is extracted from the DEM using GIS-based hydrological analysis tools. By overlaying drainage density maps with other hydrogeological parameters, more precise groundwater potential zones are identified. Drainage network and drainage density are part of the influencing factors that evaluate the potential of groundwater. Figure 8 represents the drainage network of the dendritic drainage pattern within the study area, whereas Figure 9 exhibits drainage densities ranging from 8.59 to 266 km/km2. The drainage density of an area is an essential component that indicates runoff characteristics, water infiltration, and groundwater rechargeability, all of which are related to the permeability of the prevailing land cover. As shown in Figure 9, the drainage density was grouped into very good (8.59 – 61 km/km 2 ), good (61.1 – 95.3 km/km 2 ), moderate (95.4 - 133 km/km 2 ), poor (134 - 175 km/km 2 ) and very poor (176 - 266 km/km 2 ) density. However, KWASU is located within a Drainage density ranging between very good to good drainage density of 8.59 to 95.3 km/km 2 , which shows support for higher groundwater potential due to higher permeability and water infiltration to the aquifers . 4.1.5 Lineament and Lineament Density Lineaments are linear features in the Earth's crust often associated with geological structures such as faults and fractures that enhance groundwater movement [44]. The density of lineaments in an area is directly proportional to its groundwater potential, as fractures and fault zones facilitate subsurface water storage and movement [45, 46]. Remote sensing techniques are employed to extract lineament features, and GIS tools are used to compute lineament density maps. High lineament density areas indicate zones of increased groundwater infiltration, making them significant in groundwater potential mapping [44]. These features are further validated with field observations and geological assessments. Lineament depicts structural zones of fault and fracture that functioned as secondary porosity and permeability to groundwater. Figure 10 presents the lineament map, which highlights potential fault and fracture lines. Figure 11 shows lineament density classified into five categories: very low (0 - 0.181 km/km 2 ), low (0.182 - 0.306 km/km 2 ), moderate (0.397 - 0.435 km/km 2 ), high (0.436 - 0.593 km /km2) and very high (0.594 - 0.964 km/km 2 ). Lineament density contributes to the formation of groundwater. The research area is sited in a low to moderate lineament density zone, ranging from 0 – 0.435 km/km 2 , with low lineament density areas typifying a lower groundwater potential. 4.1.6 Analysis of Groundwater Potential Zones Using Analytical Hierarchy Process Technique A comprehensive evaluation of groundwater potential is important for planning and long-term development of an area like Kwara State University. Several researchers have implemented Analytical Hierarchy Process (AHP) techniques in which the weight of each influencing factor on groundwater potential is calculated using ArcGIS through a detailed study of all these factors [4, 11, 17, 21, 35, 38, 42, 47, 48]. As groundwater availability varies in time and space, the delineation and evaluation of groundwater potential zones (GWPZ) is essential [49]. In this research, the evaluation of groundwater resources was carried out by combining several groundwater controlling parameters such as rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament and lineament density. The Analytical Hierarchy Process (AHP) was used to calculate and evaluate the percentage and rank for each class for thematic layers. Figure 12 shows the final resulting thematic map of the groundwater potential zones within KWASU and its environment, which is classified as (1) excellent, (2) good, (3) moderate, (4) poor, and (5) very poor zones. The thematic map indicated that Kwara State University is located between excellent to good categories of the groundwater potential zones . 4.2 Discussion The availability and distribution of groundwater resources based on their potentiality and rechargeability are controlled by several factors that differ across the Earth. In this study, eight factors were assessed to evaluate groundwater resources and management within Kwara State University, Malete. The rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament and lineament density were evaluated and considered as the most important factors influencing groundwater potential within the study area. Since all of these factors have no equal significance in controlling the groundwater resources, the Analytical Hierarchy Process method was used to evaluate each thematic layer factor and assign weight and rate to these factors based on the percentage of influence on the groundwater potential and recharge. Based on this method, thematic layers were used to assign the level of importance to the groundwater resources using the Weighted Overlay Analysis to weight and rank these factors in order to calculate the groundwater potential index within Kwara State University. Kwara State University. Malete is observed to be in high rainfall of approximately 1430 mm and flat-gentle slope terrain with elevation less than 300 m. High rainfall and flat-gentle slope with moderate elevation influence the groundwater potential positively, in which higher weight and rate were assigned to these factors as the high rainfall results into high precipitation and distribution that contribute to groundwater availability and recharge. High rainfall provides a large amount of water infiltration into aquifer zones, a flat-gentle slope with moderate elevation support in high levels, to the rate of water infiltration and groundwater recharge by reducing the amount of runoff within the study area. In addition, the land use/land cover also played a critical role in the water infiltration and recharge as the research area is situated within zones with crop, tree and rangeland that further reduces runoff, which resulted in high groundwater recharge. Moreover, the drainage network and drainage density, along with lineament and lineament density, were weighted to assess the groundwater resources within the study area. The drainage network follows a dendritic pattern that creates widespread water flow, while the drainage density allows for continuous water infiltration and distribution due to its lower values, which enhance permeability in the area. However, the lineament density shows low to moderate values ranging from 0 to 0.435 km/km². Areas with low lineament density have a lower potential for groundwater, but accurately delineating lineaments- faults or fracture zones- will ensure the sustainability of groundwater resources. Additionally, after assessing various factors influencing groundwater resources at Kwara State University, the institution is categorised as being within excellent to good groundwater potential zones, though accurate ground-truthing using geophysical exploration methods is essential. 5.0 Conclusion This research involves the evaluation of groundwater resources in Kwara State University using Remote Sensing and GIS techniques to provide valuable insights into the spatial distribution of groundwater resources by integrating several thematic layers such as rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament and lineament density, to successfully evaluate groundwater potential zones within the study area. The results highlight that Kwara State University is situated within a region with high rainfall, a flat-gentle slope gradient and elevation less than 300 m, land use/land cover of crop, tree and rangeland, dendritic drainage network pattern, very good to good drainage density and low lineament density. This research also demonstrates the utility of GIS-based analytical hierarchy process (AHP) techniques in prioritizing thematic layers and generating reliable groundwater potential maps, in which Kwara State University is located within excellent-good groundwater potential zones. The rapid population growth in and around Kwara State University has increased the necessity to evaluate groundwater potential zones, as such evaluations are critical for informed policymaking and effective management of water resources to ensure strategic resource allocation. Prioritizing water extraction infrastructure, such as boreholes in high-potential zones, can optimize supply efficiency and sustainable practices to prevent aquifer depletion, thereby ensuring long-term resource viability. From this investigation, it is feasible to conclude that this method serves as an orientation technique capable of streamlining decisions. However, the findings from this research can provide insights for conducting accurate future planning of groundwater regarding distribution, planning, consumption, and artificial recharge. The combination of remote sensing and GIS helps to provide indirect information about groundwater, aiding in drawing references to groundwater potential. While this offers a superficial understanding of groundwater resources, it should be complemented by further detailed geophysical fieldwork and other relevant studies to achieve comprehensive groundwater potential mapping within the University. Declarations Acknowledgements: The authors wish to show gratitude to everyone who contributes to the successful completion of this research. Author contribution: All Authors participated in the desk work planning and reviewing of this research. Jimoh Ajadi and Gabriel Efomeh Omolaiye supervise the project and review the manuscript. Mosunrat Yusuf wrote the first manuscript; Mosunrat Yusuf, Sodiq Bamidele Adam and Ajibola Damilola Alade processed and interpreted the remote sensing and GIS data. All authors contributed to the interpretation, reading and approval of the final manuscript. Funding: No external funding Consent for publication : All of the researchers’ consent was sought out and they consented to be published. Completing interests: The Authors declare no competing interests. Ethics and Consent to Participate Declarations : Not applicable. Clinical Trial number : Not applicable References Modibbo, M. A., Kana, A. A., Bello, I. E., & Eya, A. I. (2025). An Integrated Remote Sensing, Geographic Information System And Analytical Hierarchy Process For Determination Of Groundwater Potential In Keffi-Gra And Environs. Fudma Journal Of Sciences , 9 (1), 16–28. https://doi.org/10.33003/fjs-2025-0901-2769 Upadhyay, R. K., Tripathi, G., Đurin, B., Šamanović, S., Cetl, V., Kishore, N., Sharma, M., Singh, S. K., Kanga, S., Wasim, M., Rai, P. K., & Bhardwaj, V. (2023). Groundwater Potential Zone Mapping in the Ghaggar River Basin, North-West India, Using Integrated Remote Sensing and GIS Techniques. Water , 15 (5), 961. https://doi.org/10.3390/w15050961 Ajayakumar A., & Rajesh Reghunath. (2025). Delineation of groundwater recharge zones in lateritic terrains using geospatial techniques. Discover Geoscience , 3 (1). https://doi.org/10.1007/s44288-025-00110-z Hamdan, M. S., Singh, R., Pathak, R., Kumari, S., & Chauhan, V. (2024). Geospatial mapping of groundwater potential zones using multi-criteria decision-making AHP approach: A study of Kadugli district, south Kurdufan, Sudan. Journal of African Earth Sciences , 223 , 105513. https://doi.org/10.1016/j.jafrearsci.2024.105513 Morgan, H., Hussien, H. M., Madani, A., & Nassar, T. (2022). Delineating Groundwater Potential Zones in Hyper-Arid Regions Using the Applications of Remote Sensing and GIS Modeling in the Eastern Desert, Egypt. Sustainability , 14 (24), 16942–16942. https://doi.org/10.3390/su142416942 Uc Castillo, J. L., Martínez Cruz, D. A., Ramos Leal, J. A., Tuxpan Vargas, J., Rodríguez Tapia, S. A., & Marín Celestino, A. E. (2022). Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches. Water , 14 (13), 2138. https://doi.org/10.3390/w14132138 Bulbula, S. T., & Serur, A. B. (2024). Groundwater potential and recharge zone mapping using GIS and remote sensing techniques: the Melka Kunture Watershed in Ethiopia. Discover Sustainability , 5 (1). https://doi.org/10.1007/s43621-024-00521-x Derdour, A., Benkaddour, Y., & Bendahou, B. (2022). Application of remote sensing and GIS to assess groundwater potential in the transboundary watershed of the Chott-El-Gharbi (Algerian–Moroccan border). Applied Water Science , 12 (6). https://doi.org/10.1007/s13201-022-01663-x Saravanan, S., Saranya, T., Abijith, D., Jacinth, J. J., & Singh, L. (2021). Delineation of groundwater potential zones for Arkavathi sub-watershed, Karnataka, India using remote sensing and GIS. Environmental Challenges , 5 , 100380. https://doi.org/10.1016/j.envc.2021.100380 Ahmed, A., Alrajhi, A., & Alquwaizany, A. S. (2021). Identification of Groundwater Potential Recharge Zones in Flinders Ranges, South Australia Using Remote Sensing, GIS, and MIF Techniques. Water , 13 (18), 2571. https://doi.org/10.3390/w13182571 Ally, A. M., Yan, J., Bennett, G., Lyimo, N. N., & Mayunga, S. D. (2024). Assessment of groundwater potential zones using remote sensing and GIS-based fuzzy analytical hierarchy process (F-AHP) in Mpwapwa District, Dodoma, Tanzania. Geosystems and Geoenvironment , 3 (1), 100232. https://doi.org/10.1016/j.geogeo.2023.100232 El-Sorogy, A. S., Alharbi, T., Al-Kahtany, K., Rikan, N., & Salem, Y. (2024). Identification and Validation of Groundwater Potential Zones in Al-Madinah Al-Munawarah, Western Saudi Arabia Using Remote Sensing and GIS Techniques. Water , 16 (23), 3421. https://doi.org/10.3390/w16233421 Roy, D., Barman, S., Mandal, G., Mitra, R., Sarkar, A., Hossain, G., Roy, P., Hussein Almohamad, Hazem Ghassan Abdo, & Deepak Kumar Mandal. (2024). Extracting of prospective groundwater potential zones using remote sensing data, GIS, and multi-criteria decision-making approach in the Sub-Himalayan Dooars region of West Bengal, India. Applied Water Science , 14 (4). https://doi.org/10.1007/s13201-024-02124-3 Bennett, G. (2024). Analysis of methods used to validate remote sensing and GIS-based groundwater potential maps in the last two decades: A review. Geosystems and Geoenvironment , 3 (1), 100245–100245. https://doi.org/10.1016/j.geogeo.2023.100245 Osumeje, J. O., Eshimiakhe, D., Adetola Sunday Oniku, & Lawal, K. M. (2024). Application of remote sensing and electrical resistivity technique for delineating groundwater potential in North Western Nigeria. Scientific Reports , 14 (1). https://doi.org/10.1038/s41598-024-69633-8 Yousaf, B., Javid, K., Mahmood, S., Habib, W., & Hussain, S. (2024). Delineating groundwater potential zones using integrated remote sensing and GIS in Lahore, Pakistan. Environmental Monitoring and Assessment , 196 (10). https://doi.org/10.1007/s10661-024-13057-4 Gidafie, D., Nedaw, D., & Azagegn, T. (2024). Integrated remote sensing and geographic information system overlay analysis for groundwater potential evaluation using AHP and fuzzy AHP: Southern sections of the western Afar rift margin and associated rift floor. Groundwater for Sustainable Development , 26 , 101310. https://doi.org/10.1016/j.gsd.2024.101310 Kiran, G. S., Kaur, R., & Agradeep Mohanta. (2024). A hybrid approach: remote sensing, analytic hierarchy process and geographic information system for groundwater potential mapping in Dediapada, India. Environmental Science and Pollution Research . https://doi.org/10.1007/s11356-024-35666-9 Bawallah, M. A., Adebayo, A., Ilugbo, S. O., Olufemi, B., Alagbe, O. A., & Olasunkanmi, K. N. (2018). Evaluation of Groundwater Prospect in a Clay Dominated Environment of Central Kwara State, Southwestern Nigeria. International Journal of Advanced Engineering Research and Science , 5 (6), 45–56. https://doi.org/10.22161/ijaers.5.6.8 Suryawanshi, S. L., Singh, P. K., Kothari, M., Singh, M., Yadav, K. K., & Gupta, T. (2024). Assessment of groundwater potential zones for hard rock area of sabi river basin using an integrated approach of remote sensing, GIS and AHP techniques. Physics and Chemistry of the Earth, Parts A/B/C , 137 , 103820. https://doi.org/10.1016/j.pce.2024.103820 Vidya, K. M., Manoharan, A. N., Suchitra, B., & Shyni, M. (2024). Combination of remote sensing, GIS, AHP techniques and geophysical data to delineate groundwater potential zones in the Shiriya River Basin, South India. Geosystems and Geoenvironment , 3 (4), 100294. https://doi.org/10.1016/j.geogeo.2024.100294 Arya, P., Jhariya, D. C., Singh, C. K., & N Vishwakarma. (2025). Identification of groundwater potential zones using remote sensing and geographic information systems with multi-criteria decision-making techniques in the Jonk River Watershed, Chhattisgarh, India. Journal of Earth System Science , 134 (1). https://doi.org/10.1007/s12040-025-02516-2 Ganesan, S., & Subramaniyan, A. (2024). Identification of groundwater potential zones using multi-influencing factor method, GIS and remote sensing techniques in the hard rock terrain of Madurai district, southern India. Sustainable Water Resources Management , 10 (2). https://doi.org/10.1007/s40899-024-01036-z Elsebaie, I. H., Kawara, A. Q., & Alnahit, A. O. (2025). Delineation of Groundwater Recharge Potential Zones Using GIS: A Case Study for Yalamlam Watershed in Saudi Arabia. Water Science and Technology Library , 305–315. https://doi.org/10.1007/978-3-031-80520-2_17 Akudo, E. O., Ifediegwu, S. I., Ahmed, J. B., & Aigbadon, G. O. (2024). Identifying Groundwater Potential Regions in Sokoto Basin, Northwestern Nigeria: An Integrated Remote Sensing, GIS, and MIF Techniques. Journal of the Indian Society of Remote Sensing , 52 (6), 1201–1222. https://doi.org/10.1007/s12524-024-01872-8 Naeem, M., Farid, H. U., Muhammad Arbaz Madni, Albano, R., Muhammad Azhar Inam, Shoaib, M., Shoaib, M., Rashid, T., Aqsa Dilshad, & Ahmad, A. (2024). GIS-Based Analytical Hierarchy Process for Identifying Groundwater Potential Zones in Punjab, Pakistan. ISPRS International Journal of Geo-Information , 13 (9), 317–317. https://doi.org/10.3390/ijgi13090317 Adeleke, E. (2024). Climate Change in Kwara State, Nigeria: Evidence of Rainfall and Temperature Variations. Colombo Geographer , 2 (1), 2024. https://arts.cmb.ac.lk/wp-content/uploads/2024/07/Adeleke.pdf Akpenpuun, T., & Rasheed Amao Busari. (2013). Impact of Climate on Tuber Crops Yield in Kwara State, Nigeria. American International Journal of Contemporary Research , 3 (10), 6. https://www.researchgate.net/publication/351745190_Impact_of_Climate_on_Tuber_Crops_Yield_in_Kwara_State_Nigeria?enrichId=rgreq-9350783b292ddff12cc29e02185f91d0-XXX&enrichSource=Y292ZXJQYWdlOzM1MTc0NTE5MDtBUzoxMTQzMTI4MTIyODQxMjgxMkAxNzA5OTg0NjA5Njk2&el=1_x_3&_esc=publicationCoverPdf Olasunkanmi, N. K., Usman, Z. M., & Jimoh, A. A. (2023). Investigation of groundwater quality around municipal waste disposal site in Malete southwestern Nigeria. Arabian Journal of Geosciences , 16 (4). https://doi.org/10.1007/s12517-023-11359-4 Ajadi, J., Dada, S., Nnabo, P. N., & Owoeye, B. (2018). Lithostructural description and metalogeny of Alagbede gold deposit, West Central Nigeria. Journal of Environment and Earth Science , 8 (5), 115–132. https://www.researchgate.net/publication/336180630_Lithostructural_description_and_metalogeny_of_Alagbede_gold_deposit_West_Central_Nigeria Obaje, N. G. (2009). Geology and Mineral Resources of Nigeria. In Lecture Notes in Earth Sciences . Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-92685-6 Rahaman, M. (1976). Review of The Basement Geology Of South-Western Nigeria. Fatoyinbo A.A., Ishola K.S., Okolie, C. J., Daramola, O. E., HamidMosaku, I. A., O.A. Ipadeola, I.D. Arungwa, C.O. Ogbeta, & S.E. Erharhaghen. (2024). Integration of geospatial and geophysical data for assessing borehole conditions at the University of Ilorin, North-Central, Nigeria. Nigerian Journal of Technology , 43 (3), 557–567. https://www.ajol.info/index.php/njt/article/view/281379 Ishola, K. S., Fatoyinbo, A. A., Hamid-Mosaku, A. I., Okolie, C. J., Daramola, O. E., & Lawal, T. O. (2023). Groundwater potential mapping in hard rock terrain using remote sensing, geospatial and aeromagnetic data. Geosystems and Geoenvironment , 2 (1), 100107. https://doi.org/10.1016/j.geogeo.2022.100107 Al-Djazouli, M. O., Elmorabiti, K., Rahimi, A., Amellah, O., & Fadil, O. A. M. (2020). Delineating of groundwater potential zones based on remote sensing, GIS and analytical hierarchical process: a case of Waddai, eastern Chad. GeoJournal , 86 (4), 1881–1894. https://doi.org/10.1007/s10708-020-10160-0 Rahman, Md. M., AlThobiani, F., Shahid, S., Virdis, S. G. P., Kamruzzaman, M., Rahaman, H., Momin, Md. A., Hossain, Md. B., & Ghandourah, E. I. (2022). GIS and Remote Sensing-Based Multi-Criteria Analysis for Delineation of Groundwater Potential Zones: A Case Study for Industrial Zones in Bangladesh. Sustainability , 14 (11), 6667. https://doi.org/10.3390/su14116667 Sresto, M. A., Siddika, S., Haque, Md. N., & Saroar, M. (2021). Application of fuzzy analytic hierarchy process and geospatial technology to identify groundwater potential zones in north-west region of Bangladesh. Environmental Challenges , 5 , 100214. https://doi.org/10.1016/j.envc.2021.100214 Chaudhry, A. K., Kumar, K., & Alam, Mohd. A. (2019). Mapping of groundwater potential zones using the fuzzy analytic hierarchy process and geospatial technique. Geocarto International , 1–22. https://doi.org/10.1080/10106049.2019.1695959 Das, B., Pal, S. C., Malik, S., & Chakrabortty, R. (2018). Modeling groundwater potential zones of Puruliya district, West Bengal, India using remote sensing and GIS techniques. Geology, Ecology, and Landscapes , 1–15. https://doi.org/10.1080/24749508.2018.1555740 Yimer, F., Messing, I., Ledin, S., & Abdelkadir, A. (2008). Effects of different land use types on infiltration capacity in a catchment in the highlands of Ethiopia. Soil Use and Management , 24 (4), 344–349. https://doi.org/10.1111/j.1475-2743.2008.00182.x Godif, G., & Manjunatha, B. R. (2023). Delineation of groundwater potential zones using remotely sensed data and GIS-based analytical hierarchy process: Insights from the Geba river basin in Tigray, Northern Ethiopia. Journal of Hydrology: Regional Studies , 46 , 101355. https://doi.org/10.1016/j.ejrh.2023.101355 Upwanshi, M., Damry, K., Pathak, D., Tikle, S., & Das, S. (2023). Delineation of potential groundwater recharge zones using remote sensing, GIS, and AHP approaches. Urban Climate , 48 , 101415. https://doi.org/10.1016/j.uclim.2023.101415 Singh, P., Hasnat, M., Rao, M. N., & Singh, P. (2020). Fuzzy- Analytical Hierarchy Process based GIS Modelling for Groundwater Prospective Zones in Prayagraj, India. Groundwater for Sustainable Development , 100530. https://doi.org/10.1016/j.gsd.2020.100530 Kumar, M., Singh, P., & Singh, P. (2022). Integrating GIS and remote sensing for delineation of groundwater potential zones in Bundelkhand Region, India. The Egyptian Journal of Remote Sensing and Space Science , 25 (2), 387–404. https://doi.org/10.1016/j.ejrs.2022.03.003 Srinivas, G. S., Kumar, P., & P. Jyothi. (2021). Demarcation of groundwater potential zones using analytical hierarchical process in Cheyyeru watershed, India. International Journal of Energy and Water Resources , 6 (2), 149–160. https://doi.org/10.1007/s42108-021-00127-3 Nag, S. K., & Kundu, A. (2018). Application of remote sensing, GIS and MCA techniques for delineating groundwater prospect zones in Kashipur block, Purulia district, West Bengal. Applied Water Science , 8 (1). https://doi.org/10.1007/s13201-018-0679-9 Ahmadi, H., Kaya, O. A., Babadagi, E., Savas, T., & Pekkan, E. (2020). GIS-Based Groundwater Potentiality Mapping Using AHP and FR Models in Central Antalya, Turkey. Environmental Sciences Proceedings , 5 (1), 11. https://doi.org/10.3390/iecg2020-08741 Arulbalaji, P., Padmalal, D., & Sreelash, K. (2019). GIS and AHP Techniques Based Delineation of Groundwater Potential Zones: a case study from Southern Western Ghats, India. Scientific Reports , 9 (1). https://doi.org/10.1038/s41598-019-38567-x Mitra, R., & Roy, D. (2022). Delineation of groundwater potential zones through the integration of remote sensing, geographic information system, and multi-criteria decision-making technique in the sub-Himalayan foothills region, India. International Journal of Energy and Water Resources . https://doi.org/10.1007/s42108-022-00181-5 Moodley, T., Seyam, M., Abunama, T., & Bux, F. (2022). Delineation of groundwater potential zones in KwaZulu-Natal, South Africa using remote sensing, GIS and AHP. Journal of African Earth Sciences , 193 , 104571. https://doi.org/10.1016/j.jafrearsci.2022.104571 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Jun, 2025 Reviews received at journal 07 Jun, 2025 Reviews received at journal 05 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviews received at journal 02 Jun, 2025 Reviewers agreed at journal 02 Jun, 2025 Reviewers agreed at journal 01 Jun, 2025 Reviewers agreed at journal 01 Jun, 2025 Reviewers agreed at journal 01 Jun, 2025 Reviewers agreed at journal 29 May, 2025 Reviewers invited by journal 29 May, 2025 Editor assigned by journal 29 Apr, 2025 Submission checks completed at journal 29 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6458804\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":464733054,\"identity\":\"ccf44ad7-da1f-45df-b2cb-af28beafbfd4\",\"order_by\":0,\"name\":\"Jimoh Ajadi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kwara State University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jimoh\",\"middleName\":\"\",\"lastName\":\"Ajadi\",\"suffix\":\"\"},{\"id\":464733055,\"identity\":\"3f0b2761-33a9-45b4-bb89-9224b729af90\",\"order_by\":1,\"name\":\"Mosunrat Yusuf\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Kwara State University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mosunrat\",\"middleName\":\"\",\"lastName\":\"Yusuf\",\"suffix\":\"\"},{\"id\":464733056,\"identity\":\"1244198e-5ee9-44ab-8ae3-11b690d4d01d\",\"order_by\":2,\"name\":\"Gabriel Efomeh Omolaiye\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYFACHjApw8AMJD8wMCTAxA0IaeEBaWGcQZoWIGDmIUaLvPvZAwwfc2x4+Nt5DB/bttnl8bM3MH74wHDYGJcWwzN5CYwzt6XxSBzmMTbObUsuluw5wCw5g+GwGU4tDTkGzLzbDvMwHOYxk85tY07ccCOBDejCwzY4tfS/gWiRP8xj/tuyrZ6wFnkJqC0GQFuYGdsOw7XgdJiBxDuIXwwPswG9ce544syeg82SMwzScXpfvj8XGGLbbOTkzh/e+OFHWXViP3vzwQ8fKqwNG3DZcoCB/QeEyWHAwMgGYjA24I1IeYRZ7A8YGP7gVjkKRsEoGAUjFwAAgTxRgnKENpkAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"University of Ilorin\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Gabriel\",\"middleName\":\"Efomeh\",\"lastName\":\"Omolaiye\",\"suffix\":\"\"},{\"id\":464733057,\"identity\":\"55b6e73f-210d-49b4-8319-48f5025c0652\",\"order_by\":3,\"name\":\"Sodiq Bamidele Adam\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Ilorin\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sodiq\",\"middleName\":\"Bamidele\",\"lastName\":\"Adam\",\"suffix\":\"\"},{\"id\":464733059,\"identity\":\"a5dfd77d-1eb2-4016-a510-cf562e82d8ce\",\"order_by\":4,\"name\":\"Ajibola Damilola Alade\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Federal University of Technology\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ajibola\",\"middleName\":\"Damilola\",\"lastName\":\"Alade\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-04-16 02:38:08\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6458804/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6458804/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":83758402,\"identity\":\"1e4adc4d-786a-466c-ab2c-edc52449a1b4\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":165937,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMap of Nigeria showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/83397fedbeb64a15c652adca.jpeg\"},{\"id\":83758400,\"identity\":\"378ebd1e-744a-45ff-969b-fa662b4cc0aa\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":377829,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGeological Map of Kwara State University, Malete (Modified and Adopted from Ajadi et al., 2018)\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/d24f0014f029baa58dc2d2cb.png\"},{\"id\":83758398,\"identity\":\"ad41c169-bdb8-429c-ba75-e4fa88d8cdf5\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":95332,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eThe methodology workflow adopted in the research\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/6f9a0b10e0ca847e1ec1c0d8.png\"},{\"id\":83758397,\"identity\":\"75a4ad53-f09d-4830-887e-8a148338a3b8\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"jpeg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":92127,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eRainfall Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image4.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/90888b94b3fae1ebf99dc13d.jpeg\"},{\"id\":83759012,\"identity\":\"6b45aa9b-9ba9-4344-bdfd-b6e9cdd1c699\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:55:02\",\"extension\":\"jpeg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":270418,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eLand Use / Land Cover Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image5.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/aada30bad813d8fa6e11c2c5.jpeg\"},{\"id\":83758404,\"identity\":\"077ea268-517a-4742-9506-96ff5a0c7514\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"jpeg\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":188601,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eElevation Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image6.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/689256e930813279a8209486.jpeg\"},{\"id\":83759013,\"identity\":\"b725e106-de22-44e0-9e22-09610084ed49\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:55:02\",\"extension\":\"jpeg\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":278897,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eSlope Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image7.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/b0fc20d12e9b8324102e97f8.jpeg\"},{\"id\":83759014,\"identity\":\"d0e03abf-679b-4b3b-8086-8058994be314\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:55:02\",\"extension\":\"jpeg\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":210079,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDrainage Network Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image8.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/b5a0e0e462be335d906a064a.jpeg\"},{\"id\":83759203,\"identity\":\"3fa67b9e-a871-4ee0-bdde-db2581c18c04\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 09:03:02\",\"extension\":\"jpeg\",\"order_by\":9,\"title\":\"Figure 9\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":156946,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDrainage Density Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image9.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/a25ca6fa286e8d8413a427d1.jpeg\"},{\"id\":83758408,\"identity\":\"9e570e34-daee-4984-8f7d-54b93720119a\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"jpeg\",\"order_by\":10,\"title\":\"Figure 10\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":191462,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eLineament Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image10.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/caff0325791d8a139377d5c0.jpeg\"},{\"id\":83759016,\"identity\":\"9143c334-e1be-43c6-bcdf-64a3bd4304f4\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:55:02\",\"extension\":\"jpeg\",\"order_by\":11,\"title\":\"Figure 11\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":163355,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eLineament Density Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image11.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/270922406d6fc30cf4172e39.jpeg\"},{\"id\":83758406,\"identity\":\"f683ffb8-5a9f-4240-8036-0f3f2e901d78\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 08:47:02\",\"extension\":\"jpeg\",\"order_by\":12,\"title\":\"Figure 12\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":218447,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eGroundwater Potential Zone Map showing Kwara State University\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"image12.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/3d9d4b8668db453733ef7c4d.jpeg\"},{\"id\":83759796,\"identity\":\"cf46674f-9425-4cbd-88fd-705f028a8286\",\"added_by\":\"auto\",\"created_at\":\"2025-06-02 09:11:03\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":3683499,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6458804/v1/c7a9145e-7cb1-4b6a-8ac2-5f05ec58f448.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"\\u003cp\\u003eEvaluation of Groundwater Resources Using Remote Sensing and Gis Techniques Within Kwara State University, Malete, Nigeria\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Highlights\",\"content\":\"\\u003col\\u003e\\n \\u003cli\\u003eKwara State University is located within a region with annual rainfall of 1430mm, a flat-gentle slope gradient, elevation of less than 300m, comprising crops, trees, built-up and rangeland, dendritic drainage network pattern, very good drainage density and low lineament density. KWASU area has excellent-good groundwater potential zones and geophysical field studies are recommended for accurate groundwater potential mapping.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"},{\"header\":\"1.0 Introduction\",\"content\":\"\\u003cp\\u003eGroundwater represents a significant resource for socio-economic development, particularly in regions where surface water availability is erratic and insufficient [1, 2]. It is vital in all parts of the world as it is essential for both human and industrial use [3 - 6]. However, rapid population growth, industrialization, agricultural expansion, and climate variability have increased pressure on groundwater resources, necessitating systematic exploration and sustainable management strategies [7 - 10]. Kwara State University (KWASU), located in Nigeria’s North Central region, relies primarily on groundwater to satisfy its institutional and community needs. In understanding the groundwater resource within the region, the lack of a spatially explicit groundwater potential map hinders efficient resource allocation and long-term planning.\\u0026nbsp;Over the years, Remote Sensing and Geographic Information Systems (GIS) have emerged as powerful tools in groundwater studies, providing spatially distributed data that enhances the accuracy and efficiency of hydrogeological investigations [1, 11, 12]. These techniques offer significant advantages over conventional hydrogeological methods by enabling rapid assessment, cost-effectiveness, and large-scale mapping of groundwater potential zones [13]. Thus, the integration of Remote Sensing and Geographic Information Systems serves as a means to combine multiple datasets, including geological, hydrological, and topographical information, to delineate groundwater potential zones with high precision [3, 14 - 16].\\u003c/p\\u003e\\n\\u003cp\\u003eKwara State University (KWASU) is situated in a region experiencing increasing water demand due to the growing population of its students and urban expansion. Although limited studies have been conducted to assess the groundwater potential in this area using modern geospatial techniques, traditional methods of groundwater exploration, such as drilling and geophysical surveys, are often time-consuming, expensive, and spatially restricted [17 - 19]. Therefore, using RS and GIS techniques for hydrogeological mapping provides a cost-effective and systematic way to identify and evaluate groundwater potential zones, which is essential for understanding the hydrogeological characteristics of KWASU and its surroundings, thereby supporting sustainable water resource planning and management. Furthermore, it is crucial to recognise that several factors influence groundwater potential, including lithology, lineament density, drainage patterns, slope, soil type, land use/land cover (LULC), and rainfall distribution [11, 13, 20, 21]. By analysing these factors, remote sensing and GIS data can define groundwater potential zones and assess aquifer characteristics with greater precision [18, 22, 23]. Additionally, this approach not only improves the accuracy of groundwater resource evaluation but also facilitates informed decision-making for sustainable water resource management, which is vital for addressing water supply challenges and ensuring the long-term sustainability of available resources [7, 14, 16, 24 - 26].\\u003c/p\\u003e\\n\\u003cp\\u003eThe outcomes of this research have significant implications for sustainable water resource management in KWASU and its surrounding areas. By evaluating groundwater resources, this study aims to generate essential thematic maps to analyse and assess groundwater availability. It will also provide actionable insights for optimizing borehole siting, reducing infrastructure costs, and mitigating risks associated with groundwater overexploitation. The findings will contribute to the broader field of hydrogeology by demonstrating the effectiveness of remote sensing and GIS in groundwater assessment and management. Ultimately, this research will support informed decision-making for water resource development in KWASU and similar regions facing challenges related to water scarcity.\\u003c/p\\u003e\"},{\"header\":\"2.0 Description and Geology of Study Area\",\"content\":\"\\u003cp\\u003eKwara State University (KWASU) is a public institution established in 2009, located in Malete, Moro Local Government Area, Kwara State, Nigeria, serving as a hub for academic excellence and research. The university lies between latitude [8.704445; 8.684772; 8.723889; 8.743056]° N and longitude [4.451389; 4.493333; 4.510556; 4.470278]° E within a semi-urban area characterized by a mix of residential, agricultural, and academic land use, featuring a tropical climate marked by distinct wet and dry seasons. Figure 1 shows the map of Kwara State University within Nigeria, and Figure 2 presents the geological map of Kwara State University within Malete and its environment. The terrain is generally undulating, with gentle slopes and isolated hills that influence drainage patterns. The rainy season in Kwara State University and its surroundings begins at the end of March and spans until early September, while the dry season lasts from October to early March, with temperatures fluctuating between 25 °C and 30 °C during the wet season [27]. The dry season temperature ranges from 33 °C to 34 \\u003csup\\u003eo\\u003c/sup\\u003eC, experiencing intense heat during the dry months, while annual rainfall ranges from 1000 mm to 1500 mm in Kwara State [27, 28].\\u003c/p\\u003e\\n\\u003cp\\u003eKWASU lies within the Basement Complex of southwestern Nigeria, primarily composed of Precambrian crystalline rocks, and it is underlain by lithological units such as migmatitic gneiss, porphyritic granite and quartzite [29, 30]. The rocks in the study area reflect significant geological events linked to the Liberian, Eburnean and Pan-African orogenies, occurring approximately 2500 Ma, 2000 Ma, and 500 Ma, respectively, and are associated with the formation of migmatites, quartzites and Pan-African granites [31, 32]. The Groundwater occurrence in this region is controlled by weathering and fracturing, with aquifers developing in secondary porosities created by these processes. The part of the research area exhibits good aquifer characteristics, particularly within the quartzitic layers, indicating potential for groundwater resources [30]. The weathered overburden varies in thickness, typically between a few meters and over 20 meters, influencing groundwater accumulation and movement. Understanding the geological and structural framework of KWASU is important for effective groundwater exploration and sustainable management.\\u003c/p\\u003e\"},{\"header\":\"3.0 Materials Used and Methodology\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e3.1 Material Used\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFigure 3 shows a process chart for the research approach employed in this study. The materials utilized include high-resolution Landsat 8 satellite imagery for land use/land cover (LULC) mapping, as\\u0026nbsp;well as Shuttle Radar Topography Mission (SRTM) digital elevation models (DEMs) to extract elevation, slope, and drainage patterns. The Landsat imagery and SRTM DEM were acquired from the United States Geological Survey (USGS) website (http://www.earthexplorer.usgs.gov/). Specialized software such as ArcGIS facilitates the spatial analysis and integration of these diverse datasets.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e3.2 Methodology\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study integrates remote sensing and GIS techniques to evaluate groundwater resources at Kwara State University, Malete. The methodology is structured around a multi-criteria decision analysis framework, employing the Analytical Hierarchy Process (AHP) to assign weights to various hydrogeological factors such as rainfall, lineament and lineament density, drainage network and drainage density, slope, elevation, and land use/land cover. The process begins with data acquisition and preprocessing, followed by the generation of thematic layers that represent each groundwater controlling factor, as shown in Figure 3.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e3.2.1 Analytical Hierarchy Process (AHP)\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe Analytical Hierarchy Process (AHP) is employed as a multi-criteria decision analysis technique to systematically assign weights to various thematic layers based on their influence on groundwater potential [49, 50]. A pairwise comparison matrix is constructed, and consistency ratio calculations are performed to ensure logical consistency in weight assignments. The weighted overlay method in GIS is then used to integrate the ranked factors such as lineament density, slope, LULC, rainfall and drainage density into a composite groundwater potential map as indicated using equation 1 below [33 - 35]. The AHP approach enhances the objectivity and reliability of groundwater potential zone evaluation and delineation, which provide a robust framework for decision-making in sustainable groundwater resource management [2].\\u003c/p\\u003e\\n\\u003cp\\u003eThese layers are then integrated using weighted overlay analysis within the GIS environment to produce a comprehensive groundwater potential map, in which findings are presented in a detailed spatial delineation of high, moderate and low groundwater potential zones within Kwara State University. In addition, the groundwater potential index (GWPI) was estimated from the integration of the total normalized weights for the layers using Equation 1.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e𝐺𝑊𝑃𝐼\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;=\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e𝐴𝑅𝑤𝐴𝑅𝑤𝑖\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;+\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e𝐿𝑈𝐿𝐶𝑤𝐿𝑈𝐿𝐶𝑤𝑖 +\\u003c/strong\\u003e\\u003cstrong\\u003e𝑆𝑤𝑆𝑤𝑖\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e+\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003eE𝑤E𝑤𝑖\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e+\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e𝐷𝑤𝐷𝑤𝑖\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e+\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e𝐷𝑑𝑤𝐷𝑑𝑤𝑖 + 𝐿𝑤𝐿𝑤𝑖\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e+\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e𝐿d𝑤𝐿d𝑤𝑖 \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;- Eqn. 1\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eIn which are represented as Annual rainfall (AR), Land Use/Land Cover (LULC), Slope (S), Elevation (E), Drainage Network (D), Drainage Density (Dd), Lineament (L), Lineament density (Ld), and w is the normalized weight of the thematic layer; and wi is the normalized weight of sub-layer classes that is used in evaluation of the groundwater potential zones.\\u003c/em\\u003e\\u003c/p\\u003e\"},{\"header\":\"4.0 Results and Discussion\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e4.1 Results Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.1.1 Rainfall\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eRainfall is the primary source of groundwater recharge and is essential in the delineation of groundwater potential zones [36, 37]. (Rahman et al., 2022; Sresto et al., 2021). The spatial and temporal distribution of rainfall is analysed using meteorological data obtained from weather stations and satellite-derived precipitation datasets (TRMM and local gauge data of 2021). A rainfall distribution map is generated in GIS to assess variations across the study area, as shown in Fig. 4. Regions receiving higher rainfall are more likely to have greater groundwater recharge potential, especially when combined with favourable geomorphological and soil conditions [37, 38]. This parameter is integrated with other thematic layers to refine the groundwater potential assessment.\\u003c/p\\u003e\\n\\u003cp\\u003eAs shown in Fig. 4, the average annual rainfall around the study area ranges from 1318mm to 1430mm and this is classified as a high variation of rainfall region. Based on the maximum and minimum values, the rainfall map is classified into low, moderate and high, in which Kwara State University is located within a \\u003cstrong\\u003ehigher rainfall potential of approximately 1430 mm, which serves as a good indicator of potential area for groundwater\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.1.2 Land Use/Land Cover (LULC\\u003cem\\u003e)\\u0026nbsp;\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLand use and land cover play a significant role in groundwater recharge and its impact on the hydrological cycle directly by affecting surface permeability, runoff and evaporation rates [39, 40]. LULC classification is carried out using remote sensing data, which is analysed in GIS to categorize different land cover types such as forests, agricultural lands, built-up areas, and water bodies. Vegetated and agricultural areas generally enhance infiltration and groundwater recharge, whereas impervious surfaces like urban settlements reduce percolation and increase runoff [36]. Integrating LULC analysis helps in assessing the impact of anthropogenic activities on groundwater availability and potential. The land-use/land-cover (LULC) map of KWASU is characterized into five classes: water bodies, trees, built-up, crop and rangeland (Fig. 5). The research area is located within the classes of crops, trees, built-up and rangeland, with no indication of water bodies; this limits the distribution of water body reservoirs over the study area. However, as Land Use/Land Cover is the essential factor that controls groundwater infiltration, runoff and recharge, KWASU \\u003cstrong\\u003eindicate moderate weightage due to the presence of trees and crops, which help in reducing the speed of water flow and increase the rate of infiltration\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.1.3 Elevation and Slope\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSlope is a critical topographical parameter influencing surface runoff and groundwater recharge. Steep slopes promote surface runoff, reducing the opportunity for infiltration, whereas gentle slopes favour water percolation and recharge [41]. The slope map was generated using a DEM in GIS, where the gradient of the terrain is classified into various categories. Areas with lower slopes are considered more favourable for groundwater accumulation [41]. The spatial analysis of slope in relation to other hydrogeological factors aids in refining the groundwater potential zones within the study area.\\u003c/p\\u003e\\n\\u003cp\\u003eThe elevation and slope of a location are thought to be regulating elements that influence the amount of erosion and weathering processes inside it. Fig. 6 depicts elevation levels ranging from 100 m to 400 m, with \\u003cstrong\\u003eKwara State University\\u0026apos;s elevation level of 300 m indicating a reasonable rate of groundwater potential\\u003c/strong\\u003e. Moreover, the degree of slope as shown in Figure 7 is grouped into flat, gentle, moderate, steep and very steep. As a gentle slope is classified as \\u0026ldquo;good\\u0026rdquo; for groundwater recharge and flat terrain is of most favourable for infiltration, \\u003cstrong\\u003eKWASU is located within the group of flat and gentle slope, which indicate potential for a high level of groundwater, as there will be a very low level of runoff\\u003c/strong\\u003e. \\u0026nbsp;The combination of elevation and slope map analysis shows a moderate weight of groundwater potential.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.1.4 Drainage Network and Drainage Density\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eDrainage density is defined as the total length of streams per unit area that is an important hydrological parameter that affects groundwater recharge [42]. Areas with low drainage density are often associated with high infiltration rates and good groundwater potential, whereas high drainage density areas indicate increased surface runoff and lower recharge capabilities [43]. A drainage network map is extracted from the DEM using GIS-based hydrological analysis tools. By overlaying drainage density maps with other hydrogeological parameters, more precise groundwater potential zones are identified.\\u003c/p\\u003e\\n\\u003cp\\u003eDrainage network and drainage density are part of the influencing factors that evaluate the potential of groundwater. Figure 8 represents the drainage network of the dendritic drainage pattern within the study area, whereas Figure 9 exhibits drainage densities ranging from 8.59 to 266 km/km2. The drainage density of an area is an essential component that indicates runoff characteristics, water infiltration, and groundwater rechargeability, all of which are related to the permeability of the prevailing land cover. As shown in Figure 9, the drainage density was grouped into very good (8.59 \\u0026ndash; 61 km/km\\u003csup\\u003e2\\u003c/sup\\u003e), good (61.1 \\u0026ndash; 95.3 km/km\\u003csup\\u003e2\\u003c/sup\\u003e), moderate (95.4 - 133 km/km\\u003csup\\u003e2\\u003c/sup\\u003e), poor (134 - 175 km/km\\u003csup\\u003e2\\u003c/sup\\u003e) and very poor (176 - 266 km/km\\u003csup\\u003e2\\u003c/sup\\u003e) density. However, \\u003cstrong\\u003eKWASU is located within a Drainage density ranging between very good to good drainage density of 8.59 to 95.3 km/km\\u003csup\\u003e2\\u003c/sup\\u003e, which shows support for higher groundwater potential due to higher permeability and water infiltration to the aquifers\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.1.5 Lineament and Lineament Density\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eLineaments are linear features in the Earth\\u0026apos;s crust often associated with geological structures such as faults and fractures that enhance groundwater movement [44]. The density of lineaments in an area is directly proportional to its groundwater potential, as fractures and fault zones facilitate subsurface water storage and movement [45, 46]. Remote sensing techniques are employed to extract lineament features, and GIS tools are used to compute lineament density maps. High lineament density areas indicate zones of increased groundwater infiltration, making them significant in groundwater potential mapping [44]. These features are further validated with field observations and geological assessments.\\u003c/p\\u003e\\n\\u003cp\\u003eLineament depicts structural zones of fault and fracture that functioned as secondary porosity and permeability to groundwater. Figure 10 presents the lineament map, which highlights potential fault and fracture lines. Figure 11 shows lineament density classified into five categories: very low (0 - 0.181 km/km\\u003csup\\u003e2\\u003c/sup\\u003e), low (0.182 - 0.306 km/km\\u003csup\\u003e2\\u003c/sup\\u003e), moderate (0.397 - 0.435 km/km\\u003csup\\u003e2\\u003c/sup\\u003e), high (0.436 - 0.593 km /km2) and very high (0.594 - 0.964 km/km\\u003csup\\u003e2\\u003c/sup\\u003e). Lineament density contributes to the formation of groundwater. \\u003cstrong\\u003eThe research area is sited in a low to moderate lineament density zone, ranging from\\u0026nbsp;\\u003c/strong\\u003e\\u003cstrong\\u003e0 \\u0026ndash; 0.435 km/km\\u003csup\\u003e2\\u003c/sup\\u003e,\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;with low lineament density areas typifying a lower groundwater potential.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.1.6 Analysis of Groundwater Potential Zones Using Analytical Hierarchy Process Technique\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eA comprehensive evaluation of groundwater potential is important for planning and long-term development of an area like Kwara State University. Several researchers have implemented Analytical Hierarchy Process (AHP) techniques in which the weight of each influencing factor on groundwater potential is calculated using ArcGIS through a detailed study of all these factors [4, 11, 17, 21, 35, 38, 42, 47, 48]. As groundwater availability varies in time and space, the delineation and evaluation of groundwater potential zones (GWPZ) is essential [49].\\u003c/p\\u003e\\n\\u003cp\\u003eIn this research, the evaluation of groundwater resources was carried out by combining several groundwater controlling parameters such as rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament and lineament density. The Analytical Hierarchy Process (AHP) was used to calculate and evaluate the percentage and rank for each class for thematic layers. Figure 12 shows the final resulting thematic map of the groundwater potential zones within KWASU and its environment, which is classified as (1) excellent, (2) good, (3) moderate, (4) poor, and (5) very poor zones. The thematic map indicated that \\u003cstrong\\u003eKwara State University is located between excellent to good categories of the groundwater potential zones\\u003c/strong\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.2 Discussion\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe availability and distribution of groundwater resources based on their potentiality and rechargeability are controlled by several factors that differ across the Earth. In this study, eight factors were assessed to evaluate groundwater resources and management within Kwara State University, Malete. The rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament and lineament density were evaluated and considered as the most important factors influencing groundwater potential within the study area. Since all of these factors have no equal significance in controlling the groundwater resources, the Analytical Hierarchy Process method was used to evaluate each thematic layer factor and assign weight and rate to these factors based on the percentage of influence on the groundwater potential and recharge. Based on this method, thematic layers were used to assign the level of importance to the groundwater resources using the Weighted Overlay Analysis to weight and rank these factors in order to calculate the groundwater potential index within Kwara State University.\\u003c/p\\u003e\\n\\u003cp\\u003eKwara State University. Malete is observed to be in high rainfall of approximately 1430 mm and flat-gentle slope terrain with elevation less than 300 m. \\u0026nbsp;High rainfall and flat-gentle slope with moderate elevation influence the groundwater potential positively, in which higher weight and rate were assigned to these factors as the high rainfall results into high precipitation and distribution that contribute to groundwater availability and recharge. High rainfall provides a large amount of water infiltration into aquifer zones, a flat-gentle slope with moderate elevation support in high levels, to the rate of water infiltration and groundwater recharge by reducing the amount of runoff within the study area. In addition, the land use/land cover also played a critical role in the water infiltration and recharge as the research area is situated within zones with crop, tree and rangeland that further reduces runoff, which resulted in high groundwater recharge.\\u003c/p\\u003e\\n\\u003cp\\u003eMoreover, the drainage network and drainage density, along with lineament and lineament density, were weighted to assess the groundwater resources within the study area. The drainage network follows a dendritic pattern that creates widespread water flow, while the drainage density allows for continuous water infiltration and distribution due to its lower values, which enhance permeability in the area. However, the lineament density shows low to moderate values ranging from 0 to 0.435 km/km\\u0026sup2;. Areas with low lineament density have a lower potential for groundwater, but accurately delineating lineaments- faults or fracture zones- will ensure the sustainability of groundwater resources. Additionally, after assessing various factors influencing groundwater resources at Kwara State University, the institution is categorised as being within excellent to good groundwater potential zones, though accurate ground-truthing using geophysical exploration methods is essential.\\u003c/p\\u003e\"},{\"header\":\"5.0 Conclusion\",\"content\":\"\\u003cp\\u003eThis research involves the evaluation of groundwater resources in Kwara State University using Remote Sensing and GIS techniques to provide valuable insights into the spatial distribution of groundwater resources by integrating several thematic layers such as rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament and lineament density, to successfully evaluate groundwater potential zones within the study area. The results highlight that Kwara State University is situated within a region with high rainfall, a flat-gentle slope gradient and elevation less than 300 m, land use/land cover of crop, tree and rangeland, dendritic drainage network pattern, very good to good drainage density and low lineament density. This research also demonstrates the utility of GIS-based analytical hierarchy process (AHP) techniques in prioritizing thematic layers and generating reliable groundwater potential maps, in which Kwara State University is located within excellent-good groundwater potential zones.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe rapid population growth in and around Kwara State University has increased the necessity to evaluate groundwater potential zones, as such evaluations are critical for informed policymaking and effective management of water resources to ensure strategic resource allocation. Prioritizing water extraction infrastructure, such as boreholes in high-potential zones, can optimize supply efficiency and sustainable practices to prevent aquifer depletion, thereby ensuring long-term resource viability. From this investigation, it is feasible to conclude that this method serves as an orientation technique capable of streamlining decisions. However, the findings from this research can provide insights for conducting accurate future planning of groundwater regarding distribution, planning, consumption, and artificial recharge. The combination of remote sensing and GIS helps to provide indirect information about groundwater, aiding in drawing references to groundwater potential. While this offers a superficial understanding of groundwater resources, it should be complemented by further detailed geophysical fieldwork and other relevant studies to achieve comprehensive groundwater potential mapping within the University.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements:\\u003c/strong\\u003e The authors wish to show gratitude to everyone who contributes to the successful completion of this research.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contribution:\\u0026nbsp;\\u003c/strong\\u003eAll Authors participated in the desk work planning and reviewing of this research. Jimoh Ajadi and Gabriel Efomeh Omolaiye supervise the project and review the manuscript. \\u0026nbsp;Mosunrat Yusuf wrote the first manuscript; Mosunrat Yusuf, Sodiq Bamidele Adam and Ajibola Damilola Alade processed and interpreted the remote sensing and GIS data. \\u0026nbsp;All authors contributed to the interpretation, reading and approval of the final manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding:\\u003c/strong\\u003e No external funding\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e: All of the researchers\\u0026rsquo; consent was sought out and they consented to be published.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompleting interests:\\u003c/strong\\u003e The Authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics and Consent to Participate Declarations\\u003c/strong\\u003e: Not applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eClinical Trial number\\u003c/strong\\u003e: Not applicable\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eModibbo, M. A., Kana, A. A., Bello, I. E., \\u0026amp; Eya, A. I. (2025). An Integrated Remote Sensing, Geographic Information System And Analytical Hierarchy Process For Determination Of Groundwater Potential In Keffi-Gra And Environs. \\u003cem\\u003eFudma Journal Of Sciences\\u003c/em\\u003e, \\u003cem\\u003e9\\u003c/em\\u003e(1), 16\\u0026ndash;28. https://doi.org/10.33003/fjs-2025-0901-2769\\u003c/li\\u003e\\n\\u003cli\\u003eUpadhyay, R. K., Tripathi, G., Đurin, B., \\u0026Scaron;amanović, S., Cetl, V., Kishore, N., Sharma, M., Singh, S. K., Kanga, S., Wasim, M., Rai, P. K., \\u0026amp; Bhardwaj, V. (2023). Groundwater Potential Zone Mapping in the Ghaggar River Basin, North-West India, Using Integrated Remote Sensing and GIS Techniques. \\u003cem\\u003eWater\\u003c/em\\u003e, \\u003cem\\u003e15\\u003c/em\\u003e(5), 961. https://doi.org/10.3390/w15050961\\u003c/li\\u003e\\n\\u003cli\\u003eAjayakumar A., \\u0026amp; Rajesh Reghunath. (2025). Delineation of groundwater recharge zones in lateritic terrains using geospatial techniques. \\u003cem\\u003eDiscover Geoscience\\u003c/em\\u003e, \\u003cem\\u003e3\\u003c/em\\u003e(1). https://doi.org/10.1007/s44288-025-00110-z\\u003c/li\\u003e\\n\\u003cli\\u003eHamdan, M. S., Singh, R., Pathak, R., Kumari, S., \\u0026amp; Chauhan, V. (2024). Geospatial mapping of groundwater potential zones using multi-criteria decision-making AHP approach: A study of Kadugli district, south Kurdufan, Sudan. \\u003cem\\u003eJournal of African Earth Sciences\\u003c/em\\u003e, \\u003cem\\u003e223\\u003c/em\\u003e, 105513. https://doi.org/10.1016/j.jafrearsci.2024.105513\\u003c/li\\u003e\\n\\u003cli\\u003eMorgan, H., Hussien, H. M., Madani, A., \\u0026amp; Nassar, T. (2022). Delineating Groundwater Potential Zones in Hyper-Arid Regions Using the Applications of Remote Sensing and GIS Modeling in the Eastern Desert, Egypt. \\u003cem\\u003eSustainability\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(24), 16942\\u0026ndash;16942. https://doi.org/10.3390/su142416942\\u003c/li\\u003e\\n\\u003cli\\u003eUc Castillo, J. L., Mart\\u0026iacute;nez Cruz, D. A., Ramos Leal, J. A., Tuxpan Vargas, J., Rodr\\u0026iacute;guez Tapia, S. A., \\u0026amp; Mar\\u0026iacute;n Celestino, A. E. (2022). Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches. \\u003cem\\u003eWater\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(13), 2138. https://doi.org/10.3390/w14132138\\u003c/li\\u003e\\n\\u003cli\\u003eBulbula, S. T., \\u0026amp; Serur, A. B. (2024). Groundwater potential and recharge zone mapping using GIS and remote sensing techniques: the Melka Kunture Watershed in Ethiopia. \\u003cem\\u003eDiscover Sustainability\\u003c/em\\u003e, \\u003cem\\u003e5\\u003c/em\\u003e(1). https://doi.org/10.1007/s43621-024-00521-x\\u003c/li\\u003e\\n\\u003cli\\u003eDerdour, A., Benkaddour, Y., \\u0026amp; Bendahou, B. (2022). Application of remote sensing and GIS to assess groundwater potential in the transboundary watershed of the Chott-El-Gharbi (Algerian\\u0026ndash;Moroccan border). \\u003cem\\u003eApplied Water Science\\u003c/em\\u003e, \\u003cem\\u003e12\\u003c/em\\u003e(6). https://doi.org/10.1007/s13201-022-01663-x\\u003c/li\\u003e\\n\\u003cli\\u003eSaravanan, S., Saranya, T., Abijith, D., Jacinth, J. J., \\u0026amp; Singh, L. (2021). Delineation of groundwater potential zones for Arkavathi sub-watershed, Karnataka, India using remote sensing and GIS. \\u003cem\\u003eEnvironmental Challenges\\u003c/em\\u003e, \\u003cem\\u003e5\\u003c/em\\u003e, 100380. https://doi.org/10.1016/j.envc.2021.100380\\u003c/li\\u003e\\n\\u003cli\\u003eAhmed, A., Alrajhi, A., \\u0026amp; Alquwaizany, A. S. (2021). Identification of Groundwater Potential Recharge Zones in Flinders Ranges, South Australia Using Remote Sensing, GIS, and MIF Techniques. \\u003cem\\u003eWater\\u003c/em\\u003e, \\u003cem\\u003e13\\u003c/em\\u003e(18), 2571. https://doi.org/10.3390/w13182571\\u003c/li\\u003e\\n\\u003cli\\u003eAlly, A. M., Yan, J., Bennett, G., Lyimo, N. N., \\u0026amp; Mayunga, S. D. (2024). Assessment of groundwater potential zones using remote sensing and GIS-based fuzzy analytical hierarchy process (F-AHP) in Mpwapwa District, Dodoma, Tanzania. \\u003cem\\u003eGeosystems and Geoenvironment\\u003c/em\\u003e, \\u003cem\\u003e3\\u003c/em\\u003e(1), 100232. https://doi.org/10.1016/j.geogeo.2023.100232\\u003c/li\\u003e\\n\\u003cli\\u003eEl-Sorogy, A. S., Alharbi, T., Al-Kahtany, K., Rikan, N., \\u0026amp; Salem, Y. (2024). Identification and Validation of Groundwater Potential Zones in Al-Madinah Al-Munawarah, Western Saudi Arabia Using Remote Sensing and GIS Techniques. \\u003cem\\u003eWater\\u003c/em\\u003e, \\u003cem\\u003e16\\u003c/em\\u003e(23), 3421. https://doi.org/10.3390/w16233421\\u003c/li\\u003e\\n\\u003cli\\u003eRoy, D., Barman, S., Mandal, G., Mitra, R., Sarkar, A., Hossain, G., Roy, P., Hussein Almohamad, Hazem Ghassan Abdo, \\u0026amp; Deepak Kumar Mandal. (2024). Extracting of prospective groundwater potential zones using remote sensing data, GIS, and multi-criteria decision-making approach in the Sub-Himalayan Dooars region of West Bengal, India. \\u003cem\\u003eApplied Water Science\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(4). https://doi.org/10.1007/s13201-024-02124-3\\u003c/li\\u003e\\n\\u003cli\\u003eBennett, G. (2024). Analysis of methods used to validate remote sensing and GIS-based groundwater potential maps in the last two decades: A review. \\u003cem\\u003eGeosystems and Geoenvironment\\u003c/em\\u003e, \\u003cem\\u003e3\\u003c/em\\u003e(1), 100245\\u0026ndash;100245. https://doi.org/10.1016/j.geogeo.2023.100245\\u003c/li\\u003e\\n\\u003cli\\u003eOsumeje, J. O., Eshimiakhe, D., Adetola Sunday Oniku, \\u0026amp; Lawal, K. M. (2024). Application of remote sensing and electrical resistivity technique for delineating groundwater potential in North Western Nigeria. \\u003cem\\u003eScientific Reports\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(1). https://doi.org/10.1038/s41598-024-69633-8\\u003c/li\\u003e\\n\\u003cli\\u003eYousaf, B., Javid, K., Mahmood, S., Habib, W., \\u0026amp; Hussain, S. (2024). Delineating groundwater potential zones using integrated remote sensing and GIS in Lahore, Pakistan. \\u003cem\\u003eEnvironmental Monitoring and Assessment\\u003c/em\\u003e, \\u003cem\\u003e196\\u003c/em\\u003e(10). https://doi.org/10.1007/s10661-024-13057-4\\u003c/li\\u003e\\n\\u003cli\\u003eGidafie, D., Nedaw, D., \\u0026amp; Azagegn, T. (2024). Integrated remote sensing and geographic information system overlay analysis for groundwater potential evaluation using AHP and fuzzy AHP: Southern sections of the western Afar rift margin and associated rift floor. \\u003cem\\u003eGroundwater for Sustainable Development\\u003c/em\\u003e, \\u003cem\\u003e26\\u003c/em\\u003e, 101310. https://doi.org/10.1016/j.gsd.2024.101310\\u003c/li\\u003e\\n\\u003cli\\u003eKiran, G. S., Kaur, R., \\u0026amp; Agradeep Mohanta. (2024). A hybrid approach: remote sensing, analytic hierarchy process and geographic information system for groundwater potential mapping in Dediapada, India. \\u003cem\\u003eEnvironmental Science and Pollution Research\\u003c/em\\u003e. https://doi.org/10.1007/s11356-024-35666-9\\u003c/li\\u003e\\n\\u003cli\\u003eBawallah, M. A., Adebayo, A., Ilugbo, S. O., Olufemi, B., Alagbe, O. A., \\u0026amp; Olasunkanmi, K. N. (2018). Evaluation of Groundwater Prospect in a Clay Dominated Environment of Central Kwara State, Southwestern Nigeria. \\u003cem\\u003eInternational Journal of Advanced Engineering Research and Science\\u003c/em\\u003e, \\u003cem\\u003e5\\u003c/em\\u003e(6), 45\\u0026ndash;56. https://doi.org/10.22161/ijaers.5.6.8\\u003c/li\\u003e\\n\\u003cli\\u003eSuryawanshi, S. L., Singh, P. K., Kothari, M., Singh, M., Yadav, K. K., \\u0026amp; Gupta, T. (2024). Assessment of groundwater potential zones for hard rock area of sabi river basin using an integrated approach of remote sensing, GIS and AHP techniques. \\u003cem\\u003ePhysics and Chemistry of the Earth, Parts A/B/C\\u003c/em\\u003e, \\u003cem\\u003e137\\u003c/em\\u003e, 103820. https://doi.org/10.1016/j.pce.2024.103820\\u003c/li\\u003e\\n\\u003cli\\u003eVidya, K. M., Manoharan, A. N., Suchitra, B., \\u0026amp; Shyni, M. (2024). Combination of remote sensing, GIS, AHP techniques and geophysical data to delineate groundwater potential zones in the Shiriya River Basin, South India. \\u003cem\\u003eGeosystems and Geoenvironment\\u003c/em\\u003e, \\u003cem\\u003e3\\u003c/em\\u003e(4), 100294. https://doi.org/10.1016/j.geogeo.2024.100294\\u003c/li\\u003e\\n\\u003cli\\u003eArya, P., Jhariya, D. C., Singh, C. K., \\u0026amp; N Vishwakarma. (2025). Identification of groundwater potential zones using remote sensing and geographic information systems with multi-criteria decision-making techniques in the Jonk River Watershed, Chhattisgarh, India. \\u003cem\\u003eJournal of Earth System Science\\u003c/em\\u003e, \\u003cem\\u003e134\\u003c/em\\u003e(1). \\u003ca href=\\\"https://doi.org/10.1007/s12040-025-02516-2\\\"\\u003ehttps://doi.org/10.1007/s12040-025-02516-2\\u003c/a\\u003e\\u003c/li\\u003e\\n\\u003cli\\u003eGanesan, S., \\u0026amp; Subramaniyan, A. (2024). Identification of groundwater potential zones using multi-influencing factor method, GIS and remote sensing techniques in the hard rock terrain of Madurai district, southern India. \\u003cem\\u003eSustainable Water Resources Management\\u003c/em\\u003e, \\u003cem\\u003e10\\u003c/em\\u003e(2). https://doi.org/10.1007/s40899-024-01036-z\\u003c/li\\u003e\\n\\u003cli\\u003eElsebaie, I. H., Kawara, A. Q., \\u0026amp; Alnahit, A. O. (2025). Delineation of Groundwater Recharge Potential Zones Using GIS: A Case Study for Yalamlam Watershed in Saudi Arabia. \\u003cem\\u003eWater Science and Technology Library\\u003c/em\\u003e, 305\\u0026ndash;315. https://doi.org/10.1007/978-3-031-80520-2_17\\u003c/li\\u003e\\n\\u003cli\\u003eAkudo, E. O., Ifediegwu, S. I., Ahmed, J. B., \\u0026amp; Aigbadon, G. O. (2024). Identifying Groundwater Potential Regions in Sokoto Basin, Northwestern Nigeria: An Integrated Remote Sensing, GIS, and MIF Techniques. \\u003cem\\u003eJournal of the Indian Society of Remote Sensing\\u003c/em\\u003e, \\u003cem\\u003e52\\u003c/em\\u003e(6), 1201\\u0026ndash;1222. https://doi.org/10.1007/s12524-024-01872-8\\u003c/li\\u003e\\n\\u003cli\\u003eNaeem, M., Farid, H. U., Muhammad Arbaz Madni, Albano, R., Muhammad Azhar Inam, Shoaib, M., Shoaib, M., Rashid, T., Aqsa Dilshad, \\u0026amp; Ahmad, A. (2024). GIS-Based Analytical Hierarchy Process for Identifying Groundwater Potential Zones in Punjab, Pakistan. \\u003cem\\u003eISPRS International Journal of Geo-Information\\u003c/em\\u003e, \\u003cem\\u003e13\\u003c/em\\u003e(9), 317\\u0026ndash;317. https://doi.org/10.3390/ijgi13090317\\u003c/li\\u003e\\n\\u003cli\\u003eAdeleke, E. (2024). Climate Change in Kwara State, Nigeria: Evidence of Rainfall and Temperature Variations. \\u003cem\\u003eColombo Geographer\\u003c/em\\u003e, \\u003cem\\u003e2\\u003c/em\\u003e(1), 2024. https://arts.cmb.ac.lk/wp-content/uploads/2024/07/Adeleke.pdf\\u003c/li\\u003e\\n\\u003cli\\u003eAkpenpuun, T., \\u0026amp; Rasheed Amao Busari. (2013). Impact of Climate on Tuber Crops Yield in Kwara State, Nigeria. \\u003cem\\u003eAmerican International Journal of Contemporary Research\\u003c/em\\u003e, \\u003cem\\u003e3\\u003c/em\\u003e(10), 6. https://www.researchgate.net/publication/351745190_Impact_of_Climate_on_Tuber_Crops_Yield_in_Kwara_State_Nigeria?enrichId=rgreq-9350783b292ddff12cc29e02185f91d0-XXX\\u0026amp;enrichSource=Y292ZXJQYWdlOzM1MTc0NTE5MDtBUzoxMTQzMTI4MTIyODQxMjgxMkAxNzA5OTg0NjA5Njk2\\u0026amp;el=1_x_3\\u0026amp;_esc=publicationCoverPdf\\u003c/li\\u003e\\n\\u003cli\\u003eOlasunkanmi, N. K., Usman, Z. M., \\u0026amp; Jimoh, A. A. (2023). Investigation of groundwater quality around municipal waste disposal site in Malete southwestern Nigeria. \\u003cem\\u003eArabian Journal of Geosciences\\u003c/em\\u003e, \\u003cem\\u003e16\\u003c/em\\u003e(4). https://doi.org/10.1007/s12517-023-11359-4\\u003c/li\\u003e\\n\\u003cli\\u003eAjadi, J., Dada, S., Nnabo, P. N., \\u0026amp; Owoeye, B. (2018). Lithostructural description and metalogeny of Alagbede gold deposit, West Central Nigeria. \\u003cem\\u003eJournal of Environment and Earth Science\\u003c/em\\u003e, \\u003cem\\u003e8\\u003c/em\\u003e(5), 115\\u0026ndash;132. https://www.researchgate.net/publication/336180630_Lithostructural_description_and_metalogeny_of_Alagbede_gold_deposit_West_Central_Nigeria\\u003c/li\\u003e\\n\\u003cli\\u003eObaje, N. G. (2009). Geology and Mineral Resources of Nigeria. In \\u003cem\\u003eLecture Notes in Earth Sciences\\u003c/em\\u003e. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-92685-6\\u003c/li\\u003e\\n\\u003cli\\u003eRahaman, M. (1976). \\u003cem\\u003eReview of The Basement Geology Of South-Western Nigeria.\\u003c/em\\u003e\\u003c/li\\u003e\\n\\u003cli\\u003eFatoyinbo A.A., Ishola K.S., Okolie, C. J., Daramola, O. E., HamidMosaku, I. A., O.A. Ipadeola, I.D. Arungwa, C.O. Ogbeta, \\u0026amp; S.E. Erharhaghen. (2024). Integration of geospatial and geophysical data for assessing borehole conditions at the University of Ilorin, North-Central, Nigeria. \\u003cem\\u003eNigerian Journal of Technology\\u003c/em\\u003e, \\u003cem\\u003e43\\u003c/em\\u003e(3), 557\\u0026ndash;567. https://www.ajol.info/index.php/njt/article/view/281379\\u003c/li\\u003e\\n\\u003cli\\u003eIshola, K. S., Fatoyinbo, A. A., Hamid-Mosaku, A. I., Okolie, C. J., Daramola, O. E., \\u0026amp; Lawal, T. O. (2023). Groundwater potential mapping in hard rock terrain using remote sensing, geospatial and aeromagnetic data. \\u003cem\\u003eGeosystems and Geoenvironment\\u003c/em\\u003e, \\u003cem\\u003e2\\u003c/em\\u003e(1), 100107. https://doi.org/10.1016/j.geogeo.2022.100107\\u003c/li\\u003e\\n\\u003cli\\u003eAl-Djazouli, M. O., Elmorabiti, K., Rahimi, A., Amellah, O., \\u0026amp; Fadil, O. A. M. (2020). Delineating of groundwater potential zones based on remote sensing, GIS and analytical hierarchical process: a case of Waddai, eastern Chad. \\u003cem\\u003eGeoJournal\\u003c/em\\u003e, \\u003cem\\u003e86\\u003c/em\\u003e(4), 1881\\u0026ndash;1894. https://doi.org/10.1007/s10708-020-10160-0\\u003c/li\\u003e\\n\\u003cli\\u003eRahman, Md. M., AlThobiani, F., Shahid, S., Virdis, S. G. P., Kamruzzaman, M., Rahaman, H., Momin, Md. A., Hossain, Md. B., \\u0026amp; Ghandourah, E. I. (2022). GIS and Remote Sensing-Based Multi-Criteria Analysis for Delineation of Groundwater Potential Zones: A Case Study for Industrial Zones in Bangladesh. \\u003cem\\u003eSustainability\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(11), 6667. https://doi.org/10.3390/su14116667\\u003c/li\\u003e\\n\\u003cli\\u003eSresto, M. A., Siddika, S., Haque, Md. N., \\u0026amp; Saroar, M. (2021). Application of fuzzy analytic hierarchy process and geospatial technology to identify groundwater potential zones in north-west region of Bangladesh. \\u003cem\\u003eEnvironmental Challenges\\u003c/em\\u003e, \\u003cem\\u003e5\\u003c/em\\u003e, 100214. https://doi.org/10.1016/j.envc.2021.100214\\u003c/li\\u003e\\n\\u003cli\\u003eChaudhry, A. K., Kumar, K., \\u0026amp; Alam, Mohd. A. (2019). Mapping of groundwater potential zones using the fuzzy analytic hierarchy process and geospatial technique. \\u003cem\\u003eGeocarto International\\u003c/em\\u003e, 1\\u0026ndash;22. https://doi.org/10.1080/10106049.2019.1695959\\u003c/li\\u003e\\n\\u003cli\\u003eDas, B., Pal, S. C., Malik, S., \\u0026amp; Chakrabortty, R. (2018). Modeling groundwater potential zones of Puruliya district, West Bengal, India using remote sensing and GIS techniques. \\u003cem\\u003eGeology, Ecology, and Landscapes\\u003c/em\\u003e, 1\\u0026ndash;15. https://doi.org/10.1080/24749508.2018.1555740\\u003c/li\\u003e\\n\\u003cli\\u003eYimer, F., Messing, I., Ledin, S., \\u0026amp; Abdelkadir, A. (2008). Effects of different land use types on infiltration capacity in a catchment in the highlands of Ethiopia. \\u003cem\\u003eSoil Use and Management\\u003c/em\\u003e, \\u003cem\\u003e24\\u003c/em\\u003e(4), 344\\u0026ndash;349. https://doi.org/10.1111/j.1475-2743.2008.00182.x\\u003c/li\\u003e\\n\\u003cli\\u003eGodif, G., \\u0026amp; Manjunatha, B. R. (2023). Delineation of groundwater potential zones using remotely sensed data and GIS-based analytical hierarchy process: Insights from the Geba river basin in Tigray, Northern Ethiopia. \\u003cem\\u003eJournal of Hydrology: Regional Studies\\u003c/em\\u003e, \\u003cem\\u003e46\\u003c/em\\u003e, 101355. https://doi.org/10.1016/j.ejrh.2023.101355\\u003c/li\\u003e\\n\\u003cli\\u003eUpwanshi, M., Damry, K., Pathak, D., Tikle, S., \\u0026amp; Das, S. (2023). Delineation of potential groundwater recharge zones using remote sensing, GIS, and AHP approaches. \\u003cem\\u003eUrban Climate\\u003c/em\\u003e, \\u003cem\\u003e48\\u003c/em\\u003e, 101415. https://doi.org/10.1016/j.uclim.2023.101415\\u003c/li\\u003e\\n\\u003cli\\u003eSingh, P., Hasnat, M., Rao, M. N., \\u0026amp; Singh, P. (2020). Fuzzy- Analytical Hierarchy Process based GIS Modelling for Groundwater Prospective Zones in Prayagraj, India. \\u003cem\\u003eGroundwater for Sustainable Development\\u003c/em\\u003e, 100530. https://doi.org/10.1016/j.gsd.2020.100530\\u003c/li\\u003e\\n\\u003cli\\u003eKumar, M., Singh, P., \\u0026amp; Singh, P. (2022). Integrating GIS and remote sensing for delineation of groundwater potential zones in Bundelkhand Region, India. \\u003cem\\u003eThe Egyptian Journal of Remote Sensing and Space Science\\u003c/em\\u003e, \\u003cem\\u003e25\\u003c/em\\u003e(2), 387\\u0026ndash;404. https://doi.org/10.1016/j.ejrs.2022.03.003\\u003c/li\\u003e\\n\\u003cli\\u003eSrinivas, G. S., Kumar, P., \\u0026amp; P. Jyothi. (2021). Demarcation of groundwater potential zones using analytical hierarchical process in Cheyyeru watershed, India. \\u003cem\\u003eInternational Journal of Energy and Water Resources\\u003c/em\\u003e, \\u003cem\\u003e6\\u003c/em\\u003e(2), 149\\u0026ndash;160. https://doi.org/10.1007/s42108-021-00127-3\\u003c/li\\u003e\\n\\u003cli\\u003eNag, S. K., \\u0026amp; Kundu, A. (2018). Application of remote sensing, GIS and MCA techniques for delineating groundwater prospect zones in Kashipur block, Purulia district, West Bengal. \\u003cem\\u003eApplied Water Science\\u003c/em\\u003e, \\u003cem\\u003e8\\u003c/em\\u003e(1). https://doi.org/10.1007/s13201-018-0679-9\\u003c/li\\u003e\\n\\u003cli\\u003eAhmadi, H., Kaya, O. A., Babadagi, E., Savas, T., \\u0026amp; Pekkan, E. (2020). GIS-Based Groundwater Potentiality Mapping Using AHP and FR Models in Central Antalya, Turkey. \\u003cem\\u003eEnvironmental Sciences Proceedings\\u003c/em\\u003e, \\u003cem\\u003e5\\u003c/em\\u003e(1), 11. https://doi.org/10.3390/iecg2020-08741\\u003c/li\\u003e\\n\\u003cli\\u003eArulbalaji, P., Padmalal, D., \\u0026amp; Sreelash, K. (2019). GIS and AHP Techniques Based Delineation of Groundwater Potential Zones: a case study from Southern Western Ghats, India. \\u003cem\\u003eScientific Reports\\u003c/em\\u003e, \\u003cem\\u003e9\\u003c/em\\u003e(1). https://doi.org/10.1038/s41598-019-38567-x\\u003c/li\\u003e\\n\\u003cli\\u003eMitra, R., \\u0026amp; Roy, D. (2022). Delineation of groundwater potential zones through the integration of remote sensing, geographic information system, and multi-criteria decision-making technique in the sub-Himalayan foothills region, India. \\u003cem\\u003eInternational Journal of Energy and Water Resources\\u003c/em\\u003e. https://doi.org/10.1007/s42108-022-00181-5\\u003c/li\\u003e\\n\\u003cli\\u003eMoodley, T., Seyam, M., Abunama, T., \\u0026amp; Bux, F. (2022). Delineation of groundwater potential zones in KwaZulu-Natal, South Africa using remote sensing, GIS and AHP. \\u003cem\\u003eJournal of African Earth Sciences\\u003c/em\\u003e, \\u003cem\\u003e193\\u003c/em\\u003e, 104571. https://doi.org/10.1016/j.jafrearsci.2022.104571\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"discover-geoscience\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)\",\"snPcode\":\"44288\",\"submissionUrl\":\"https://submission.nature.com/new-submission/44288\",\"title\":\"Discover Geoscience\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Discover Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6458804/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6458804/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"This study combined remote sensing and GIS techniques to evaluate the groundwater potential zones at Kwara State University (KWASU) by assessing groundwater resources using the Analytical Hierarchy Process (AHP). This involved integrating and overlaying thematic layers through the weight overlay analysis tool to assign weights and rank these layers based on their characteristics or influence on groundwater potential and recharge within the institution. The thematic layers used included rainfall, land use/land cover, slope, elevation, drainage network, drainage density, lineament, and lineament density, all significantly impacting groundwater distribution. The results revealed that Kwara State University is situated in an area with higher rainfall of approximately 1430 mm, a flat-gentle slope gradient, and an elevation of less than 300 m, with land use/land cover comprising crops, trees, and rangeland, alongside a dendritic drainage network pattern, very good to good drainage density, and low lineament density. The Analytical Hierarchy Process evaluated and categorised Kwara State University as an excellent to good groundwater potential zone, indicating that the delineation of groundwater resources is reliable. This study provides insights for future groundwater management planning and further recommends fieldwork studies to achieve detailed groundwater potential mapping within Kwara State University.\",\"manuscriptTitle\":\"Evaluation of Groundwater Resources Using Remote Sensing and Gis Techniques Within Kwara State University, Malete, Nigeria\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-06-02 08:46:58\",\"doi\":\"10.21203/rs.3.rs-6458804/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-06-24T19:06:39+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-07T05:14:29+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-05T13:58:00+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"333520751425486378538868608829686442551\",\"date\":\"2025-06-04T05:13:14+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"81295991911033156750462221936612332017\",\"date\":\"2025-06-03T21:53:48+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-02T19:57:40+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"295452388892127328249119922287175295555\",\"date\":\"2025-06-02T18:32:21+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"8681446955113500130835783385884272399\",\"date\":\"2025-06-02T00:55:37+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"217449151143896847345716970905706924363\",\"date\":\"2025-06-01T06:49:28+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"149736266737770272837249161284165014051\",\"date\":\"2025-06-01T04:43:02+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"159422679496392061331002616986474204745\",\"date\":\"2025-05-30T03:30:34+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-05-29T21:27:10+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-04-29T04:30:52+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-04-29T04:28:59+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Discover Geoscience\",\"date\":\"2025-04-16T02:27:26+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"discover-geoscience\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [Discover Geoscience](https://www.springer.com/journal/44288)\",\"snPcode\":\"44288\",\"submissionUrl\":\"https://submission.nature.com/new-submission/44288\",\"title\":\"Discover Geoscience\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Discover Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"3c6fa156-78c3-403e-adc5-b95bdb305b64\",\"owner\":[],\"postedDate\":\"June 2nd, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-09-11T05:38:14+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2025-06-02 08:46:58\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6458804\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6458804\",\"identity\":\"rs-6458804\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}