A GIS-Based Transmissivity-Constrained Frequency Ratio Approach for Groundwater Potential Assessment in Basement Terrain
DOI:
https://doi.org/10.63746/njtd.v23i2.4103Keywords:
Frequency Ratio model, Transmissivity, Groundwater potential, GIS, Basement complexAbstract
: Groundwater potential assessment in crystalline basement terrains is challenging due to heterogeneous subsurface conditions and limited recharge pathways. This study applied a transmissivity-constrained Frequency Ratio (FR) model within a Geographic Information System (GIS) framework to delineate groundwater potential zones (GPZs) in southwestern Nigeria. A total of 150 Vertical Electrical Sounding (VES) datasets were analyzed, of which 88 points with transmissivity >15 m²/d were considered hydraulically effective and used for model calibration. Twelve thematic layers—elevation, lithology, slope, drainage density, surface and subsurface lineament densities, geomorphology, curvature, topographic wetness index, soil texture, land use/land cover, and depth to fracture—were integrated to evaluate their influence on transmissivity. The FR analysis revealed that subsurface lineament density, lithology, and drainage density exerted the strongest control on transmissivity (FR > 2.5), indicating a high likelihood of groundwater occurrence in these classes. In contrast, steep slopes and high drainage density areas (FR < 1.0) showed limited groundwater potential. The resulting groundwater potential prediction map (GwPPM) classifies about 11.35% of the zone as very low potential, while 30.17%, 45.40% and 13.08% are categorized as low, moderate and high potential zones, respectively. Moderate-to-high potential zones, mainly around Igede-Ekiti and Iyin-Ekiti, correspond to highly fractured granitic terrains with gentle slopes and low drainage density. Validation with borehole yield data yielded ~80% accuracy, confirming model reliability. These results demonstrate that integrating transmissivity with FR-based GIS modeling provides an effective approach for groundwater assessment and supports sustainable exploration in basement terrains.
References
Adiat, K. A. N.; Ajayi, O. F.; Akinlalu, A. A. and Tijani, I. B. (2020). Prediction of groundwater level in basement complex terrain using artificial neural network: a case of Ijebu-Jesa, southwestern Nigeria. Applied Water Science, 10(1), 8. https://link.springer.com/article/10.1007/s13201-019-1094-6. SpringerLink
Adiat, K. A. N.; Adegoroye, A. A.; Adebiyi, A. D., Akeredolu, B. E. and Akinlalu, A. A. (2019). Comparative assessment of aquifer susceptibilities to contamination using geophysical and hydrochemical data. Heliyon, 5 (5), e01499. https://doi.org/10.1016/j.heliyon.2019.e01499.
Agbemuko Ojo, S.; Abam, T. K.; Tamunobereton-Ari, I. and Amakiri, A. R. C. (2021). Hydrogeological and Geophysical Investigation of Ground Water Potentials in Basement Terrain of Ado Ekiti, Southwestern Nigeria. IOSR Journal of Applied Geology and Geophysics 9(4): 11–25. https://iosrjournals.org/iosr-jagg/papers/Vol.%209%20Issue%204/Ser-2/B0904021125.pdf.
Chandra, S.; Auken, E.; Maurya, P. K.; Ahmed, S. and Verma, S. K. (2019). Large scale mapping of fractures and groundwater pathways in crystalline hardrock by AEM. Scientific Reports, 9 (1), 398. https://doi.org/10.1038/s41598-018-36153-1
Das, S. and Pardeshi, S. D. (2018). Integration of different influencing factors in GIS to delineate groundwater potential areas using IF and FR techniques: a study of Pravara basin, Maharashtra, India. Applied Water Science, 8 (7), 197. https://www.researchgate.net/publication/328102974_Integration_of_different_influencing_factors_in_GIS_to_delineate_groundwater_potential_areas_using_IF_and_FR_techniques_a_study_of_Pravara_basin_Maharashtra_India
Driscoll, F.G. (1986). Groundwater and wells (2nd ed.). Johnson Filtration Systems.
Fernandes, A. J. (2023). Structural geology applied to fractured aquifer characterization. Groundwater Project. https://doi.org/10.21083/978-1-77470-009-9
Heigold, P. C.; Gilkeson, R. H.; Cartwright, K. and Reed, P. C. (1979). Aquifer transmissivity from surficial electrical methods. Ground Water, 17 (4): 338–345. https://doi.org/10.1111/j.1745-6584.1979.tb03325.x
Ige, O. O.; Ameh, H. O. and Olaleye, I. M. (2021). Borehole inventory, groundwater potential and water quality studies in Ayede Ekiti, Southwestern Nigeria. Discover Water, 1 (1), 2. https://link.springer.com/article/10.1007/s43832-020-00001-z.
Jenks, G. F. (1967). The data model concept in statistical mapping. International Yearbook of Cartography, 7, 186–190.
Krásný, J., 1993. Classification of transmissivity magnitude and variation. Groundwater, 31(2), pp.230-236, Dublin, Ohio.
Lachassagne, P.; Dewandel, B. and Wyns, R. (2021). Hydrogeology of weathered crystalline/hard-rock aquifers—guidelines for the operational survey and management of their groundwater resources. Hydrogeology Journal, 29 (8): 2561-2594. https://doi.org/10.1007/s10040-021-02339-7
MacDonald, A. M.; Bonsor, H. C.; Dochartaigh, B. É. Ó. and Taylor, R. G. (2012). Quantitative maps of groundwater resources in Africa. Environmental Research Letters, 7 (2), 024009.
Moore, I. D.; Grayson, R. B. and Ladson, A. R. (1991). Digital terrain modelling: A review of hydrological, geomorphological, and biological applications. Hydrological Processes, 5 (1): 3-30. https://doi.org/10.1002/hyp.3360050103
Moshe, A. and Beza, M. (2024). Assessment of groundwater potential zones using GIS-based multicriteria decision analysis: a case study on Enemor and Ener Woreda, Central Ethiopia Region. H2Open Journal, 7 (3): 286-302. https://doi.org/10.2166/h2oj.2024.020
Naghibi, S. A.; Pourghasemi, H. R. and Dixon, B. (2016). GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran. Environmental monitoring and assessment, 188 (1), 44. https://opus.lib.uts.edu.au/bitstream/10453/130841/4/Manuscript%20Clean.pdf
Nazaripour, H.; Sedaghat, M.; Shafaie, V. and Movahedi Rad, M. (2024). Strategic assessment of groundwater potential zones: a hybrid geospatial approach. Applied Water Science, 14 (8), 185. https://doi.org/10.1007/s13201-024-02243-x
Offodile, M. E. (1983). The occurrence and exploitation of groundwater in Nigeria basement complex. Journal of Mining and Geology, 20 (1 & 2): 131–146.
Offodile, M. E. (2002). Ground water study and development in Nigeria. Mecon Geology & Eng. Services. https://www.scirp.org/reference/referencespapers?referenceid=2826344.
Olomo, O. K.; Danga, O. A. and Aliyu, A. O. (2025). Exploration of quality groundwater through lineament delineation in Okene and its surroudings. Geosystems and Geoenvironment, 4 (1), 100350. https://doi.org/10.1016/j.geogeo.2024.100350
Olorunfemi, M. O. and Fasuyi, S. A. (1993). Aquifer types and the geoelectric/hydrogeologic characteristics of part of the central basement terrain of Nigeria (Niger State). Journal of African Earth Sciences, 16: 309–317.
https://www.sciencedirect.com/science/article/abs/pii/089953629390051Q.
Olorunfemi, M. O. and Olorunniwo, M. A. (1985). Geoelectric parameters and aquifer characteristics of some parts of southwestern Nigeria. Geologia Applicata e Idrogeologia, 20 (1): 99-109. https://www.researchgate.net/publication/248345801.
Oyedele, A. A.; Ayodele, O. S. and Olabode, O. F. (2019). Groundwater quality assessment and characterization of shallow basement aquifers in parts of ado ekiti metropolis, Southwestern Nigeria. SN applied Sciences, 1 (7), 669. https://link.springer.com/article/10.1007/s42452-019-0683-1.
Pourghasemi, H. R. and Beheshtirad, M. (2015). Assessment of a data-driven evidential belief function model and GIS for groundwater potential mapping in the Koohrang Watershed, Iran. Geocarto International. DOI: 10.1080/10106049.2014.966161.
Pourghasemi, H. R. and Pourtaghi, Z. S. (2014). GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, Iran. Hydrogeology Journal, 22 (3): 643-662. DOI: 10.1007/s10040-013-1089-6.
Rahim, O. A.; Yin, H.; Ullah, S. and Durrani, A. N. (2025). Delineation of groundwater potential zones and recharge using multi-source big data and systematic analysis approach. Sustainable Futures, 100872. https://doi.org/10.1016/j.sftr.2025.100872
Rahmati, O.; Nazari Samani, A.; Mahdavi, M.; Pourghasemi, H. R. and Zeinivand, H. (2015). Groundwater potential mapping at Kurdistan region of Iran using analytic hierarchy process and GIS. Arabian Journal of Geosciences, 8 (9): 7059-7071.
https://www.sciencedirect.com/science/article/pii/S2212429216301161
Todd, D.K. and Mays, L.W. (2005). Groundwater hydrology (3rd ed.). John Wiley and Sons.
World Health Organization. (2004). Guidelines for drinking-water quality (Vol. 1). World health organization. https://www.who.int/publications/i/item/9789241549950
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