Modeling of aquifer geo-hydraulic characteristics with geo-electrical methods at a major coastal aquifer system in Uyo, southern Nigeria

Abstract

Characterization of aquifer geo-hydraulic properties is essential for groundwater management and conservation. This work demonstrates the use of electrical resistivity surveying data in the characterization of important geo-hydraulic properties within a major coastal aquifer in southern Nigeria. Geo-electrical data acquired along profile lines with the use of Schlumberger array configuration were used to determine the aquifer geo-hydraulic parameters such as aquifer resistivity ρb, water resistivity ρw, porosity Φ, formation factor F, hydraulic conductivity K, transmissivity T, permeability Kp, and tortuosity τ. The resistivity inversion models delineated the occurrence of four lithological layers, with resistivity of the geo-layers ranging from 2.4 to 4,393 Ω m. Contour maps were created to show the distribution of the various geo-electrical and geo-hydraulic parameters over the study area. Regression curves showing the relationship between the geo-hydraulic parameters were generated and used to generate empirical relationships between the parameters. The empirical formulas developed for these geo-hydraulic parameters will aid in future work seeking to characterize aquifer zones and model aquifer geo-hydraulic units. In all, electrical resistivity surveying was found to be a noninvasive, cost-effective, and efficient method of characterizing aquifer geo-hydraulic properties via nonpoint geo-electrical data collected over the earth's surface.

Volumetric estimation of groundwater reserve in Akwa Ibom State University main campus, southern Nigeria using surficial resistivity measurements

“…This was attainable by expunging points considered as outliers and determining the average of the ρs values obtained at the crossover points with the dominant trend maintained (George et al, 2017(George et al, , 2022aEkanem et al, 2020Ekanem et al, , 2022a. The curve smoothening was essential to reduce the root mean square errors (RMSE) in the later stage of computer assisted interpretation, which was accomplished in this research by using the WINRESIST computer software (Evans et al, 2015, Ekanem 2021, 2022aUdosen et al, 2023Udosen et al, , 2024c. The smoothened VES curves were supplied as inputs to the software, which uses the least-squares inversion technique to compute a theoretical resistivity model (Vander Velpen and Sporry 1993).…”