Abstract
Groundwater exploration in basement terrain can be somewhat challenging. Aquifer parameters like hydraulic conductivity and transmissivity can help in predicting groundwater potential zones in basement terrains. The vertical electrical sounding investigation that involved the Schlumberger configuration was employed to map the subsurface layers within the crystalline basement of the Obudu Complex, southeastern Nigeria. Secondary electrical resistivity data (Dar Zarrouk parameters) and a few pumping test-derived hydraulic parameters (i.e., transmissivity and hydraulic conductivity) were employed to develop empirical models. These models were used to predict hydraulic parameters at locations where only geoelectrical parameters (i.e., aquifer layer thickness and electrical resistivity) exist. Results showed that the northeastern part of the study area and areas located within zones of major faults displayed relatively higher values of hydraulic conductivity and transmissivity. The study area was classified into good, moderate, and poor groundwater potential aquifer zones. This integrated approach can be adopted in other areas with similar geology, where pumping test information is scarce or limited, as an alternative means of predicting aquifer properties and delineating groundwater potential zones for sustainable development and management of groundwater resources.
HIGHLIGHTS
Electrical resistivity technique was used to estimate aquifer parameters in the Obudu basement.
Empirical models derived were used to deduce these parameters elsewhere within the basement.
Results show a good fit where both pumping test-derived and geoelectrical predicted values exist.
It provided reliable site-specific and cost-effective alternatives to pumping test-derived parameters.
INTRODUCTION
The residents of the northeastern parts of Cross River State, Nigeria, domiciled within the basement terrain of the Obudu plateau, have over the years suffered from water scarcity problems. This critical situation is due to the nature of groundwater occurrence in basement terrain (Sarwade et al. 2007; Puranik 2009; Mondal 2021; Hassan et al. 2022), the low specific capacity of boreholes, consistent variations and discontinuities in aquifer properties (Limaye 2010), and other complexities such as irregular subsurface structural characteristics) associated with the exploration and quantitative assessment of the resources (Darko & Krásny 2003). Several boreholes within the area under investigation have failed due to limited knowledge and understanding of the structural, hydrogeological, hydrological, and geomorphological conditions of the basement environment by some borehole contractors (Mondal et al. 2008; Guevara-Mansilla et al. 2020; Ige et al. 2021). Groundwater transmission in fractured rocks depends mainly on the interconnectivity and extent of fractures, which are products of local and regional-scale tectonic activities, weathering, and lithology. Recent studies have shown that hard rock lithologies have specific individual hydrodynamic properties (Chandra et al. 2010; Courtois et al. 2010; Dewandel et al. 2011; Mondal et al. 2016; Ebong et al. 2021a; Lachassagne et al. 2021). For instance, the hydrodynamic properties of the saprolite layer have been reported to be capacitive, whereas the stratiform fissured layer displays transmissive properties (Lachassagne et al. 2021). In addition, unweathered granitic rocks possess low primary porosity and low hydraulic conductivity in contrast to metamorphic rocks that have lost their original hydrodynamic characteristics through metamorphic processes and have acquired secondary porosity that can facilitate groundwater transmission (Achtziger-Zupancik et al. 2017).
In this study, we propose to estimate aquifer parameters to facilitate groundwater exploration decisions and sustainable groundwater resources management within the northeastern part of Cross River State that constitutes the study area. These parameters include porosity, hydraulic conductivity, and transmissivity. Some of these parameters are derived conventionally from pumping tests, tracer test experiments, and grain size analysis from drilled boreholes. Although these methods are relatively expensive (i.e., the cost of borehole drilling and pumping tests), they have been used over the years and are relied upon to produce dependable results. Besides, the hydrogeologic conditions of interest for groundwater to occur in basement terrain, such as faults and fractures are to a certain extent localized (i.e., laterally limited) within the subsurface. Thus, aquifer properties derived from the pumping test of a particular borehole can result in inaccurate characterization when used to extrapolate or predict aquifer properties some few meters to a kilometer away from the borehole point (Sanderson & Zhang 1999). However, with few pumping test-derived hydraulic parameters and adequately constrained electrical resistivity sounding at these pumping test locations, empirical models can be developed and used to predict these parameters in the vicinity of the borehole and elsewhere within the study area where geoelectrical measurement information exists. The vertical electrical sounding (VES) technique when combined with hydrogeological measurements can provide a reliable alternative approach for the estimation of aquifer parameters. This approach has been utilized in resolving a variety of hydrological, hydrogeological, environmental and engineering problems (Obianwu et al. 2015; Guevara et al. 2017; Akpan et al. 2018; George et al. 2018; Arétouyap et al. 2019; Ndubueze et al. 2019; Asfahani & Ahmad 2020; Ebong et al. 2021b, 2023; Haq et al. 2022; Karthik et al. 2022), vadose zone infiltration rates, groundwater protective capacity and vulnerability assessments (Mhamdi et al. 2015; Akpan et al. 2016; Hussain et al. 2017), and geohydraulic parameter estimation (Ebong et al. 2014; Vogelgesang et al. 2020; Mahmud et al. 2022). More so, Asfahani & Al-Fares (2021) provided reliable estimates of hydraulic parameters within the Quaternary basaltic aquifer in the Deir Al-Adas area, southern Syria. The less-expensive geoelectrical resistivity method constitutes a rapid and versatile procedure that does not disturb the environment in any significant manner and can provide reliable results when adequately constrained (Akpan et al. 2015; Ebong et al. 2021a). This cost-effective technique is frequently used to resolve groundwater-related problems where good electrical resistivity contrasts exist between the saturated and unsaturated layers. Also, it is suitable for environmental and hydrogeological surveys in both sedimentary basins and hard rock terrains (Aleke et al. 2018; Mahmud et al. 2022). In spite of these advantages, geophysical data are fraught with errors, albeit the data acquisition may have been performed under favorable conditions. The errors are introduced into the results due to the unresolved ambiguity problem associated with converting geophysical data into representative geological models (Ebong 2012). The application of lithologic and other information derived from nearby boreholes as constraints during the VES forward modeling process remarkably minimize the ambiguity problems associated with one–dimensional (1D) modeling (Ebong et al. 2017; Bahammou et al. 2021).
This study aims to improve water security by effectively locating sustainable groundwater target zones and developing an empirical-based technique for estimating aquifer parameters in fractured rocks. The objective of the study is to generate aquifer empirical models based on modeled electrical resistivity data and few available pumping test information and apply the empirical models to estimate aquifer hydraulic properties (such as transmissivity, hydraulic conductivity, and fractional porosity) of fractured basement aquifer in other locations within the study area.
LOCATION AND GEOLOGY
Location
Geology and hydrogeology
The dominant rocks within the OBC are grouped into the Migmatitic Gneiss Complex and the Pan-African Older Granites (Ebong et al. 2021a). These rocks include migmatites, gneisses, undifferentiated granites, and schists. Details of the nature and characteristics of these rocks are well documented (Ekwueme 1990, 2003; Ukwang et al. 2003). The gneissic rocks have been intruded by pegmatite in several locations (Ekwueme 1994). At other locations, the gneisses have been folded and refolded with enclosed xenoliths while in some locations where schists are dominant, intense shearing, and fracturing due to thermal contacts have been reported (Edem et al. 2016). Several weakly foliated boulders of garnet gneisses, charnockites, dolerite dykes on banded amphibolites having sharp contacts due to brittle deformation and massive quartz veins with multiple fractures have been reported (Oden et al. 2012; Ebong et al. 2021a).
Hydrogeologically, the study area depends on weathering and secondary tectonic activities for groundwater transmission and storage. Ebong et al. (2021a) identified potential aquifer types namely, the regolith aquifer type and the dolerite-intrusion-induced fracture-aquifer type within the OBC. Hence, the weathered and fractured zones constitute the main aquifer zones within the area and were mapped in this study. Since the aquifer zones are limited to the weathered and fractured column, which occur at relatively very shallow depths, the inhabitants of the area tend to depend on hand-dug wells and very few deep boreholes in the area which are often not functional, especially during the dry season. Edet & Okereke (2005) reported that the weathered overburden regolith (∼38 m thick on average) and fractured basement rock aquifers can provide average permeability and transmissivity of ∼7.5 × 10−1 m/day and 3.8 × 10−1 m2/day, respectively. Groundwater-specific capacity and yield estimated from lineament density within the regolith wells were in the range of 40–270 m3/day/m and 700–4,050 m3/day, respectively (Edet & Okereke 2005). Static water levels in the area vary between 5 and 15 m and depths of hand-dug wells range from a few meters to ∼15 m while tube wells may extend to ∼50 m (Okereke et al. 1995).
METHODOLOGY
Materials and methods
The VES technique that involves measuring the difference in potential between the potential electrode pair arising from current injected into the ground through the current electrode pair was employed in this investigation (Bhattacharya & Patra 1968; Binley 2015; Ahmed et al. 2022; Chibuike et al. 2023). The Integrated Geo Instruments and Services (IGIS) signal enhancement resistivity meter (model SSR-MP-ATS) was utilized in measuring the earth resistance within the shallow subsurface. Twenty-one electric soundings were carried out using the Schlumberger array with current electrode separation (AB) that ranged from 2 to 500 m and sometimes up to 600 m in areas where accessibility is unlimited. Consequently, the potential electrode pair (MN) separation ranged between 0.5 and 20 m. The quality of the VES data was generally good, but in dry grounds where the contact resistance was high, water was used to moisten the ground around the electrodes, to reduce the contact resistance and enhance the current input in such areas (Uhlemann et al. 2018; Ebong et al. 2021a). Water samples from boreholes and hand-dug wells closest to the VES points were collected and the electrical conductivity (EC) was measured using a hand-held conductivity meter.
Data analysis and interpretation
In anisotropic geological units, is >1 since electrical resistivity is greatest in the transverse direction (Yeboah-Forson & Whitman 2014). These parameters are used to characterize groundwater potential in hard rock environments where groundwater availability depends on weathered and fractured conduits.
One of the significance of the formation factor is that it can be employed in the estimation of hydraulic conductivity of the saturated medium (Kelly 1977). Hydraulic conductivity is the capacity of an aquifer to transmit water through fractures and pore spaces under the influence of hydraulic gradient (Lobo-Ferreira et al. 2005). It determines the ability of a geologic formation to transmit a unit volume of groundwater in unit time at the existing viscosity through a unit cross-sectional area, measured perpendicularly to the flow direction, under a hydraulic gradient of unit change in the head through a unit flow length (Lohman 1979; Maliva & Missimer 2012). In other words, it is a coefficient of permeability that measures the ease with which water flows through a medium and depends on the properties of the medium, such as pore fluid density and viscosity, and acceleration of gravity (Vukovic & Soro 1992). In fractured basement aquifers, hydraulic conductivity may vary from 0 to 1,000 m/day (Kruseman & de Ridder 1990; Gnanachandrasamy et al. 2019; Saravanan et al. 2019) and depends on the intrinsic permeability, fracture width, density and interconnectivity of fractures, and hydraulic gradient. The Kozeny–Carman method is widely used to derive hydraulic conductivity but falls short in heterogeneous strata (Zhu et al. 2016).
Based on the strong statistical significance of these models (i.e., the strong relationship between the variables), they can be applied at any location within the Obudu area and environs where geoelectrical data exist, to directly evaluate the transmissivity and hydraulic conductivity of the aquifer to enhance the selection of appropriate sites that can provide optimum groundwater yield to boreholes. The application of the models can be summarized in the following steps;
Step 1: Acquire geoelectrical data for the proposed survey area
Step 2: Compute the longitudinal conductance (S) of the formation
Step 3: Determine the transmissivity of the aquifer formation by substituting the computed longitudinal conductance value into Equation (9).
Step 4: Determine the hydraulic conductivity of the aquifer formation using Equation (11) from known saturated aquifer thickness.
However, if the formation factor is estimated based on Equations (7) and (8), then Equations (10) and (11) can be used to evaluate the hydraulic conductivity and transmissivity, respectively.
RESULTS
VES points . | Coordinates in degrees . | Resistivity (Ωm) . | Thickness (m) . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Longitude . | Latitude . | ρ1 . | ρ2 . | ρ3 . | ρ4 . | ρ5 . | h1 . | h2 . | h3 . | h4 . | |
1 | 9.248 | 6.638 | 715.6 | 44.4 | 150.5 | 1,508.7 | – | 0.7 | 12.8 | 27.5 | – |
2 | 9.178 | 6.621 | 147.3 | 38.6 | 214.1 | 9,427.5 | – | 1.3 | 4.8 | 49.5 | – |
3 | 9.041 | 6.524 | 149.2 | 28.2 | 437.7 | 1,039.7 | 1,426.7 | 1.1 | 5.1 | 10.3 | 25.6 |
4 | 9.208 | 6.642 | 181.2 | 567.8 | 143.0 | 2,401.5 | – | 0.3 | 4.6 | 35.4 | – |
5 | 9.080 | 6.539 | 430.6 | 3,020 | 270.0 | 943.1 | 1,684.3 | 0.9 | 4.1 | 17.3 | 36.3 |
6 | 9.200 | 6.611 | 215.3 | 58 | 208.1 | 1,146.2 | – | 1.8 | 12.6 | 45.9 | – |
7 | 9.294 | 6.619 | 232 | 137.8 | 30.0 | 137.1 | 438.5 | 0.6 | 2.6 | 15.7 | 25.9 |
8 | 9.311 | 6.634 | 157.1 | 14.1 | 100.0 | 1,535.0 | – | 3.3 | 6.6 | 36.5 | – |
9 | 9.138 | 6.637 | 105.3 | 805.9 | 252.0 | 2,278.6 | – | 0.2 | 12.5 | 36.3 | – |
10 | 9.051 | 6.566 | 1,381 | 353.3 | 142.8 | 1,468.8 | – | 2.4 | 9.0 | 19.7 | – |
11 | 9.196 | 6.597 | 327.4 | 37.3 | 272.7 | 1,802.7 | – | 2.2 | 4.3 | 35.1 | – |
12 | 9.095 | 6.554 | 1,073.5 | 273.1 | 154.7 | 1,127.3 | 4,546.2 | 1.3 | 4.3 | 34.2 | 50.1 |
13 | 9.099 | 6.568 | 1,281.4 | 321.2 | 420.0 | 362.0 | 2,099.8 | 1.0 | 4.3 | 18.7 | 38 |
14 | 9.417 | 6.518 | 336.9 | 889.7 | 495.3 | 3,329.3 | – | 0.2 | 13.8 | 24.3 | – |
15 | 9.126 | 6.591 | 1,493.1 | 144.7 | 1,624.2 | 1,348.8 | – | 5.9 | 11.0 | 27.3 | – |
16 | 9.191 | 6.558 | 744.5 | 228.3 | 1,139.0 | 878.3 | – | 1.2 | 35.9 | 6.0 | – |
17 | 9.184 | 6.545 | 685.5 | 236.39 | 1,558.1 | 1,911.4 | – | 2.2 | 7.5 | 14.0 | – |
18 | 9.245 | 6.687 | 214.6 | 62.2 | 277.3 | 681.4 | – | 1.1 | 7.0 | 28.1 | – |
19 | 9.251 | 6.699 | 161.2 | 51.3 | 155.4 | 3,632.6 | – | 1.4 | 6.5 | 35.5 | – |
20 | 9.193 | 6.649 | 884.6 | 483.3 | 156.4 | 2,295.3 | – | 1.9 | 8.4 | 16.0 | – |
21 | 9.025 | 6.637 | 34.0 | 130.0 | 225.2 | 1,240.6 | – | 2.9 | 6.7 | 10.2 | – |
VES points . | Coordinates in degrees . | Resistivity (Ωm) . | Thickness (m) . | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Longitude . | Latitude . | ρ1 . | ρ2 . | ρ3 . | ρ4 . | ρ5 . | h1 . | h2 . | h3 . | h4 . | |
1 | 9.248 | 6.638 | 715.6 | 44.4 | 150.5 | 1,508.7 | – | 0.7 | 12.8 | 27.5 | – |
2 | 9.178 | 6.621 | 147.3 | 38.6 | 214.1 | 9,427.5 | – | 1.3 | 4.8 | 49.5 | – |
3 | 9.041 | 6.524 | 149.2 | 28.2 | 437.7 | 1,039.7 | 1,426.7 | 1.1 | 5.1 | 10.3 | 25.6 |
4 | 9.208 | 6.642 | 181.2 | 567.8 | 143.0 | 2,401.5 | – | 0.3 | 4.6 | 35.4 | – |
5 | 9.080 | 6.539 | 430.6 | 3,020 | 270.0 | 943.1 | 1,684.3 | 0.9 | 4.1 | 17.3 | 36.3 |
6 | 9.200 | 6.611 | 215.3 | 58 | 208.1 | 1,146.2 | – | 1.8 | 12.6 | 45.9 | – |
7 | 9.294 | 6.619 | 232 | 137.8 | 30.0 | 137.1 | 438.5 | 0.6 | 2.6 | 15.7 | 25.9 |
8 | 9.311 | 6.634 | 157.1 | 14.1 | 100.0 | 1,535.0 | – | 3.3 | 6.6 | 36.5 | – |
9 | 9.138 | 6.637 | 105.3 | 805.9 | 252.0 | 2,278.6 | – | 0.2 | 12.5 | 36.3 | – |
10 | 9.051 | 6.566 | 1,381 | 353.3 | 142.8 | 1,468.8 | – | 2.4 | 9.0 | 19.7 | – |
11 | 9.196 | 6.597 | 327.4 | 37.3 | 272.7 | 1,802.7 | – | 2.2 | 4.3 | 35.1 | – |
12 | 9.095 | 6.554 | 1,073.5 | 273.1 | 154.7 | 1,127.3 | 4,546.2 | 1.3 | 4.3 | 34.2 | 50.1 |
13 | 9.099 | 6.568 | 1,281.4 | 321.2 | 420.0 | 362.0 | 2,099.8 | 1.0 | 4.3 | 18.7 | 38 |
14 | 9.417 | 6.518 | 336.9 | 889.7 | 495.3 | 3,329.3 | – | 0.2 | 13.8 | 24.3 | – |
15 | 9.126 | 6.591 | 1,493.1 | 144.7 | 1,624.2 | 1,348.8 | – | 5.9 | 11.0 | 27.3 | – |
16 | 9.191 | 6.558 | 744.5 | 228.3 | 1,139.0 | 878.3 | – | 1.2 | 35.9 | 6.0 | – |
17 | 9.184 | 6.545 | 685.5 | 236.39 | 1,558.1 | 1,911.4 | – | 2.2 | 7.5 | 14.0 | – |
18 | 9.245 | 6.687 | 214.6 | 62.2 | 277.3 | 681.4 | – | 1.1 | 7.0 | 28.1 | – |
19 | 9.251 | 6.699 | 161.2 | 51.3 | 155.4 | 3,632.6 | – | 1.4 | 6.5 | 35.5 | – |
20 | 9.193 | 6.649 | 884.6 | 483.3 | 156.4 | 2,295.3 | – | 1.9 | 8.4 | 16.0 | – |
21 | 9.025 | 6.637 | 34.0 | 130.0 | 225.2 | 1,240.6 | – | 2.9 | 6.7 | 10.2 | – |
VES points . | Coordinates in degrees . | TR (Ωm2) . | S (Ω−1) . | ρL (Ωm) . | ρT (Ωm) . | . | |
---|---|---|---|---|---|---|---|
Longitude . | Latitude . | ||||||
1 | 9.248 | 6.638 | 5,207.99 | 0.47 | 86.87 | 127.02 | 1.2 |
2 | 9.178 | 6.621 | 10,974.72 | 0.36 | 152.59 | 197.39 | 1.1 |
3 | 9.041 | 6.524 | 31,432.57 | 0.24 | 178.10 | 746.62 | 2.0 |
4 | 9.208 | 6.642 | 7,728.44 | 0.26 | 156.62 | 191.77 | 1.1 |
5 | 9.080 | 6.539 | 51,675.07 | 0.11 | 552.77 | 881.83 | 1.3 |
6 | 9.200 | 6.611 | 10,670.13 | 0.45 | 135.15 | 176.95 | 1.1 |
7 | 9.294 | 6.619 | 4,519.37 | 0.73 | 61.06 | 100.88 | 1.3 |
8 | 9.311 | 6.634 | 4,261.49 | 0.85 | 54.33 | 91.84 | 1.3 |
9 | 9.138 | 6.637 | 19,242.41 | 0.16 | 303.49 | 392.70 | 1.1 |
10 | 9.051 | 6.566 | 9,307.26 | 0.17 | 188.29 | 299.27 | 1.3 |
11 | 9.196 | 6.597 | 10,452.44 | 0.25 | 165.93 | 251.26 | 1.2 |
12 | 9.095 | 6.554 | 64,338.35 | 0.28 | 318.26 | 715.67 | 1.5 |
13 | 9.099 | 6.568 | 24,272.56 | 0.16 | 378.83 | 391.49 | 1.0 |
14 | 9.417 | 6.518 | 24,381.03 | 0.07 | 587.73 | 636.58 | 1.0 |
15 | 9.126 | 6.591 | 54,741.65 | 0.10 | 456.71 | 1,238.50 | 1.6 |
16 | 9.191 | 6.558 | 15,923.37 | 0.16 | 262.60 | 369.45 | 1.2 |
17 | 9.184 | 6.545 | 25,094.43 | 0.04 | 539.59 | 1,058.84 | 1.4 |
18 | 9.245 | 6.687 | 8,463.59 | 0.22 | 165.30 | 233.80 | 1.2 |
19 | 9.251 | 6.699 | 6,075.83 | 0.36 | 119.29 | 140.00 | 1.1 |
20 | 9.193 | 6.649 | 8,242.86 | 0.12 | 215.87 | 313.42 | 1.2 |
21 | 9.025 | 6.637 | 3,266.64 | 0.18 | 108.72 | 164.98 | 1.2 |
Minimum | 3,266.64 | 0.04 | 54.33 | 91.84 | 1.0 | ||
Maximum | 64,338.35 | 0.85 | 587.73 | 1,238.50 | 2.0 |
VES points . | Coordinates in degrees . | TR (Ωm2) . | S (Ω−1) . | ρL (Ωm) . | ρT (Ωm) . | . | |
---|---|---|---|---|---|---|---|
Longitude . | Latitude . | ||||||
1 | 9.248 | 6.638 | 5,207.99 | 0.47 | 86.87 | 127.02 | 1.2 |
2 | 9.178 | 6.621 | 10,974.72 | 0.36 | 152.59 | 197.39 | 1.1 |
3 | 9.041 | 6.524 | 31,432.57 | 0.24 | 178.10 | 746.62 | 2.0 |
4 | 9.208 | 6.642 | 7,728.44 | 0.26 | 156.62 | 191.77 | 1.1 |
5 | 9.080 | 6.539 | 51,675.07 | 0.11 | 552.77 | 881.83 | 1.3 |
6 | 9.200 | 6.611 | 10,670.13 | 0.45 | 135.15 | 176.95 | 1.1 |
7 | 9.294 | 6.619 | 4,519.37 | 0.73 | 61.06 | 100.88 | 1.3 |
8 | 9.311 | 6.634 | 4,261.49 | 0.85 | 54.33 | 91.84 | 1.3 |
9 | 9.138 | 6.637 | 19,242.41 | 0.16 | 303.49 | 392.70 | 1.1 |
10 | 9.051 | 6.566 | 9,307.26 | 0.17 | 188.29 | 299.27 | 1.3 |
11 | 9.196 | 6.597 | 10,452.44 | 0.25 | 165.93 | 251.26 | 1.2 |
12 | 9.095 | 6.554 | 64,338.35 | 0.28 | 318.26 | 715.67 | 1.5 |
13 | 9.099 | 6.568 | 24,272.56 | 0.16 | 378.83 | 391.49 | 1.0 |
14 | 9.417 | 6.518 | 24,381.03 | 0.07 | 587.73 | 636.58 | 1.0 |
15 | 9.126 | 6.591 | 54,741.65 | 0.10 | 456.71 | 1,238.50 | 1.6 |
16 | 9.191 | 6.558 | 15,923.37 | 0.16 | 262.60 | 369.45 | 1.2 |
17 | 9.184 | 6.545 | 25,094.43 | 0.04 | 539.59 | 1,058.84 | 1.4 |
18 | 9.245 | 6.687 | 8,463.59 | 0.22 | 165.30 | 233.80 | 1.2 |
19 | 9.251 | 6.699 | 6,075.83 | 0.36 | 119.29 | 140.00 | 1.1 |
20 | 9.193 | 6.649 | 8,242.86 | 0.12 | 215.87 | 313.42 | 1.2 |
21 | 9.025 | 6.637 | 3,266.64 | 0.18 | 108.72 | 164.98 | 1.2 |
Minimum | 3,266.64 | 0.04 | 54.33 | 91.84 | 1.0 | ||
Maximum | 64,338.35 | 0.85 | 587.73 | 1,238.50 | 2.0 |
Location . | VES points . | Coordinates in degrees . | ρb (Ωm) . | ρw (Ωm) . | ha (m) . | F . | ϕ . | Pumping test . | Predicted . | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Longitude . | Latitude . | T (m2/day) . | k (m/s) . | Tp (m2/day) . | kp (m/s) . | |||||||
Ablesang | 1 | 9.248 | 6.638 | 150.5 | 9.8 | 28 | 15.4 | 0.22 | – | – | 52.3 | 1.56 × 10−5 |
Agasham | 2 | 9.178 | 6.621 | 214.1 | 18.5 | 50 | 11.6 | 0.26 | – | – | 41.2 | 1.26 × 10−5 |
Alege | 3 | 9.041 | 6.524 | 437.7 | 40.0 | 10 | 10.9 | 0.27 | – | – | 28.0 | 1.21 × 10−5 |
Amunga | 4 | 9.208 | 6.642 | 143.0 | 11.4 | 35 | 12.6 | 0.25 | – | – | 30.1 | 1.35 × 10−5 |
Ashikpe | 5 | 9.080 | 6.539 | 270.0 | 18.5 | 17 | 14.6 | 0.23 | – | – | 14.5 | 1.50 × 10−5 |
Bayayam | 6 | 9.200 | 6.611 | 208.1 | 19.2 | 46 | 10.8 | 0.28 | 49.6 | 1.25 × 10−5 | 49.6 | 1.20 × 10−5 |
Beegbong | 7 | 9.294 | 6.619 | 137.1 | 11.4 | 26 | 12.1 | 0.26 | – | – | 79.2 | 1.30 × 10−5 |
8 | 9.311 | 6.634 | 100.0 | 9.9 | 37 | 10.1 | 0.29 | – | – | 91.7 | 1.14 × 10−5 | |
Begiatsul | 9 | 9.138 | 6.637 | 252.0 | 22.7 | 36 | 11.1 | 0.27 | 18.5 | 1.19 × 10−5 | 20.2 | 1.22 × 10−5 |
Biuhwe | 10 | 9.051 | 6.566 | 142.8 | 10.2 | 20 | 14.0 | 0.23 | – | – | 20.6 | 1.46 × 10−5 |
Bukemanya | 11 | 9.196 | 6.597 | 272.7 | 25.6 | 35 | 10.6 | 0.28 | – | – | 29.5 | 1.19 × 10−5 |
Karo | 12 | 9.095 | 6.554 | 154.7 | 11.2 | 34 | 13.8 | 0.24 | – | – | 32.7 | 1.44 × 10−5 |
Kikong | 13 | 9.099 | 6.568 | 362.0 | 23.3 | 38 | 15.6 | 0.22 | – | – | 20.5 | 1.58 × 10−5 |
Kundeve | 14 | 9.417 | 6.518 | 495.3 | 31.3 | 24 | 15.8 | 0.22 | – | – | 10.3 | 1.60 × 10−5 |
Ohong | 15 | 9.126 | 6.591 | 144.7 | 14.1 | 11 | 10.3 | 0.28 | – | – | 13.6 | 1.16 × 10−5 |
Okambi | 16 | 9.191 | 6.558 | 228.3 | 16.9 | 36 | 13.5 | 0.24 | 22.3 | 1.43 × 10−5 | 20.5 | 1.42 × 10−5 |
17 | 9.184 | 6.545 | 236.39 | 16.9 | 8 | 13.9 | 0.23 | – | – | 8.1 | 1.45 × 10−5 | |
Shikpeche | 18 | 9.245 | 6.687 | 277.3 | 15.4 | 28 | 18.0 | 0.20 | – | – | 26.2 | 1.76 × 10−5 |
19 | 9.251 | 6.699 | 155.4 | 15.4 | 36 | 10.1 | 0.29 | – | – | 41.1 | 1.14 × 10−5 | |
Udigie | 20 | 9.193 | 6.649 | 156.4 | 12.2 | 16 | 12.8 | 0.25 | – | – | 16.2 | 1.37 × 10−5 |
Ukpada | 21 | 9.025 | 6.637 | 225.2 | 20.0 | 10 | 11.3 | 0.27 | – | – | 22.4 | 1.24 × 10−5 |
Minimum | 100.0 | 9.8 | 8 | 10.1 | 0.20 | 18.5 | 1.19 × 10−5 | 8.1 | 1.14 × 10−5 | |||
Maximum | 495.3 | 40.0 | 50 | 18.0 | 0.29 | 49.6 | 1.43 × 10−5 | 91.7 | 1.76 × 10−5 | |||
Average | 226.8 | 17.8 | 28 | 12.8 | 0.25 | 30.1 | 1.29 × 10−5 | 31.8 | 1.36 × 10−5 | |||
Standard Deviation | 102.1 | 7.6 | 12 | 2.2 | 0.03 | 17.0 | 1.27 × 10−6 | 21.6 | 1.76 × 10−6 |
Location . | VES points . | Coordinates in degrees . | ρb (Ωm) . | ρw (Ωm) . | ha (m) . | F . | ϕ . | Pumping test . | Predicted . | |||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Longitude . | Latitude . | T (m2/day) . | k (m/s) . | Tp (m2/day) . | kp (m/s) . | |||||||
Ablesang | 1 | 9.248 | 6.638 | 150.5 | 9.8 | 28 | 15.4 | 0.22 | – | – | 52.3 | 1.56 × 10−5 |
Agasham | 2 | 9.178 | 6.621 | 214.1 | 18.5 | 50 | 11.6 | 0.26 | – | – | 41.2 | 1.26 × 10−5 |
Alege | 3 | 9.041 | 6.524 | 437.7 | 40.0 | 10 | 10.9 | 0.27 | – | – | 28.0 | 1.21 × 10−5 |
Amunga | 4 | 9.208 | 6.642 | 143.0 | 11.4 | 35 | 12.6 | 0.25 | – | – | 30.1 | 1.35 × 10−5 |
Ashikpe | 5 | 9.080 | 6.539 | 270.0 | 18.5 | 17 | 14.6 | 0.23 | – | – | 14.5 | 1.50 × 10−5 |
Bayayam | 6 | 9.200 | 6.611 | 208.1 | 19.2 | 46 | 10.8 | 0.28 | 49.6 | 1.25 × 10−5 | 49.6 | 1.20 × 10−5 |
Beegbong | 7 | 9.294 | 6.619 | 137.1 | 11.4 | 26 | 12.1 | 0.26 | – | – | 79.2 | 1.30 × 10−5 |
8 | 9.311 | 6.634 | 100.0 | 9.9 | 37 | 10.1 | 0.29 | – | – | 91.7 | 1.14 × 10−5 | |
Begiatsul | 9 | 9.138 | 6.637 | 252.0 | 22.7 | 36 | 11.1 | 0.27 | 18.5 | 1.19 × 10−5 | 20.2 | 1.22 × 10−5 |
Biuhwe | 10 | 9.051 | 6.566 | 142.8 | 10.2 | 20 | 14.0 | 0.23 | – | – | 20.6 | 1.46 × 10−5 |
Bukemanya | 11 | 9.196 | 6.597 | 272.7 | 25.6 | 35 | 10.6 | 0.28 | – | – | 29.5 | 1.19 × 10−5 |
Karo | 12 | 9.095 | 6.554 | 154.7 | 11.2 | 34 | 13.8 | 0.24 | – | – | 32.7 | 1.44 × 10−5 |
Kikong | 13 | 9.099 | 6.568 | 362.0 | 23.3 | 38 | 15.6 | 0.22 | – | – | 20.5 | 1.58 × 10−5 |
Kundeve | 14 | 9.417 | 6.518 | 495.3 | 31.3 | 24 | 15.8 | 0.22 | – | – | 10.3 | 1.60 × 10−5 |
Ohong | 15 | 9.126 | 6.591 | 144.7 | 14.1 | 11 | 10.3 | 0.28 | – | – | 13.6 | 1.16 × 10−5 |
Okambi | 16 | 9.191 | 6.558 | 228.3 | 16.9 | 36 | 13.5 | 0.24 | 22.3 | 1.43 × 10−5 | 20.5 | 1.42 × 10−5 |
17 | 9.184 | 6.545 | 236.39 | 16.9 | 8 | 13.9 | 0.23 | – | – | 8.1 | 1.45 × 10−5 | |
Shikpeche | 18 | 9.245 | 6.687 | 277.3 | 15.4 | 28 | 18.0 | 0.20 | – | – | 26.2 | 1.76 × 10−5 |
19 | 9.251 | 6.699 | 155.4 | 15.4 | 36 | 10.1 | 0.29 | – | – | 41.1 | 1.14 × 10−5 | |
Udigie | 20 | 9.193 | 6.649 | 156.4 | 12.2 | 16 | 12.8 | 0.25 | – | – | 16.2 | 1.37 × 10−5 |
Ukpada | 21 | 9.025 | 6.637 | 225.2 | 20.0 | 10 | 11.3 | 0.27 | – | – | 22.4 | 1.24 × 10−5 |
Minimum | 100.0 | 9.8 | 8 | 10.1 | 0.20 | 18.5 | 1.19 × 10−5 | 8.1 | 1.14 × 10−5 | |||
Maximum | 495.3 | 40.0 | 50 | 18.0 | 0.29 | 49.6 | 1.43 × 10−5 | 91.7 | 1.76 × 10−5 | |||
Average | 226.8 | 17.8 | 28 | 12.8 | 0.25 | 30.1 | 1.29 × 10−5 | 31.8 | 1.36 × 10−5 | |||
Standard Deviation | 102.1 | 7.6 | 12 | 2.2 | 0.03 | 17.0 | 1.27 × 10−6 | 21.6 | 1.76 × 10−6 |
S/N . | Locations . | Parameters . | Groundwater potential . | ||
---|---|---|---|---|---|
Range of resistivity (Ωm) . | Aquifer thickness range (m) . | Transmissivity (m2/day) . | |||
1 | VES-1, VES-2, VES-6, VES-7, VES-8 and VES-19 | 100–214 | 26–50 | >40 | Good |
2 | VES-3, VES-4, VES-5, VES-9, VES-10, VES-11, VES-12, VES-13, VES-16, VES-18, VES-20 and VES-21 | 143–438 | 10–38 | <40–15 | Marginal |
3 | VES-14, VES-15 and VES-17 | 145–495 | 8–24 | <15 | Poor |
S/N . | Locations . | Parameters . | Groundwater potential . | ||
---|---|---|---|---|---|
Range of resistivity (Ωm) . | Aquifer thickness range (m) . | Transmissivity (m2/day) . | |||
1 | VES-1, VES-2, VES-6, VES-7, VES-8 and VES-19 | 100–214 | 26–50 | >40 | Good |
2 | VES-3, VES-4, VES-5, VES-9, VES-10, VES-11, VES-12, VES-13, VES-16, VES-18, VES-20 and VES-21 | 143–438 | 10–38 | <40–15 | Marginal |
3 | VES-14, VES-15 and VES-17 | 145–495 | 8–24 | <15 | Poor |
Table 5 presents the results of correlation analysis performed on transmissivity and hydraulic conductivity data from pumping test experiments at three specific borehole locations, juxtaposed with the corresponding values predicted via the hydro-geoelectrical technique at the same spatial coordinates, yielded correlation coefficients (R2) of 0.98 and 0.89, respectively. Furthermore, an error analysis was performed on the hydraulic parameters, specifically transmissivity and hydraulic conductivity. The root mean square error (RMSE) and mean absolute percentage error (MAPE) were calculated to evaluate the accuracy of the predictions. For transmissivity, the RMSE and MAPE were determined to be 1.439 and 5.807, respectively. In the case of hydraulic conductivity, the corresponding values were and 0.027, respectively. These low error values demonstrate the high precision of the predictive models used in estimating these hydraulic parameters. The accuracy of the predictions was assessed by calculating the percentage accuracy, which was observed to be 94.19 and 99.97%, respectively, for transmissivity and hydraulic conductivity. These results highlight the robustness and reliability of the employed predictive models in accurately characterizing the hydraulic parameters within the area under investigation.
S/N . | Parameter . | VES-6 . | VES-9 . | VES-16 . | R2 . | RMSE . | MAPE . | Accuracy (%) . |
---|---|---|---|---|---|---|---|---|
1 | Aquifer electrical resistivity, ρb (Ωm) | 208 | 252 | 228.3 | – | – | – | – |
2 | Saturated aquifer thickness, ha (m) | 46 | 36 | 36 | – | – | – | – |
3 | Longitudinal conductance, S (Ω−1) | 0.45 | 0.16 | 0.16 | – | – | – | – |
4 | Transverse resistance, TR (Ωm2) | 10,670.1 | 19,242.4 | 15,923.37 | – | – | – | – |
5 | Electrical formation factor | 10.8 | 11.1 | 13.5 | – | – | – | – |
6 | Aquifer transmissivity derived from pumping test, T (m2/day) | 49.6 | 18.5 | 22.3 | 0.99 | 1.43895 | 5.807 | 94.19 |
7 | Predicted aquifer transmissivity from geoelectric sounding, Tp (m2/day) | 49.6 | 20.2 | 20.5 | ||||
8 | Aquifer hydraulic conductivity derived from pumping test, k (m/s) | 1.25 × 10−5 | 1.19 × 10−5 | 1.43 × 10−5 | 0.89 | 3.5 × 10−7 | 0.027 | 99.97 |
9 | Predicted aquifer hydraulic conductivity from geoelectric sounding, kp (m2/day) | 1.20 × 10−5 | 1.22 × 10−5 | 1.42 × 10−5 |
S/N . | Parameter . | VES-6 . | VES-9 . | VES-16 . | R2 . | RMSE . | MAPE . | Accuracy (%) . |
---|---|---|---|---|---|---|---|---|
1 | Aquifer electrical resistivity, ρb (Ωm) | 208 | 252 | 228.3 | – | – | – | – |
2 | Saturated aquifer thickness, ha (m) | 46 | 36 | 36 | – | – | – | – |
3 | Longitudinal conductance, S (Ω−1) | 0.45 | 0.16 | 0.16 | – | – | – | – |
4 | Transverse resistance, TR (Ωm2) | 10,670.1 | 19,242.4 | 15,923.37 | – | – | – | – |
5 | Electrical formation factor | 10.8 | 11.1 | 13.5 | – | – | – | – |
6 | Aquifer transmissivity derived from pumping test, T (m2/day) | 49.6 | 18.5 | 22.3 | 0.99 | 1.43895 | 5.807 | 94.19 |
7 | Predicted aquifer transmissivity from geoelectric sounding, Tp (m2/day) | 49.6 | 20.2 | 20.5 | ||||
8 | Aquifer hydraulic conductivity derived from pumping test, k (m/s) | 1.25 × 10−5 | 1.19 × 10−5 | 1.43 × 10−5 | 0.89 | 3.5 × 10−7 | 0.027 | 99.97 |
9 | Predicted aquifer hydraulic conductivity from geoelectric sounding, kp (m2/day) | 1.20 × 10−5 | 1.22 × 10−5 | 1.42 × 10−5 |
R2, correlation coefficient; RMSE, root mean square error; MAPE, mean absolute percentage error.
DISCUSSION
Aquifer characterization of the OBC
Due to the cost-effectiveness and speed of the electrical resistivity technique, it permits greater spatial coverage and provides valuable pilot information that is needed for rapid aquifer characterization decisions. Aquifer characterization provides information on aquifer parameters and numerical models required for groundwater resources management, sustainability and prediction. These parameters that including the D-Z parameters, hydraulic conductivity, porosity, and transmissivity were evaluated within the OBC. TR values were observed to increase from the northern segment toward the south (Figure 6(b)). The low TR values within the northern portion correlated geologically with the portion of the study area dominated by migmatitic rocks. The migmatites have been subjected to intense weathering processes leading to reduced resistivity values of the formations within this area. TR values tend to show high values toward the south, around the massive porphyritic granite dominant terrain. On the other hand, S values were observed to increase from the western segment toward the northeastern part of the study area where it attained its maximum value (Figure 6(c)). The high S values are dominant within the parts where gneissic rocks have been intensely fractured and the aquifer formation electrical resistivity values within these areas have been reduced due to groundwater transmission. Crystalline basement terrains are usually dominated by episodes of faulting, fracturing, and intrusions leading to weathering of preexisting rocks. These processes alter the configuration and characteristics of crystalline rocks leading to heterogeneity in their electrical resistivity signatures. This phenomenon is responsible for the variations in electrical anisotropy within the area.
Equation (13) gives the average F value as 11.65 – the slope of the equation. The lowest value of F was observed around VES-8 and VES-19 while relatively high values were observed at area (VES-18). The northern segment and areas located along major fault zones were notable portions with relatively high hydraulic conductivity (Figure 6(e)). The networks of fractures that provide semi-confined aquifers within the area are interconnected adequately which allows groundwater circulation (Ebong et al. 2014, 2021a; Ekwok et al. 2020). Lower values of k were observed around some locations within the central part sandwiched between the two dominant parallel faults and the western segments of the study area. The lower values that are dominant, especially within the western part of the landscape are due to minor occurrence of fracture networks. Also, the central and western segments have been identified to have relatively little or sparse lineament structures (Ebong et al. 2021a).
This R2 value implies that the estimated relationship between these two parameters is good. However, the TR values tend to considerably decrease as T increases because the magnitude of resistance offered by the crystalline basement rock is high, except in VES-21 where the layer electrical resistivities were relatively low and correspond to the thick regolith layer. Hence, the relatively low transmissivity observed within the area under investigation (Figure 6(d)).
Aquifer potential delineation
The resistivity of the fractured-aquifer formation and the estimated transmissivity were used to delineate aquifer potential zones. Locations with ρ range of 100–214 Ωm, T > 40 m2/day and h of the range of 26–50 m were categorized as having good aquifer potential (Table 4). The locations include VES-1, 2, 6, 7, 8, and 19. Moderate potential aquifer zones were observed within VES-3, 4, 5, 9, 10, 11, 12, 13, 16, 18, 20, and 21 with ρ that range between <143 and 438 Ωm, T that range between <40 and 15 m2/day and h between 10 and 38 m while poor potential aquifer zones that have ρ that range between 145 and 495 Ωm, T < 15 m2/day and h that range from 8 to 24 m were observed in VES-14, 15, and 17. In general, the groundwater potential classification indicates that a decrease in electrical resistivity values of aquifer formation reflects higher fracture density and water content. Hence, adequate structural elements (i.e., fractures and faults) and thickness of the saturated formation are important factors to also consider in siting productive boreholes within such areas.
CONCLUSION
Hydrogeologic and electrical resistivity techniques were used to study the OBC for the purpose of developing empirical models used in predicting aquifer hydraulic parameters and delineating potential aquifer zones. The VES technique applied in this study involved the Schlumberger electrode configuration. This technique provided layer parameters used in computing secondary geoelectrical information (i.e., Dar Zarrouk parameters). The D-Z parameters, i.e., longitudinal conductance and TR range between 0.04 and 0.85 Ω−1 and between 3,266.64 and 64,338.35 Ωm2, respectively. These wide variations are due to the intrinsic electrical anisotropic nature of the basement terrain. This variation in electrical anisotropy results from the influence of electrical current flow by some factors like geologic structures (i.e., faults and fractures) and topographic conditions. The combination of these primary and secondary parameters alongside water electrical resistivity measurements, and a few pumping test-derived hydraulic parameters were used to develop empirical models used in evaluating aquifer parameters such as fractional porosity of the fractured-aquifer layer (0.20–0.30), hydraulic conductivity (1.14 × 10−5 to 1.76 × 10−5 m/s), and transmissivity (8.1–91.7 m2/day). Based on the estimated aquifer parameters, groundwater potential zones were delineated within the study area. The results of this investigation provided good, moderate, and poor groundwater potential zones that were semi-confined (i.e., fractured basement aquifers). Additionally, this approach can be applied in hard rock terrains elsewhere to estimate aquifer parameters and delineate suitable sites for productive boreholes. This study develops empirical models for the estimation of fractured-aquifer hydrogeological, physical, and geohydraulic parameters where pumping test information is limited which enables the delineation of groundwater potential zones required for adequate management of groundwater resources and sustainability.
ACKNOWLEDGEMENT
The first author wishes to thank Prof. I. Othman, General Director of the Syrian Atomic Energy Commission for allowing Prof. J. Asfahani to participate in this research paper.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.