Introduction

The Niger-delta region of Nigeria is under serious and increasing pressure not only due to the expanding population but also to the increasing activities of the oil and gas exploration industries. The exploration activities of the oil and gas industries have greatly affected the surface water in most of the Niger-delta region of Nigeria. As such, assessing the water is difficult since most of the surface water is contaminated as a result of oil spillage on both water and land. Groundwater is an important resource that is used for drinking water, irrigation, and industrial processes. However, groundwater can easily become contaminated by pollutants from agricultural, industrial, and residential sources. Additionally, groundwater can become depleted if it is overused or if there is a prolonged drought (Ibanga & George, 2016; Omeje et al., 2023). Groundwater, unlike phreatic water or soil moisture, occurs in the saturated zone of the subsurface. Since alternative water sources are unreliable and expensive to develop, groundwater provides a reliable option to meet the ever-increasing demand of the rural populace. Man relies greatly on groundwater for his daily water needs since it requires minor water treatment to make it potable. The underlying aquifer can be contaminated as a result of inappropriate or uncontrolled activities at the land surface, which include the disposal of waste and spillage of chemicals. The quality of groundwater is continuously aggravated by increasing pressure from pollution as a result of widespread vulnerability to contamination from spilled hydrocarbons and leachates arising from indiscriminate surface disposal of wastes (Abam & Nwankwoala, 2020). Groundwater availability depends largely upon the subsurface and surface geology as well as climate, porosity and permeability of a geologic formation, which controls its ability to hold and transmit water through the aquifer layers (George et al., 2022). Groundwater occurs in an aquifer which is a geologic formation capable of storing and transmitting sufficient quantity of water necessary for human survival and economic development (Bricker et al., 2017; Nugraha et al., 2021). Aquifer repositories provide a dependable water supply option that can meet the water needs of a community. According to literatures on the earth’s subsurface, it acts as a natural filter through a process called natural attenuation. When water or other substances pass through soil and rock layers, the layers act as a physical and chemical barrier that can remove impurities and pollutants (George et al., 2014; Obiora et al., 2016).

Factors such as the depth to the water table and materials overlying the aquifer layers influence an aquifer’s vulnerability. According to researchers (Akpan et al., 2013; Ekanem et al., 2021; George et al., 2014; Ibuot et al., 2019a; Nugraha et al. 2021), increased permeability of rocks leads to increased percolation and infiltration of surface pollutants into the subsurface aquifer. Many authors (Abiola et al., 2009; Adeniji et al., 2014; Bayewu et al., 2018; Ekanem et al., 2021; Ibuot et al., 2017a, 2019b; Mogaji et al., 2011; Obiora et al., 2015; Thomas et al., 2020) have investigated the protective capacity and vulnerability of groundwater repositories. When hazardous chemicals are intentionally disposed of, accidentally spilled, or applied to the ground for agricultural purposes, they percolate through the subsurface, and when they eventually reach the groundwater repositories, they can contaminate its potability and pose a serious threat to public health.

Permeability, porosity, and overburden thickness of a geologic formation control the rate of groundwater contamination (Ibuot et al., 2017b; Obiora et al., 2015). The surface pollutants infiltrating the subsurface depend on the nature of the geologic materials that overlie the aquifer units and lead to polluting plumes. Since the earth's layers act as natural filters for percolating fluids, groundwater is usually available, clean, and bereft of contaminants or pollutants (Ibuot et al., 2017b; Umar & Igwe, 2019). The purification of water as it flows through the voids is enhanced by the sluggish flow of groundwater through the subsurface. The permeability and thickness of the protective layers determine the protectivity (protective capacity) of the aquifers and the ease of fluid flow through the subsurface (Obiora & Ibuot, 2020). Groundwater can flow through pores, fissures, and fractures in rocks and carry with it dissolved pollutants as it percolates through the subsurface strata. The flow of groundwater through the subsurface is controlled by the nature of the subsurface geological composition (Bashir et al., 2014; George et al., 2015) and gravity. The nature of the subsurface materials is an important factor to consider in any hydrogeologic environment, since its properties and variations are the goals of hydrogeologic and hydrogeophysical investigations (Daniel et al., 2022; Opara et al., 2020).

The indiscriminate disposal of waste (poor waste management) enhances the deterioration of groundwater quality since leachates that are formed from dumpsites, sewage from latrines, leakage from pipes, and oil spillage percolate through the covering layers of the subsurface into the hydrogeologic units (Hossain et al., 2014; Oseji et al., 2018; Umar & Igwe, 2019). Different chemical substances are leached into the aquifer units and their concentrations can change the chemistry of groundwater, thus altering the potability of groundwater. The water can also be corrosive if the geomaterials contain more corrosive-enhancing substances. In groundwater exploration, the water is pumped to the surface through pipes, and these pipes can be affected by corrosion if the subsurface geomaterial is corrosive. Corrosivity is a geologic hazard that can cause lead and copper in pipes to leach into drinking water and cause leaks in plumbing. The degree of corrosivity varies depending on the conductivity of the geomaterials.

The electrical resistivity method has been employed in different locations and by different researchers (Adeniji et al., 2014; Aleke et al., 2018; George, 2020; Ibanga & George, 2016; Ibuot & Obiora, 2021; Ibuot et al., 2022; Lahjouj et al., 2020; Putranto et al., 2018) in appraising the hydrogeological conditions of the heterogeneous earth subsurface. These include mapping of saturated hydrogeologic layers from the adjoining formations, groundwater potential, aquifer vulnerability, assessment of the infiltration rate of the vadose zone, groundwater contamination studies, and flow unit analysis. Due to the resistivity contrast observed in the zone of saturation, the resistivity method is preferred to other geophysical methods since the variation of resistivity/conductivity of the argillites is displayed vertically and horizontally (Loke, 2009; 2015; Obiora et al., 2018). The electrical resistivity method utilizes vertical electrical sounding (VES) to investigate the variations of subsurface geologic materials. The study area has witnessed the decline in the quality of surface water, loss of aquatic life, and land due to environmental pollution resulting from oil exploration. Consequently, one of the major challenges of the residents of the area is that of ensuring potable water in adequate amounts to meet the needs of the growing human population. Most of the aquifers in the area are usually exploited without any assessment of the aquifer’s protectivity against contamination or the quality of the groundwater. Also, there is no available information about the corrosivity of the subsurface layers. This study is motivated by these situations to enhance the development of an effective and sustainable groundwater management scheme to evade any outbreak of water-borne diseases in the area. The aim of this study is, therefore, to use the surface electrical resistivity method to investigate the subsurface properties to assess the protectivity and corrosivity of aquifer units and also the variability of these properties.

Location and geological setting of the study area

The Federal College of Education (Technical), Omoku, lies between latitudes 5.33° N and 5.35° N, and longitudes 6.63° E and 6.66° E (Fig. 1) and is located in the coastal town of Omoku in Rivers State, Nigeria. Because of its rich oil and gas deposits, the community is home to the Nigerian Agip Oil Company (NAOC), and other multinational oil companies operating in the community. It is also a central business hub of the Orashi region of the Rivers State of Nigeria (Tamunobereton-ari et al., 2014). The study area lies within the Niger Delta Basin, which is underlain by the Benin Formation, Agbada Formation, and Akata Formation. The Akata Formation, which is mainly shale and clay, and the Agbada Formation, which is generally fluviatile and fluviomarine, are of primary interest to the petroleum industry (Abam & Nwankwoala, 2020). The Akata and Agbada formations provide hydrocarbon source rock and a reservoir and account for almost all the hydrocarbons in the region. The Benin Formation, which occurs at shallower horizons, comprises a continental deposit of sand and gravel (Abam & Nwankwoala, 2020), is important in groundwater exploration.

Fig. 1
figure 1

Geologic map of study area showing VES points

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Materials and methods

Theoretical background

Empirical relations exist that link the aquifer hydraulic properties with electrical properties (George et al., 2015; Ibanga & George, 2016; Ibuot et al., 2017b; Obiora et al., 2018). These relations provide a cost-effective means of deriving aquifer hydraulic properties (hydraulic conductivity, transmissivity, etc.) from surficial resistivity measurements without the need to do any pumping tests which is usually expensive. Archie (1942) developed a model equation that relates the electrical resistivity of rocks/soils and the pore-water resistivity. This relationship can be expressed using Eq. 1 as the quotient of the bulk electrical resistivity (\({\rho }_{\mathrm{b}}\)) to pore-water resistivity (\({\rho }_{\mathrm{w}}\)) for a fully saturated and clay-free formation.

$$F=\frac{{\rho }_{\mathrm{b}}}{{\rho }_{\mathrm{w}}}$$
(1)

where \(F\) is the formation factor which represents a macroscopic property of rock/soil. Formation factor as function of the porosity of the rock pore structure, and pore size distribution. The formation factor is affected by factors such as the mineralogy of the rock, the degree of compaction, and the salinity and conductivity of the pore fluid. It is typically reported as a dimensionless number, with lower values indicating more conductive rocks and higher values indicating more resistive rocks (Ekanem et al., 2022).

Considering a water-saturated sediment, porosity which is the percentage of the rock/soil that is void of materials determines the quantity of water an aquifer can hold in storage. Porosity can have a significant impact on the properties and behaviour of a material. Highly porous materials tend to have low density, and high permeability. On the other hand, materials with low porosity tend to have higher density, and lower permeability. Then, effective porosity (\(\phi )\) of a saturated geologic formation can express using Eq. 2.

$$\phi ={\left(\frac{a}{F}\right)}^{{\frac{1}{m}}}$$
(2)

where a and m are Archie constants, a is the geometric factor (\(a=0.52)\) and m is the cementation factor (\(m=1.54)\). The conductivity of water saturated rock/soil is very sensitive to changes in either of a or m.

The hydraulic conductivity, K, which is related to porosity was estimated using the Kozeny-Carman-Bear’s equation as expressed in Eq. 3. It depends on the pore dynamics of the sand the fluid is flowing through and measures the capacity of a geologic formation or other porous media to transmit fluids. Hydraulic conductivity plays an important role in a wide range of applications, from groundwater flow and contamination studies to civil engineering and soil science.

$$K=\left(\frac{{\delta }_{\mathrm{w}}.g}{{\mu }_{\mathrm{d}}}\right).\left(\frac{{{d}_{m}}^{2}}{180}\right).\left(\frac{{\phi }^{3}}{{\left(1-\phi \right)}^{2}}\right)$$
(3)

where \(\phi\) is the effective porosity, g is the acceleration due gravity (10 m/s2), \({\delta }_{\mathrm{w}}\) is the density of water (1000 kg/m3), \({d}_{\mathrm{m}}\) is site mean diameter (0.00036 m) measured using the micrometre screw gauge, \({\mu }_{\mathrm{d}}\) is the dynamic viscosity of water which is approximately 0.0014 kg/ms (Fetters, 1994).

The protectivity and potentiality of the aquifer are determined using the Dar Zarrouk parameters (longitudinal conductance and transverse resistance) and transmissivity. The protectivity, which expresses the ability of the overlying layers to retard percolating fluids, is greatly influenced by permeability, soil particle size, porosity, and the thickness of the protecting layers (Adeniji et al., 2014; Ekanem et al., 2021; Obiora et al., 2015).

The product of hydraulic conductivity (K) and thickness (h) gives the values of transmissivity (\({T}_{\mathrm{r}}\)) which describe the transmitting ability of an aquifer to allow groundwater to move wholly in its saturated thickness. This property is expressed in Eq. 4 according to Niwas and Singhal (1981). Transmissivity rates the ease of an aquifer to transmit water over a unit thickness of hydraulic conductivity and across the entire thickness of the aquifer.

$$T_{{\text{r}}} = Kh$$
(4)

The total longitudinal conductance (S) and transverse resistance (T), which are functions of the first-order geoelectric parameters (resistivity and thickness), were estimated at each VES point using the mathematical relation as given in Eq. 5.

$$S={\sum\limits_{i}^{n}}\frac{{h}_{i}}{{\rho }_{i}}$$
(5)
$$T=\sum_{i}^{n}\rho h$$
(6)

where \(\rho\) and h are the resistivity and thickness of the overlying layers.

Data acquisition and processing

The electrical resistivity survey was conducted in the study area using the Integrated Geo and Instrument Services (IGIS) signal enhancement resistivity meter with model SSR-MP-ATS and its accessories. The vertical electrical sounding (VES) technique utilizing the Schlumberger electrode configuration was used in acquiring VES data at twelve locations within the study area. The technique involved the injection of current into the earth through a pair of current electrodes (A and B), while a pair of potential electrodes (M and N) measured the potential differences generated. The half-current electrode separation (AB/2) ranged between 1 and 200 m while the potential electrode (MN/2) ranged between 0.25 and 30 m. The IGIS resistivity meter computed the ratio of potential difference to current as the apparent resistance of the subsurface layers penetrated by the current. The apparent resistance was converted to apparent resistivity using Eq. 7.

$${\rho }_{\mathrm{a}}=G.{R}_{\mathrm{a}}$$
(7)

where \({R}_{\mathrm{a}}\) is the apparent resistance and \(G\) is the geometric factor for Schlumberger electrode configuration and is expressed in Eq. 8 as;

$$G=\pi .\left[\frac{{\left(\frac{\mathrm{AB}}{2}\right)}^{2}-{\left(\frac{\mathrm{MN}}{2}\right)}^{2}}{\mathrm{MN}}\right]$$
(8)

where AB and MN are the current and potential electrodes distances, respectively.

Using the conventional manual curve matching technique, the smoothened VES curves were interpreted to generate the initial values of layer resistivities and thicknesses (Zohdy et al., 1974). The initial values were used as input parameters in a WINRESIST software program, which electronically carried out a least-squares inversion of the field data and gave a resistivity model curve where the true values of resistivity, thickness, and depth at each VES point can be obtained. After a series of iterations, reasonably acceptable variations between the field and theoretical data were realized through the absolute resulting root-mean-square (RMS) error. The best fitting models to the data represent the subsurface resistivity models. Samples of the VES-interpreted resistivity model curves are shown in Figs. 1 and 2. The values of resistivity and thickness of the layers were used in Eqs. 1–6 to derive the geohydraulic properties (formation factor, porosity, hydraulic conductivity, transmissivity, longitudinal conductance, and transverse resistance) and the corrosivity of the topmost layer of the earth from surface resistivity measurements without the need to do any pumping tests, which are usually expensive.

Fig. 2
figure 2

Model resistivity curve at VES 5

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Results and discussion

The interpretation of VES data gives the representative VES curves as shown in Figs. 2 and 3. This led to the realization of the values of the resistivity, thickness, and depth of the geo-electric layers within the maximum current electrode separation presented in Table 1, and four geo-electric layers were delineated in all locations. The first layer which is extensively exposed at the surface has a resistivity range of 35.1–891.6 Ωm, and averages to 415.3 Ωm and was delineated as motley topsoil. The relatively higher resistivity values observed in some locations may be due to the presence of high grain size materials like gravels, coarse sands, breccias and other detrital geomaterials in lithostrata of this layer (Ekanem et al., 2020; George et al., 2015; Ibuot et al., 2013). This layer has thickness and depth that varies from 0.6 to 4.5 m respectively in vertical extent. This geoelectric layer boosts the seapage of fluids into the underlying lithologic units. The second geoelectric layer with resistivity values ranging from 34.1 to 816.8 Ωm averaging about 337.5 Ωm has thickness and depth ranging from 4.1 to 16.6 m and 6.1 to 17.9 m, respectively. The lower resistivity may be attributed to the presence of conductive argillaceous materials and clay intercalations. This layer was delineated as a medium-grained sand dominated by lithostrata, and on average is less resistive than the overlying layer and is also highly permeable. This indicates that the underlying hydrogeologic unit is vulnerable to surface contaminants. Underlying the second layer is the third layer, which was interpreted as a fine-medium grained sand-dominated layer. The resistivity values of the layer vary from 41.6 to 1475.9 Ωm with a mean value of 513.03 Ωm, the thickness and depth of this lithologic layer vary from 9.2 to 50.3 m and 16.8 to 68.2 m, respectively. This was identified as the main hydrogeologic unit with the highest resistivity and thickness observed at VES 7. The fourth layer has variable resistivity spanning from 20.6 to 2645.4 Ωm with thickness and depth not defined within the maximum current electrode separation. The high resistivity values at some locations suggest that this layer is compose of gravelly sand. The result obtained was compared with borehole lithology logs of existing and nearby borehole (Fig. 4) which shows strong correlations.

Fig. 3
figure 3

Model resistivity curve at VES 7

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Table 1 Summary of electrical resistivity survey in the study area
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Fig. 4
figure 4

Borehole lithology and inferred layers at VES 5 and VES 7

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The variations observed across the subsurface imply the variability in intra-lithological composition of the argillaceous geomaterials (George et al., 2015; Ibuot et al., 2013). The results in Table 1 also reveal the study area to be characterised by the HK, HA, KH, KQ, AK, AA, and QH curve types, and these variations infer changes in subsurface lithologies. Seven curve types were identified, where HK and KH were dominant, with each constituting 25%. HA has a 16.67% composition while KQ, AK, AA, and QH had the least dominance, constituting 8.33%. The distribution of these curve types is displayed in a pie chart and shown in Fig. 5. The utility pipes that convey water are buried in the topmost layer of the earth's subsurface. The resistivity values of this layer were used in assessing the corrosivity potential of this layer. The ratings according to Oladapo et al. (2004) and Mosuro et al. (2017) were employed. The results revealed that VES 1, 2, 3, 6, 7, 8, 9, and 10 were practically noncorrosive (PNC), VES 4 and 5 were observed to be moderately corrosive (MC), while VES 10 and 11 were slightly corrosive (SC). Areas that are practically noncorrosive (PNC) are good for the burying of underground metal pipes without corrosion. Areas that are slightly and moderately corrosive have low potential for corroding pipes, rupturing or causing leakage of underground metal pipes (Ibuot et al., 2017b; Obiora et al., 2015; Umar & Igwe, 2019). This may be due to ferruginous substances in the geomaterials of the topsoil. The percentage distribution of corrosivity of the topmost layer is shown in Fig. 6, where 66.67% represents PNC while 16.67% represents MC and SC.

Fig. 5
figure 5

Percentage distribution of the curve types

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Fig. 6
figure 6

Percentage distribution of the corrosivity

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The primary geoelectric indices (resistivities and thicknesses) were used in estimating the secondary geoelectric indices (formation factor, porosity, hydraulic conductivity, transmissivity, longitudinal conductance, and transverse resistance) presented in Table 2. The resistivity and thickness of the saturated units (aquifer) vary from 41.6 to 1475.9 Ωm and 9.2 to 50.3 m, respectively. The variation of resistivity in this layer may is influenced by the nature of the subsurface geomaterials and the continuous bioturbating activities (Ekanem et al., 2021; Thomas et al., 2020). The pore-water resistivity (\({\rho }_{\mathrm{w}}\)) has values ranging from 47.5 1083.4 Ωm with an average of 359.77 Ωm, and Fig. 7a and b shows the distributions of bulk aquifer resistivity and pore-water resistivity. There is similarity in the variational trends as an increase in one lead to a corresponding increase in the other. The southern zone of the mapped area shows high values for both parameters. It can be deduced that an area with high bulk resistivity is more saturated with pore water in its repositories. The result of the resistivity values could be affected by the nature of the subsurface geomaterials and the electrical resistivity of the subsurface, according to researchers (Ekanem et al., 2021; George et al., 2015; Ibuot et al. 2021; Uwa et al., 2018). It is affected by the density, shape, size, pore size, and porosity of the constituent geomaterials; lithology; water content; clay content; and salinity.

Table 2 Results of the estimated geohydraulic properties
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Fig. 7
figure 7

a Distribution of aquifer resistivity b distribution of water resistivity

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The study area has topographic elevations that range from 10 to 19 m with an average of 13 m, indicating a low-lying region. The image map (Fig. 8) shows the lowest elevation in the southeastern zone of the mapped area. This implies that water flows from topographically high regions to topographically low regions (southeastern region), and can predict the direction of flow of contaminants (Ekanem et al., 2021; Ibuot et al., 2019a, 2019b). The formation factor is estimated from Eq. 1 as the ratio of bulk resistivity to water resistivity, whose range and mean are 0.43–4.57 and 1.62, respectively. The spatial variation of the formation factor is displayed in the image map (Fig. 9). According to Ekanem et al. (2020), the formation factor is sensitive to pore-fluid and lithogical textures. Regions with high values of formation factor may be inferred as regions with more resistive rocks. The effective porosity, which depends on the grain composition of the soil, the way it is formed and the pressure to which it is exposed (Halek and Svec, 1979), has values ranging from 0.24 to 1.13 with a mean value of 0.59. The image map (Fig. 10) displayed the variation of porosity across the study area. The regions with high porosity may be delineated as regions having low density and high permeability. It is observed from Figs. 9 and 10 that the values of formation factor increase at locations where values of porosity decrease. This may be attributed to high argillite-sand mixing ratios that reduce pore-matrix ratios in aquifers.

Fig. 8
figure 8

2-D image showing distribution of elevation

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Fig. 9
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2-D image map showing variation of formation factor

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Fig. 10
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2-D image map showing variation of porosity

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Hydraulic conductivity is a geoelectrical parameter that measures the ease with which saturated soil pores allow water to move. The estimated hydraulic conductivity range and mean are 0.0001–7.4027 m/day and 0.6692 m/day respectively. Figure 11 shows the distribution of hydraulic conductivity where a zone with a high magnitude of hydraulic conductivity is observed in the southeastern part of the study area. This zone with relatively high hydraulic conductivity indicates a zone with high permeability and high groundwater transmissibility (Ekanem et al., 2022; Vázquez-Báez et al., 2019). The zone with high hydraulic conductivity can be delineated as zone with high water availability and rapid groundwater recharge. The variation may be attributed to the existence of dead-end pores as a result of residual argillites in the tortuous path (George et al., 2015). The aquifer transmissivity varies from 0.0019 to 225.7824 with a mean of 19.7004; this parameter is important in determining the ability of a saturated thickness to allow fluid (groundwater) to pass through its entire thickness. It is a function of hydraulic conductivity and thickness. The image map (Fig. 12) depicts the distribution of transmissivity, which follows the same trend as hydraulic conductivity (Fig. 11). This implies that an increase in hydraulic conductivity leads to a corresponding increase in transmissivity.

Fig. 11
figure 11

2-D image map showing the distribution of hydraulic conductivity

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Fig. 12
figure 12

2-D image map showing the distribution of transmissivity

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To assess the protective capacity of the aquifer, the inferred resistivities and thicknesses were used to estimate the longitudinal conductance. The estimated values range from 0.0048 to 0.1022 \({\Omega }^{-1}\) with an average of 0.0235 \({\Omega }^{-1}\), with aid in classifying the aquifer protective capacity of the study area based on the rating in Table 3 (Abiola et al., 2009; Henriet, 1976). The result revealed that the study area has generally poor protective capacity. This implies that the entire study area is susceptible to contaminants percolating into the subsurface, so pollutants may more easily enter the groundwater repositories. This can result in the contamination of drinking water wells/boreholes, which can have serious health implications. Figure 13 displays the distribution of longitudinal conductance across the study area.

Table 3 Longitudinal conductance (mho) and aquifer protective capacity rating (Abiola et al., 2009; Henriet, 1976)
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Fig. 13
figure 13

2-D image map showing the distribution of longitudinal conductance

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The estimated transverse resistance has values ranging from 1549.40 to 20,710.30 \({\mathrm{\Omega m}}^{2}\) and a mean of 8651.93 \({\mathrm{\Omega m}}^{2}\). The distribution (Fig. 14) of this parameter revealed the variational trend in the size and potential of groundwater in the study area. An increase in resistivity translates to a corresponding increase in transverse resistance.

Fig. 14
figure 14

2-D image map showing the distribution of transverse resistance

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Conclusion

The study was carried out to assess the aquifer repositories, protective capacity, and corrosivity employing the surficial electrical resistivity method. The result revealed the study area to be characterized by four geo-electrical layers with inferred layer resistivities, thicknesses, and depths constrained by borehole geological information. The third layer, with a resistivity range of 41.6–1475.9 Ωm, was delineated as the aquifer unit in all the VES locations, with thickness ranging from 9.2 to 50.3 m. The geohydraulic parameters (formation factor, hydraulic conductivity, porosity, transmissivity, longitudinal conductance, and transverse resistance) were estimated using modelled equations and their spatial distributions are displayed in the image maps. The fine-to-medium grained sand that characterized the aquifer units revealed the prolific groundwater potential of the study area. Greater part of the study area is poorly protected, this implies that groundwater in the area is likely polluted by some materials percolating through the overlying layers. This can have serious implications for both human and environmental health, as well as economic and social well-being. The corrosivity rating of the top soil indicates that it is practically noncorrosive (PNC), moderately corrosive (MC), and slightly corrosive (SC), with PNC accounting for 66.67% and MC and SC accounting for 16.67%. The protective capacity rating revealed that the study area is generally poorly protected. This implies that the groundwater in the area is prone to contamination due to the high permeability of the protective layers. The result of this study is very promising as it provides useful information that will help in groundwater exploitation, development, and management.