Introduction

The knowledge subsurface information is vital in groundwater exploration for proper management and protection of groundwater repositories. Groundwater is an essential natural asset that supports domestic, agricultural and industrial activities and its suitability is of great worry for its sustainability and efficient use (George et al., 2015a; Ibuot et al., 2019a; Martínez et al., 2008; Obiora et al., 2015). The availability of this natural resource is affected by its thickness, permeability, porosity, fractures and fissures. The continuous deterioration of groundwater quality has become a growing concern to communities which may affect health, economic and social development of communities. Several boreholes/wells have been drilled and are under threat as a result of desecrations triggered by percolation of contaminants through the vulnerably porous layers of the earth subsurface (Akpan et al., 2013; George et al., 2014; Thomas et al., 2020). Groundwater quality is affected by pollutants emanating from dumpsites, sewage sites, leakage from surface and underground storage, oil spillage, mining activities, sewage from latrines, underlined petroleum pipes and septic tanks, and infiltrates into the aquifer units through the pores and crevices of rocks or soils after decomposition and become point source of groundwater pollution (Agrawal et al., 2011; Anosike et al., 2019; Aweto & Mamah, 2014; Eugene-Okorie et al., 2020; Ganiyu et al., 2015; Hossain et al., 2014; Umar & Igwe, 2019). It can also be attributed to geochemical reactions that occur in the subsurface geologic materials (George et al., 2014; Rawat et al., 2018). Groundwater quality is threatened and degraded by anthropogenic pollutants and are controlled by the geologic environment. The anthropogenic influences on groundwater repositories have become serious issues in many communities in the world (Kumar & Singh, 2018; Shil et al., 2019). Bulk electrical resistivity of soil depend on different factors such as soil type, water content, saturation, and pore fluid property.

The introduction of contaminants into groundwater repositories through rock fractures and pore spaces increases the concentration of organic and inorganic geofluids, thus changing the electrical properties of the subsurface rocks and groundwater. (Al-Tarazi et al., 2008). The geochemical processes, chemical and mineral composition of subsurface rocks and factors related to groundwater flow influence the quality of groundwater (Ibuot et al., 2019b; Inim et al., 2017; Thomas et al., 2020). According to literatures, porosity, permeability, and overburden thickness of geologic formation has great influence on groundwater susceptibility to contamination (Akakuru et al., 2022; Liu et al., 2018; Obiora et al., 2015). Subsurface sediments/rocks control groundwater chemistry since water from their sources flows through these sediments/rocks before their collection and storage in aquifer units (Pazand et al., 2011; Thomas et al., 2020). Many researchers have assessed groundwater quality/status for different purposes using hydrogeochemical data (Akakuru et al., 2022; Barzegar et al., 2017; Moussa et al., 2020; Papazotos et al., 2019), which results reveal the level of concentration of different ions.

The use of electrical resistivity technique can give information about the various geohydraulic parameters distributed across the subsurface, and provides a cost-effective and dependable means to identify the subsurface characteristics through the measurement of apparent resistivity (Aweto & Mamah, 2014; George et al., 2018; Ibuot et al., 2019a, 2017a; Olafisoye et al., 2013). The resistivity method could also be integrated with physicochemical method in studying groundwater quality (Akpan et al., 2013; Ehirim et al., 2010; Ibuot et al., 2017a; Lopes et al., 2012; Olofsson et al., 2006; Ugwu & Nwosu, 2009). The application of geoelectric and hydrogeological properties are effective and complementary characteristics which help in appraising groundwater repositories and the status of groundwater quality (George et al., 2014; Yahaya et al., 2021).

This study integrates both electrical resistivity and physicochemical methods in assessing the groundwater repositories to determine the nature of the aquifers, their distribution, and characteristics as it influences aquifer productivity and groundwater movement. Also, the study will ascertain the level of groundwater contamination in the study area. These will help in proper management and exploration strategies within the study area and areas having comparable geologic characteristics.

Materials and methods

Location, geology and hydrogeology of the study area

The study area falls between latitudes 5.07° N–5.28° N and longitudes 7.64° E–7.75° E (Fig. 1) and covers part of Ikot Ekpene Local Government Area of Akwa Ibom state. The study area is highly drained by the inland coastal water and is situated within the equatorial rain forest belt. The study area is of semi-temperate climate characterized by tropical climate having a mean annual temperature from 20.0 to 30.6 °C, while the maximum and minimum daily temperature ranges between 28 and 30 °C during March and 23 °C and 24 °C during July and August (Evans et al., 2010; George et al., 2010; Ibuot et al., 2013). The wet season is warm, oppressive, and overcast and the dry season is hot, muggy, and mostly cloudy. The study area consists of Coastal Plain sands weathered into lateritic layers located within the Benin Formation of the Niger Delta Basin where most of the aquifer units are found. The lithology shows mature, coarse and moderately sorted sandstone. The Miocene Akata Formation, Miocene-Pliocene Agbada Formation, and the Oligocene Benin Formation are geological Formations that characterized the study area from base to the top respectively. The major hydrogeologic units in the area is found in the middle and the upper sand units of the Benin Formation (Akpan et al., 2013; Edet & Worden, 2009).

Fig. 1
figure 1

Geologic map showing the location of the study area in Akwa Ibom state

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Vertical electrical sounding

Vertical electrical sounding (VES) utilizing Schlumberger electrode configuration was used for this study involving thirteen vertical electrical soundings with ABEM SAS 4000 Terrameter to measure the resistive property of the subsurface in the course of current injection into the ground. The VES was completed with half current electrode spacing \(\left( \frac{AB}{2} \right)\) ranging from 1.0 to 500 m and half potential electrode spacing \(\left( \frac{MN}{2} \right)\) ranging from 0.25 to 20 m. The apparent resistivity for the Schlumberger electrode array used was estimated using:

$$ \rho_{{\text{a}}} = K \cdot R_{{\text{a}}} $$
(1)

where K is the geometric factor which depends on the electrode configuration used, the geometric factor is given by:

$$ K = \pi \cdot \left[ {\frac{{\left( \frac{AB}{2} \right)^{2} - \left( \frac{MN}{2} \right)^{2} }}{MN}} \right] $$
(2)

\(R_{{\text{a}}}\) is the apparent resistance that is measured.

Reading of Ra for each electrode combination was made and the calculated apparent resistivity was inputted into the WINRESIST software for computer modeling. The values of resistivity, depth and thickness of each geoelectric layers were determined from the curves generated (Fig. 2). Using a bilogarithmic graph sheets, graphs of apparent resistivity (\(\rho_{{\text{a}}}\)) against current electrodes separation \(\left( \frac{AB}{2} \right)\) was first plotted and smoothened for curve matching by means of master curves charts. This aid the removal of the effect of lateral inhomogeneities and other noisy signatures such as outliers at crossover points that did not match with the dominant curve trend and were deleted. A number of the deleted data may have been the electrical signatures of the thin clay materials that may have suffered suppression from the overlying and underlying thick sandy aquifers.

Fig. 2
figure 2

Geoelectric curve at VES 1and its parameter

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The percolation of contaminants into the hydrogeologic units is affected by the hydrogeologic unit properties and the knowledge of water-transmitting properties (hydraulic conductivity, transmissivity, porosity, formation factor and tortuosity) which are important in this study. The subsurface is characterized by pores and its connectivity, the knowledge of the pore properties give information about the movement of fluid in the subsurface (George et al., 2015a, b; Ibuot et al., 2019a).

The amount of pore spaces in a formation is porosity which is given by the relation;

$$ {\text{Porosity }}\left( \phi \right) = \frac{{\text{Volume of pores}}}{{\text{Total rock volume}}} $$
(3)

Factors as density, clay contents, tortuosity, hydraulic conductivity affects spatial variability of formation porosity (George et al., 2015a, 2015b). The relationship between porosity, bulk resistivity and water resistivity is given in Eq. (4);

$$ \rho = a\rho_{{\text{w}}} \phi^{{ - {\text{m}}}} $$
(4)

where \(\rho\) and \(\rho_{{\text{w}}}\) are the bulk resistivity and water resistivity respectively, while a and m represent the pore geometric factor and cementation factor respectively (Keller & Frishknecht, 2012). The variation of cementation factor is affected by the formation lithostratigraphy, permeability dependent factors and geologic age of geomaterials (Ekanem, 2020; Obianwu et al., 2011). The effective porosity (ϕ\()\) was estimated using Eq. (5), According to Aleke et al., (2018), porosity is also dependent on the mode of formation of rocks and pressures to which rocks are exposed. Increase in porosity leads to decrease in electrical resistivity of a formation, and will also influence the values of the cementation factor of the propagating medium.

$$ \phi = 25.5 + 4.5{\text{ln}}K $$
(5)

where K is hydraulic conductivity and \(\phi\) is the porosity.

The ease with which pore fluids passes through a permeable medium is the hydraulic conductivity. The hydraulic conductivity \(\left( K \right)\) was estimated using Eq. (6), this parameter (K) measures the resistance to movement of water flowing through a porous medium and is a function of the liquid as well as the medium (Omeje et al., 2021).

$$ K = 386.40\rho^{ - 0.93283} $$
(6)

where \(\rho\) is the layer resistivity.

Transmissivity of the hydrogeologic unit was estimated using Eq. (7). This property connects the bulk of areal flow through a porous medium and it is controlled primarily by the nature of geological formations (George et al., 2018).

$$ T_{{\text{r}}} = Kh $$
(7)

where h is the aquifer thickness.

A pore geometry factor of 0.62 and cementation factor of 2.15 from their experiment on compacted sandstones as express in the Humble equation (Eq. 8);

$$ F = \frac{0.62}{{\phi^{2.15} }} $$
(8)

where F is the formation factor. The geometric patterns of grains and the resulting porosity affect the cementation factor of the propagating media considerably (George et al., 2018). The presence of dead-end pores or impermeable geologic materials of cementation or induration in formations can obstruct effective pore fluid transmission within and across the aquifer units. The flow of fluid in the subsurface may be control by these parameters which are dependent on the pore geometry, nature of grain size, non-uniformity of pore grain orientations and type of pore grains and channels and hydraulic pressure.

The fundamental parameters (layer resistivity and thickness) that characterized the subsurface geologic helped in deriving the aquifer vulnerability index (AVI) using Eq. (9), this will help in quantifying the vulnerability of the hydrogeologic units by hydraulic resistance to vertical flow of water through the covering layers.

$$ C = \mathop \sum \limits_{i = 1}^{n} \frac{{h_{i} }}{{\kappa_{i} }} $$
(9)

where C is the hydraulic resistance, \(\kappa_{i}\) is the hydraulic conductivity while \(h_{i}\) is the thickness of the protective layers. The relationship between hydraulic resistance (C), log C and AVI is shown in Table 1.

Table 1 Hydraulic resistance/aquifer vulnerability index rating (Thomas & Yusrizal, 2018)
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Physicochemical methods

A total of six water samples (BH A, BH B, BH C, BH C, BH D, BH E and control BH) were collected from six different boreholes sited within the study area and analyzed for physical and chemical parameters and results given in Table 3. The bottles containing the water samples were covered tightly and during the analysis, the refrigerated water samples were allowed to attain room/ambient temperature. The water conductivity and pH were measured using water conductivity and 09 Kion pH meters. The cations (\({\mathrm{K}}^{+}\), \({\mathrm{Na}}^{2+}\), \({\mathrm{Ca}}^{2+}\), \({\mathrm{Mg}}^{2+}\) \({\mathrm{Cu}}^{2+},\) \({\mathrm{Mn}}^{2+}\) and \({\mathrm{Fe}}^{2+}\)) were determined using an atomic absorption spectrophotometer (Unicam 969 AAS) at 455 nm. To determine the anions, the water samples were acidified with nitric acid (HNO3) to prevent the metallic ions from adhering to the walls of the container. The anions (\(\mathrm{S}{{\mathrm{O}}_{4}}^{2-}\), \({\mathrm{Cl}}^{-}\) and \({\mathrm{F}}^{-}\)) were determined using a DR 2000 spectrophotometer at 450 nm. The results obtained were compared with the World Health Organization (WHO) standard (WHO, 2017), to assess the contamination status of the groundwater in the area.

Results and discussion

VES

The VES results give information about the subsurface hydrolitho-facies (Table 2) with the respectively values of resistivity, depth and thickness of each layer and define the lithology of the study area with a stratigraphic succession. The values in Table 2 were obtained from the modeled VES curves, 3–5 geoelectric layers were obtained across the study area. VES 4 has resistivity values for 5 layers with corresponding values of thickness and depth while the fifth layer which is defined only by resistivity is undefined within the maximum current electrode separation. VES 1, 2, 3, 5, 6, 9 and 12 have 4 geoelectric layers each, while VES 7, 8, 10, 11 and 13 has 3 geolectric layers each with the last layers undefined. The variation in resistivity at depths may be attributed to geology, topography, lithology, water quality and degree of saturation. In layer 1, the resistivity values ranged from 58. 2 Ωm at VES 12 to 1405.2 Ωm at VES 9, while both the thickness and depth ranged from 0.8 to 3.3 m. The second layer has resistivity values ranging from 178. 7 Ωm at VES 5 to 1867.7 Ωm at VES 10, it thicknesses and depths ranged from 7.2 to 94.5 m and from 8.0 to 95.6 m respectively. The third layer which harbors most of the aquifer has resistivity values ranging from 42.3 Ωm at VES 5 to 2099.9 Ωm at VES 8, while the thickness and depth ranged from 38.7 m to 87.3 m and from 46.4 m to 1182.2 m, respectively, but undefined in VES 7, 8, 10, 11 and 13. The geohydraulic parameters were estimated from the values of the resistivity and thickness using Eqs. (4) to (9) (Table 3). The parameters (hydraulic conductivity K, transmissivity Tr, porosity \(\phi \), formation factor F and hydraulic resistance C), the AVI was determined in terms of Log C to determine the vulnerability status of the area. The aquifer resistivity and thickness ranged from 65.0 to 1867.7 Ωm and from 17.4 to 94.5 m respectively, this low resistivity suggests the presence of sand intercalated with clay. The spatial distribution (Fig. 3) showed that greater part of the study area has low resistivity suggesting the presence of fractured zones and conductive geologic materials which may be attributed to permeation and accumulation of leachate ensuing from dumpsite situated close to some VES points. This suggests that infiltrated contaminants are concentrated more in the deeper layers.

Table 2 Summary of results from geoelectric survey
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Table 3 Calculated aquifer geohydraulic parameters from resistivity and thickness of aquifer layer
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Fig. 3
figure 3

Distribution of aquifer resistivity

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The hydraulic conductivity affects the dynamic behavior of fluids flow in aquifer layers, the estimated values vary from 0.3431 to 7.8686 \(\mathrm{m}/\mathrm{day}\) with an average value of 2.5635 \(\mathrm{m}/\mathrm{day}\). The distribution of hydraulic conductivity (Fig. 4) shows that the northeastern part has highest values of this parameter. It indicates the effect of resistivity on hydraulic conductivity, as increase in resistivity lowers hydraulic conductivity. This distribution of hydraulic conductivity may affect the productivity of wells and the speed of pollutant spread.

Fig. 4
figure 4

Distribution of hydraulic conductivity

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In Fig. 5 shows the variation of aquifer transmissivity and the region with high transmissivity corresponds to the area with high hydraulic conductivity which shows that both parameters are directly proportional to each other. The values of transmissivity estimated from K and h range from 19.6616 to 653.8802 m2/day, which indicates a moderate to high aquifer potential. The high aquifer potential may be due to the porous nature of the hydrologic unit and the interconnectivity of the pore spaces (Ekanem et al., 2019; George et al., 2018). The values of effective porosity ranges from 20.69 to 33.60%, based on these values it could be inferred that the aquifer layers are more of unconsolidated sediments such as coarse sand intercalated with clay (George et al., 2015a, b; Ibuot et al., 2019a, b).

Fig. 5
figure 5

Distribution of aquifer transmissivity

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In Fig. 6 shows high porosity in the northeastern part of the study area which reflects the same trend as transmissivity and hydraulic conductivity. Areas in the southwest and southeast have low porosity indicating the presence of poorly sorted materials compare to the northeast with high porosity, and areas with high porosities are associated with low resistivity areas. The variations in porosity values may be due to the presence of clay and shaly materials within the aquifer units (George et al., 2017).

Fig. 6
figure 6

Distribution of aquifer effective porosity

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Formation factor is lowest in the northeast and corresponds to regions having lowest aquifer resistivity (Fig. 7). The low values of formation factor indicate that the aquifer repositories have high conductivity hence are not affected by higher concentration of contaminants. The closed range observe in these parameters suggest a fairly homogeneous to moderately anisotropic medium which can aid the transport of particles in aquifer layers.

Fig. 7
figure 7

Distribution of formation factor

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The hydraulic resistance (C) ranged from 0.23 to 121.54 with an average value of 22.56, the AVI was determined from the log of C. The contour map (Fig. 8) shows the variation of C with lowest values of C in the western and southern parts of the study area. The ability of earth medium to impede fluid flow determines of its protective capacity since the earth medium act as a natural filter to the infiltrating fluids (Mogaji et al., 2007; Obiora et al., 2015). AVI was rated and classified into extremely high, high and moderate, the highly vulnerable zone reveals the ease of percolation of contaminants through the protective layers. These zones depict high permeability and low clay content and thus vulnerable to contamination.

Fig. 8
figure 8

Distribution of hydraulic resistance

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Physicochemical

The analysis of the water samples gives the results for physical and chemical parameters (Table 4). The pH values which ranged from 6.7 to 8.5 fell within the range of WHO standard from 6.5 to 8.5 for drinking water. Boreholes with pH values lower than 7 indicates that water in those boreholes are slightly acidic, while above 7 are slightly basic, these may be due to the dissolution, draining, decomposition of vegetative materials and also dissolution of minerals by the atmospheric carbon dioxide (CO2) from the industries situated within the study area (George et al., 2014; Ibuot, et al., 2017b, 2019b). The electrical conductivity with range of 28.3–1183 \(\upmu \)S/cm is below the WHO standard suggesting less amount of dissolved ions/solid in the water samples (George et al., 2014) The concentrations of Na+ (2.9–11.9 mg/L), Ca2+ (0.9–15.9 mgL), SO2− (0.6–7.0 mg/L), Fe2+ (0.004–0.11 mg/L) and Cl− (5.8–76.9 mg/L) are below the WHO standard, also K+ (0.6–18.5 mg/L), F− (0.003–1.9 mg/L) and Cu2+ (0.004–0.11) have high concentrations in some boreholes that exceed the WHO standard. The high concentration of K+ in may be due to the consequence of fertilizer and industrial activities. The variations in the physicochemical parameters across the study area may be a function of the geologic layer in which groundwater is stored. The presence of these ions in groundwater repositories affects the bulk electrical properties through the vadose zones to the aquifer units (Akpan et al., 2013; Thomas et al., 2020). The low concentration of Na+ may be due to the low rate of soil reaction, ion exchange, oxidation and or reduction (George, Ibanga, et al., 2015). The control borehole which is located far from the dumpsite shows values less than the investigated boreholes, this indicates that away from the pollutants source the more suitable the groundwater for human consumption.

Table 4 Result of physicochemical analysis
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VES and physicochemical

The results of the surface resistivity (VES) technique have reveal the lithological variation of the subsurface layers. The technique allows the extrapolation of geoelectric and geohydraulic parameters estimated from already established equations. It can be inferred from this study that the lithologic characters such as grain size distribution, permeability, porosity and the geometry of the pore space affects the aquifer units. The contour maps are relevant in showing how these parameters are distributed in the subsurface. Some ions were below the WHO standards, while some were above the acceptable standard. These variations may be due to the unequal draining of the subsurface by contaminant-loaded plume (Anosike et al., 2019). The relatively high concentrations of K+, F− and Cu2+ in the groundwater samples may be attributed to tectonically induced secondary structures like, divides, fault lineaments, and folds of the sedimentary facies and thus leads to leaching, precipitation, and dissolution in the groundwater repositories (George et al., 2014; Thomas et al., 2020). The rate of infiltration of contaminants into the aquifer units is influence by the high permeability of the top geologic layers and communicating pore channels linking the pore-aquifer geologic formation (Ibuot & Obiora, 2021).

Conclusion

The surface resistivity and physicochemical methods were successfully employed to assess the hydrogeologic units of the study area. This study delineated three to five geoelectric layers with values of their resistivity, depth and thickness. The geohydraulic parameters estimated from the electrical parameters show wide variations of the parameters, which indicate the variations in grain sizes and the pore geometry. The hydraulic resistance was used to predict the AVI, where the study area was classified into extremely high, high and moderate vulnerability zones. It could be inferred from this study that the aquifer protective layers are highly permeable thus easy percolation of contaminant fluids into the aquifer units. The contaminants that percolate into the subsurface on reaching the aquifer layer affect the groundwater chemistry by either increasing or decreasing the concentrations of ions. The physicochemical method was performed for cations (\({\mathrm{K}}^{+}\), \({\mathrm{Na}}^{2+}\), \({\mathrm{Ca}}^{2+}\), \({\mathrm{Mg}}^{2+}\) \({\mathrm{Cu}}^{2+},\) \({\mathrm{Mn}}^{2+}\) and \({\mathrm{Fe}}^{2+}\)), anions (\(\mathrm{S}{{\mathrm{O}}_{4}}^{2-}\), \({\mathrm{Cl}}^{-}\) and \({\mathrm{F}}^{-}\)), pH and electrical conductivity. The water samples analyzed revealed low concentrations of Na+, Ca+, Mg2+, SO42−, Fe2+, Mn2+ and Cl− which are below the WHO standard while the concentrations of K+, F− and Cu2+ were high and above the WHO standard in some boreholes. The results could help in assessing the groundwater quality of the area, improve the groundwater management plan of the area and demonstrate the economic feasibility of the integrated methods.