Introduction

The study area lacks abundant surface water resources resulting to increase the demand for groundwater (Uguwanyi et al. 2015; Ossai et al. 2020). Insufficient knowledge of the aquifer nature of the subsurface materials limits groundwater development in the area which is important for borehole construction and in several cases has resulted in unproductive boreholes, extremely low yield, total failure of some boreholes in the area and risk of spending large sum of money in sinking boreholes that will eventually be unsuccessful. Poor quality of water resources does not only affect the environment and socio-economic activities but the health of the populace (risk of water related diseases). Unsafe water is one of the major factors attributed to about 88% of death due consumption of polluted groundwater which results in water related diseases such as diarrhea (UNICEF 2006; Black et al. 2003). Globally water related diseases kill around 525,000 children under the age of 5 (WHO 2008, 2017) thus the need to crave for safe and clean water arises.

Tremendous increase in population has increased industrialization, urbanization and indiscriminate dumping sites yielding contaminated plumes which when percolated into the aquifer layers renders it unsuitable for human consumption (Ibuot et al. 2017a, b). Although, groundwater generally is naturally protected from contamination, it can be unsafe owing to the susceptibility of its protective layers (McDonald et al. 2005). Substantial amount of money will be needed to clean up groundwater once it is contaminated, but most times it is not feasible to achieve clean up within a reasonable time frame (Talabi & Kayode, 2019; Ossai et al. 2020) because replacing contaminated sources with potable sources like treated bottled water are costly and non-comparable to that of existing ground water resources (Abdalla 1990). Notwithstanding that pumping test method is good in evaluating aquifer characteristics; it is capital intensive and consumes much time. However, the results from Shingal and Niwas (1985) indicate that the DC resistivity method provide a fast, less expensive and noninvasive way to study aquifers.

There is a need for geophysical study in this area in order to understand the true nature of the aquifer repositories, delineate areas with good protective layers and possible contamination source for effective groundwater exploration, exploitation and management. Electrical resistivity method is one of the best tools in geophysical investigation used for site investigation toward the determination of overburden resistivity and thickness (Kearey and Brooks 1991). Many authors proved that in order to achieve long lasting boreholes and sustainable supply of water, electrical resistivity survey should be carried out so as to identify groundwater prospective potential and good protective capacity zones for groundwater exploitation (Ezeh et al. 2012; Ugwuanyi et al. 2015; Mallums et al. 2019; Obiora and Ibuot, 2020; Ossai et al. 2020; Ochuko et al. 2021). The significance of using resistivity method in geological terrains to delineate subsurface geological structures, aquifer layers and types of aquifer, thickness and depth extent is successful because of the correlation that exists between electrical properties, geologic formations and fluid contents (Ossai et al. 2020). In groundwater exploration, the vertical electrical sounding (VES) technique is commonly used due to its proneness to near surface lateral inhomogeneities and extraneous current (stray/telluric currents), greater probing depth, well developed and more diversified interpretation techniques, lesser time and its simplicity to determine the variation of the subsurface geomaterials.

The estimation of the geophysically based protection index (GPI) which is used for quantification of aquifer vulnerability have been employed successfully by researchers to delineate areas that have poor protection level hence vulnerable to pollution (Rottger et al. 2005; Casas et al. 2008). Resistivity of most rocks depends on moisture content in their pores, geometry of these pores and the salinity of the water (Todd 1980). Researchers have reported that groundwater quality is majorly affected by percolation of pollutants into aquifer zones (George et al. 2013; Ibuot et al. 2017a, b, 2019a) which is also hugely controlled by the characteristics of the aquifer/overlying layers, recharge-discharge rate and the type of pollutants. The impact of pollutants on groundwater quality has been assessed and results from various works revealed high conductivity of polluted aquifer as evident from the works of (Ugwu and Nwosu 2009; Omogunloye and Jimoh 2013; Ganiyu et al. 2015 and Ibuot et al. 2019a). The electrical conductivity of some pollutants is often much higher than that of natural groundwater, and this large gap in their electrical conductivity value enables contaminated plumes to be detected using geophysical methods. Vertical electrical sounding (VES) is a noninvasive method that helps in understanding aquifer hydrogeological behaviors and revealing contaminant zones due to the conductive nature of most pollutants (Pomposiello et al. 2012, Ekanem, 2020; Ibuot et.al. 2020; Thomas et al. 2020). The subsurface properties affect the withdrawal and flow of groundwater which depends on the formation pore connectivity, pore angularity, compaction, pore-grain volume ratio, resistivity and heterogeneity of formations (George et al. 2017; Ibuot et al. 2019b; Ibuot and Obiora 2021). This research employed electrical resistivity technique to investigate and characterize the aquifer repository, protective capacity of the aquifer overlaying layers using GPI and subsurface properties that influence the flow of groundwater.

Location and geology of the study area

The study area is guinea-savanna vegetation located within the Anambra Sedimentary Basin of the Lower Benue Trough covering Nsukka, Igbo-Eze north, Igbo-Eze south and parts of Udenu Local Government Areas of Enugu State. The study area lies between latitudes 6° 8′ N–7° 03′ N and longitudes 7° 15′ E–7° 31′ E. It has common boundaries with Kogi State, Benue State, Uzo-uwani, Igbo-etiti and Isi-uzo with approximately 3961 km2 total surface area (Fig. 1). There is an increasing population of 894,682 at 2006 census to 1,207,200 projected 2016 censuses,Footnote 1 which increased the quest for safe water supply, affect water supply availability, water demand patterns and need for proper knowledge of the subsurface geology (Duan and Kaoru 2020). This area of study is accessible through a network of major (Federal highway) and minor roads in addition to several foot paths. The geologic rocks in this area are the Upper Cretaceous in age mainly the upper Nsukka Formation and the underlying Ajali Sandstone which are dominant within the study area (Fig. 2). The two major landforms in this area are the geomorphic residual hills and dry valleys which occur as a result of weathering and differential erosion of clastic materials which are remnant of Nsukka Formation. The residual hills sometimes form outliers on the Ajali Sandstone and are capped by thick deposit of red earth materials and laterite which are permeable, particularly those of Ajali Sandstone thereby allowing easy water percolation into the groundwater table. The Ajali Sandstone consists of thick friable, poorly sorted, coarse-medium grained cross-bedded sandstone of Maastrichtian age (Omeje et al. 2021). Nsukka Formation has a significant groundwater potential and harbors a number of low to moderate yield wells in Nsukka areas due to formation of perched aquifer in Nsukka areas. Eroded remnants of this formation constitute outliers and its thickness averages 250 m (Ezeh and Ugwu 2010). The topography is highly undulating with elevation which varies between 281 and 521 m above sea level measured in the field peaked at Umuabo-Ehalumona area at 521 m. Discharge of the existing perched aquifers occur in hilly areas such as Asho hill in Nsukka, Aku hill in Obukpa, Abile hill in Ibagwa-aka and Awula in Ibagwa-Ani.

Fig. 1
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Map showing the location of the study area

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Fig. 2
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Map showing the Geology of the study area and sampled VES points

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Materials and methods

The study involves a total of fifty vertical electrical sounding points carried out using IGIS resistivity meter and its accessories. The survey employed the vertical electrical sounding (VES) with the maximum current electrode separation of 900 m and half potential electrode spacing of 40 m. Also borehole log were obtained from borehole drilling cites close to some VES points. The potential electrodes were expanded symmetrically about a fixed center of spread (Ibuot et al., 2013; George et al. 2015). The apparent resistivity for this configuration is given by Eq. 1:

$$\rho_{a} = \pi \cdot \, \left[ {\frac{{\left( {\frac{{{\text{AB}}}}{2}} \right)^{2} - \left( {\frac{{{\text{MN}}}}{2}} \right)^{2} }}{{{\text{MN}}}}} \right] \cdot R_{a}$$
(1)

The equation can be simplified to

$$\rho_{a} = G_{s} \cdot R_{a}$$
(2)

where GS is the geometric factor \(\pi \cdot \left[ {\frac{{\left( {\frac{{{\text{AB}}}}{2}} \right)^{2} - \left( {\frac{{{\text{MN}}}}{2}} \right)^{2} }}{{{\text{MN}}}}} \right] \,\) and \(R_{a}\) is the apparent resistance.where AB/2 and MN/2 are the half current and half potential electrode separations, respectively. The apparent resistivities were computed from the field data using Eq. 2, and the values were plotted on a bi-log-graph having apparent resistivity value against half current electrode spacing. Data filtering and smoothening were carried out where necessary to remove traces of noise in the data (Loke 2001). The WINRESIST software program was used in the computer modeling, iteration and curve matching as carefully designed and programmed for Schlumberger array by Zohdy. A good fit with little RMS error was obtained between the field and model curve revealing true values of resistivity, depth, thickness and number of geoelectric layers in Fig. 3. The result of the geoelectric curves revealed 4–6 geoelectric layers as presented in Table 1 and the fourth and fifth layer is found to be associated with larger thickness and was delineated as the water bearing layer (aquifer) in the study area. For better interpretation and understanding of a particular geologic model, it is necessary to combine different parameters such as thicknesses and resistivities of a geoelectric section (Zohdy et al. 1974; Maillet 1947). These principal parameters (resistivity and thickness) are not left out in estimating the hydraulic conductivity, porosity and evaluating geophysically based protection index (GPI). The resistivity model curves for some of the VES stations are shown in Fig. 3. The resistivities and thicknesses of the layers above the aquifer layer were used to estimate the geophysically based protection index (GPI) which aided in the quantification of aquifer protective capacity. The electrical conductivity (σi) and thickness (hi) were used in estimating the geophysically based Protection Index (Casas et al. 2008) or Integrated Electrical Conductivity, IEC (Rottger et al. 2005). The geophysically based Protection Index (GPI) can be used to assess the aquifer vulnerability using Eqs. 3 and 4;

$${\text{GPI}} = \sum\limits_{i = 1}^{n} {h_{i} } * \sigma {}_{i}$$
(3)
$${\text{Or}}\;\;\;\;\sum\limits_{i = 1}^{n} {h_{i} } * \frac{1}{{\rho_{i} }}$$
(4)

where \(\sigma_{i} = {1 \mathord{\left/ {\vphantom {1 {\rho_{i} }}} \right. \kern-\nulldelimiterspace} {\rho_{i} }}\), resistivity (ρi) and thickness (hi) of each layer above the aquifer are obtained from the inversion of resistivity sounding data. The GPI value will have a maximum value when the thickness of low resistivity cap above the aquifer is greater, giving the highest protection level to the groundwater against contamination from the surface (Casas et al. 2008). The rating will be done using Table 1.

Fig. 3
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Geoelectric curve for VES 7

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Table 1 Rating of protective capacity based on GPI (Casas et al. 2008)
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The obtained primary parameters (true resistivity and thickness of each layers) from the computer iteration were used to estimate the geohydraulic parameters of the covering layers. Hydraulic conductivity indicates the porous and fractured areas of the subsurface rocks that allow easy movement of groundwater through the pore spaces. It is calculated using Eq. 5 according to Heigold et al. (1979).

$$K = 386.40\rho^{ - 0.93282}$$
(5)

where \(\rho\) is resistivity of the aquifer overlying layers.

Porosity (\(\phi\)) is the ability of the earth to sieve fluids and is controlled by grain size and shape, degree of rating, extent of cementation and fracturing. The effective porosity was calculated using the relation from Marotz (1968) expressed as Eq. 6.

$$\phi = 25.5 + 4.5\ln K$$
(6)

where K is the hydraulic conductivity of the aquifer or overlying layer.

Formation Factor can be expressed in a simplest form as a power law of the effective porosity and geometric factors. An empirical relation, Archie’s Law (Eq. 7) was used to describe this relationship:

$$F = \frac{a}{{\phi^{m} }}$$
(7)

where a is pore cementation factor, m is geometry factor of the pore (empirical constants) and \(\varnothing\) is effective porosity. Values of a in the range of 0.47–2.3 can be found in the literature. The value of m is generally considered to be a function of the kind of cementation present and is reported to vary from 1.3 for completely uncemented soils or sediments to 2.6 for highly cemented rocks, such as dense limestone. For this analysis, values for a and m that was used are 0.5 and 1.5, respectively. In addition to the above analysis, the corrosivity of the first layers will be classified and rated based on their resistivity values using Table 2. Corrosivity describes how aggressive water is at destroying or weakening (corroding) pipes and fixtures which causes lead and copper in pipes to leach thus causing rusts and leaks in plumbing pipes and eventually making the groundwater less potable.

Table 2 Classification of soil resistivity in terms of corrosivity (Baeckmann and Schwenk 1975; Agunloye 1984; Oladapo et al. 2004)
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Results and discussion

The qualitative interpretation of results of the 1-D resistivity (VES) data processed with WinResist software is presented in (Table 3); it defined the lithology and stratigraphic sequence of 5–6 layers. The model curves obtained exhibit thirteen (13) different curve types: KHK taking about 10%, AAKQ, KHAK, KHAA, HKQ, HKQQ and HAA taking 12%, AAA, AKH, HAK and KHKQ taking 24% while AKQ and AAK take 20 and 34%, respectively, which further confirms the variation in lithology, formation and inhomogeneity of the study area. VES profiles were quantitatively analyzed and the results give the geoelectrical information of resistivity, thickness and depth of the subsurface hydrolithofacies example Fig. 3 which shows the geoelectric curve for VES 7. The first layer resistivity ranged from 40.4 to 3367.1 Ωm. This shows that the layer is dominated by low to medium resistive materials made up of sandstone topsoil intercalated with clay. The thickness and depth of this layer varies between 0.5 and 3.9 m. The second geoelectric layer with a resistivity range of 92.2 to 11,730.1 Ωm is made of low to high resistivity materials dominated by silty shale to dry unconsolidated sand. This layer is generally less conductive compared to the overlying lithologic units, the thickness and depth of this layer range from 1.5 to 20.4 m and 2.6 to 23.2 m, respectively. The third layer dominated by highly resistivity materials are made of unconsolidated dry sandy silt, this layer on the average is less conductive than the overlying lithologic units. The layer resistivity values ranged from 85.3 to 73,324.3 Ωm with thickness and depth ranging from 3.6 to 85.7 and 8.9 to 94.6 m, respectively. The fourth layer has a resistivity range of 153.7 to 91,659.2 Ωm with thickness and depth range of 22.4 to 174.3 and 31.3 to 218.4 m. This shows that this layer is also more resistive than the overlying layers; this lithologic unit harbors about 84% of the aquifer in the study area and this agrees with result of Omeje et al. (2021) whose result was obtained from a small part within the study area. The fifth layer has resistivity values ranging from 312.8 to 16,675.1 Ωm, the thickness and depth of this layer is undefined except for VES 3, 8, 12, 13, 24, 23 and 38 with ranges of 45.1 to 154.4 and 104.3 to 198.0 m, respectively. This layer is less resistive and more conductive than the overlying layers harboring 14% of the aquifers in at the study area. The sixth layer is observed only in VES 3, 8, 12, 13, 24, 23 and 38 with resistivity range of 1118.9 to 6892.0 Ωm with undefined thickness and depth within the maximum current electrode separations in all the VES stations. It can be said that the sediments in this layer are not compacted, hence lower resistivity values indicating higher conductive geomaterial. Since the layer is below the water table, the sediments in this lithologic unit are considered to be unconsolidated (Mooney, 1980). Generally, it can be inferred from the result that variation in resistivity with depth is majorly affected by geology, topography, drainage system, lithology, water quality and degree of saturation (George et al. 2014).

Table 3 Summary of result of resistivity survey form computer modeling using WINRESIST software
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Borehole log

The earth materials that dominates the subsurface are fine-medium grain sand, coarse grain sand, dark gray shale, fine grain sand, medium-coarse grain sand, the fine grain sand and the medium-coarse grain sand harbors most of the aquifer layers. The thicknesses of the layers in meters at various depths are evident within the location. The geoelectric layers depth from the VES analysis was constrained using borehole logs obtained from drilling sites close to some VES points as shown in Fig. 4 aided the analysis and interpretation of layers depth and aquifer layers in the study area (Batayneh 2009). The resistivity values from the field survey were constrained using the obtained borehole log to help reduce the intrinsic problems of equivalence and suppression encountered during the interpretation of VES data (George 2021). It also aided the analysis and interpretation by reducing the choice of layer models and identification of the aquifer layer within the locations drilled (Vanovermereen 1989).

Fig. 4
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Borehole lithology logs. a: borehole lithologic log close to VES 5, 22 and 29, b: borehole lithologic log close to VES 4, c: borehole lithologic log close to VES 15

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Table 4 presents the estimated values of overburden/bulk layer resistivity, conductivity, thickness, GPI, hydraulic conductivity, formation factor, porosity and corrosivity of the first geoelectric layer. The overburden layer resistivity and thickness ranged from 589.8 to 85,094.8 Ωm and 8.9 to 99.5 m with mean values of 42,642.3 Ωm and 54.2 m. The spread of the overburden resistivity as shown in its contour map (Fig. 5) reveals that low resistivity values dominate the study area indicating presence of high conductive material while the highest overburden resistivity is mainly within the southwestern part. The relatively high resistivity values and the presence of low conducting geomaterials may be attributed to low percolation of subsurface contaminants (Aleke et al. 2018). The aquifer resistivity range obtained in this study area is far higher than the range obtained by Ugwuanyi et al. (2015), Ezema et al. (2020), Obiora and Ibuot (2020), Omeje et al. (2021), who adopted electrical resistivity method to investigate aquifer repositories in little parts of the study area.

Table 4 Calculated GPI and overburden geohydraulic parameters from resistivity and thickness of overlying layers
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Fig. 5
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2D and 3D contour map showing the variation of bulk resistivity in the study area

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The contour map of the overburden thickness (Fig. 6) shows the variation of this parameter across the area depicting areas with high to low thickness of geologic material. It is shown that areas with high overburden resistivity correspond to areas with high overburden thickness and vice versa. The aquifer units located in areas with high overburden thickness may likely have high protective capacity and may not be vulnerable to pollution (Burger et al. 1992; Obiora and Ibuot 2020). Results of aquifer thickness corresponds with the results of aquifer thickness determined by Ugwuanyi et al. (2015), Ezema et al. (2020), Obiora and Ibuot (2020) and Omeje et al. (2021) who studied aquifer characteristics in areas having similar geologic features with some part of the study area showing similar trend variation with aquifer thickness of this study area though of different magnitude. This shows that areas with similar geologic features can vary in groundwater accumulation.

Fig. 6
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2D and 3D contour map showing the variation of bulk thickness in the study area

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The estimated GPI of the overlying layer has value ranging from 0.0004 to 0.0690 Ω−1with average value of 0.0010 Ω−1 while the hydraulic conductivity (K) of the overlying layer has values varying from 0.0097 to 1.0056 mday−1 with average value of 0.5077 mday−1. The GPI contour map in Fig. 7 revealed areas with high and low vulnerability and its rating in Table 4 using Table 1 is from weak to fair level of contamination. Some areas in the western and eastern part of the study area have aquifers with the highest risk of contamination. Since the earth medium act as a natural filter to the percolating fluid, its ability to retard fluid infiltrating into the subsurface is a measure of its protective capacity (Mogaji et al. 2007; Obiora et al., 2015; Obiora and Ibuot 2020; Ossai et al., 2020). This implies that aquifers in the areas with low protection level have the highest tendency to being protected from polluted leachates easily due to high overburden resistivity and thickness with low porosity and hydraulic conductivity of the overlying layer (Mallums et al. 2019). This result of GPI is consistent with that of Ossai et al. (2020) who employed aquifer vulnerability index (AVI) method in carrying out vulnerability assessment.

Fig. 7
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2D and 3D contour map showing the variation of GPI in the study area

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The spread of hydraulic conductivity (Fig. 8) for the overburden layers reveal that the western and eastern part of the study area have the highest value of overburden hydraulic conductivity implying high infiltration and good area for groundwater accumulation. The hydraulic conductivity ranged from 0.009 to 0.539 Ω−1 m−1 with an average of 0·274 Ω−1 m−1. It is observed that areas with maximum value of GPI correspond to areas of high hydraulic conductivity and porosity, indicating that the zone is being saturated with contaminants of high conductive minerals in the aquifer layers. The Southwestern and part of Southeastern in the study area is observed to have high hydraulic conductivity values while low values trend from the North to South. The high value is an indication of high conductivity, high porosity, high transmissivity, low resistivity and low thickness (Oseji et al. 2018).

Fig. 8
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2D and 3D contour map showing the variation of bulk hydraulic conductivity in the study area

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The fractional porosity value of the overlaying layers ranged from 4.6553 to 25.5253 with the mean values of 15.0903 while the value of the formation factor (F) ranged from 0.0039 to 0.0498 with the mean value of 0.0268. It can be inferred that the porosity of the overlaying layer influences the easy flow of fluid during infiltration, low to moderate porosity level sweeps across the area except some part in the western and eastern region which has high bulk porosity level in Fig. 9 corresponding to high bulk hydraulic conductivity. This implies that a highly porous layer allows free flow of fluids. On the contrary, areas of high formation factor correspond to area of high bulk thickness and resistivity as shown in the contour map (Fig. 10), areas with high porosity is attributed to areas with low formation factor and vice versa. When the formation factor is high, the hydraulic conductivity, porosity, recharge and infiltration rate will be very low. The variation of elevation in the study area considered as one of the factors influencing groundwater movement and transmission and zones with low elevation are associated with low overburden thickness and resistivity, high GPI, high risk of contamination, high porosity, hydraulic conductivity and vice versa.

Fig. 9
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2D and 3D contour map showing the variation of bulk porosity in the study area

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Fig. 10
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2D and 3D contour map showing the variation of bulk formation factor in the study area

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Corrosivity describes how aggressive water is at destroying or weakening (corroding) pipes and equipment. Corrosive water reduces the quality of groundwater and can lead to health related problems such high blood pressure, gastro intestine disease and kidney and liver problems. Corrosivity of soil in the study area was determined using the first layer resistivity and comparing with that of Table 2. The first layer soil of all the VES locations has resistivity value greater than 180 Ωm indicating that the soil materials are practically non-corrosive agrees with results of Roberge 2000, Omeje et al. (2021) and can favor the laying/burying of underground iron tanks/pipes without deterioration or rusting. VES 19, 35 and 43 have resistivity of the soil materials less than 180 Ωm but greater than 60 Ωm, this is an indication of slightly corrosive geomaterials which when in contact with metals pipes can corrode the pipes, hence not suitable for laying underground pipes but concrete and steel underground reservoirs can be constructed for water storage. This result and suggestions compares positively with the works of Obiora et al., 2016. The second layer is practically non-corrosive and is hereby advised that engineers should go beyond the first layer while installing metal pipes beneath the earth surface in those locations whose geomaterials can be slightly or moderately corrosive or install plastic pipes.

Conclusion

Electrical resistivity method was successfully employed to evaluate the groundwater repositories in terms of groundwater potential and protective capacity of parts of Enugu North, Eastern Nigeria. The results of the geoelectric survey revealed that the study area is made up of five to six geoelectric layers and different geoelectric curves obtained revealed the heterogeneity and variation in lithologic formation within the study area. The fourth and fifth layers were found to harbor most of the aquifer units with some parts having low groundwater potential. Some areas in the western and eastern part of the study area have high risk of groundwater protection against contamination while other locations with low protection level are not vulnerable to contamination from surface contaminants. It is inferred from the study that hydraulic conductivity and porosity in the Southwest is high indicating that the groundwater potential will be good in VES 47 and its environ though with high risk of being contaminated. A good borehole in the study area should be drilled to a depth within the fourth and fifth layer (aquifer unit). Most of VES points in the first layer are practically non-corrosive which implies that the top layer is made up of geologic materials that cannot cause corrosion of pipes or any metal. This study have thrown more light in the understanding of the aquifer protective capacity, corrosive nature, groundwater potential and the properties of the aquifer repositories in the inhomogeneous study area which will serve as a guide to other researchers and borehole drillers for effective groundwater development, management and exploiting aquifers with good protective capacity in order to obtain potable water. Based on the results from this research it is suggested that aquifer in areas that have low or little contamination risk should be explored while attempt should be made in those areas with high pollution risk to reduce the pollution rate by total stoppage of refuse dumping, laying sewage pipes and treatment of pumping water before use. Finally this study showcased that GPI is an important method in delineating hydrogeological units that are prone to contamination by virtue of the unique combined effect of the overlying layer thicknesses. Since adequately thick aquifer overlying layer could prolong/delay the transit time of contaminants into aquifers underneath thereby degrading the contaminants caused by the synergistic effects of geologic and biogenic activities and making such areas not to be minimally weak to pollution. Areas with high GPI values are associated with low values of overburden thickness which makes the protective capacity to be weak and susceptible to pollution.