Introduction

Geo-electric strategies are deeply grounded and generally used to settle an assortment of hydro-geophysical, land, and ecological subsurface identification issues (Opara et al. 2021; Eyankware et al. 2022a, b; Onu and Ibezim 2004; Hussein and Tarig 2014; Idornigie and Olorunfemi 2006). It is a non-disastrous testing innovation and an exceptionally helpful apparatus for portraying pressure-driven boundaries, spring weakness, dampness content, porosity, immersion, type, and mineral creations of soil and application possibilities because of the great specialized, ceaseless, quick, and monetary advantages (Guma et al. 2015; Aigbadon et al. 2023). The main role of the resistivity strategy is to quantify the expected contrasts on a superficial level because of the ongoing stream inside the ground. Since the component which controls the liquid stream and electric flow and conduction are for the most part administered by similar actual boundaries and lithological credits, the water-powered and electric conductivities are subject to one another (Nwachukwu et al. 2019; Urom et al. 2021). 

As Breusse (1963) stated, real progress in the use of electrical strategies for groundwater surveys began during WW11. Information on the benefits of well boundaries, such as pressure-controlled conductivity and permeability in the study area, is valuable in assessing the site’s groundwater capacity. The usual approach to determining the stated swelling limits was to use siphon test techniques, which proved to be costly, tedious, and boring (Agidi et al. 2022). Similarly, various equations accessible to determine spring attributes from a survey of siphon test information include spring congruence, thickness, uniformity, isotropic, well capacity, and fluid under field conditions. It is important given that various speculations about the nature of the flow are guaranteed (Freeze and Cherry 1979). Surface electrical strategies have emerged as a more convenient option than siphon test techniques for securing well boundaries (Opara et al. 2022). This strategy is costly and time-consuming and is used to predict boundaries even in areas without current wells (Freeze and Cherry 1979; Kruseman and de Ridder 1994; Sattar et al. 2016). With this in mind, the effort to drill exploratory wells in the world’s hydrogeological shells has been reduced.

Various studies have been conducted on the use of geoelectric techniques in estimating desirable hydraulic parameters for aquifers (Uma 1989; Mbonu et al. 1991; Ekwe et al. 2006; Monye 2017). Uma (1989) evaluated the groundwater resources in the Imo River Basin. He concluded that the complex geological setting of the Imo River Basin provides a similarly complex water horizon setting. These aquifer systems generally have the same extent as the formation. According to him, it is almost impossible for aquifers to cross geological boundaries due to regional strata and general trends in strata. He identified three aquifers: shallow-borderless aquifers, confined aquifers, and deep-borderless aquifer systems. However, his data were so sparse that he could not make a general statement about the hydraulic properties of the Central Imo River Basin aquifer (Ekwe et al 2006; Emberga et al. 2019). Mbonu et al. (1991), while investigating the characteristics of some aquifers in the Umuahia region of Southeastern Nigeria, identified three different geo-electric layers covering conductive underground geoelectricity. The results of the survey also show two zones where hydraulic properties and water quality differ from each other. Ekwe et al. (2006) used the electrical resistivity method to estimate the shape, hydraulic conductivity, and permeability of the aquifer in the central part of the Imo River Basin. The study revealed that the sedimentary sequence in Southeastern Nigeria contains multiple aquifers. Eyankware et al. (2022c) argued that by calculating the permeability of aquifers based on the results of resistivity measurements, it is possible to depict areas with good groundwater potential. His study points out that resistivity exploration can determine the depth of the water table, the thickness of the aquifer, and the geology of the ground, thus revealing the distribution and potential of the aquifer.

An accurate assessment of groundwater resources and quantitative characterization of aquifers in and around Njaba is essential to address some hydrogeological issues associated with groundwater exploration and development. The Njaba region is experiencing enormous development and growth in population density. This population growth has increased the demand for freshwater to meet the needs of agricultural, household, and industrial water. Most residents of the study area often rely on the use of surface water that is normally contaminated or generally inaccessible, and most wells in the area are pumped from water-containing units that are vulnerable to surface pollution.

Fluid permeability, storage capacity, diffusivity, resistivity in the horizontal direction, conductivity in the vertical direction, permeability coefficient, depth, and thickness of aquifers are the basic characteristics that explain groundwater hydrology (Sheriff 1991). As a result, many research methods are often used to estimate the spatial distribution of the above hydraulic parameters. Field estimates of the above parameters are not always available. Hydraulic conductivity seems to be the most problematic to obtain due to the wide range of observed values or the unsatisfactory values observed in the laboratory measurements (Oli et al. 2022).

Therefore, the integration of the aquifer properties calculated from the borehole and the surface resistivity parameters extracted from the surface resistivity measurements is because both properties are related to pore space structure and non-uniformity. It is very effective because it allows correlation between the properties of the layer and the electrical aquifer (Eke et al. 2015; Niwas et al. 2006).

Location, physiography, and climate of the study area

The review region Njaba and its environs are in Imo State, Southeastern Nigeria, and lies between scopes 5°39′00″N and 5°45′30″N and longitude 6°58′30″E and 7°3′30″E (Fig. 1). The Njaba River advantageously outlines Umuaka and Ekwe in the western boundaries. The review region extends as an undulating land surface with an openly level surface at a rise of around 183–244 m. The review area has thick vegetation with a mean yearly precipitation of around 1800–2500 mm, which takes care of a broad hydrological framework, for which the Njaba waterway is important for. Temperature goes from around 27 to 32 °C with February to April being the most blazing. Relative dampness goes from 70 to 80% (Ekwe et al. 2006; Obasi et al. 2020; Onyekuru et al. 2021).

Fig. 1
figure 1

Location and topographic map of the study area

Full size image

Geology of the study area

The Njaba study area is largely covered by the Benin Formation, which is composed primarily of sand from continental rivers beneath vast areas of Southern Nigeria. It is typical of sand around Benin City and is estimated to be 3050 m thick (Akakuru et al. 2021). The Benin layer is characterized by a high sand content (70–100%) and forms the top layer of the Niger Delta deposition sequence. These giant sands were deposited in the continental environment, including the river regions of the Upper Delta Plains (braided and winding systems) (Obasi et al. 2020). It is composed of fragile sand and small clay deposits (Short and Stauble 1967). The thickness of the Benin Formation varies, perhaps over 6000 ft, but according to Avbovbo (1978) of Ebuta (2015), the average thickness of the formation in the study area is about 800 m.

The hydrogeological significance of the study area is attributed to the Benin Formation, which has a high degree of permeability, and has prevented the development of a stream network (Short and Stauble 1967). The highly permeable formation is prevented by impervious strata. The Njaba River which flows through the study area is a tributary of the Orashi River. The Njaba rises near Orlu and joins the Orashi River near Oguta Lake. The area has an aquifer replenishment of about 2.5 billion cubic meters per day (Ekwe et al. 2006). The aquifer is characterized by fairly high permeability, transmissivity, and storage coefficients, which makes it an excellent source of groundwater (Akakuru et al. 2021; Urom et al. 2021; Eyankware et al. 2021; Opara et al. 2021; Ekwe et al. 2006). Groundwater flow is in a south-west direction with estimated gradients of 2 to 3%. Drilling of boreholes has revealed that the upper levels of the aquifer can be estimated to be within the range of 185–190ft (Eyankware et al. 2022c; Ekwe et al. 2006) (Fig. 2).

Fig. 2
figure 2

Geology of the study area

Full size image

Materials and method

In this study, we estimated the use of geo-hydrogeological characteristics of the study area using electro-geophysical and hydrogeological techniques. The Schlumberger configuration was used to measure the resistivity. VES data was obtained from the field using ABEM Terrameter SAS 4000. This study used a maximum current electrode spacing of 1000 m. A total of 23 VES datasets were collected along profiles at various locations. Analysis of the resulting resistivity and half-current electrode spacing yielded a layered earth model consisting of discrete layers of specified thickness and apparent resistivity. The data obtained were plotted as a plot of apparent resistivity against half-current electrode spacing (AB/2) on a log plot scale. Approximately, the probing depth at each spread is two-thirds (2/3) of the electrode spacing at which bending occurs on the chart (Vingoe 1972). The VES results were modeled using computer iterative inversion models. Resistivity curves were developed. The smoothened curves were qualitatively interpreted using master curves and standard charts (Opara et al. 2022; Orellana and Mooney 1966). In the Schlumberger arrangement (Fig. 3), the current–potential pairs of the electrodes share a common center, but the distances between adjacent electrodes are different, so a ≠ b. Pumping test data were collected from monitoring wells that are close to the sampled points.

Fig. 3
figure 3

Schlumberger array

Full size image

Data evaluation and modeling

Theoretically, the resistivity (ρ) of a material is directly proportional to the potential difference (V) and inversely proportional to the induced current (I).

$$\mathrm\rho\propto\frac{\mathrm V}{\mathrm I}$$
(3.1)
$$\rho=K\left(\frac{\mathrm V}{\mathrm I}\right)$$
(3.2)

where K is the geometric factor and can be obtained thus:

$$K=\pi\left\{\frac{\left[\left(\frac{\mathrm{AB}}2\right)^2-\left(\frac{\mathrm{MN}}2\right)^2\right]}{\mathrm{MN}}\right\}=\pi\left(\frac{\mathrm a^2}{\mathrm b}-\frac{\mathrm b}4\right)$$
(3.3)

Hence,

$$\rho=\pi\left(\frac{\mathrm a^2}{\mathrm b}-\frac{\mathrm b}4\right)\left(\frac{\mathrm V}{\mathrm I}\right)\mathrm{Or}\;\rho=\pi\left(\frac{\mathrm a^2}{\mathrm b}-\frac{\mathrm b}4\right)\;R$$
(3.4)

Recall \(\rho =\mathrm{KR}\)

where R is the resistance.

The geometric coefficient K depends on the electrode spacing. R responds to the resistance of the bulk volume between the potential electrodes. Apparent resistivity data is interpreted as the depth to the bedrock or bedrock, and to other interfaces where strong electrical contrast is present. Next, the vertical curve of depth is interpreted, assuming that the earth is composed of layers with almost constant resistivity. Due to the different resistances, the layers are separated by a planar interface.

Estimation of aquifer Dar-Zarrouk parameters

Quantitative interpretation of vertical electrical exploration data often leads to the formation of geoelectric layers. Information from these geoelectric layers improves the identification of layer parameters such as aquifer depth and thickness. The layer parameters thus obtained are used to evaluate the Dar-Zarrouk parameters (Opara et al. 2022; Umayah and Eyankware 2022).

Telluric conductance (LC) is a telluric parameter used to define the target area of groundwater potential. High longitudinal conductance values ​usually indicate a relatively thick continuum and should be given the highest priority for groundwater potential. Longitudinal conductance (LC) is obtained by dividing the aquifer thickness (h) by the resistivity of the aquifer (ρ).

$${\boldsymbol L}_{\boldsymbol C}\boldsymbol\;\boldsymbol=\boldsymbol\;\frac{\boldsymbol h}{\boldsymbol\rho}$$
(4.1)

Transverse resistance (TR) is one of the parameters used to define a target area with good groundwater potential. It is directly related to permeability and the highest lateral resistance values probably reflect the highest aquifer permeability values.

$${\boldsymbol R}_{\mathit T}\boldsymbol{\mathit\;=\;}\boldsymbol h\boldsymbol\rho$$
(4.2)

Estimation of aquifer hydraulic parameters

The hydraulic properties of the aquifer can be determined using the Dar-Zarrouk parameters (lateral resistance and conductance). Niwas and Singhal (1981) established an analytical relationship between transmittance and lateral resistance on the one hand and transmittance and longitudinal conductivity on the other.

From Darcy’s law, the fluid discharge Q is given by

$$\boldsymbol Q\boldsymbol=\boldsymbol k\boldsymbol{\mathit'}\boldsymbol I\boldsymbol A$$
(4.3)

And from Ohm’s law

$$\boldsymbol J\boldsymbol{\mathit=}\boldsymbol\sigma\boldsymbol E$$
(4.4)

where K—hydraulic conductivity; I—hydraulic gradient; A—cross-sectional area perpendicular to the direction of flow; J—current density; E—electric field intensity; and σ—electrical conductivity (inverse of resistivity).

Considering a prism of aquifer material having a unit cross-sectional area and thickness, h, Niwas and Singhal (1981) combined Eqs. (4.3) and (4.4) to get:

$${\boldsymbol T}_{\boldsymbol N\boldsymbol\&\boldsymbol S}\boldsymbol=\boldsymbol k^{\boldsymbol'}\boldsymbol\delta\boldsymbol R=\frac{\mathrm k^{'}{\mathrm L}_{\mathrm C}}{\mathrm\delta}$$
(4.5)

where T—aquifer transmissivity; R—transverse resistance; \({{\varvec{L}}}_{{\varvec{C}}}\)—longitudinal conductance; k’—hydraulic conductivity.

The results of hydraulic conductivity and aquifer conductivity estimated from borehole observations are consistent and give the term k’ known as a diagnostic parameter. Symptomatic boundaries are the solid lines that connect the Dar-Zarrouk boundaries to the terrain, so boundaries that are usually indexed for areas with different land placements are determined to improve the geographic impact of the prediction cycle. However, the diagnostic parameters (kσ) are very stable in geographically homogeneous areas (Eyankware and Akakuru 2022). Hydropower conductivity (Niwas and Singhal 1981) is obtained as given in condition 4.6 in that the spring resistance ρ increases the symptomatic continuity.

$${\mathbf K}_{\mathbf N\boldsymbol\&\mathbf S}\boldsymbol=\mathbf k\boldsymbol'\boldsymbol\sigma\boldsymbol\rho$$
(4.6)

Heigold et al. (1979) carried out a cross-plot of aquifer resistivity values ​obtained by parametric vertical electrical exploration near the control well region with subsequent connection coefficients with the hydraulic conductivity values ​estimated from the three observation wells. I applied a non-rectangular line and won 0.94. This fitted least squares line provided a striking relationship between the hydraulic conductivity and resistivity of the aquifer given in condition 4.7.

$${\mathbf K}_{\mathbf{HG}}\boldsymbol=\mathbf{386}\boldsymbol.\mathbf{40}\boldsymbol\rho_{\mathbf{rw}}^{\boldsymbol-\mathbf0\boldsymbol.\mathbf{93283}}$$
(4.7)

where KHG—hydraulic conductivity was estimated using the Heigold et al. (1979) equation in cm/sec; ρrw—resistivity of the water-saturated aquifer in ohm-cm. It is this kind of expression that gives an overall idea of the water-producing strength of the aquifer from surface electrical measurements.

The empirical formulas of Heigold et al. (1979) and Niwas and Singhal (1981) were used to estimate the geological properties of the aquifer from the surface resistivity data in the study area. However, using these empirical formulas, the aquifer parameters may be underestimated or overestimated in areas that do not resemble certain geological settings. To solve this problem, new empirical relationships were developed using pump test data collected from three surveillance wells in the current study area. An empirical formula was developed for the study area because the area is geologically homogeneous and is generally covered by the Benin Formation. The purpose of the new model was to limit the predictive power of empirical formulas using local geology. Therefore, in this study, we applied the least squared line to the cross-plot of the water permeability coefficient values ​measured from the three monitoring wells and the water saturation resistance of the water-saturated aquifer to establish the power law relationship, with coefficient of determination of R2 = 0.605). This led to the empirical formula given in Eq. 4.8.

$${\boldsymbol K}_{\mathbf{NM}}\boldsymbol=\boldsymbol6^{\boldsymbol\ast}\boldsymbol{10}^{\boldsymbol-\boldsymbol7}{\boldsymbol\rho\mathbf w}^{\boldsymbol1\boldsymbol.\boldsymbol{720}}$$
(4.8)

where ρw is the water-saturated aquifer resistivity (Ωm), KNM is the hydraulic conductivity in (m/day), estimated using the New Model (Fig. 4).

Fig. 4
figure 4

Plot of hydraulic conductivity from the New Model

Full size image

The three T values obtained from the pumping test were plotted against the corresponding RT for each of the locations. A new model was developed and was designated “Transmissivity from New Model” (TNM). An empirical relationship for TNew Model, with a very strong positive correlation (R2 = 0.902), was developed for the study area as shown in Eq. 4.9 (Fig. 5).

Fig. 5
figure 5

Plot of T values from pumping test and transverse resistance

Full size image
$${\mathbf T}_{\mathbf{NM}}=\mathbf0\boldsymbol.\mathbf{009}\mathbf R_{\mathbf T}^{\mathbf0\boldsymbol.\mathbf{761}}$$
(4.9)

The storativity (S) of the confined aquifer system, and the deep and thick unconfined aquifer which may be hydraulically similar to it, may be estimated from the rule of thumb equation given by Todd (1980) as:

$$\mathbf S\boldsymbol=\mathbf3\boldsymbol\times\mathbf{10}^{\boldsymbol-\mathbf6}\mathbf b$$
(4.10)

where b is the saturated thickness of the aquifer.

Hiscock (2005) found that by integrating the spring properties of permeability T and conservative S, it is possible to characterize a single developmental limit called the hydraulic diffusion coefficient D, as shown in condition 4.11. Therefore, the aquifer diffusion coefficient is the ratio of the spring permeability coefficient (m2/day) to the aquifer retention rate.

$$\mathbf{D}=\mathbf{T}/\mathbf{S}$$
(4.11)

Result and discussion

Layer parameters of the study area

The results of the layer parameters are presented in Table 1.

Table 1 Summary of layer parameters
Full size table

Modeled resistivity curves/geoelectric curve types of some locations

The results of some selected (NJ8 and NJ9) computer-modeled curve types are presented in Figs. 6–7. This was ascertained by the entering of a model represented by the apparent resistivity and thickness of each layer of the curve. The theoretical interpretation of these curves includes NJ8 (HAKHAKQ curve type) and NJ9 (KHAKQ type). About ten layers were identified from the geo-electric curve (Figs. 6 and 7). Aquifer resistivity (Ωm) of 7770 was observed for NJ8 (Fig. 6) with a corresponding aquifer depth and thickness of 100 m and 36.1 m respectively. The aquifer resistivity (Ωm) value recorded at Umuokwara Ihebinowere-1 (NJ9) showed a higher value of 28,700 when compared to the value observed at NJ8, but lesser values of aquifer depth and thickness were recorded, with values being 84 and 28.7 m respectively (Fig. 7).

Fig. 6
figure 6

Modeled curve type at Duruewuru Amucha, Njaba LGA (NJ8)

Full size image
Fig. 7
figure 7

Modeled curve type at Umuokwara Ihebinowere-1 (NJ9), Njaba LGA

Full size image

Modeled curve type at Umuokwara Ihebinowere-1 (NJ9), Njaba LGA Fig. 8

Fig. 8
figure 8

Geo-electric section across profiles. a A-A′. b B-B′. c C–C′

Full size image

Correlation of geo-electric sections across selected profiles

Three profile lines were drawn across the study area. The geo-electric sections and lithologic cross-sections of the VES points that cut across the lines were correlated as represented in the figures. Sections A-A′, B-B′, and C–C′ are presented with their interpretative lithology, as can be seen from the legend. The variations in lithology can be explained in the varying sub-surface resistivity values. The aquifer resistivity values indicate that the aquifer media is majorly sandstone and sand units of the aquiferous Benin Formation (Fig. 8). The correlation of the sandstone units along the various profiles showed that it occurred in most of the sounded points (the sandstone unit appearing and disappearing at almost equal depth at NJ2, NJ8, and NJ18), with the thickest occurrence at NJ17. The highly prolific nature of the aquifer system in NJ17 (Fig. 8c) can be attributed to the extensive nature of the sandstone unit and the favorable aquifer geometrical parameters, where aquifer depth was observed to be 122 m and aquifer thickness, 50.5 m. These aquifer materials are mostly bounded top and bottom, by low-resistivity materials of varying thickness (Fig. 8), which provide confinement to the aquifer system. These low-resistivity materials are known to occur in major parts of the Imo River Basin and have been reported by Opara et al. (2012 and 2022) to be responsible for the confined and semi-confined nature of the aquifer system in the study area.

Iso-resistivity values of the study area

Iso-resistivity spread of 5 m, 20 m, 50 m, 100 m, 150 m, 200 m, 250 m, 300 m, 400 m, and 500 m, were probed, which gave their corresponding depth slices (Fig. 9). Results showed various resistivity values at the different AB/2. There is a fairly increasing resistivity value across all depths of probe for NJ1, NJ4, NJ8, NJ9, NJ12, NJ16, and NJ19. Other VES points showed an approximate decrease in resistivity values as the depths of the probe increased. Some locations as well showed an increasing-reducing-increasing trend of resistivity values. An averaged high resistivity value can be traced to the presence of the sand lithology of the Benin Formation in the region. Generally, Umuokpurufor Amakor recorded an average highest resistivity value across the increasing depths of the probe, with a minimum resistivity value of 190 Ωm at AB/2 = 5 m and a maximum resistivity value of 11,150 Ωm at AB/2 = 500 m; while Community Borehole, Umuodiri, recorded an averaged least resistivity value across all depths of the probe, with minimum resistivity value of 97 Ωm, maximum resistivity value of 1600 Ωm, and averaged resistivity value of 1282 Ωm. Various iso-resistivity values at different AB/2 are presented in Table 2.

Fig. 9
figure 9

Iso-resistivity geospatial models at AB/2 = 5, 50, 150, 300, 500 m

Full size image
Table 2 Apparent resistivity values at various depths corresponding to AB/2
Full size table

Aquifer electrical, geometrical, and Dar-Zarrouk parameters

Aquifer electrical, geometrical, and Dar-Zarrouk parameters are presented in Table 3.

Table 3 Aquifer electrical, geometrical, and Dar-Zarrouk parameters
Full size table

High aquifer resistivity (Ωm) was recorded at Umuokwara Ihebinowerre (Fig. 10), followed by Umuolu Obeapku, with values of 28,700 and 27,900. A drop in aquifer resistivity was observed at Community Borehole, Umuodiri, with a resistivity value of 990, an indication of a sand body with clay admixtures.

Fig. 10
figure 10

Geospatial model of aquifer electrical, geometrical, and Dar-Zarrouk parameter

Full size image

Opara et al. (2022), Umayah and Eyankware (2022), and Eyankware et al. (2020a, b) have shown that evaluation of aquifer potential and geo-hydraulic properties is achieved using aquifer thickness and depth which are among the major parameters. From the electrical resistivity sounding done at the study area, a shallow aquifer depth of 79.2 m was recorded at Acharaji Akah, while a deep aquifer depth of 115 m was found at Comprehensive High School, Umuaka. Average aquifer depth of 92.5 m was observed (Fig. 10), and corresponds with the regional aquifer depth of the study area, as earlier established from pumping test data and other hydrogeological studies.

The thickest aquifer observed was at Umudara Ubokoro Atta, with a thickness of 48.5 m, and at Comprehensive High School, Umuaka, with a thickness of 48.4 m. These are prolific aquifer units and can accommodate a borehole for commercial water supply in the study area. The least aquifer thickness was observed at Umuolu Obeakpu, with a thickness of 23.4 m. An average aquifer thickness of 37.71 m was observed in the study area.

The aquifer longitudinal conductance, Lc, across the study area varies between 0.0009Ω−1 at Umuokwara Ihebinowere-1 (NJ9) and 0.031613Ω−1 at Community Borehole Umuodiri (NJ19), with an average value of 0.00611693Ω−1. From the geospatial Lc map of the study area, it can be delineated that high Lc values were recorded in the Northwestern part of the study area. Moderate Lc was recorded in the central part, while low Lc was observed in the remaining parts (Fig. 10). Regions of high longitudinal conductance are known to have a good aquifer protective capacity.

The highest value of aquifer transverse resistance was recorded at Umuolu Obeakpu-1 (NJ17) with an RT value of 1,408,950Ωm2, while the least RT was recorded at Community Borehole Umuodiri (NJ19) with an RT value of 30,987Ωm2. The average RT value in the study area is 407,178.1739Ωm2.

Aquifer hydraulic parameters

Results of aquifer hydraulic parameters are presented in Table 4.

Table 4 Summary of aquifer geo-hydraulic parameters
Full size table

Aquifer hydraulic conductivity, K

An average diagnostic constant of 0.00123225 was used to estimate K from the model proposed by Niwas and Singhal (1981). It can be shown that the KNS value ranges from 1.2199275 m/day at Community Borehole Umuodiri (NJ19) to 35.36557 m/day at Umuokwara Ihebinowere-1 (NJ9). The average KNS value is 13.04738 m/day. Based on the hydraulic conductivity values, the aquifer geo-material within the Benin Formation is thus interpreted to be sand, sandstone, and gravel (Nwachukwu et al. 2019; Ekwe et al. 2018). The K from Niwas and Singhal (1981) shows that the western and central parts of the study area are characterized by high values (Fig. 11). In summary, areas with high aquifer conductivity are usually associated with high hydropower flow values, thus indicating areas with high groundwater potential.

Fig. 11
figure 11

Geospatial models of aquifer hydraulic conductivity, K

Full size image

The highest KHG value was recorded at NJ19 with a value of 0.620324221 m/day, while the least KHG was observed at NJ9 with KHG value of 0.026828176 m/day.

Based on KNM, the highest value was recorded at Umuokwara Ihebinowere-1 (NJ9), with KNM value of 27.90068 m/day, while the least KNM value was observed at Community Borehole Umuodiri (NJ19), with KNM value of 0.0852 m/day.

From the above models, it can be seen that the highest and lowest hydraulic conductivity values are the same for NJ9 and NJ19 respectively. When the two models are compared, there exists a strong positive correlation as represented in Fig. 12.

Fig. 12
figure 12

Plot of KNM against KNS

Full size image

Aquifer transmissivity

Aquifer transmissivity measured in m2/day (Niwas and Singhal 1981) was estimated in the study area by taking the product of diagnostic parameters and lateral resistance. Average diagnostic constant, k’σ, of 0.00123225 was used for the study area since they are underlain by the same formation-Benin Formation. Aquifer transmissivity, TNS, showed a high value at Umuolo Obeapku-1, with a TNS value of 1736.178638m2/day. The least TNS value of 38.18373075m2/day was recorded at Community Borehole Umuodiri. The average TNS value in the study area is 507.745305m2/day. The groundwater potential in this part of the study area can be categorized as predominantly high (100–1000 m2/day) and very high (greater than 1000m2/day), according to Krasny (1993).

The three T values obtained from the pumping test were plotted against the corresponding RT for each of the locations (Fig. 13). A new model was developed and was designated “Transmissivity from New Model” (TNM). An empirical relationship for TNew Model, with a very strong positive correlation, was developed for the study area as shown in Eq.  4.9.

Fig. 13
figure 13

Plot of Transmissivity New Model

Full size image
$${\mathbf T}_{\mathbf{NM}}\boldsymbol=\mathbf0\boldsymbol.\mathbf{009}{\mathbf R}_{\mathbf T}^{\mathbf0\boldsymbol.\mathbf{761}}$$
(4.16)

Just as in the case of TNS, the highest TNM value was recorded at NJ17, with value of 430.0877m2/day, while the least value was recorded at NJ19, with a transmissivity value of 23.552 m2/day. An average TNM value of 159.043m2/day was observed for the study area.

Aquifer storativity and diffusivity

To estimate aquifer storativity in the area, Eq. 4.10 was used. The highest aquifer storativity value of 0.0001515 was recorded at Umuolu Obeakpu-1 (NJ17), while the least value was recorded at Umuolu Obeakpu-2 (NJ16), with a storativity value of 0.00113139. This is consistent with the typical storativity range of 5 × 10−5 to 5 × 10−3 for a confined aquifer (Todd 1980). The hydraulic diffusivity across the study area ranges from 2,838,830.2 at Umuokwara Ihebinowere-1 (NJ9) to 695,615.1 at Obinwanne Umuaka (NJ2). The average diffusivity across the study area is 1,398,057.749 (Fig. 14).

Fig. 14
figure 14

Geospatial models for aquifer transmissivity, storativity, and diffusivity

Full size image

Discussion

Aquifer resistivity value ranges from 28,700 (Ωm) to 27,900 (Ωm). A drop in aquifer resistivity was observed at Community Borehole, Umuodiri, with a resistivity value of 990(Ωm), an indication of a sand body with clay admixtures. A mean aquifer depth of 95 m was recorded for the study area, while an average thickness of 37.71 m was observed in the study area. This is in line with the regional hydrogeology of the study area (Ekwe et al. 2006; Obasi et al. 2020). The results of the aquifer Dar-Zarrouck parameters showed that the study area has a characteristic high transverse resistance. Where high transmissivity values are recorded, a good aquifer potential is expected. This range of values agrees with previous studies within the Imo River Basin (Akakuru et al. 2021; Urom et al. 2021; Eyankware et al. 2021; Opara et al. 2012; Ekwe et al. 2006). Based on the findings of this study, several aquiferous zones with their corresponding geo-hydraulic parameters have been evaluated. The iso-resistivity values have confirmed the presence of low-resistivity materials as depth increases. This is in agreement with the geology of the study area (Short and Stauble 1967). The study area has a homogeneous geology and an average diagnostic constant of 0.00123225 was used to estimate hydraulic conductivity from the new proposed model. Hydraulic conductivity from the new model showed that the values obtained are closely related to the values from monitoring wells and pumping test data. The highest hydraulic conductivity value of 27.90068 m/day was recorded in the study area, with the least value of 0.0852 m/day. Aquifer transmissivity value for the study area ranges from 430.0877 to 23.552 m2/day. An average transmissivity value of 159.043m2/day was observed for the study area. These findings agree with the previous studies done in the Imo River Basin (Akakuru et al. 2021; Urom et al. 2021; Eyankware et al. 2021; Opara et al. 2012; Ekwe et al. 2006). Urom et al. (2021) stated that the average hydraulic conductivity for Owerri Metropolis is 15.5 m/day, while the average transmissivity value is 1007.18m2/day. Although the results of aquifer transmissivity, as described by Urom et al. (2021), differed from the values obtained in this study, there are similarities in the values of aquifer hydraulic conductivity as obtained at the different sampling points. The highest aquifer storativity value of 0.0001515 was recorded in the study area, with the least value of 0.00113139. This is consistent with the typical storativity range of 5 × 10−5 to 5 × 10−3 for a confined aquifer (Todd 1980). The hydraulic diffusivity across the study area ranges from 2,838,830.2 to 1,398,057.749. This agrees with the study of Opara et al. (2012) and Urom et al. (2021). Uma (1989) appraised the groundwater resources of the Imo River Basin. He concluded that the complex geologic setting of the Imo River Basin provides the environment for equally complex aquiferous horizons which are co-extensive with the geologic formation. Based on the storativity and diffusivity values, he identified three aquiferous units—a shallow unconfined aquifer, a confined aquifer, and a deep unconfined aquifer system. Based on the results of this study, the use of the empirical formula for the determination of aquifer geohydraulic parameters has proved effective. It has shown that these parameters can be acquired easily without the usual difficulties and high cost of obtaining pumping test data. The results have also revealed that the aquifer potential of the study area is fair. The parts of the study areas with good and prolific aquifer systems can serve as points for a regional water supply scheme (Akakuru et al. 2021; Urom et al. 2021; Opara et al. 2012).

Conclusion

Aquifer geohydraulic parameters’ estimation in Njaba and environs using electrical resistivity method and the integrated Dar-Zarrouck parameters has proven to be a cost-effective alternative. Also, the use of the proposed New Model for the estimation of aquifer hydraulic conductivity and transmissivity has not been previously carried out in the study area. The very similar survey results and pumping test results demonstrate the importance of electrical resistivity surveys for the quantitative estimation of aquifer parameters. Computer-modeled interpretation techniques helped solve the true width, resistivity, and depth of the aquifer. The diagnostic constant Kσ proved to be very useful in this study. It was useful to depict specific lithological stratigraphic units within the area that are consistent with the geology of the area. The Kσ value was also used to estimate the permeability and permeability coefficients for all sounding points in the study area. Hydraulic conductivity, as obtained from a new model, showed a high value of 27.90068 m/day and a low value of 0.0852 m/day, an indicator of fairly clean sand. Transmissivity from a new model developed for the study area ranges from 430.0877 to 23.552 m2/day. The storativity value ranges from 0.0001515 to 0.00113139, indicating a confined aquifer, while average aquifer diffusivity of 1398057.749 was recorded. This result indicates that most of the study area holds more potential for groundwater than other areas. The low transmissivity and hydraulic conductivity values around Umuodiri suggest poor groundwater potentials. This is opposed to the values found at Umuolu Obeakpu, which rather suggest high productivity. A thorough aquifer vulnerability and hydro-chemical evaluation should be carried out to ascertain the aquifer protective capacity and the water quality of the aquifer systems of the study area. The establishment of regional water schemes to facilitate a sustainable water supply to areas with low groundwater potentials (such as Umuodiri) is highly recommended.