Introduction

The development of any community is dependent on access to basic amenities like good roads, electricity supply and water. Water is essential for the survival of all living things (Vuorinen et al. 2007) and is the most abundant and widely used component on Earth (Chow et al. 1988). While water is indeed abundant in nature, accessing it in sufficient quantity and quality remains a principal challenge (Salako et al. 2009; Sirhan et al. 2011). The issue becomes particularly critical in urban and peri-urban areas, where human activities are significant contributors to the contamination of surface water (Koji et al. 2017). The area under study is a peri-urban centre characterized by bustling economic activities, including agriculture, forest exploitation, fishing, and various industries. The region is confronted with a significant challenge regarding access to safe drinking water due to the absence of a sustainable water supply network. While surface water sources such as rivers, streams, lakes and ponds, are available for the local population, they prove to be inadequate solutions as they are seasonal, unreliable, and often of poor quality (Tepoule et al. 2022). Surface waters are susceptible to contamination from surface processes, such as the discharge of chemicals and leaching from waste dumps into water bodies. These contaminants contribute to the spread of waterborne diseases, some of which can be fatal (Konwea and Ajayi 2021; Konwea et al. 2023). Consequently, there is a high demand for groundwater as a potential and sustainable alternative to overcome water-related challenges of the local population and improve access to a reliable and safe water supply.

Groundwater is obtainable in aquifers, which are water-bearing permeable rocks found beneath the earth’s surface (Bello et al. 2019; Kirsch 2009). Groundwater is recommended for its natural microbiological quality and overall chemical quality, making it suitable for various purposes. It is a relatively safe and reliable source of drinking water in both rural and urban areas (Adeyemo et al. 2017), requiring little or no disinfection before use (Obiora et al. 2016). However, groundwater can be susceptible to pollutants from anthropogenic sources, which are transported along its flow path. Successful groundwater exploration therefore requires a sufficient understanding of the characteristics of the subsurface aquifers. In a basement complex, such as the current study area, groundwater is commonly located within fractured and weathered formations, acting as aquifer formations. Its distribution is not uniform and can be confined to specific zones or pockets within these fractured and weathered formations (Dan-Hassan and Olorunfemi 1999; Datta et al. 2020; Mogaji and Omobude 2017; Olorunfemi and Fasuyi 1993). Hence, good knowledge of the aquifer’s hydraulic parameters, such as transmissivity, transverse resistance, longitudinal conductance, hydraulic conductivity, reflection coefficient, fracture contrast, and more, is crucial for the successful exploration, exploitation, and management of groundwater resources (Evans et al. 2010; George et al. 2016). The spatial variability of these aquifer properties due to geological heterogeneity emphasizes the importance of acquiring a deep understanding of them, as they play a significant role in determining the capacity and potential of aquifer reservoirs (George et al. 2015; Ekanem et al. 2020). The electrical resistivity method is an ancient geophysical exploration technique that has been widely used in groundwater exploration. It is a non-invasive technique used for probing depths in the subsurface. This method has been demonstrated by numerous authors that conducting electrical resistivity surveys is crucial for achieving long-lasting boreholes and ensuring a sustainable supply of water (Abdelrahman et al. 2023; Dhinsa et al. 2022; Ebong et al. 2021; Eugene-Okorie et al. 2020; Iserhien-Emekeme et al. 2017; Olabanji et al. 2019; Omosuyi et al. 2020; Rajendran et al. 2020; Rodrigue et al. 2022). Among the numerous electrode configurations used in resistivity measurements, the vertical electrical sounding (VES) technique with Schlumberger electrode configuration is highly preferred. This is because the VES technique is relatively fast, dependable and cost-effective in acquiring details of subsoil electrical characteristics. In addition, the instrumentation is simple, field logistics are easy and the analysis of data is less tedious and more direct when compared with other geophysical techniques (Ekine and Osobonye 1996; Zohdy et al. 1974). Parameters derived from VES measurements have proven to be valuable for planning and drilling groundwater wells. The lack of geophysical knowledge among individuals in the study area has resulted in unproductive boreholes, borehole failure, and contaminated groundwater with associated health risks. This study is aimed at evaluating the geoelectric and hydraulic parameters, as well as the aquifer potential in the study area to guide the siting and development of productive wells and boreholes.

Location of study area and geology

The study was conducted within the Sanaga maritime division in the littoral region of Cameroon (Fig. 1). It is located between Latitude 3.55–4.6 °N and Longitude 10.08–11 °E with elevation ranging from 29 to 862 m from the west to the east respectively (Fig. 2). The Sanaga maritime division has a population of 162315 persons following the 2010 population statistics, with a total land area of 9311 km2 (Noiha et al. 2015; Tchindjang et al. 2016). It is inhabited by the indigenous people of Malimba, Pongo-Songo, Bakoko or Elog Mpo’o, Bassa and Bonangasse, as well as several other ethnic groups from across Cameroon following rural and urban migration (Nzeket et al. 2019). These individuals depend mainly on agriculture, fishing, and timber exploitation as their primary source of income. The climate of the study area is warm, humid, and of the Equatorial Guinean type, characterized by significant rainfall. It is made up of two seasons: the rainy season and the dry season. The rainy season is longer and lasts from March to October while the dry season lasts from November to February, with some fluctuations from climate changes. The study area has a mean annual rainfall between 3000 and 4000 mm, a mean temperature of 28 °C and a mean humidity of 88% (Tonga et al. 2013). The relief consists of hills and valleys with gentle slopes. The soils in the area exhibit a ferralitic composition characterized by a sandy-clayey and lateritic texture. They range in color from yellowish-brown to bright brown and are formed from the weathering of underlying rocks (Nga et al. 2016; Tang et al. 2012). The study area is situated in the basement complexes of the Nyong unit (Bon et al. 2022; Lavenir et al. 2019) and the Yaounde group (Jude et al. 2021; Stendal et al. 2006). The geology of the study area is represented in Fig. 3. The Nyong unit is one among the three partitions of the Ntem complex, which includes the Ayna series, the Ntem and the Nyong unit (Teutsong et al. 2021). The Nyong unit is situated in the northwestern part of the Ntem complex and is composed of metasedimentary and metavolcanic rocks, including syn to late-tectonic granitoids and syenites. These rocks have been discovered to result from high-grade metamorphism, dated at 2050 Ma (Lerouge et al. 2006). The prevalent rock types in the Nyong unit are biotite-hornblende gneisses with a composition of Tonalite-Trondhjemite-Granodiorite (TTG), orthopyroxene-garnet gneisses (charnockites), garnet amphibole pyroxenites, and quartzites associated with banded iron formation (Nédélec et al. 1993; Shang et al. 2007; Toteu et al. 1994). Additionally, magmatic rocks such as syenites, granodiorites, and augen-metadiorites are also present (Mimba et al. 2014). The Yaoundé Group is situated in the southern area of the Central African Orogenic Belt (Bondje et al. 2020). It consists mainly of migmatites, granulites, and schists (Victor et al. 2014), which have been divided into two lithological units, namely, the meta-igneous and metasedimentary units (Toteu et al. 2006). The meta-igneous unit comprises pyroxenites, talcschists, and pyriclasites, while the metasedimentary unit is made up of kyanite-garnet gneiss, garnet-plagioclase gneiss, and garnet micaschist with calcsilicate rocks, quartzite, and talcschist intercalation (Stendal et al. 2006; Yonta-Ngoune et al. 2010).

Fig. 1
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Location map of the study area showing VES points

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Fig. 2
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Elevation map of the study area showing forty-six stations of measurement for VES

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Fig. 3
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Geological map of the study area (Dumort 1968)

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Materials and methods

Forty-six VES were carried out in the study area using the Schlumberger electrode configuration. Data was collected following a geophysical campaign conducted in the study area, using specific equipment for various measurements: The ABEM Terrameter SAS 1000 for resistivity measurement, measuring tape for taking distances, Global Positioning System (GPS) for taking coordinates and elevations of the VES points, electrical wires as electrode cables, two batteries to provide the DC source, crocodile clips to attach electrode cables to electrodes, and a hammer to send electrodes into the ground. The VES survey was conducted by arranging the four electrodes in a straight line. The potential electrodes (M, N) were positioned around a fixed center point of the array while symmetrically increasing the spacing of the current electrodes (A, B). This process resulted in a decreasing potential difference across M and N, eventually exceeding the measuring capabilities of the instrument. At this point, a new potential distance value was set, typically greater than the previous value. The direct current was introduced into the ground using the current electrodes and the resulting potential difference between the potential electrodes was measured. The half current electrode spacing (AB/2) was employed and systematically varied from 1 to 120 m. To reduce ambiguity in interpreting geoelectrical data, selected VES points were strategically positioned near existing boreholes in the study area. This approach was implemented to enable a comparative analysis between the VES data and the information obtained from the borehole logs. The numerical value for the geometric factor (\(K\)) for each pair of the current and potential electrode spacing was determined using Eq. (1).

$$K=\pi .\left[\frac{{\left(\frac{AB}{2}\right)}^{2}-{\left(\frac{MN}{2}\right)}^{2}}{MN}\right]$$
(1)

where MN/2 is half the distance between potential electrodes and AB/2 is half the distance between the current electrodes.

The apparent resistivity \(({\rho }_{a})\) was obtained from the following equation:

$${\rho }_{a}=KR$$
(2)

Where \(R=\Delta V/I\) is the resistance, I is the current, and \(\Delta V\)the potential difference between the two potential electrodes. To analyze the field data, it was initially plotted on a bi-logarithmic graph, with the apparent resistivity on the vertical axis and the current electrode separation on the horizontal axis. The data was then smoothened to eliminate any traces of noise. The JOINTEM software was employed in modeling, iteration, and curve matching (Zohdy et al. 1974). The analysis yielded a good fit between the field data and modelled curves, with minimal root mean square (RMS) error. This successful fit provided accurate estimations of true resistivity, thickness, depth and the number of geoelectric layers for each VES (Fig. 4). The depth of investigation for each sounding curve was determined by taking into consideration the relationship between current electrode spacing and depth of investigation proposed by Roy and Apparao (1971). The resistivity and thickness of a given geoelectric layer establish the characteristics of a geoelectric unit and play a crucial role in the interpretation and understanding of geoelectric models. In the context of the aquifer unit, the resistivity and thickness values obtained from the model curves were used to estimate various parameters following the methodologies and approaches described in the works of Ekanem (2020), Raji and Abdulkadir (2020), Obiora et al. (2017), Oladunjoye et al. (2018) and Raji and Abdulkadir (2022), which are relevant due to their geological similarity to the study area. The estimated parameters included the Dar-Zarouk parameters, hydraulic conductivity, transmissivity, reflection coefficient, and fracture contrast. The Dar-Zarouk parameters specifically refer to the longitudinal conductance (S) and the transverse resistance (T) (Maillet 1947). For a given geologic unit having resistivity \((\rho)\) and thickness (h), the longitudinal conductance was estimated using Eq. (3).

Fig. 4
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Typical 1-D resistivity modelled curves a VES 15 b VES 32 c VES 43

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$$S=\frac{h}{\rho }$$
(3)

The transverse resistance was calculated by the following equation:

$$T=h\rho$$
(4)

The aquifer longitudinal conductance is important in determining its protective capacity against subsurface contamination. It measures the ability of the aquifer to hinder the vertical migration of contaminants through its thickness and resistivity characteristics. To determine the aquifer’s vulnerability in the study area, the aquifer protective capacity rating suggested by Oladapo and Akintorinwa (2007) was used (Table 1). The hydraulic conductivity (K) measures the ease with which groundwater flows via the pore spaces and was calculated using the equation of Heigold et al. (1979). K serves as an indicator of the porous and fractured areas present in subsurface rocks, which allow the smooth flow of groundwater through the pore spaces (Ossai et al. 2023).

Table 1 Aquifer protective capacity rating proposed by Oladapo and Akintorinwa (2007)
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$$K=386.4{\rho }_{aq}^{-0.93283}$$
(5)

where \(386.4\) and \(-0.93283\) are constants, and \({\rho }_{aq}\) is the resistivity of the aquifer in \({\Omega }\) m. The aquifer transmissivity (Tr), which establishes the relationship between the thickness and the hydraulic conductivity was estimated using Eq. (6) suggested by Niwas and Singhal (1981). The transmissivity quantifies the ability of a geologic unit to transmit water through it under a hydraulic gradient.

$${T}_{r}=K\sigma T=\frac{KS}{\sigma }=Kh$$
(6)

where S is the longitudinal conductance in mhos, T is the transverse resistance in \({\Omega } {\text{m}}^{2}\), \({\sigma }\) is the electrical conductivity and K is the hydraulic conductivity. The evaluated transmissivity values were used to determine the aquifer potential of the study area following the classification of Krasny (1993) presented in Table 2.

Table 2 Classification of transmissivity magnitude (Krasny 1993)
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The reflection coefficient (Rc) and fracture contrast (Fc) were evaluated using Eqs. (7) and (8), respectively (Olayinka 1996).

$${R}_{c}=\frac{{\rho }_{n}-{\rho }_{n-1}}{{\rho }_{n}+{\rho }_{n-1}}$$
(7)
$${F}_{C}=\frac{{\rho }_{n}}{{\rho }_{n-1}}$$
(8)

where \({\rho }_{n }\)is the nth layer’s resistivity identified as the aquifer layer and \({\rho }_{n-1}\) is the layer resistivity that overlies the nth layer.

Results and discussion

Iso-Resistivity maps

The maps for lateral and horizontal fluctuations in apparent resistivity were generated at depths of investigation of 5.28 m (AB/2 = 13.2 m), 23.2 m (AB/2 = 58 m), and 33.2 m (AB/2 = 83 m) (Fig. 5). The maps display apparent resistivity values ranging from 92 to 11837 \({\Omega }\)m and were categorized into three domains: the resistive, the low-conductive and the conductive domains. The conductive domain is represented by low apparent resistivity (92–500 \({\Omega }\)m), the low-conductive domain is represented by moderate apparent resistivity (500–2000 \({\Omega }\)m), while the resistive domain corresponds to high apparent resistivity (2000–11837 \({\Omega }\)m). Figure 5 reveals an uneven distribution of apparent resistivities throughout the study area, which may result from the flow of current in different lithological units.

Fig. 5
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Variations in apparent resistivity in the study area a AB/2 = 13.2 m b AB/2 = 58 m c AB/2 = 83 m

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At AB/2 = 13.2 m (Fig. 5a), a resistive domain is observed in the central part of the study area with some traces in the southwestern parts with a resistivity ranging from 2196 to 6472 \({\Omega }\)m and may reflect the presence of gneiss or quartzite. The conductive domain is more in the northwestern part and extends to the upper margin of the central part with resistivity ranging between 92 and 444 \({\Omega }\)m, which may reflect the presence of clayey sand or laterite. The low-conductive domain is widespread across the study area but primarily at the southwest-central with a resistivity that varies from 503 to 1786 \({\Omega }\)m and may reflect the presence of laterite. At AB/2 = 58 m (Fig. 5b), The resistive domain observed in previous depth (5.28 m) becomes more pronounced with high resistivity (3261–11,837 \({\Omega }\)m), indicating the existence of a healthy gneiss basement. Similarly, the conductive domain is highly pronounced in the northeastern part of the study area and spans from 142 to 483 \({\Omega }\)m. This could be attributed to the presence of a more or less weathered basement. The low-conductive domain varies from 535 to 1641 \({\Omega }\)m and could potentially be indicative of the presence of a more or less weathered basement. At AB/2 = 83 m (Fig. 5c), the resistive domain occupies the same pattern as in AB/2 = 58 m with resistivity that varies from 3836 to 11767 \({\Omega }\)m which could represent a fresh bedrock. The low-conductive domain shows an increase in resistivity (565–1789 \({\Omega }\)m) occupying more areas in the northeastern sector than at AB/2 = 58 m. This may represent the wethered basement with some fresh bedrock. The conductive domain spans from 264 to 474 \({\Omega }\)m and represents the weathered bedrock

Geoelectric and hydraulic parameters

The results from the modelling of VES data indicate sounding curves with 3 to 5 geoelectric layers (Table 3). Specifically, VES 20, 28–30, 38, and 46 exhibit 3 layers, while VES 1–2, 5–10, 12–14, 16–19, 21–27, 31–37, 39–41, and 43–45 show 4 layers. Furthermore, VES 4, 11, 15, and 42 reveal the presence of 5 geoelectric layers. Nine sounding curves were obtained and classified as A, AA, H, HA, HK, HKH, KH, KHK, and QH. The presence of such a diverse range of curves suggests the heterogeneous nature of the subsurface. The frequency distribution of these curves is depicted in Fig. 6, revealing the dominance of KH and QH curves. The first geoelectric layer represents the topsoil and laterite topsoil with a resistivity and thickness that range between 106 and 1915 \({\Omega }\)m and 0.4-6 m, respectively. The second layer is characterized by laterite, clayey sand, gneiss and quartzite with a resistivity and thickness range of 60-9650 Ωm and 1–15 m, respectively. The third and fourth geoelectric layers constitute the aquifer unit of the study area and represent the weathered formations with resistivity and thickness values that vary from 93 to 16500 \({\Omega }\)m and 18–47 m, respectively. The fifth geoelectric layer was interpreted as the bedrock (fresh/weathered) and contains cracked gneiss and fresh gneiss material with resistivity values ranging from 144 to 16,601 \({\Omega }\)m and infinite thickness. The interpretation of geo-electric layers was guided by the analysis of lithologic logs obtained from boreholes in the study area. A correlation between the borehole logs and the VES curves lithology is in agreement (Fig. 7).

Table 3 Summary of VES results
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Fig. 6
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Frequency distribution of curve types in the study area showing the dominance of the KH and QK curves

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Fig. 7
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Correlation between borehole litho-logs and VES stations a VES 3 b VES 22 c VES 33

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The spatial variation of aquifer resistivity across the study area is shown in Fig. 8. The aquifer resistivity ranges from 93 to 16500 \({\Omega }\)m with a mean value of 1722 \({\Omega }\) m. The distribution of aquifer resistivity reveals that the northeastern sector and parts of the southwestern sector of the study area exhibit low resistive materials with values less than 500 \({\Omega }\) m, indicating the presence of water-bearing fractures with high conductive fluids. In contrast, the central sector is characterized by high resistivity, suggesting a low concentration of fluids. It can be inferred that this high resistive may be less suitable for accessing high-yield groundwater sources through drilling boreholes with high expectations of water productivity (Omosuyi 2010). The aquifer thickness varies between 18 and 47 m with an average value of 29 m. The observed variation in aquifer thickness can be attributed to a difference in the resistance of rocks to weathering. The contour map of aquifer thickness (Fig. 9) shows that the study area is significantly characterized by thick aquifers above 22 m, with the thickest aquifers mainly localized in the central and southwestern sectors of the study area. Thick aquifers provide a larger volume of rock material capable of storing and transmitting groundwater, which is essential for sustainable groundwater resources.

Fig. 8
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Contour map for aquifer resistivity showing its variation in the study area

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Fig. 9
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Contour map for variation in aquifer thickness in the study area

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The Dar-Zarouk parameters, hydraulic conductivity, transmissivity, reflection coefficient and fracture contrast were obtained from the aquifer resistivity and thickness (Table 4). The Dar-Zarouk parameters were used to assess the aquifer’s vulnerability to leachate contamination. The values of the longitudinal conductance were used to generate a contour map which gives the distribution of longitudinal conductance across the study area (Fig. 10). The longitudinal conductance in this study ranges from 0.0026 to 0.28 mhos, with an average value of 0.076 mhos. By comparing these values with the aquifer protective rating in Table 1, the study area can be classified into 3 different categories: poor, weak and moderate aquifer protective capacities. However, the spatial distribution of longitudinal conductance indicates that the study area predominantly falls within the poor to the weak range, accounting for approximately 63% and 24%, respectively. This suggests that the hydrogeological units in the study area are susceptible to contamination from surface sources. It is worth noting that there is an increasing trend in longitudinal conductance values from the central to the northeastern sector of the study area. Notably, the northeastern sector exhibits significantly higher longitudinal conductance values compared to other areas. This suggests that the aquifer protective capacity improves in the northeast, indicating a relatively lower susceptibility to surface source contamination in that particular area. The transverse resistance ranges from 1981 to 702405 \({\Omega } {\text{m}}^{2}\) with a mean of 60809 \({\Omega } {\text{m}}^{2}\) and is represented by the contour map in Fig. 11. The transverse resistance values obtained in this study are considerably lower than those obtained by Eugene-Okorie et al. (2020). The highest transverse resistance values are visible at the central and southwestern parts of the study area while the lowest values are localised in the northeastern parts.

Table 4 Estimated aquifer parameters from aquifer resistivity and thickness
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Fig. 10
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Contour map showing the distribution of aquifer longitudinal conductance in the study area

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Fig. 11
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Contour map for variation in transverse resistance in the study area

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The distribution of hydraulic conductivity in the study area is represented by the contour map in Fig. 12 and spans a range from 0.05 to 5.67 m/day with a mean value of 1.63 m/day. The range of conductivity values obtained in this study is lower than those reported by Okpoli and Ozomoge (2020). Variations in hydraulic conductivity may be attributed to the inhomogeneity of facies change and variations in grain sizes within the aquifer system. Based on the range of hydraulic conductivity values observed in this study, the study area is demarcated into three zones: low (0.05–0.86 m/day), moderate (0.86–3.7 m/day), and high (3.7–5.6 m/day) hydraulic conductivity zones. The high hydraulic conductivity zone is localized in the northeastern part of the study area with some traces in the central and southwestern regions. The moderate zone is widespread across the study area and accounts for 48% of the entire study area. The low zone is localized at the central and extreme southwestern parts of the study area. High hydraulic conductivity zones are associated with lower clay content, indicating greater permeability and ease of fluid flow (Heigold et al. 1979). The aquifer transmissivity values range from 2 to 150 \({\text{m}}^{2}/\text{d}\text{a}\text{y}\) with a mean value of 42.1 \({\text{m}}^{2}/\text{d}\text{a}\text{y}\). These transmissivity values correspond to a range of aquifer potential ratings suggested by Krasny (1993), which spans from low to high (Table 2). Following this classification, it is evident from Fig. 13 that 26%, 63% and 13% of the study area has low, moderate and high transmissivity, respectively. A comparison between the distribution of hydraulic conductivity and transmissivity reveals that areas of high transmissivity closely align with zones of high hydraulic conductivity and vice versa. As a result, it can be inferred that the aquifers located in the northeastern part of the study area exhibit high permeability with high water-bearing potential (Oguama et al. 2019). Figure 14 provides insight into the correlation between hydraulic conductivity and transmissivity. The plot illustrates a linear relationship, where higher values of transmissivity are observed to be associated with higher values of hydraulic conductivity. The strength of this correlation is indicated by a strong correlation coefficient of 0.908. Table 5 presents the results of borehole pumping tests conducted near certain VES points (VES 1, 3, 20 22 and 30) in the study area. Their borehole yields range from 0.22 to 3.3 L/s reflecting variation in aquifer characteristics within the study area. As per MacDonald et al. (2005), boreholes located near VES 1, 3, 20, and 22 exhibit moderate yields, ranging from 0.22 to 1.1 L/s, while the borehole near VES 30 demonstrates a high yield of 3.3 L/s. These borehole yield values further support the findings of aquifer transmissivity in the study area, as borehole yield serves as an indicator of aquifer transmissivity in basement complex settings (MacDonald et al. 2012).

Fig. 12
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Contour map showing the distribution of hydraulic conductivity in the study area

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Fig. 13
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Spatial distribution of aquifer transmissivity in the study area

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Fig. 14
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Correlation between aquifer hydraulic conductivity and transmissivity

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Table 5 Borehole parameters
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The spatial variation of the reflection coefficient and fracture contrast in the study area are represented in Figs. 15 and 16, respectively. The reflection coefficient and fracture contrast serve as indicators for identifying water-filled fractures within the aquifer network (Obiora et al. 2016). The presence of high density water-filled fractures is indicated in areas exhibiting reflection coefficients below 0.8 and fracture contrast values below 19 (Olayinka et al. 2000). Furthermore, areas with negative values of the reflection coefficient suggest a higher extent of fracturing. The reflection coefficient in this study ranges from − 0.67 to 0.93 with a mean of -0.059, while the fracture contrast ranges from 0.19 to 29.5, with a mean of 2.86. The distribution of fracture contrast and reflection coefficient suggests that the high degree of fracturing is localized in the northeastern parts of the study area. Groundwater potential in a basement complex relies on the aquifer resistivity, thickness, and transmissivity as well as the reflection coefficient and fracture contrast (Raji and Abdulkadir 2020). This is because the aquifer recharge and discharge potential depends on the size of the aquifer, degree of fractures and the availability of water in the fractures. In this study, the spatial variation of aquifer resistivity, transmissivity, reflection coefficient and fracture contrast are consistent. Based on this analysis, twenty-two VES points were identified as groundwater potentials of the study area (Table 6).

Fig. 15
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Contour map for variation in aquifer reflection coefficient in the study area

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Fig. 16
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Contour map showing the variation in fracture contrast in the study area

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Table 6 Recommended groundwater potential areas
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Conclusion

This study employed the electrical resistivity technique to assess the groundwater potential in parts of the Sanaga maritime division where the development of groundwater through boreholes and wells has been plagued by a high rate of failure. To investigate the aquifer layer in the study area, the VES technique involving the Schlumberger electrode configuration was employed, and the obtained data were analyzed. Results from modeled sounding curves revealed that the subsurface consists of 3 to 5 geoelectric layers: topsoil, laterite, weathered formation, cracked gneiss and fresh/healthy gneiss. The sounding curves were best described as A, AA, H, HA, HK, HKH, KH, KHK, and QH, which revealed the heterogeneity of the subsurface in the study area. The third and fourth geoelectric layers with resistivity ranging from 93 to 16500 \({\Omega }\)m and thickness ranging from 18 to 47 m were identified as the aquifer unit of the study area. These parameters were used to evaluate the aquifer characteristics including the longitudinal conductance, transverse resistance, hydraulic conductivity, transmissivity, reflection coefficient and fracture contrast. The hydraulic conductivity ranged from 0.05 to 5.67 m/day with a mean of while the transmissivity ranged from 2 to 150 \({\text{m}}^{2}/\text{d}\text{a}\text{y}\) with an average value of 42.1 \({\text{m}}^{2}/\text{d}\text{a}\text{y}\). The transmissivity and hydraulic conductivity revealed that the groundwater potential of the study area is generally moderate. The reflection coefficient and facture contrast revealed that the study area generally has high density water-bearing fractures with a high degree of fracturing in the northeastern parts. Twenty-two VES points were recommended as aquifer potentials of the study area with aquifer resistivity and thickness that vary from 93 − 47 \({\Omega }\)m and 19–40 m, respectively. The hydrogeological units of the study area showed poor, weak and moderate aquifer protective capacity with values ranging from 0.0026 to 0.28 mhos