Introduction

In hard rock terrains, groundwater potential mapping is relatively complex due largely to highly variable nature of the geological terrain (Kellgren 2002: Anbazhagan et al. 2011) extensive hydrogeological investigations are required in basement complex environment to understand groundwater conditions (Solomon and Quiel 2006; Balamurugan et al. 2008; Pradhan 2009). Evans and Myers 1990; Sener et al. 2005; Singh and Singh 2009; Sharma and Kujur 2012 all noted that several methods commonly adopted in delineating groundwater potential depending on the available data which include remote sensing and Geological Information System(GIS). Several statistical methods can also be adopted for groundwater mapping where adequate information on different influencing parameters to groundwater accumulation and movement are available. These include frequency ratio (Davoodi et al. 2013), multi-criteria decision evaluation (Murthy and Mamo 2009; Kumar et al. 2014), logistic regression model (Ozdemir 2011), weights-of-evidence model (Ozdemir 2011; Pourtaghi and Pourghasemi 2014), random forest model (Rahmati et al. 2016 Naghibi et al. 2016), maximum entropy model (Rahmati et al. 2016), boosted regression tree (Naghibi et al. 2016; Naghibi and Pourghasemi 2015), classification and regression tree (Naghibi et al. 2016), multivariate adaptive regression spline model (Zabihi et al. 2016), certainty factor model (Zabihi et al. 2016), evidential belief function (Pourghasemi and Beheshtirad 2015; Naghibi and Pourghasemi 2015), and generalized linear model (Naghibi and Pourghasemi 2015). These information are lacking in many third world country hence proper understanding of hydrogeological characteristics for successful exploitation of groundwater in basement areas depend largely on geophysical methods.

Various forms of water exploratory projects are used in the provision of potable water for human usage and great importance is geophysics which serves as important tool in exploration. Offodile (1983) documented that careful studies accompanied by improved drilling techniques yield favorable results even in problematic areas. Geophysical methods, therefore, play an important role in the exploration of suitable and productive groundwater reservoirs. The geophysical survey is employed to determine geoelectric parameters of formations, identify aquifer units and also determine its depth and lateral extent (Telford et al. 1976).

The types of geophysical method used for a survey depends mainly on the extent or size of area to be surveyed, the cost of the survey, geology of the area and the ease of the interpretation of data obtained. It also provides information on the depth of water table, the lithology in the subsurface layering and ensures a higher degree of accuracy in the location of hydro resources (Omosuyi et al. 2003). They are important in the search and location of suitable groundwater potentials either singly or combined. Various combinations of geophysical methods have been used with an accompanying increase in the degree of accuracy in the location of suitable groundwater reservoir. A combination of the electromagnetic method and the electrical resistivity gave a higher rate of 90% as opposed to 82% by the electromagnetic method and the 85% by the resistivity method (White 1986).

In areas underlain by crystalline rocks, groundwater occurs in fracture zone or in highly weathered basement (Olorunfemi and Fasuyi 1993; Ariyo et al. 2003). The electromagnetic and resistivity methods are both responsive to water bearing basement fracture columns due to the relatively high bulk electric conductivities, both methods were, therefore, found relevant and were hence integrated in the geophysical investigation. The VLF-EM method was adopted as a fast reconnaissance tool to map possible linear features such as; fault, and fracture zones while the electrical resistivity method was used to investigate prominent electromagnetic anomalies and provide a geo-electric image or section of the subsurface sequence.

In spite the many studies (Olorunfemi and Olorunniwo 1985; Olayinka and Olorunfemi 1992; Okwueze 1996; Oladapo and Akintorinwa 2007; Oloruntola and Adeyemi 2014) on groundwater potential in many parts of Nigeria, most of the studies were carried out in urban centers such as Lagos, Abeokuta, Ibadan where hydrogeological information is readily available. Awa-Ilaporu, SW is located within the Basement Complex terrain of southwestern Nigeria like many areas in southwestern Nigeria it is a community of indigenous rural people and students of a non-residential Olabisi Onabanjo University, which lacks municipal water supply. The inhabitants rely mainly on low yield, pollution prone shallow wells many of which dries up during dry season. Most of the attempts to construct deeper borehole have either failed outrightly or produced low yield borehole. As a result of this, the need to explore other promising high water yield areas to supplement water supply mostly during the dry season or drought is obvious, hence the need for a more detailed evaluation of the groundwater potential of the community.

The aim of this study is, therefore, to delineate the groundwater potentials in Awa-Ilaporu, near Ago Iwoye southwestern Nigeria, by determining the depth of occurrence of suitable aquifers; and also to provide background information for the future development of groundwater within the area by delineating potential areas for borehole drilling.

Location of the study area and geological setting

The study area (Fig. 1) is located in Awa-Ilaporu, near Ago Iwoye, south western Nigeria; it falls between latitude 6°57′ to 6°59′ North of the Equator and longitudes 3°55′ and 3°57′ East of the Greenwich Meridian. The drainage shows a dendritic drainage pattern and the major river in the area is River Ome and all other tributaries take their source from this river. It is located within the tropical rain forest which is characterized by a tropical climate with alternating wet and dry season, within the year. According to  Onakomaiya et al. (1992), the wet season spans from March to October and peaks in June/July while the dry season spans from November to February. The mean annual rainfall ranges from 100 to 1500 mm with average rainfall of about 100 mm. Ogunrayi et al. (2016) observed fluctuations in rainfall and temperature pattern of Akure which is part of southwestern Nigeria, the climate of the region indicates that the beginning of rainfall is becoming earlier which implies possible longer rainy season in the area. The temperature on the other hand, showed an increasing trend indicating warming throughout the year.

Fig. 1
figure 1

The location map of the study area

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There are lots of vegetation covers such as trees, shrubs and grasses. The temperature of the area ranges from 18 to 34 °C (Iloeje 1986).

The area is found within the southwestern crystalline Basement Complex of Nigeria. Geologically, it is made up of three major rock types; granite gneiss, banded gneiss and pegmatites which serves as an intrusive body. Awa-Ilaporu and environs were in the past agrarian communities with very low population. However, the establishment of the then Off-Campus Ogun State University (now Olabisi Onabanjo University) led to rapid geometric increase in the population of the communities.

Materials and methods

Two geophysical methods were used for this work; the very low frequency electromagnetic (VLF-EM) and vertical electrical sounding (VES). The location and arrangement of the two methods in the area is shown in Fig. 2.

Fig. 2
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Map of the study area showing the location of the VES points and VLF Traverse in the study area

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The VLF-EM survey

The VLF-EM is a type of continuous wave field electromagnetic method and it is most widely used in the reconnaissance mode. VLF traverses can be run quickly and inexpensively to anomalous areas which may require further investigation either with more detailed geophysical measurement and/or drilling and sampling (Telford et al. 1976). This was one of the methods employed in this research work.

The VLF-EM survey was carried out at different stations and were surveyed at 10 m interval along eight traverses approximately east–west direction ranging from 290 to 700 metres in length using ABEM WADI VLF-EM unit. The VLF-EM was used to initially delineate areas with conductive or fractured zone.

VLF systems make use of the energy emanating from distant powerful radio transmitters and measure the perturbations in plane-wave radio signal (15–30 kHz). These low frequency signals are trapped between the earth and the ionosphere.

The primary field (the transmitted radio signal) causes eddy currents to be induced in conductive geological units or structure. Faraday’s principle of EM induction shows that any oscillating magnetic field (e.g. the radio wave) will produce an electric field and electric current in a conductive media. Those eddy currents in turn create a secondary magnetic field which is measured by the VLF receiver. The secondary or perturbed field may be phase shifted and oriented in a different direction than the primary field depending on the shape or geometry of the conductor, the orientation of the conductor and conductivity contrast with the surrounding material (e.g. the host rock). The instrument measures two components of magnetic field or equivalently the “tilt angle” and ellipticity of the field. Some instruments also measure the third magnetic component and/or the electric field. The electrical field is measured by inserting two probes in the ground spaced about 5 meters (McNeil and Labson 1992). VLF interpretation is generally qualitative or subjective in nature and sometimes may be subjected to quantitative interpretation with the aid of filtering technique from which the true filtered real are determined. Anomalous areas are identified and a gross characterization attached to the anomaly (e.g. steeply dipping conductor or thickening conductive overburden). Some simple modeling may be carried out for simple geometric structures (McNeil and Labson 1992).

Data filtering are applied in other to eliminate errors and enhance interpretation of data. This is done by applying a filter operator (Q) which transform true anomaly inflection to peak positive anomalies also referred to as conductivity because they are proportional (Parasnis 1986). The filter operation is given by Fraser (1969):

$${\text{F}}1 = \left[ {\left( {\varPhi_{3} + \varPhi_{4} } \right) - \left( {\varPhi_{1} + \varPhi_{2} } \right)} \right]\quad {\text{Fraser filtering}},$$

where Ф1, Ф2, Ф3 and Ф4 are consecutive readings of the measured raw data obtained on the field.

Vertical electrical sounding (VES) survey

The second type of geophysical survey method used is the electrical resistivity method using the schlumberger electrode configuration. Twenty-three (23) Vertical Electrical Sounding stations were carried out in the field using OHMEGA resistivity meter which investigates the subsurface resistivity conditions by passing electric current into the ground through a pairs of current electrodes and measuring the resulting voltage differences between pair’s potential electrodes. Repeated measurements of current and potential difference were made at these same points using a larger current electrode separation (AB/2) in each successive electrode probe to determine the depth to the bed rock. In the probe, the spacing AB/2 was varied in a line direction to a maximum of 100 m in a station, keeping the center of the electrode configuration fixed. The values obtained were then plotted on a log–log paper as points with the resistivity values being on the vertical axis and the current electrode spacing (AB/2) on the horizontal axis. The points were joined and curve marched manually using pre-calculated master curves and their auxiliaries. The results obtained from the exercise were used as input-model for the eventual computer aided iteration using WINRESIST program.

The reflection coefficient of each station in the area was calculated using the method of Bhattacharya and Patra (1968), Olayinka (1996). Loke (1997) and Olasehinde and Bayewu (2011):

$$K_{n} = (\rho_{n} - \rho_{n - 1} )/(\rho_{n} + \rho_{n - 1} ),$$

where \(K_{n}\) is reflection coefficient for the nth layer, n is the number of layers, \(\rho_{n}\) is the layer resistivity of the nth layer and \(\rho_{n - 1}\) is the layer resistivity overlying the nth layer.

Results and discussion

Very low frequency-electromagnetic method (VLF-EM)

Traverse 1 is 400 m in length (Fig. 3). The filtered real value ranges from −131.7 to 118.0 Siemens, while the filtered imaginary ranges from −30.3 to 68.9 Siemens. The traverse shows the maximum peak at both positive and negative region with a more prominent filtered real peak at horizontal distance of 70–100 m. This usually signifies or corresponds to the area of high conductivity or area with the presence of fracture. This is marked F1 on the graph. The correspondent Karous–Hjelt pseudosection filtering confirms the moderately high conductivity which extends below 50 m depth. This conductivity could be due to the presence of fracture or accumulation of clayey materials. (McNeil and Labson 1992). Also at horizontal distance between 200 and 250 m, there is an observation of the filtered real and filtered imaginary both positively peaking together; this usually signifies a relatively thick overburden (McNeil and Labson 1992). This area is, therefore, marked T1.

Fig. 3
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The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 1

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Traverse 2 (Fig. 4) is 700 m long (Fig. 4). The filtered real values ranges from −57.6 to 53.0 Siemens, while the filtered imaginary ranges from −52.0 to 51.5 Siemens. A fracture F2 is observed where the positive peak of the filtered real coincides with the negative peak of the imaginary at station 635 meters on the traverse. Also a thick overburden T2 is identified at distance between 310 and 350 m where the positive peak of filtered real and imaginary coincide. In the Karous–Hjelt filtering pseudo-section, the extent of the fractured identified is below 40 m depth, this can either be a localized zone of fracture or thick clayey materials in the region.

Fig. 4
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The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 2

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Traverse 3 is 600 m in length (Fig. 5). The filtered real values ranges from −28.7 to 69.2 Siemens, while the filtered imaginary ranges from −67.5 to 100.7 Siemens. A positive anomalous value of filtered real is observed at distance between 100 and 140 m and it is identified as a fracture F3. Area of thick overburden is observed at distance interval of 600 and 650 m and marked as T3. The Karous–Hjelt pseudosection also agrees with the plot and showed the extent of the identified fracture to be 40 m deep while the thick overburden is about 30 m deep.

Fig. 5
figure 5

The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 3

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Traverse 4(Fig. 6) is 400 metres in length. The filtered real values ranges from −305.4 to 142.2 Siemens, while the filtered imaginary values ranges from −17.8 to 20.7 Siemens. The profile shows a maximum peak at the positive region with a more prominent filtered real peak at 285 m, which also correspond to high conductive region. There are occurrences of fracture between at 270–290 m (F4a) and at 310–330 m (F4b) along this traverse. This also shows in the Karous–Hjelt filtering pseudo-section and reveal that the fractures extend to more than 50 m.

Fig. 6
figure 6

The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 4

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Traverse 5 (Fig. 7) is also 400 m in length. The filtered real values ranges from −53.0 to 48.5 Siemens, while the filtered imaginary values ranges from −31.7 to 28.9 Siemens. The profile shows a maximum peak at positive region with a more prominent filtered real peak at 260 m. The fracture, thick overburden, and shallow overburden are marked as F5, T4 and S2, respectively. The Karous–Hjelt pseudosection showed the extent of the identified fracture to be inclined and also extended to more than 50 m deep while the thick overburden is about 40 m deep.

Fig. 7
figure 7

The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 5

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Traverse 6 (Fig. 8) is 290 metres in length. The filtered real values range from −47.5 to 34.2 Siemens, while the filtered imaginary values ranges from −36.7 to 36.7 Siemens. On the profile is S3 at point 230 metres with approximately width of 22 m and correspond to area of shallow overburden. Fractures F6 and F7 are observed on the traverse at 5–30 and 200–230 m, respectively. The Karous–Hjelt pseudosection showed that the extent of the identified fracture F6 extended to about 20 m deep while F7 extended to 45 m deep.

Fig. 8
figure 8

The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 6

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Traverse 7 (Fig. 9) is 400 m. The filtered real value ranges from −73.5 to 552.1 Siemens, while the filtered imaginary ranges from −6.6 to 6.6 Siemens. The traverse shows a maximum peak of filtered real at 30 m along the traverse with width of about 40 m; this is thus corresponded to fracture F8 and fracture F9 was observed at 320 m of the traverse with the width of about 30 m. The Karous–Hjelt pseudosection showed the extent of the identified fracture F8 to be about 28 m deep while F9 is 40 m deep.

Fig. 9
figure 9

The VLF-EM traverse and Karous–Hjelt pseudosection for Traverse 7

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Traverse 8 (Fig. 10) is 400 m long. The filtered real values range from −203.7 to 146.8 Siemens, while the filtered imaginary ranges from 0.0 to 0.9 Siemens. The high maximum peak of the positive filtered real implies fractured zones, F10 was observed at 200 m of the traverse of width of about 30 m and F11 at point 280 m with width of about 30 m, respectively. The Karous–Hjelt pseudosection showed the identified fractures F10 and F11 to be inclined and they are also interconnected. They are extended to more than 40 m deep.

Fig. 10
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The VLF-EM traverse and Karous-Hjelt pseudosection for Traverse 8

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Vertical electrical sounding (VES) data

The areas delineated as high conductive/fracture zones and thick overburden along the traverse were considered as points of interest in the VES survey.

Interpretation of VES data is both quantitative and qualitative, it involves the determination of the thickness and resistivity of different horizons and the inference of their lithologies based on their resistivity and reflection coefficient values.

The curve types observed in the area are 3-layer H-type (26%); 4-layer HA-type (9%) and KH (52%); and 5-layer HKH-type (13%). The curve types include KH, HA, HKH and H. The KH type is the most predominant and it is typical of tropics area (Olayinka and Olorunfemi 1992). It is often possible to make qualitative hydrologic deduction from curve type (Worthington 1993).

Typical iterated curves generated from the field measurements in the area are shown in Fig. 11. Table 1 revealed the geoelectric parameters of the various layers and showed the inferred lithologies from the geoelectric interpretation.

Fig. 11
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Typical VES curve types observed in the study area (a-d)

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Table 1 Results of vertical electrical sounding
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The geoelectric interpretation revealed 3-5 geoelectric layers: top soil (66–870 Ωm), the weathered layer which comprises of clay/clayey sand/sand/laterite (28.3–2342.7 Ωm), underlying this layer is the fractured basement (480.0–1415.9 Ωm) and the fresh basement (655.9–18,265.4 Ωm). The fractured and fresh basement layers were differentiated using the values of reflection coefficient obtained from each VES point, which is the measure of competence of the basement layer. (Olayinka 1996; Olasehinde and Bayewu 2011). From the calculated reflection coefficient, the reflection coefficient map was produced (Fig. 12) and shows a value range of (0.59–0.98). Olayinka (1996) observed that an area of lower reflection coefficient value (<0.8) exhibits weathered or fractured basement rock thus, favors a high water potential. Therefore, areas with relatively lower reflection coefficient (i.e. <0.8) represents areas where the bedrock is fractured/or intensely weathered.

Fig. 12
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Map of the reflection coefficient in the study area

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The apparent resistivity values of the area were contoured to produce the isoresistivity map (Fig. 13) and it revealed that the apparent resistivity increases radially from the central part of area outwardly. The resistivity ranges between 150-850 Ωm.

Fig. 13
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The Iso-resistivity map of the study area

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The overburden thickness in the area varies between 6.3 and 65.6 m. The isopach map of the area (Fig. 14) showed overburden thickness range of 20–50 m at the northern, eastern and some part at the south of the study area, while the relatively thin overburden thickness of about 5–15 m were noticed virtually around the central and western part study area. The overburden thickness is shallow in most part of the probing stations, which indicates the closeness of the basement to the surface. Therefore, groundwater occurrence in this area will largely depend on the occurrence of fractures in areas where there is thin overburden thickness. From the VES interpreted result, it can be deduced that VES 5, VES 7, VES 8, VES 9, VES 11, VES 12, VES 16, VES 17 and VES 19 are the most promising areas for the sitting of boreholes based on consideration of resistivities of the last layer, overburden thickness, or its respective reflection coefficient according to Olayinka (1996).

Fig. 14
figure 14

Isopach map of the overburden in the study area

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Groundwater potential evaluation

The groundwater potential of a basement complex area is determined by a complex inter-relationship between the geology, post emplacement tectonic history, weathering processes and depth, nature of the weathered layer, groundwater flow pattern, recharge and discharge processes (Olorunfemi et al. 2004). Decrease in the reflection coefficient and relatively high overburden thickness enhance the productivity of boreholes in some parts of the basement complex of southwestern Nigeria (Olorunfemi and Olorunniwo 1985).

The present evaluation of the groundwater potential of the study area has been based on aquifer geoelectrical parameters obtained from VES interpretation result. Some of the factors that are considered for groundwater potential in the study area are, overburden thickness, reflection coefficient and presence of fractures and these are expressed in Table 2.

Table 2 Groundwater Potential across the 23 VES stations
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Based on the aforementioned factors, groundwater potential map of the study area was produced from the data in Table 2, and the potential of groundwater in the study area is delineated into three (3) segments: the high groundwater potential, the medium groundwater potential and the low groundwater potential. Three basic criteria were considered in evaluating promising points for groundwater potential:

  1. i.

    Areas with high yield: These are the areas with overburden thickness greater than 13 m and/or with reflection coefficient less than 0.8.

  2. ii.

    Areas with medium yield: (i) Areas with overburden thickness greater than 13 m but less than 30 m and with reflection coefficient greater than or equal to 0.8

  3. iii.

    Areas potential with low yield are: (i) Areas with overburden thickness less than 13 m and or with reflection coefficient greater than or equal to 0.8.

Based on these criteria, the northern, northeastern and eastern areas have the highest and brightest potential for future groundwater exploration and development in addition to the existing ones in the study area, while the medium and the low yield water potential are found at the western and central part of the area.

Apart from the hand dug wells in this area, two prominent water boreholes are present and were dug by individuals to get a more hygienic and good quality water to drink. These wells are located in the part of the study area shown in Fig. 15. Well 1 has a low yield. Most times, it is usually pumped twice in a day (Early morning and evening) into a storage tank and the quantity of water per community member is strictly controlled as a result of the low yield. Well 2, however, is located in area classified as having high groundwater potential. Unlike Well 1, Well 2 yield is higher and quantity of water per community member is not controlled and the well is left for the community to fetch continuously unregulated. The existing wells confirm the reliability of the groundwater potential map, hence the map provides a useful guide for further groundwater development.

Fig. 15
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Groundwater potential map of the study area

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Conclusion

The combination of electromagnetic profiling and vertical electrical resistivity surveys in the study area has contributed to a better understanding of the groundwater occurrence in this part of basement complex of Southwestern Nigeria. Geological features suspected to be basement fractures (zones of high conductivities) identified from VLF-EM anomaly curves were confirmed by geoelectric subsurface information developed from interpretation results of vertical electrical soundings. Three (3) to five (5) major subsurface geoelectric layers were delineated from VES interpretation result; these include the top soil (mostly sandy), sandy or lateritic layer clay or sandy clay (partly weathered to weathered layer) and the basement bedrock (fractured/fresh basement). Other VES stations have appreciable groundwater within the weathered layer but because of high reflection coefficient (>0.8) which indicates that the basement beneath is fresh, it might not harbor or store adequate or sufficient groundwater, the borehole, when drilled might not be productive enough. Integration of VLF-EM and electrical resistivity sounding results enabled identification of good site for productive borehole and groundwater in a typical crystalline terrain as the studied area. The Groundwater potential map produced shows a reliable agreement with the groundwater discharge from existing boreholes within the study area.

It is, however, recommended that detailed studies which might involve the use of multiple approach such as statistical modeling coupled with remote sensing data should be used to predict the groundwater potential of the covered areas more accurately and faster. This will also help to cover wider area extent and, therefore, help the communities locally and on regional basis.