Mapping Groundwater Occurrence in Enugu Urban Area, Southeastern Nigeria Using In-Situ and Remotely Sensed Geophysical Data

Abstract

Groundwater exploration in Enugu Urban, southeastern Nigeria, is constrained by complex subsurface geology within the Anambra Basin. This study investigates the spatial controls on groundwater occurrence by combining gravity-derived sediment thickness and rock density models with Vertical Electrical Sounding (VES) data and in-situ well information. Gravimetric modelling reveals sediment thicknesses ranging from approximately 2 to 3 km, with thicker sedimentary sections occurring in structurally depressed zones and thinner sections associated with uplifted basement areas. Rock density values (2.648-2.689 g cm^-3) indicate heterogeneous lithological conditions that influence groundwater storage and flow. VES results show significant resistivity variation (3.8-987.6 Ωm), reflecting a predominantly shale-dominated stratigraphy with localized weathered and fractured zones that may serve as potential aquifers. However, extensive low-resistivity layers primarily correspond to clay-rich, low-permeability units, thereby limiting groundwater productivity. Analysis of 50 in-situ wells indicates that the majority are shallow (4.5-50 m) and highly seasonal, with over half drying shortly after the rainy season, confirming limited near-surface storage and strong dependence on rainfall recharge. Integration of geophysical and well data enabled the delineation of groundwater potential zones, with more favourable conditions associated with moderate sediment thickness, lower density contrasts, and structurally controlled features at depth. The results demonstrate that groundwater occurrence is highly heterogeneous and primarily controlled by lithological variability and structural complexity. This study highlights the effectiveness of incorporating geophysical remote sensing approaches for hydrogeological characterization and provides a basis for targeted groundwater development in complex sedimentary environments.

1. Introduction

In recent years, the application of gravity field measurements in hydrogeological investigations has attracted increasing attention. Gravimetric methods provide valuable information on subsurface mass variations and have proven effective in detecting hydrological signals associated with groundwater systems (Crossley et al., 2013; Piccolroaz et al., 2015; Asmari et al., 2016; Mohamed et al., 2017; Oussou et al., 2022). These techniques can reveal structural patterns controlling aquifer geometry, estimate the thickness and distribution of water-bearing formations, and improve hydrogeological modelling and characterization (Mohamed et al., 2015; Haile & Semir, 2016; Abuzied & Alrefaee, 2017). Consequently, gravity-based approaches have become an important tool for identifying groundwater accumulation zones and understanding recharge and depletion processes within sedimentary basins.

Groundwater exploration involves investigating subsurface formations to understand the hydrological cycle, evaluate groundwater quantity and quality, and identify the nature and distribution of aquifer systems. Previous studies have demonstrated the usefulness of gravity data for detecting near-surface soil moisture variations and groundwater anomalies at local scales (Crossley et al., 2013; Zaenudin et al., 2020). For instance, gravity field variations have been successfully used to identify primary and secondary aquifers in crystalline terrains and to delineate groundwater basins through forward modelling and gravity separation techniques (Crossley et al., 2013; Zaenudin et al., 2020).

Electrical resistivity methods also remain among the most widely applied geophysical techniques for groundwater exploration. Techniques such as Vertical Electrical Sounding (VES) and Horizontal Electrical Profiling (HEP), also known as Constant Separation Traversing (CST), enable the investigation of vertical and lateral variations in subsurface resistivity. Among these approaches, VES has proven particularly suitable for hydrogeological studies in sedimentary basins because it enables characterization of subsurface layering and identification of potential aquifer horizons (Atakpo et al., 2008; Oguama et al., 2019; Nwachukwu et al., 2022). Various electrode configurations have been applied in groundwater investigations, including Wenner, Schlumberger, dipole-dipole, and pole-dipole arrays; however, the Schlumberger configuration is widely regarded as one of the most efficient and commonly used due to its depth penetration and sensitivity to vertical resistivity contrasts (Bhatnagar et al., 2022).

Several studies have applied electrical resistivity techniques to assess groundwater potential in southeastern Nigeria (Oguama et al., 2019; Nwachukwu et al., 2022). For instance, previous investigations in Enugu State employed VES and Electrical Resistivity Tomography (ERT) to evaluate groundwater potential and vulnerability, revealing that groundwater occurrence in the region is largely restricted to weathered or fractured shale aquitards at shallow depths, with localized deeper water sources within sandy siltstone units (Oguama et al., 2019; Nwachukwu et al., 2022).

Existing studies have demonstrated the effectiveness of incorporating gravity and electrical resistivity methods for groundwater exploration. For instance, Adugna and Lamessa (2024) combined 2D/3D ERT with gravity modelling to delineate aquifers and structural controls, showing that resistivity constrains hydrogeological units while gravity defines basin geometry and structural features. Similarly, Taha et al. (2021) highlighted the importance of multi-geophysical integration for improving structural and hydrogeological interpretation in complex terrains. More recently, Moges et al. (2026) demonstrated that combining gravity and VES data enhances the characterization of basin structure and hydrogeological heterogeneity

Despite these advances, comprehensive geophysical investigations that integrate gravity data with electrical resistivity measurements remain limited in the Enugu Urban area of the Anambra Basin. Most existing studies rely on gravity profiles or localized resistivity surveys, which provide only partial insights into the complex subsurface structures controlling groundwater occurrence. Given that groundwater is stored within the pores and fractures of subsurface rocks, its availability is strongly influenced by the porosity, permeability, and structural configuration of the host formations. Therefore, understanding the geometry and spatial distribution of aquifer systems requires a combined analysis of multiple geophysical datasets.

Unlike other studies that focused on groundwater quality or long-term temporal variability, this study primarily aims to investigate and map the spatial controls on groundwater occurrence using gravity-derived maps and electrical resistivity characteristics. By combining multiple (in-situ and remotely sensed) geophysical datasets, the study provides new insights into the subsurface architecture governing groundwater distribution and offers a framework for improved groundwater exploration and water resource management in the region.

2. Materials and Methods

2.1. Geographical and Stratigraphic Setting of the Study Area

The study area, Enugu Urban (Fig. 1), lies within the Anambra Basin, which experienced significant sediment deposition following the Santonian tectonic event in southeastern Nigeria. The basin stratigraphy reflects a transgressive-regressive depositional system associated with a typical coastal setting and variable sediment supply (Whiteman, 1982; Nwajide & Reijers, 1996). Its evolution has been linked to asymmetrical subsidence related to the Atlantic fracture system and the Charcot fracture zone during the separation of the African and South American plates, which led to the opening of the Benue Trough. Subsequent thermal contraction following rifting further enhanced basin subsidence (Benkhelil, 1982; Binks & Fairhead, 1992; Obi et al., 2001).

Fig. 1. Location map of Anambra Basin superposed on the elevation map (sourced from European Space Agency, 2024) of Nigeria.

The stratigraphic succession of the Anambra Basin ranges from the post-Santonian to the earliest Tertiary and includes the Nkporo Group (Nkporo Shale, Enugu Shale, and Owelli Sandstone), the Mamu Formation (Lower Coal Measures), the Ajali Formation, and the Nsukka Formation (Upper Coal Measures) (Reyment, 1965; Agumanu, 1993; Nwajide, 2013). Fig. 2 illustrates the stratigraphic position of the Nkporo Group within the basin succession (Figs. 2–3).

Fig. 2. The stratigraphy and environment of deposition of sedimentsin the Anambra Basin southeastern Nigeria showing the lithology and description (modified after Uzoegbu et al., 2013).

Fig. 3. Geological map of Anambra Basin (modified after Murat, 1972).

The Nkporo Group forms the basal unit of the Anambra Basin and was deposited during the Campanian, reaching a maximum thickness of about 1,000 m (Reyment, 1965). It comprises the Nkporo Shale, Enugu Shale, and Owelli Sandstone. Fossil assemblages reported in previous studies suggest a predominantly marine depositional origin, although some authors propose a deltaic influence. The unit generally exhibits a coarsening-upward sequence consisting of basal shale overlain by interbedded sandstones, with occasional thin limestone beds indicating short marine transgressive episodes (Agumanu, 1993; Nwajide, 2013). The Owelli Sandstone is composed mainly of medium- to coarse-grained feldspathic sandstone, commonly cross-bedded and interpreted as fluvial deposits from subenvironments such as point bars and floodplains. The Enugu Shale represents a shallow-to marginal-marine deposit that grades into channel and marsh environments (Nwajide, 2013; Odunze & Obi, 2013).

Overlying the Nkporo Group is the Mamu Formation, deposited during the Lower to Middle Maastrichtian in alternating shallow marine and deltaic environments. The formation consists predominantly of sandstones, shales, siltstones, and mudstones with occasional coal seams, which led to its earlier designation as the Lower Coal Measures (Nwajide, 2013; Obaje et al., 2011). Its thickness varies between approximately 75 and 1,000 m across the basin. The depositional environment is interpreted to range from estuarine and tidal floodplains to swamp settings (Reyment, 1964).

2.2. Bouguer Gravity Data

Bouguer gravity data used in this study were derived from a tailored 25″ × 25″ absolute gravity dataset generated using the stochastic combination technique of Apeh and Tenzer (2022). This approach integrates terrestrial gravity observations from 64 stations obtained from the Nigerian Geological Survey Agency (2017), residual gravity data from Hirt et al. (2019), and the XGM2019e_2159 global gravity model (Zingerle et al., 2019) computed on the Multi-Error-Removed Improved Terrain Digital Elevation Model (MERIT DEM)topographic surface. The stochastic combination method has previously been validated in studies conducted in South Africa and Cameroon (Odera et al., 2024), with additional validation over southeastern Nigeria reported by Apeh and Tenzer (2022).

The Bouguer gravity data was computed by applying gravity reduction procedures involving the latitude, Bouguer gravity, and free-air corrections to the compiled absolute gravity data (Heiskanen & Moritz, 1967). The well-known crustal density of 2.67 g/cm³ was used for gravity reduction (Heiskanen & Moritz, 1967). The Bouguer gravity anomaly, ∆g_B, is defined in the following form (Heiskanen & Moritz, 1967):

∆g_B = g − δg_B + δg_t + δg_F − γ₀       (1)

where g is the absolute gravity value, δg_B is the simple planar Bouguer gravity correction (2GρH), δg_F isthe spherical free-air correction (0.3086H), δg_t isthe planarterrain gravity correction, and γ₀ is the normal gravity computed at the reference ellipsoid and defined for a particular normal gravity field model. The planar terrain correction was incorporated into the residual gravity effects; hence, there was no need to compute a terrain correctionforthe 167 km integrationarea around the computation point.

2.3. Sediment Thickness Determination

Sediment thickness beneath the study area was estimated following the approach of Apeh et al. (2023b) to determine basement relief and subsurface geometry. Because the study area lies within a highly rifted continental setting, the optimum upward continuation method of Zeng et al. (2007) was applied to separate the Bouguer gravity field into regional and residual components (Figs. 4a, b). This method determines the optimal continuation height by maximizing the cross-correlation between the original gravity data and the upward-continued field, thereby isolating localized signals from regional trends. Based on this approach, the regional-residual separation was performed at an optimal continuation height of 10 km, consistent with the findings of Apeh et al. (2023b) over the study area.

Fig. 4. Maps of (a) residual gravity field data and (b) regional gravity field data for sediment thickness determination.

The separated residual gravity data were used to prepare the sediment thickness data by applying the mathematical expression in the Fourier domain given in Eq. (2) (Parker, 1973; Pham et al., 2021):

\(\begin{align}h(x, y)=F^{-1}\left[-\frac{F[\Delta g(x, y)] e^{k \mid z_{0}}}{2 \pi \gamma \rho}-\sum_{n=2}^{\infty} \frac{(-|k|)^{n-1}}{n!} F\left[h^{n}(x, y)\right]\right]\end{align}\)       (2)

where ρ is the density contrast, γ is the Newton’s gravitational constant, h is the interface topography at the reference depth z₀, F denotes the Fourier transform operator, F^–1 is the inverse Fourier Transform, and \(\begin{align}k = \sqrt{k_x^2+k_y^2}\end{align}\), with k_x and k_y denoting the wave-numbers along the plane direction. To ensure the convergence of Eq. (2), a low-pass filter is normally applied during the calculation. The filter is defined in Eq. (3) in the following form:

\(\begin{align}B(k)=\left\{\begin{array}{c}1, \text { for }\left(\frac{k}{2 \pi}\right)<W H \\ \frac{1}{2}\left[1+\cos \left(\frac{k-2 \pi W H}{2(S H-W H)}\right)\right], \text { for } W H \leq\left(\frac{k}{2 \pi}\right) \leq S H, \\ 0, \text { for }\left(\frac{k}{2 \pi}\right)>S H\end{array}\right.\end{align}\)       (3)

where WHand SHdescribe smaller and greater roll-off frequencies of the filter design, respectively. This filter cuts off the frequencies higher than SH and fully passes the frequencies greater than WH while attenuating between WH and SH. Eqs. (2) and (3) were applied to estimate sediment thickness across the study area using optimal gravimetric inversion parameters derived by Apeh et al. (2023b). These parameters include a density contrast of 0.23 g cm^–³, an average sediment depth of 2.7 km, and roll-off frequencies of WH = 0.025614 and SH = 0.050418. The adopted density contrast falls within the range reported for Cretaceous to recent sediments in and around the study area (Adighije, 1981), while the roll-off frequencies were obtained from spectral analysis of the residual gravity data.

2.4. Crustal Thickness Data and Density Model

Crustal thickness beneath the study area (Fig. 5a) was estimated using the gravimetric inversion approach described in Eqs. (2) and (3) to compute the gravity effect of the regional field. The inversion employed a density contrast of 0.45 g cm^–³ and a reference Moho depth of 26 km, consistent with parameters reported by Apeh et al. (2023a) for the region. The lateral distribution of subsurface rock density was subsequently modelled by applying an inverse density deconvolution filter (apparent density mapping) to the residual gravity field. The residual gravity data (Fig. 5b) were obtained by computing the gravity effect of the estimated crustal thickness (Fig. 5c) and removing it from the Bouguer gravity field.

Fig. 5. Maps of (a) crustal thickness data, (b) residual gravity field data, and (c) gravity effects of crustal thickness data used for rock density modelling.

The gravity effects of the crustal thickness data were computed in Eq. (4) as follows (Parker, 1973; Granser et al., 1989):

\(\begin{align}g=2 \pi \gamma \rho z_{0}+2 \pi \gamma \rho F^{-1}\left\{\mathrm{e}^{-|k| z_{0} \sum_{n=1}^{\infty}} \frac{(-|k|)^{n-1}}{n!} F\left(h^{n}\right)\right\}\end{align}\)       (4)

where z₀ refers to the mean depth of the density interface, ρ is the density contrast between the lower crust and the uppermost mantle, and h is the single-valued function describing the topography of the density interface z = z₀ + h.

The rock density distribution within the region was computed by applying the inverse density deconvolution filter (apparent density technique) in the spectral domain using the transfer function in Eq. (5) as follows (Granser et al., 1989; Apeh et al., 2024a):

\(\begin{align}\rho=\frac{1}{2 \pi \gamma} F^{-1}\left\{\frac{|k| \mathrm{e}^{|k| \mathrm{z}_{1}}}{1-\mathrm{e}^{|k| t}} F(g)\right\}\end{align}\)       (5)

where ρ refers to density, t is the thickness of the slab (source depth of the upper crust or short wavelength component obtained from spectral analysis), z₁ refers to depth to the top of the slab (since terrain correction removed gravity effects caused by variations in topography near each observation point, z₁ was taken as zero), kis the wavenumber, γ is the gravitational constant, gis the gravity effect and F refers to the Fourier Transform.

Approximate density ranges for common rock types reported in previous studies (Apeh et al., 2024b; Carmichael, 2017) were used, together with available geological information, to classify the derived rock density values and interpret the underlying lithological units. This approach enabled the identification of potential groundwater zones based on inferred rock-density formations.

2.5. Vertical Electrical Sounding and In-Situ Well Data

Apparent resistivity measurements were acquired at three locations within areas of recurrent dry-season water scarcity using an ABEM Terrameter (SAS1000, Type-33002100) with a Schlumberger electrode configuration. In this arrangement, the potential electrodes were positioned near the center of the array with relatively small spacing, while the current electrodes were placed symmetrically at larger distances. The depth of investigation was increased by progressively expanding the current electrode spacing while maintaining constant potential electrode separation.

The terrameter transmits square-wave current signals to minimize induction and attenuation effects. Electrical current was injected into the ground through metal stakes acting as current electrodes, and the resulting potential difference was measured to obtain resistance values. Apparent resistivity was then computed by applying the Schlumberger geometric factor to the measured resistance.

Field verification of groundwater conditions was conducted during the driest period of the year (February–March 2024). A total of 50 wells located within water-scarcity-prone areas of Enugu Urban were surveyed to determine well depths, seasonal water availability, and geographic coordinates. Well depths were measured using a weighted steel tape, while geographic positions were recorded with a Garmin handheld Global Positioning System (GPS) receiver. The spatial distribution of the VES stations and surveyed wells, overlaid on an elevation map, is shown in Fig. 6.

Fig. 6. Elevation and surface drainage maps showing the locations of the 50 in-situ wells and Vertical Electrical Sounding points within the study area (sourced from European Space Agency, 2024).

2.6. Approach to Hydrogeological Characterization Using the Datasets

Previous studies have demonstrated a strong relationship between tectonic structures and groundwater occurrence. For example, Demircioğlu (2024) reported a close spatial association between springs and tectonic lineaments in Turkey, highlighting the role of faults and fractures in enhancing aquifer permeability through the development of pores and discontinuities. These structural features often correspond to sharp contrasts in Bouguer gravity anomalies produced by tectonic processes. Accurate mapping of such structures is therefore important for aquifer characterization because faults and fractures strongly influence groundwater distribution and flow (Singh et al., 2013; Bruno & Vesnaver, 2021).

In addition, hydrogeological studies have shown that surface topography and sediment thickness can significantly affect groundwater flow and discharge patterns in unconfined aquifers. Areas with shallow sediments or reduced sediment thickness along flow paths often promote groundwater discharge at the surface (Hinton et al., 1993). Consequently, analysing structural features such as faultlines and/or lineaments provides important insights into groundwater occurrence and distribution within the study area.

Groundwater potential zones are delineated using an integrated interpretation of vertical electrical resistivity, rock density, sediment thickness data as well as structural information derived from gravity data. The zones are delineated using a multi-criteria interpretation approach, where each parameter is interpreted based on its hydrogeological significance. These parameters are interpreted using a qualitative weighting scheme, where areas exhibiting moderate resistivity, relatively low-to-moderate density, moderate-high sediment thickness, and proximity to structural features are classified as high groundwater potential. Conversely, zones characterized by very low resistivity (clay-rich), high density (compact lithology), and absence of structural features were classified as low potential. Structural information (fault lines and gravity-derived lineaments) for the study area was adopted from Apeh et al. (2024a), whereas geological formations were delineated from the geological map reported by Epuh et al. (2025), as shown in Fig. 7.

Fig. 7. Extracted fault lines and/or lineaments overlaid on geological formations within the study area (modified after Apeh et al., 2024a; Epuh et al., 2025).

3. Results

3.1. Bouguer Gravity Map

The Bouguer gravity map of the study area, together with its regional context, is presented in Fig. 8. The maps provide critical insights into the subsurface structural framework controlling groundwater occurrence within Enugu Urban. The map reveals zones of low gravity anomalies (3.5–10.0 mGal), interpreted as areas of thicker sedimentary cover, and zones of high gravity anomalies (10–18 mGal), corresponding to relatively shallow basement or reduced sediment thickness.

Fig. 8. Maps of (a) Bouguer gravity anomalies of the study area and (b) location of the study area within regional Bouguer gravity anomalies.

These Bouguer gravity anomalies reveal localized zones of alternating high and low gravity signatures, corresponding to lateral density contrasts within the sedimentary sequence. Low residual gravity anomalies are interpreted as zones of reduced density, likely associated with weathered, fractured, or porous materials that may enhance groundwater storage. Conversely, high residual anomalies indicate denser and more compact lithologies, such as unweathered shale or basement highs, which are less favourable for groundwater accumulation.

Notably, the spatial distribution of gravity anomalies delineates several linear and curvilinear features, which are indicative of faults, fractures, or structural lineaments within the subsurface. These features are of hydrogeological significance, as they can act as conduits for groundwater recharge and flow, especially in shale-dominated terrains where primary porosity is limited. The alignment of some of these structures with zones of relatively low gravity further supports their interpretation as potential groundwater-bearing zones.

3.2. Vertical Electrical Resistivity and In-Situ Well Observations

The interpreted VES curves generated using WinRESIST v1.0 are presented in Fig. 9, while the corresponding variations in apparent resistivity with electrode spacing for the three survey locations are summarized in Table 1.

Table 1. Variation of apparent resistivity with varying electrode spacing at the three VES locations

Fig. 9. Computer modelling curves for vertical electric sounding data obtained at (a) New Artisan in Premier Layout, Enugu (VES 1: N6.454°, E7.5403°, EVN: 154 m). (b) Braithwaite Junction Staff Quarters in UNEC (VES 1: N6.4220°, E7.5074°, EVN: 219 m). (c) Ugbor Street in Achara Layout, Enugu (VES 3: N6.4076°, E7.5069°, EVN: 192 m). RMS: root-mean-square, EVN: elevation.

The VES data provide insights into the vertical stratification, lithological variability, and hydrogeological conditions controlling groundwater occurrence in the study area (Table 1, Fig. 9). Three VES stations were interpreted using layered resistivity models, revealing multi-layered subsurface conditions with resistivity values ranging from 3.8 to 987.6 Ωm. Across all locations, five geo-electric layers were consistently identified, reflecting variations in lithology and degree of saturation.

At VES 1 (Premier Layout), a thin lateritic topsoil (~0.8 m, 987.6 Ωm) overlies wet weathered shale (63.8 Ωm) and a thick low-resistivity clay layer (5.8 Ωm) extending to ~59 m depth, underlain by moderately resistive wet clay/shale units. At VES 2 University of Nigeria, Enugu Campus (UNEC) a relatively resistive near-surface sequence (109–202.9 Ωm) overlies a thick weathered shale unit (~119.5 m, 31 Ωm), followed by a very low-resistivity layer (3.8 Ωm) interpreted as saturated clay/shale. At VES 3 (Achara Layout), a moderate-resistivity lateritic layer (279.1 Ωm) overlies wet lateritic shale (41.8 Ωm) and a thick low-resistivity weathered shale unit (8.2 Ωm) extending to ~99 m depth, underlain by more resistive shale formations.

The dominance of low-resistivity layers (<10 Ωm) across the profiles indicates high moisture content but generally low permeability, suggesting predominantly aquitard conditions. Consequently, groundwater occurrence is largely confined to moderate resistivity zones (20–100 Ωm), which likely represent weathered or fractured shale with improved permeability. These zones occur mainly at depths greater than 30 m, indicating that productive aquifers are deep and structurally controlled, whereas shallow layers (0–10 m) are thin, weakly developed, and highly dependent on rainfall recharge.

The spatial distribution and depths of surveyed wells are shown in Fig. 10. The in-situ well dataset provides quantitative validation of groundwater occurrence patterns inferred from geophysical analyses. A total of 50 wells distributed across the study area were analysed, with depths ranging from 4.5 to 50.3 m. The depth distribution (Fig. 10) shows a strong dominance of shallow wells, with approximately 80% (<10 m), 14% (10–30 m), and only 6% (>30 m). This indicates that groundwater exploitation in the study area is largely confined to near-surface aquifers. As shown in Fig. 10, approximately 60% of wells dry up shortly after the rainy season, while 40% retain water into the dry season. However, sustained year-round water availability is largely restricted to deeper wells (>30 m), whereas shallow wells exhibit strong seasonal dependence, drying between February and April.

Fig. 10. The spatial distribution and depths of the in-situ wells data.

Furthermore, the variability in well performance over short distances suggests the presence of localized permeable units, such as sandstone lenses or fracture networks, embedded within the dominant shale sequence. The in-situ well data confirm that groundwater occurrence in Enugu Urban is primarily controlled by spatial variations in subsurface structure, lithology, and depth, rather than by uniform aquifer conditions.

A clear relationship exists between well depth and water retention capacity. Nearly all deep wells (>30 m) remain productive throughout the dry season, whereas many shallow wells (<10 m) dry early. This trend indicates that shallow aquifers are primarily sustained by direct rainfall recharge, making them highly vulnerable to seasonal depletion. In contrast, deeper wells access more stable groundwater systems, likely controlled by fractured zones, weathered layers, or permeable interbeds. From a hydrogeological perspective, the predominance of shallow wells relying on direct rainfall recharge explains the widespread seasonal water scarcity. The rapid depletion of these wells reflects limited permeability and storage capacity within the dominant shale formations.

These findings are consistent with previous studies (Oguama et al., 2019; Nwachukwu et al., 2022), which indicate that groundwater occurrence in the Enugu area is largely controlled by shallow weathered/fractured zones and localized deeper sandstone lenses with higher porosity and permeability.

3.3. Sediment Thickness Distribution

Fig. 11 illustrates the spatial variation in sediment thickness (Fig. 11a) with the locations of in-situ wells superimposed (Fig. 11b). The sediment thickness map derived from gravity inversion (Fig. 11a) reveals significant spatial variability across Enugu Urban, providing key insights into the subsurface geometry that controls groundwater occurrence. The estimated sediment thickness ranges from approximately 2 to 3 km, indicating a relatively thick sedimentary sequence consistent with the regional geological setting of the Anambra Basin.

Fig. 11. Map of sediment thicknesses within the study area (a) and the relative positions of the in-situ wells data overlaid on it (b).

A clear spatial trend is observed, with maximum sediment thickness in the northwestern part of the study area and a progressive decrease toward the southeastern region. This pattern suggests a basement surface that deepens toward the northwest, forming a sedimentary depocenter, while the southeastern area is characterized by a relatively uplifted or shallow basement. These variations reflect the structural configuration inferred from the Bouguer gravity map (Fig. 8) and highlight the role of basement morphology in controlling sediment accumulation. From a geophysical remote sensing perspective, sediment thickness serves as an indirect indicator of subsurface conditions that influence aquifer development, including basement relief, degree of weathering, and structural deformation.

The overlay of in-situ well locations on the sediment thickness map (Fig. 11b) provides an important link between geophysical interpretation and observed groundwater conditions. Areas with relatively thicker sedimentary cover, particularly in parts of Abakpa-Nike and adjacent northwestern zones, show a higher tendency for wells to retain water into the late dry season. This suggests that increased sediment thickness may enhance groundwater storage capacity, likely due to deeper weathered zones and potentially permeable interbeds. However, the relationship between sediment thickness and groundwater occurrence is not strictly linear. While thicker sediments generally imply greater storage potential, the results indicate that lithological composition and structural characteristics exert stronger control on groundwater availability. In several locations, particularly within shale-dominated zones, even substantial sediment thickness does not translate to productive aquifers due to low permeability and limited interconnected pore spaces.

3.4. Rock Density Distribution

Fig. 12 presents the spatial distribution of rock densities (Fig. 12a) with the locations of in situ wells superimposed (Fig. 12b). The rock density model derived from gravity inversion (Fig. 12a) provides important constraints on subsurface lithological variability and structural conditions that influence groundwater occurrence within Enugu Urban. The estimated densities range from 2.64 to 2.67 g cm^–³, consistent with typical sedimentary formations dominated by shale and siltstone, with minor intercalations of sandstone. The spatial distribution of density values exhibits clear heterogeneity across the study area. Relatively low-density zones are observed predominantly in the western and parts of the northeastern regions, whereas higher density values are concentrated in the southern and localized central areas. These variations reflect differences in lithological composition, degree of compaction,and structural deformation.

Fig. 12. Map of rock density model of the study area (a) and the relative positions of the in-situ wells data overlaid on it (b).

The overlay of in-situ well locations on the density model (Fig. 12b) reveals a notable relationship between density variations and groundwater persistence. Areas with moderate to relatively low-density values tend to coincide with wells that retain water into the late dry season, particularly within the Abakpa-Nike area. In contrast, regions dominated by higher density values correspond to areas where wells frequently dry up shortly after the rainy season, indicating limited groundwater storage capacity. In addition, the density model reveals subtle lateral variations and gradients that may correspond to structural discontinuities, such as fractures or fault zones. These features are expressed as localized density contrasts and are hydrogeologically important, as they may enhance permeability and facilitate groundwater movement within otherwise low-permeability formations.

3.5. Groundwater Distribution and Aquifer Classification

The criteria used for groundwater potential classification are summarized in Table 2, where electrical resistivity, rock density, and sediment thickness data, as well as structural features, were interpreted based on their hydrogeological significance. Electrical resistivity values were categorized as low (<10 Ωm), moderate (10–100 Ωm), and high (>100 Ωm), corresponding respectively to clay-rich (low permeability), weathered/fractured (moderate permeability), and compact formations (low permeability). Rock density values were grouped into low (<2.655 g cm^–³), moderate (2.655–2.665 g cm^–³), and high (>2.665 g cm^–³), corresponding to variations in lithological composition and porosity. Sediment thickness was classified into low (<2.0 km), moderate (2.0–2.5 km), and high (>2.5 km). In addition, fault lines and gravity-derived lineaments (structural information) from Apeh et al. (2024a), as well as geological formations extracted from the geological map of Epuh et al. (2025), were incorporated as zones of enhanced groundwater potential due to increased secondary porosity.

Table 2. Summary of the criteria used for groundwater potential classification

A qualitative interpretation approach was adopted, whereby areas exhibiting moderate resistivity, low density, high sediment thickness, and structural control were classified as having high groundwater potential (i.e., high aquifer type). Moderate potential zones reflect partial satisfaction of these conditions, while low potential zones correspond to areas dominated by clay-rich lithology, high density, and limited structural influence.

Fig. 13 shows the groundwater distribution zones of the study area, which are mainly based on the aforementioned factors. Three main types of aquifers (ranging from low to high) are depicted in Fig. 13. Sediment thickness and rock density values were reclassified according to the criteria presented in Table 2 and integrated using ArcGIS Pro geoprocessing tools. The combined analysis of the reclassified datasets enabled the delineation of aquifer types across the study area. These results were subsequently interpreted in conjunction with VES data, in-situ well information, and inferred structural features to evaluate the hydrogeological characteristics and groundwater potential of the area.

Fig. 13. Groundwater potential zones within the study area.

Areas classified as low aquifer potential are underlain by impermeable sedimentary units with limited storage capacity and rely primarily on direct precipitation, resulting in rapid well depletion after the rainy season. In contrast, high aquifer potential zones are areas with favourable lithological and structural conditions that support sustained groundwater storage year-round. These zones constitute potential hotspots for groundwater development and could serve as sources for water supply to adjacent low- to moderate-potential areas during the dry season (February–April). However, local lithological heterogeneity may result in variability in groundwater potential even within the same classified zones.

4. Discussion

4.1. Structural Controls Revealed by Gravity-Resistivity Interpretation

The regional Bouguer gravity field (Fig. 8b) defines a northwest-southeast structural gradient, reflecting variations in basement depth and basin architecture. However, this large-scale pattern alone does not sufficiently explain groundwater occurrence. The integration of regional and residual gravity components with resistivity data enhanced subsurface characterization by revealing localized structural heterogeneities not discernible in individual geophysical datasets.

Specifically, areas characterized by low regional gravity values and negative residual anomalies are interpreted as zones of thicker sedimentary cover, but their groundwater potential becomes evident only when coupled with moderate resistivity signatures. This combined response indicates zones where structural depressions coincide with enhanced permeability, likely due to fracturing or weathering. In contrast, gravity data alone would classify these zones purely as depocenters, without resolving their hydrogeological viability. Thus, the integration demonstrates that basin geometry (gravity) and lithological permeability (resistivity) must be jointly considered to identify effective groundwater zones.

4.2. Lithological Constraints and Misleading Resistivity Signatures

The VES results (Table 1, Fig. 9) confirm a predominantly shale-dominated subsurface, with multilayered A- and H-type resistivity curves. A critical finding is that low resistivity values (<10 Ωm), although indicative of saturation, correspond mainly to clay-rich aquitards rather than productive aquifers. This distinction cannot be reliably made using resistivity data alone and is clarified through integration with gravity-derived maps.

Moderate resistivity zones (10–100 Ωm), particularly at depths >30 m, are interpreted as weathered or fractured shale units with improved permeability. These zones are spatially associated with gravity-inferred structural features, suggesting that fracturing enhances secondary porosity in otherwise low-permeability formations. This combined interpretation resolves a key ambiguity: while resistivity identifies saturation, gravity-derived maps distinguish between confined, low-yield clay zones and structurally enhanced aquifers.

4.3. Sediment Thickness and Basin Architecture

The sediment thickness model indicates a north-westward increase in thickness, consistent with regional basin evolution. While thicker sedimentary sections are generally associated with greater groundwater storage potential, the results show that sediment thickness alone is not a reliable predictor of groundwater occurrence.

The integration with resistivity and structural data reveals that moderate sediment thickness combined with structural discontinuities is more favourable than uniformly thick shale sequences. In the northwestern depocenter, thicker sediments coincide with zones of structural complexity, increasing the likelihood of groundwater accumulation in weathered or fractured units. Conversely, in the southeastern region, shallow basement conditions limit storage capacity, even where localized saturation is observed. This finding represents an important refinement over previous interpretations: groundwater potential is governed not by sediment thickness per se, but by its interaction with lithological variability and structural features.

4.4. Density Variations and Subsurface Heterogeneity

The rock density model (Fig. 12) provides additional constraints on subsurface heterogeneity. Low- to moderate-density zones (~2.648–2.665 g cm^–³) are interpreted as weathered or fractured formations, which may enhance groundwater storage and flow. High-density zones (>2.665 g cm^–³), in contrast, correspond to compact, unweathered lithologies with limited permeability.

However, density alone does not uniquely define groundwater potential. The integration with resistivity data shows that moderate-density zones associated with moderate resistivity values and structural features represent the most favourable hydrogeological conditions. This highlights the importance of combined datasets in distinguishing between porous but impermeable clay units and structurally enhanced permeable zones.

Furthermore, density contrasts delineate zones of potential structural weakness, which may act as conduits for recharge and groundwater flow. These features are not directly observable in resistivity data but become evident through gravity analysis, reinforcing the complementary nature of the methods.

4.5. Validation with In-Situ Well Data

The in-situ well data provide independent validation of the integrated geophysical interpretation. Productive wells are consistently associated with zones exhibiting moderate resistivity, moderate density, and structural influence, particularly at depths greater than 30 m. In contrast, shallow wells (<10 m), which dominate the dataset, show high failure rates and strong seasonal dependence.

This confirms that groundwater occurrence in the study area is depth-dependent and structurally controlled, rather than uniformly distributed. Importantly, the well data demonstrate that zones identified as favourable by integrated geophysical analysis correspond to actual water retention and yield, whereas interpretations based on single datasets would not reliably predict these outcomes.

A limitation of this study is the relatively limited spatial coverage of the VES dataset, which comprises three measurement locations. Given the pronounced lithological heterogeneity of the study area, a denser resistivity survey would ideally provide improved resolution of lateral subsurface variability. However, the VES points were strategically located within zones characterized by recurrent groundwater scarcity, allowing targeted investigation of representative hydrogeological conditions.

To mitigate the limitations associated with sparse resistivity data, the VES results were interpreted in conjunction with gravity-derived maps and in situ well observations. The consistency observed between resistivity interpretations, gravity anomalies, and well performance provides cross-validation and enhances confidence in the inferred hydrogeological conditions. In particular, the agreement between low-permeability zones identified from resistivity data and areas of poor well performance supports the reliability of the integrated interpretation.

Therefore, while the VES dataset alone may not fully capture lateral heterogeneity, its combination with regional-scale gravity data and field observations provides a robust basis for delineating groundwater potential zones. Future studies incorporating higher-density resistivity measurements or two-dimensional electrical resistivity tomography would further refine the spatial resolution of subsurface characterization.

5. Conclusions

This study evaluated groundwater distribution in Enugu Urban, southeastern Nigeria, to better understand the causes of seasonal water scarcity. An integrated approach combining gravimetric forward and inverse modelling, vertical electrical sounding, and in-situ well data was employed to characterize subsurface conditions and aquifer geometry. Gravity data derived from a tailored model were used to estimate sediment thickness and rock density distribution, while VES measurements and information from 50 wells provided complementary hydrogeological constraints.

Results indicate that sediment thickness across the study area ranges from approximately 2 to 3 km, with thicker sedimentary sections corresponding to potential groundwater accumulation zones and thinner sections reflecting uplifted basement regions with limited storage capacity. Estimated rock densities (2.648–2.689 g cm^–³) reveal significant lithological heterogeneity and density contrasts, with structurally weakened zones (e.g., fractures and faults) representing favourable conditions for groundwater occurrence. VES results show a wide range of resistivity values consistent with shale-dominated lithologies, while well data (depths of 4.5–50 m) indicate that most shallow wells fail to sustain water through the dry season due to limited aquifer capacity and reliance on surface recharge.

The combination of these datasets enabled the identification of potential groundwater hotspots associated with deeper, more permeable, and structurally enhanced zones. These areas provide suitable targets for groundwater development and could support improved water supply systems within the region. Summarily, the study highlights the dominant role of lithological variability and structural controls, rather than sediment thickness alone, in governing groundwater occurrence. The findings provide a framework for groundwater exploration and resource management in Enugu Urban and similar sedimentary basin environments.

Author Contributions

Conceptualization, Methodology, Software, Writing–original draft, Supervision: Ugwuoti AI, Ugbor CC, Apeh OI, Ebinne SE; Data curation, Writing–review & editing, Software, Validation: Onah EU, Moka EC, Uzodinma VN; Visualization, Investigation, Writing-review & editing: Chukwu KC, Ehiemere CI, Arungwa ID, Chiemelu NE, Ndukwu RI.

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Funding

None.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.