1 Introduction

Groundwater is one of the most important natural resources on Earth. Among its many important uses are irrigation, human sustenance, and the promotion of urban and industrial development [1,2,3]. To properly utilize this groundwater supply, it is necessary to identify subterranean characteristics such as folds, faults, fractures, joints, and other hidden features. Delineating and characterizing the complex underlying structures of the earth has recently become increasingly dependent on the use of advanced geophysical techniques [4,5,6]. With this new method, key zones such as the saturated and unsaturated zones, as well as water tables at different depths, are precisely identified by using the physical characteristics of subsurface layers to define the vertical profiles [3, 7,8,9,10,11,12,13,14,15,16,17,18,19, 21].

Geophysical surveys are vital tools for groundwater exploration because they allow for the mapping of aquifer depths, the identification of confining units that may impede groundwater movement, the identification of preferred pathways for fluid migration, such as fault zones and fractures, and the discovery of possible groundwater sources [3, 8, 14, 20,21,22]. Electrical resistivity tomography effectively delineates subsurface geological structures by measuring the resistance of the ground to electrical current. Variations in resistivity can be correlated with different geological formations, identifying zones of high resistivity that are potential aquifers. Gravity surveys provide information on subsurface density variations. These variations can be used to map geological structures, identify zones of high density (e.g., potential bedrock or dense aquifers), and assess the depth of potential aquifers [5, 23].The goal of the current study is to evaluate groundwater potential in the Uke Burqa watershed area using integrated electrical and gravity techniques.

Since the town's groundwater pump failed ten years ago, Uke town's water supply is now obtained from treated Qarsa River water. Additional water sources are required because the community's need for purified spring water has proven to be unmet. To address this issue, the project intends to map possible aquifers and identify geological structures within the study area using integrated electrical and gravity methodologies to determine appropriate drilling sites.

The research area is located in the Oromia Regional State's Guto Gida Woreda (Uke town), in the Western Lowlands of Ethiopia. With an elevation of approximately 1385 m, Uke town's coordinates span longitudes 360 31′ 14′′ to 360 31′ 54'' E and latitudes 90 22′ 11′′ to 90 23′ 03'' N. It is situated along the main gravel Nekemte-Bahir Dar route approximately 35 km north of Nekemte Town and 35 km south of Gutin Town (Fig. 1). Access to Nekemte's central and north-central regions is made possible by this route, which passes through Gutin.

Fig. 1
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Location map of the study area

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The geology of the East Wollega zone and well data are part of the Proterozoic rocks of the Western Ethiopian Shield, which is assumed to be the southern extension of the Arabian-Nubian Shield (.A.N.S.). According to [2], show that the region is primarily composed of quaternary soil (Qs), succession of the Abay Basin, especially in the central region, where it makes up approximately 11% (2422.7 sq. km) of the entire mapped area(see Fig. 2a), with red clay soil being the most common type(see Fig. 2b). This red clay soil from the Anger Graben was discovered to have a limited capacity to hold water in its pore space, which means that it is not a good aquifer; instead, it is more suitable for replenishing the underlying rocks. The banks of the Anger River are home to a concentration of fluvial sediments, which are composed of volcanic rocks, especially large, worn, and fractured basalts, and alluvial deposits in the top layer. The predominant type of volcanic rock is fine-grained, black to grayish, and very susceptible to different degrees of fracturing and weathering.

Fig. 2
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a Geological map and (b) well data showing subsurface layers in the study area

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2 Materials and methodology

The study utilized GPS, an electrode-shooting hammer, a laptop computer, and an electrical resistivity meter for profile position and resistivity measurements. These data are processed using specialized software to generate 2D or 3D images of the subsurface resistivity distribution. The data were analyzed from various sources, geological literature, and geophysical investigations. The current was injected during the surveys, and the Bureau of Gravimetry International's 2013 model's raw data were used. A groundwater well inventory and geological maps were also generated.

2.1 2D Electrical tomography method

Electrical Resistivity Tomography (ERT) is a geophysical technique that uses electrical measurements at the surface to create images of subsurface structures. It works by injecting electrical current into the ground and measuring the resulting potential differences, revealing variations in electrical resistivity, which is influenced by the composition, porosity, and water content of the subsurface. Electrical resistivity tomography are proves invaluable for groundwater investigations due to its ability to, it effectively identifies the boundaries of different formations, pinpointing potential aquifers and confining layers (aquitards) and provides information about the thickness and depth of aquifers, critical for groundwater resource assessment [5, 22, 26]).

As shown in Fig. 3, the electrodes were placed in a field survey in a straight line with constant spacing and connected to a 72-electrode cable that was attached to a multicore system. The Wenner electrode array was positioned across the surface for an electrical resistivity tomography survey, which allowed apparent electrical resistivity to be determined [7, 24, 25]. There was a 300-m gap between profiles five and six, and there was a 10-m gap between each electrode. Using a total of 72 electrodes and a 710-m profile length, 579 data points from each profile and 3474 data points overall were collected.

Fig. 3
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Map showing the locations of the 2D ERT profiles

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IRIS Instruments' Prosys II software was used to preprocess the ERT data, insert the topography, filter the data, and remove erroneous field data. Bad data points were identified, and negative resistivity measurements and high and low readings were eliminated before inversion. Bad data points are removed to improve the quality of the data. The filtered and topographical insertion data were transferred to the RES2DINV program for processing. Commercial software produces inverse models representing subsurface structures [22, 26]. The data were processed using the RES2DINV inversion algorithm to create a 2D resistivity section. The 3D inversion process involved combining 2D files into 3D format and performing the inversion. This method was crucial for capturing 3D subsurface features, which are often unreachable using a 2D survey technique alone.

2.2 Gravity method

Gravity methods in geophysical studies rely on the measurement of variations in the Earth's gravitational field, which are caused by density variations within the subsurface. These density differences, arising from the presence of different rock types or geological formations, produce subtle changes in the gravitational field [4,5,6, 14, 26, 29]. Gravity surveys are also beneficial for groundwater investigations because they can they help pinpoint structures that influence groundwater flow, such as faults, folds, and buried channels, provide information on the depth of bedrock, crucial for understanding the potential extent of aquifers, distinguish between high-density formations (bedrock) and low-density formations (unconsolidated sediments) that could potentially host groundwater [27, 29]

The Bureau of Gravimetry International (BGI) provided the gravity data that were used in this study. The Gravity Recovery and Climate Experiment (GRACE) and Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) satellite gravity, EGM2013, and short-wavelength topographic gravity effects are composited to create Global Gravity Model Plus 2013 (GGMplus), which provides a 200-m resolution of the Earth between ± 600 degrees of latitude. The latitude, longitude, and gravity acceleration are among the information contained in the data. The gravity data for the target area were obtained via GGMplus acceleration data access for the N05 latitude and E036 longitude regions via the GGMplus download page [http://ddfe.curtin.edu.au/gravitymodels/GGMplus/]. The study extracted target area gravity data from longitudes of 36.523–36.5551 and latitudes of 9.360–9.395 degrees, plotted them using ggmplus2013_v4.m and test-access-ggmplus, and loaded them into MATLAB R2017a for processing. A high-resolution DEM was used to calculate height values, which are crucial for free-air and Bouguer correction calculations.Gravity cannot be directly measured or understood from gravity measurements. Therefore, to exclude the impacts resulting from indirect geological interest, the gravity data must be reduced to geod data before the study section is interpreted in terms of geological and geophysical properties. The necessary steps have already been followed in the reduction and processing of the data. The International Gravity Formula of 1967, or the International Association of Geodesy Formula of 1967, has been used to determine the theoretical gravity at a given latitude. All secondary gravity data were reprocessed by applying all standard gravity corrections using the average density of metamorphic rocks, which is 2.74 g/cm3 [29], 1 g/cm3 of fluid saturation, 35% porosity, and 80% effective porosity [27]. When there is a noticeable deviation of the points from north to south, these formulas are employed to apply latitude corrections.

The complete Bouguer anomaly map (Fig. 12) of all the points taken into consideration in the gravity data was ultimately created utilizing the gravity data results after the free-air anomaly values were calculated as part of the processing sequence using Oasis Montaj software. The complete Bouguer anomaly was thus broken down into elements linked to shallow-depth residual anomalies and those from deeper sources that identify regional abnormalities using high-pass and low-pass filtering techniques [4,5,6, 14, 28].

3 Results

3.1 Electrical resistivity tomography

After removing noisy data, 563 of the 579 data points that were initially gathered for profile 1 were determined to be appropriate for the inversion process. The resulting ERT inverted section (Fig. 4) clearly shows a low-resistivity material layer in the topsoil, with a resistivity ranging from approximately 5.7 to 50.7 Ω.m., which is interpreted as reddish clay soil. The next layer has resistivity values that are typical of clay soil with quartz, ranging from 50.7 to 142 Ω.m. The resistivity values of anomalies designated B (void zone and weak zone) range from 142 to 1259 Ω.m. This indicates that the slate is weathered, moderately fractured, or highly fractured. The slate reaches the base of the profile at depths of approximately 330–420 m and 550–620 m along the profile to a depth of 100 m. Moreover, large basement rocks, represented by anomaly A, have resistivity values between 3965 and infinity.

Fig. 4
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ERT inversion for Profile 1

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For electrical resistivity imaging, a total of 579 data points were collected along profile 2. Approximately 578 data points were used for the inversion after the dataset was automatically filtered and noisy data were removed. The layer's upper portion consists of low-resistivity materials, whose resistivity values range from 6.0 to 51.1 Ω.m and whose thicknesses range from 4 to 11 m. It was determined that this uppermost layer was reddish clay. All aquifer strata have thicknesses that increase from 340 to 610 m in a north‒south direction. The next layer has resistivity values in the range of 51.1 to 139 Ω.m, which is in line with the properties of clay soil mixed with quartz. The resistivity anomalies in the 139–362 Ω.m range point to slate that is somewhat cracked and worn. Furthermore, resistivity readings between 362 to 1158 Ω.m indicate large amounts of slate in depth intervals between 39.6 and 57.5 m and lateral thicknesses between 360 and 420 m and between 540 and 590 m. Massive basement bedrock can be seen in the southern section of the profile, where it extends from 18 to 280 m in depth. The range of high resistivity values in this region of the stratum, which vary from 3657 Ω.m to infinite ohm.m., respectively, indicates the presence of basement rock (see Fig. 5).

Fig. 5
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ERT inversion for profile 2

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Similarly, 574 data points from profile 3 were gathered, kept after removing noisy data, and utilized for the inversion. The model's overall resistivity values vary greatly, suggesting that the underlying geology is not homogeneous and ranges from low to high electrical resistivity values (4.6–9868 Ω.m). It is evident from the 2D inverted section (Fig. 6) that the resistivity values of the top layer range from 4.6 to 47.6 Ω.m across the profile, with reddish clay being highlighted. The resistivity values in the second layer, which correspond to the properties of clay with quartz soil, range from 47.6 to 144 Ω.m. The variance in resistivity readings between anomalies of 144–378 Ω.m. suggests that the slate is moderately cracked and worn. This aquifer zone has resistivity values ranging from 378 to 1412 Ω.m. The comparatively greater resistivity value suggests a fairly massive slate aquifer at a depth of 18 to 65 m.

Fig. 6
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ERT inversion for profile 3

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After automatic filtering and the removal of noisy data by visual examination from the dataset, approximately 577 data points from profile 4 were chosen for inversion. Reddish clay is indicated by the study region, where the resistivity ranges from approximately 4.1 to 37.6 Ω.m. The resistivity of the inverted model of the next layer ranges from 37.6 to 113 Ω.m, which is typical of the top layer of clay with quartz soil. At a depth of approximately 18.5–110 m, the severely worn and moderately fragmented slate is indicated by an intermediate layer resistivity ranging from 113–1132 Ω.m. The resistivity variation region at the subsurface shows a resistivity anomaly that varies in the degree of fracture between the high-marked resistivity regions (A, A1, and A2 (massive basement rock)) and the low-marked resistivity regions B, B1, and B2 (week zone area)). One side of the indicated (A, A1, and A2) has a low-resistivity anomaly. Figure 7 illustrates the properties of the enormous rocks in this region, which exhibit a high resistivity range > 3144 Ω.

Fig. 7
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ERT inversion for profile 4

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After automatically filtering and removing bad data from the dataset via visual examination, 570 electrical resistivity data points from profile 5 were used for inversion. The profile results indicate that as depth increases, so does the subsurface resistivity. Under the profile, the inverted model resistivity (Fig. 8) displays fluctuating low resistivity values < 1045 Ω.m from the surface to a depth of approximately 57 m. This profile's top layer is made up of reddish clay that ranges in resistivity from 7.6 to 52.3 Ω.m and is located at a depth of approximately 10–20 m. The worn-out basement came next, its upper portion has a resistivity ranging from 52.3 to 137 Ω.m and is uniformly thick throughout the profile line, displaying a layer of clay with quartz. The following was determined to be slate that was moderately fragmented and heavily worn, with a resistivity value of 137–359 Ω.m. Beneath this layer lies a basement rock, the upper portion of which is a saturated basement or highly fractured slate. The resistivity of this rock ranges from 359 to 1045 ohms.m. The layer's high resistivity values (2962-Ω.m to infinity) in the 80–120 m depth range indicate that the subsurface materials are resistant, leading to the interpretation that the substance is a large basement rock.

Fig. 8
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ERT inversion for profile 5

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Using an automatic filter and an inspection process to remove noisy data, 572 electrical resistivity data points from profile 6 were used for the inversion, which displays the reddish clay, according to the study results from this profile, which shows a resistivity range of 7.0–45.2 Ω.m. The resistivity values of the next layer inverted model, which are typical of clay soil with quartz, vary from 45.2–115 Ω.m. The sharp resistivity anomaly between 45.2–1055 Ω.m contrasts (designated B and B1 (week zone area)) is thus regarded as a degree of weathered, intermediate, and high fracture slate; this anomaly is obtained at 180–290 m and 390–390 m. According to the inverted model resistivity with tomography (see Fig. 9), these high resistivity zones at the locations designated A and A1 (large basement rocks) are larger than 2895 Ω.m.

Fig. 9
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ERT inversion for profile 6

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3.2 3D inverted model resistivity (combinations of profiles 1, 2, and 3)

The subsurface of the research area exhibits an anomaly of varying resistivity values, as indicated by the marked portions denoted as A&A1, B&B1, and C&C1 in Fig. 10. Week zones that may be connected to the high-aquifer productive zones are depicted in the 3D model, with low resistivity values roughly indicating regions A and A1. In the areas indicated at C&C1 (moderate productive aquifer zone), the 3D model has intermediate resistivity values. The subsurface, representing the low-productivity aquifer zone, is represented by a 3D model with high resistivity values around regions identified at B&B1 (large basement rock).

Fig. 10
figure 10

3D model resistivity fence diagram from all inversion profiles 1 and 2&3 showing subsurface features of the Burka Uke catchment. Inset: A1, A, B, B1, C, and C1 show anomalous regions of various resistivity values

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3.3 3D inverted model resistivity values (combined profiles 4, 5, and 6)

For every profile, the top surface is uniform and exhibits very low resistivity values (< 36 Ω.m.) (Fig. 11). The 3D model with low resistivity values roughly represents the weak zone area (A), which is an area with good groundwater potential. The locations shown at B (massive basement rock) in the 3D model with high resistivity values roughly indicate low discharge potential.

Fig. 11
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3D model resistivity fence diagram from inversion profiles 4, 5 and 6 showing subsurface features of the Burka Uke catchment study area. Inset: A and B show anomalous regions of various resistivity values

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3.4 Complete bouguer anomaly map

Lateral gravity fluctuations in the Earth's underlying materials are generally visible on the entire Bouguer anomaly map. Because no topographic effects have been minimized to suggest that the area is flat, complete Bouguer anomaly values also mirror gravity fluctuations in the Earth's crust and upper mantle [4,5,6, 28]. The lower rock densities beneath the location at the measurement point range from 41.59 to 46.79 mGal, as shown by the low values of the entire Bouguer anomaly. The low-amplitude reflections reflecting a ring-shaped structure suggest the presence of intrusive (cavity) luminous bodies in the subsurface, according to the complete Bouguer anomaly map (Fig. 12) displayed in the research area. A high Bouguer anomaly value indicates high rock density beneath the measurement point, which ranges from 48.90 to 51.79 mGal. Generally, the existence of deeper denser materials or shallower or near-surface elevated blocks of basement rocks could be the cause of these high-gravity anomaly zones [28].

Fig. 12
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Complete Bouguer anomaly map of Quaternary soils in the study area

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3.4.1 Regional and residual gravity anomalies

The distribution of the gravity field is depicted in the regional gravity anomaly map (Fig. 13a). High-gravity anomalies are caused by deeper-density structures. The study's regional trend was a straight line, and the gravity density decreased from the south to the north. The following is a summary of the essential features of the regional gravity anomaly map of the research area. The regional gravity anomaly in the research area varies from 43.95 to 48.52 mGal, suggesting that the deep-seated sources are deeper in the north and shallower in the south. A true representation of the gravity anomaly map distribution in the study area is provided by the residual gravity anomaly map (Fig. 13b). The following is a summary of the features of the residual gravity anomaly map of the research area: there is a maximum of 5.21 mGal and a minimum of -3.96 mGal for the residual gravity anomaly field in the understudied area.

Fig. 13
figure 13

a Regional and (b) residual gravity anomaly maps

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4 Discussion

4.1 2D and 3D electrical tomography

This study focuses on the evaluation of subsurface resistivity layers in formations due to lithological changes and potential groundwater storage. The results show that region A exhibits high values, suggesting potential for groundwater reserves. From profile 1 (Fig. 4) at depths of 100 m and the lateral variation of 280–380 m, profile 4 (Fig. 7) at depths of 110 m and the lateral variation of 270–340 m, and profile 6 (Fig. 9) at depths of 120 m and the lateral variation of 220–300 or 390–480 m, the intermediate layer consists of extremely worn and moderately cracked slate and strongly fractured slate. At depths of 18.5–110 m, the intermediate layer consists of extremely worn and moderately cracked slate and strongly fractured slate. The variation in resistivity between regions marked at (A, \({{\varvec{A}}}_{1}\), and \({{\varvec{A}}}_{2}\)) and low-resistivity regions marked at (B, B1, and B2) indicates water flow within the formation from profile 4 (Fig. 7). One side of the region has a low resistivity, making it a viable target for groundwater exploration and development. On the other hand, the other side works as a barrier to groundwater flow, at least down to a depth of 110 m. This portion is described as a highly fractured slate or saturated basement with a resistivity ranging from 359 to 940 ohms and is saturated with water. The other portion is interpreted as a highly worn and moderately fractured slate, with a resistivity value of 137–359 Ω.m. However, due to extremely shallow depth estimates of 55 m, the profile 5 results suggest that there may not be good groundwater potential.

The high resistivity values observed in the depth range of 80 to 120 m indicate that the subsurface materials are resistive and could be a good aquifer for groundwater accumulation. The high-resistivity zones marked at A and A1 are greater than 1895 Ω.m., and the regions marked by A are selected for drilling in the order of preference. The values of high-resistivity regions marked by B zones indicate massive rocks. In conclusion, this study highlights the importance of geological structures, such as weak zones, fractures, voids, dykes, and arts, for groundwater prospecting(Table 1).

Table 1 The resistivity value with the corresponding geological formation and the groundwater prospect evaluation
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4.2 Complete bouguer and residual gravity anomaly discussion

This study focuses on the variations in subsurface gravity attraction due to density variations and structures [10]. The Bouguer anomaly map shows low gals with a ring shape, suggesting an intrusive illuminated body in the study area (Fig. 12). High values indicate high rock densities beneath massive basement rocks. The residual gravity anomaly map interprets gravity data to delineate structural fault elements in the area. The map shows trends in structural elements, such as southwest‒northeast and southeast trends. The density distribution on the map is influenced by local geological structures [9]. A low-amplitude gravity anomaly is observed in the catchment of the study area, possibly due to dissolution cavities in areas underlain by Quaternary soils. These low gravity values represent potential hydrogeological exploration areas filled with light sediments [4,5,6, 28]. Positive gravity anomalies are found north, northwest, northeast, and west of the catchment, mainly due to the uplift of denser basement rock.

4.2.1 2D Gravity modeling

The last stage of gravity interpretation is gravity modeling, which establishes subsurface bodies, depth, and density. In the study area, it is built along profile 1 cross sections A-A' (Fig. 15) and B-B' (Fig. 16). Gravity models are created using anomaly values derived from the residual gravity anomaly map (Fig. 15). The density contrast between the body of interest and the surrounding material is calculated along profile 1 and cross-section B-B'. Both models are created using the Geosoft Oasis Montaj GM-SYS 2D gravity modeling program.

Assuming density values of 1.9 g/cm3 for reddish clay cover, 2.54 g/cm3 for clay with quartz, 2.75 g/cm3 for extensively weathered rocks and moderately fractured slate, 2.8 g/cm3 for strongly fractured slate, and 2.85 g/cm3 for bedrock layers, this study modeled two profiles along trending directions [4,5,6, 28]. Making a geologic model based on conjecture and determining geophysical reactions is known as forward modeling [30]. Due to the nonlinear nature of gravity computationlos, the outcome is dependent on the initial model.

4.2.2 2D Gravity modeling along A-A'

According to Figs. 14 and 15, the error found for the fit between the estimated and observed gravity values is 0.031% along cross-section A-A'. The anomaly in the gravity profile along the A-A' cross-section varies between -1.5 and -2.5 mGal. The final gravity model, which corresponds to the first layer, has reddish clay at the surface at a relatively low density. The clay with quartz is thought to represent the second layer. There may be substantial groundwater potential at these levels, as evidenced by the heavily worn and somewhat fragmented slate in the third layer. After this layer showed an enormous amount of bedrock, the fourth layer is understood as fractured slate, which represents an extremely good occurrence of groundwater potential.

Fig. 14
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Residual gravity anomaly map

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Fig. 15
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2D gravity modeling along A-A’

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4.2.3 2D Gravity modeling along B-B'

The B-B' cross-sections in Figs. 14 and 16 show a fit error of 0.175% between the estimated and measured gravity values. This residual gravity profile anomaly varies from 0.1 to -1.2 mGal, and cross-section B-B' is approximately 0–750 m long and 150 m deep. The first layer is composed of reddish clay. The clay with quartz is thought to represent the second layer. A good occurrence of groundwater potential zones may be indicated by the third layer's extensively worn and somewhat fragmented slate rock permeability. A very good occurrence of groundwater potential is depicted by the fourth layer, which is regarded as cracked slate, and a large amount of bedrock is indicated by the last layer.

Fig. 16
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2D Gravity modeling along B-B'

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5 Conclusions

This study successfully employed an integrated geophysical approach, combining 2D and 3D electrical resistivity tomography (ERT) with 2D gravity modeling, to investigate groundwater potential in the Burka Uke Catchment area, western Ethiopia. The integration of these techniques provided a comprehensive understanding of the subsurface geology and its influence on groundwater distribution and flow. The ERT results revealed distinct resistivity zones, highlighting areas of potential groundwater accumulation. The significant contrast in resistivity values indicated a high fracture density, suggesting enhanced groundwater storage within these zones. The gravity modeling further corroborated these findings by identifying fault structures that likely influence groundwater flow patterns.

The combined interpretation of ERT and gravity data allowed for the delineation of a north–south-oriented aquifer extending across the study area. This comprehensive understanding of the aquifer geometry and its structural controls provides a valuable framework for sustainable groundwater management in the Burka Uke Catchment. This research highlights the efficacy of integrating geophysical methods for comprehensive groundwater investigations. The findings provide crucial insights for resource management in the Burka Uke catchment and offer a valuable approach for addressing the increasing water demands of the region. Future investigations could focus on more detailed magnetic method, 3D gravity modeling, and incorporating hydrogeological data to refine the understanding of groundwater flow dynamics and optimize resource management strategies.