Environ Monit Assess (2022) 194:719

https://doi.org/10.1007/s10661-022-10341-z

Evaluation of aquifer hydraulic conductivity

and transmissivity of Ezza/Ikwo area, Southeastern Nigeria,
using pumping test and surficial resistivity techniques
I. C. Oli · A. I. Opara · O. C. Okeke ·
C. Z. Akaolisa · O. C. Akakuru · I. Osi‑Okeke ·
H. M. Udeh

Received: 21 July 2021 / Accepted: 11 August 2022 / Published online: 2 September 2022
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022

Abstract Aquifer hydraulic parameters includ- day, with a mean value of 0.2883 m/day. The trans-
ing hydraulic conductivity and transmissivity play a missivity values estimated across the study area range
very important role in the assessment and manage- between 0.29 and 57.27 m ­ 2/day with a mean value
2
ment of groundwater. Conventionally, these param- of 6.59 ­m /day. Transmissivity values obtained were
eters are best estimated employing pump test, which interpreted with Krásný’s transmissivity classifica-
is usually expensive and time-consuming. The use of tion, and this delineated the study area into three
surficial electrical resistivity data integrated with few groundwater potential zones: very low, low, and inter-
available pumping test data provides a cost-effective mediate zones. The study shows that the areas under-
and efficient alternative. A total of thirty-five (35) lain by the Ebonyi Formation have a higher ground-
vertical electrical soundings with a maximum half- water potential than those underlain by the Abakaliki
current electrode spacing of 150 m using the Schlum- Formation. These findings are supported by the
berger array were used in this study. Five (5) of these geology of the area, which revealed that the Abaka-
soundings were parametric soundings carried out in liki Formation is dominated by shales with very low
the vicinity of monitoring wells for correlation and permeability, while the Ebonyi Formation consists
comparative purposes. The empirical relationships of shales with alternations of sand/sandstones, which
between the hydraulic parameters derived from the statistical analysis of the different model equations
pump test data and the aquifer resistivity data were used in estimating the hydraulic parameters of the
established for the Ebonyi and Abakaliki Formations, study area revealed that the new model empirical
respectively, and, in turn, used to estimate aquifer equations proposed and used in the present study
hydraulic parameters in areas away from wells. Aqui- proved to be the best alternatives to pumping test
fer hydraulic conductivity estimated across the study data.
area varies from 0.49 to 1.5735 m/day with a mean
value of 0.9205 m/day for the Ebonyi Formation, Keywords Aquifer potential · Hydraulic
while the Abakaliki Formation has hydraulic con- conductivity · Pump test · Transmissivity · Vertical
ductivity values that vary from 0.0775 to 1.3023 m/ electrical sounding

I. C. Oli (*) · A. I. Opara · O. C. Okeke · C. Z. Akaolisa · Introduction

O. C. Akakuru · I. Osi‑Okeke · H. M. Udeh
Federal University of Technology Owerri, Owerri, Imo, In the study area, surface water is a major source of
Nigeria
water for domestic purposes, but due to challenges of
e-mail: doziebase992@yahoo.com

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population growth, climate change, and contamina- aquifer resistivity parameters estimated through
tion from anthropogenic sources, its potentials have geo-electrical techniques has been fully achieved by
been pushed to its very limit (Opara et al., 2020; Urom several authors (Chenet al., 2001; Dasargues, 1997;
et al., 2021). Groundwater is the second largest fresh- Ejiogu et al., 2019; Ekwe et al., 2020; Frohlichet
water reservoir in the world, accounting for 12% of al., 1996; Harry et al., 2018; Hasan et al., 2020;
the world’s freshwater reserve, the largest resource Heigold et al., 1979;Kalinski et al., 1993; Kelly &
being ice-locked water (87%), while surface water Frohlich, 1985; Mbonu et al., 1991; Nwosu etal.,
accounts for just around 1% of the world’s freshwa- 2013; Ponzini et al., 1984; Purvance & Andricevic,
ter reserves (Gleick, 2011). Groundwater presents 2000; Sinha et al.,2009; Ugada et al., 2013). Ugada
itself as a viable and safe source of potable water et al. (2013) made use of the Dar Zarrouk param-
and a widely accepted and better alternative to sur- eters to estimate the aquifer properties of Umuahia.
face water resources (McDonald et al., 2002; Singh, Ngwoke (2013) determined aquifer parameters in
2007). The search for groundwater in the study Ishiagu, Ebonyi State, using geo-electric methods.
area was intensified because of the dearth of clean and Also, Ekwe et al. (2020) determined aquifer param-
potable surface water as most surface water across the eters from geo-sounding data in parts of the Afikpo
study area are either saline, contaminated by mining sub-basin, southeastern Nigeria. However, Sinha
activities, or infested with coliform and other patho- et al. (2009) proposed a hydrogeological model of
gens (Obarezi & Nwosu, 2013; Obiora et al., 2015). the relationship between geo-electric and hydraulic
Most surface water within the study area over the parameters of an anisotropic aquifer.
years have been plagued by Guinea worm which has Also, analytical equations generated by the inte-
further compounded the status of the surface water gration of surface resistivity techniques and pumping
(Aghamelu et al., 2013; Okoronkwo, 2003). Also, test data had been used to estimate aquifer hydrau-
the availability and productivity of groundwater in lic parameters in different parts of Nigeria by some
boreholes within the study area are usually problem- authors (Ejiogu et al., 2019; Emberga et al., 2021;
atic because most of the boreholes drilled are either Opara et al., 2020; Urom et al., 2021). These studies
abortive, unproductive, or have extremely low yields. suggested that the estimation of hydraulic parameters
Successful exploration, exploitation, and effec- from geologically constrained geo-electrical equa-
tive management of groundwater resources there- tions is feasible. However, such a relationship depends
fore require an adept knowledge of the aquifer on specific areas and may have limited application in
conditions including their geometrical and hydrau- other areas except in areas of similar geology (Hasan
lic parameters (Amos-Uhegbu, 2013; Ezeh, 2012; et al., 2019; Purvance & Andricevic, 2000; Rehfeldt
Hasan et al., 2020; Ogbuagu et al., 2018). These et al., 1992; Salem, 1999; Urom et al., 2021). An
aquifer hydraulic parameters include transmissivity empirical equation that is formation-specific and con-
and hydraulic conductivity values. The conventional strained by the geology of the study area was proposed
means of determining these parameters are usually and used in the present study. The predictive accuracy
through pumping test (Butler et al., 1999), but this of the model derived from the present study was
approach is usually expensive and may be challeng- increased by carrying out parametric soundings at
ing in places where wells are widely spaced; thus, locations with existing monitoring wells from which
the interpolation of aquifer properties between the pumping test data were acquired. This was done to
wells is usually difficult and often incorrect, since avoid overestimating or underestimating the predicted
geological conditions vary relatively over very aquifer hydraulic parameter values (Opara et al., 2020).
small distances (Bogoslovsky & Ogilvy, 1977; Conventionally, the only direct method of esti-
Muldoon & Bradbury, 2005). Vertical electrical mating aquifer parameters is the pumping test tech-
sounding (VES) is an alternative means of estimat- nique. However, in most developing countries of the
ing hydraulic properties of the groundwater sys- world, there is a serious dearth of pumping test data
tem before drilling (Ekwe & Opara, 2012; Mbonu due to the huge cost of this very important analysis.
et al., 1991; Opara et al., 2020; Ugada et al., 2013). To solve this problem, some classical publications
The integration of hydraulic parameters evaluated have been made on how to estimate aquifer param-
via pump testing in nearby monitoring wells and eters from geophysical methods (e.g., Heigold et al.,

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1979; Niwas & Singhal, 1981, etc.). However, both from resistivity data. The objective is to provide an
the Heigold et al. (1979) and Niwas and Singhal empirical relationship that is formation-specific, i.e.,
(1981) equations generally used in the area to esti- based on the local geology of the area because it is
mate hydraulic parameters from resistivity data were believed that incorporating the effect of local geol-
generated using data from overseas in areas with little ogy will improve the quality of the predictions using
or no relationship with the geology of the study area. resistivity data. This study therefore aims to establish
The present study which is centered on alternative a relationship between aquifer parameters (hydraulic
means of estimating aquifer hydraulic characteristics conductivity and transmissivity) and electrical resis-
in areas with limited pumping test data using surficial tivity-related parameters (aquifer resistivity, trans-
resistivity methods therefore proposed and used a set verse resistance, etc.) and to make use of this relation-
of new empirical models together with the Heigold ship to estimate aquifer hydraulic parameters in areas
et al. (1979) and Niwas and Singhal (1981) equations. with a paucity of pumping test data.
These new sets of models were generated with empir-
ical data from the study area and are therefore con-
strained by the local geology of the area. The various Location and geology of the study area
model equations were therefore comparatively used
and ranked to know the best alternative model equa- The study area which is in southeastern Nigeria
tions that can be used to estimative aquifer hydraulic lies between latitude 6˚ 4′ 76″ N and 6˚ 11′ 94″ N
parameters from resistivity data on a regional scale and longitude 7˚ 58′ 32″ E and 8˚ 9′ 99″ E (Fig. 1)
when pumping test data are scarce or not readily and occupies an area of 442.57 k­ m2. The fieldwork
available. which involved field surficial electrical resistivity
The idea behind this therefore is to improve the data acquisition took place between the 20th and 24th
predictive capacities of the empirical equations September 2019.
used to estimate aquifer hydraulic characteristics

Fig. 1  Accessibility and drainage map of the study area

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Based on the works of Reyment (1965), the anoxic environment, which aligns with Agumanu’s
study area falls within the Asu River Group formed (1989) concept of formation. The sandstones occur as
during the Albian age and was folded into a north- minimal litho-facies or lenses.
east trend known as the Abakaliki Anticlinorium.
Agumanu (1989) subdivided the Asu River Group
based on stratigraphy into the Ebonyi Formation and Methodology
Abakaliki Formation. The Ebonyi Formation (Mid-
Albian) is underlain by the Abakaliki Formation Pump testing was carried out in a total of five (5)
(Late Albian–Cenomanian). The Ebonyi Formation wells in the study area to determine the aquifer
dominates the eastern axis of the study area, which is hydraulic parameters. The constant rate pumping
made up of shales, rapid alternations of sandstones, method with a single well was adopted, with draw-
siltstones, wacke stones, oolithic and serpulid stones, down observations on the same well. The static water
and mudstones (Fig. 2) (Oli et al., 2020). level was measured before the start of the pumping
The eastern axis of the study area on the other hand test using the electrical water level probe (dipper). A
falls within the Abakaliki Formation, which is mostly 1.5 Hp submersible pump was installed into the well,
dark-gray to black shales, and mudstones interspersed and pumping was done for 180 min. Dynamic water
with siltstones, small feldspathic sandstones, and black levels in the boreholes were measured at stopwatch
micritic limestones. The stratigraphy of this forma- intervals. After pumping was stopped, residual draw-
tion indicates a reducing depository condition and downs were also measured at different time intervals.

Fig. 2  Geologic map of the study area showing the VES and well locations

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Also, thirty-five (35) sounding points were Estimates from surficial resistivity data
selected in the study area with a parametric sound-
ing performed at each of the wells where the pump- Several electrical resistivity-based empirical equa-
ing test was conducted, with the aid of an ABEM tions have been previously used to estimate aqui-
Terrameter (SAS 4000). The sounding points were fer hydraulic and transmissivity values across the
geo-referenced using a handheld Global Positioning study area. These empirical equations include the
System (GPS). The VES data acquisition was exe- equations of Niwas and Singhal (1981) and Heigold
cuted using the Schlumberger array, with a maximum et al. (1979) and the proposed new model.
half-current (AB/2) electrode separation of 150 m The determination of aquifer hydraulic character-
and half-potential (MN/2) electrode separation of istics can be accomplished by using parameters of
15 m. Apparent resistivity (ρa) values were deduced transverse resistance and longitudinal conductance
from the observed field data using Eq. (1): from Dar-Zarrock parameters. Niwas and Singhal
( 2 ) (1981) developed, on one hand, an empirical
a b ΔV relation between transmissivity and transverse resist-
𝜌a = 𝜋 − (1)
b 4 I ance and, on the other, longitudinal conductance and
transmissivity. Based on Darcy’s law, the fluid dis-
charge Q is given by Eqs. (4) and (5):
Q = KIA (4)
Estimation of geo‑hydraulic parameters
And from Ohm’s law
Estimates of geo‑hydraulic parameters from pumping test J = 𝛿E (5)

The Cooper and Jacob solution method was used to where K = hydraulic conductivity, I = hydraulic gra-
determine the aquifer-derived parameters (transmis- dient, A = cross-sectional area perpendicular to the
sivity and hydraulic conductivity) from the pumping direction of flow, J = current density, E = electric field
test. This was achieved using a computer software intensity, and δ = electrical conductivity (inverse of
(Aquifer Win32) by plotting drawdown against their resistivity).
respective time data acquired in the semi-log format Considering a prism of an aquifer material hav-
during the pumping test. The transmissivity values ing a unit cross-sectional area and thickness h,
were calculated using the formula by Freeze and Niwas and Singhal (1981) combined Eqs. (4) and
Cherry (1979) as shown in Eq. (2): (5) to get the equation given in Eq. (6):

2.3Q T = k𝛿R = KL∕𝛿 (6)

T= (2)
4𝜋ΔS where T = aquifer transmissivity, R = transverse resist-
where T = transmissivity in ­m2/day, Q = discharge rate ance, δ = aquifer conductivity, and L = longitudinal
in ­m3/day, and ΔS = change in drawdown over one conductance.
logarithmic cycle. It is well documented that quantitative represen-
The hydraulic conductivity was calculated from tations of vertical electrical sounding data contrib-
the transmissivity and aquifer depth values, which is, ute to the creation of geo-electric layers in resis-
in this case, assumed to be the length of the screen, tivity measurements. Layer parameters like aquifer
using the equation by Freeze and Cherry (1979) as depth and thickness therefore can be better iden-
shown in Eq. (3): tified with information from geo-electric layers.
The resulting layer parameters are usually used to
T determine the Dar-Zarrock parameters. Therefore,
K= (3)
B the product of the aquifer’s apparent resistivity (ρ)
where K = hydraulic conductivity in m/day, b = aqui- and the aquifer’s thickness (h) results in transverse
fer thickness in m, and T = transmissivity in ­m2/day. resistance (R) as shown in Eqs. (7) and (8):

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were used to estimate transmissivity and hydraulic

R = hp (7)
conductivity at locations where pumping test was not
conducted.
KNS = k𝛿𝜌 (8) These cross-plots yielded two sets of novel empiri-
Niwas and Singhal (1981) maintained that areas cal equations of hydraulic conductivities (K) and
with similar geologic settings and water quality transmissivities for Ebonyi and Abakaliki Forma-
usually have fairly constant diagnostic constants tions, respectively, as given in Eqs. (11)–(14):
(diagnostic constants is the product of the hydraulic
K ebfm = 4.1559Rw
−0.319
(11)
conductivity (k) from pumping test and the electrical
conductivity (δ). Based on this, therefore, the aquifer
hydraulic parameters which vary spatially across an K afm = 0.0114Rw
0.7792
(12)
area both for the areas with pumping test values and
areas without wells can be estimated from resistivity T ebfm = 5330.4R−0.928 (13)
data measured at the surface of the earth.
Also, the Heigold et al. (1979) equation was used in
T afm = 0.0092R0.8117 (14)
this study to estimate hydraulic parameters across the
study area. The Heigold et al. (1979) empirical equa- where Kebfm = hydraulic conductivity for the Ebonyi
tion is based on the relationship between hydraulic Formation, Kafm = hydraulic conductivity for the
conductivity (K) obtained from pumping test from Abakaliki Formation, Tebfm = transmissivity for the
monitoring wells and water resistivity estimated from Ebonyi Formation, Tafm = transmissivity for the Ebonyi
resistivity data carried out close to the wells as shown Formation, Rw = aquifer resistivity, and R = transverse
in Eq. (9): resistance. The coefficient of determination (R2) for
Kebfm, Kafm, Tebfm, and ­Tafm was found to be 1.0, 0.997,
KHG = 386.40Rw−0.93283 (9) 1.0, and 1.0, respectively, exhibiting a very strong posi-
tive relationship between the parameters.
where Rw is aquifer resistivity. Then, the transmis-
sivity of the aquifer (T) can now be estimated using
the relationship given by Niwas and Singhal (1981)
in Eq. (10): Results and discussion
T = k𝛿T = ks∕𝛿 = kh (10)
Interpretation of layer parameters
where δ is the electrical conductivity (inverse of
resistivity) and S is the longitudinal conductance. VES data were used to extract interpreted curves
Finally, a new set of formation-specific empirical (Fig. 4). Interpretation of the geo-electric curves
equations that has a relationship with the intrinsic across the study area revealed four to seven (4–7)
rock properties in the study area were proposed and geo-electric layers with different intra-facies and
used in the present study. Using the empirical rela- inter-facies changes (Table 1). The curve types were
tionship established between hydraulic conductiv- observed to be mainly of the QH, QHK, QHKH,
ity derived from the pumping test in the study area QQH, KHK, QHAK, and QQHK types. Ngwoke
and aquifer resistivity on one hand and that between (2013) stated that the existence of several curve
transmissivity and transverse resistance, a set of two types shows a non-uniformity of resistivity pat-
formation-specific model equations that are geo- terns across the study area. The non-uniformity of
logically constrained and sensitive were generated. layering and modification of layer properties is due
Hydraulic conductivity and transmissivity acquired to differential weathering, fracture anisotropy, and
from the wells where pumping tests were conducted other geological factors, which generally result in
were plotted against aquifer resistivity and transverse differences in resistivity trends across the area of
resistance values, respectively, obtained from para- study. The dominant curve type is the QH curve
metric soundings at the well locations in the differ- with approximately 37%, QHK with 23%, and HK
ent formations (Fig. 3a, b, c, and d), which thereafter type with 9%, with the QQH, KHK, and QHAK
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Fig. 3  Cross-plots showing relationships between aquifer hydraulic parameters and VES estimated parameters: a Kebfm, b Kafm, c
Tebfm, d Tafm

accounting for 6%, respectively, while QQHK, KH, Aquifer hydraulic conductivity (K) estimates of the
HA, and QHK each account for 5%. study area

Hydraulic conductivity (K), which is a measure of the

Aquifer hydraulic parameters ease with which a fluid will pass through a medium,
and transmissivity (T), which is the rate of flow of
The results of aquifer hydraulic parameters acquired fluid under a unit hydraulic gradient through a unit
using the pump testing techniques in the five wells width of the aquifer of thickness, were estimated
are presented in Table 2. The pumping test data using the Niwas and Singhal (1981) (KNS) equation,
were analyzed and plotted using Copper–Jacob Heigold et al. (1979) (KHG) equation, and the new
straight line curve with the aid of Aquiwin-32 soft- empirical equations as shown in Table 3.
ware. Sample plots of the processed pumping test Hydraulic conductivity values estimated from the
data acquired from the study area are presented in Heigold model using (Eq. (11)) for the Ebonyi For-
Fig. 5. mation vary from 0.75 to 22.6 m/day, with a mean

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Fig. 4  Sounding curves from a VES 4, b VES 7, c VES 18, d VES 20

value of 5.84 m/day, while that of the Abakaliki For- by taking the product of the diagnostic constant
mation varies from 1.78 to 39 m/day and has a mean ( kδ) and aquifer resistivity (ρ) at VES locations as
value of 17.8 m/day. From the hydraulic conductivity shown in Eq. (8). The average diagnostic constant of
map (Fig. 6a), the areas underlain by the Abakaliki 0.00721 was used for areas underlain by the Ebonyi
Formation (Eastern axis) have a higher value com- Formation, while areas underlain by the Abaka-
pared to those areas underlain by the Ebonyi Formation liki Formation have a mean diagnostic parameter of
(western axis). This is in agreement with the 0.00352. The estimated hydraulic conductivity of
geology of the study area as previously explained by the study area for the Ebonyi Formation ranges from
Agumanu (1989). Generally, across the study area, 0.15 to 5.87 m/day, with a mean value of 1.32 m/
shales dominate the Abakaliki Formation and usually day. For the Abakaliki Formation, which is overlain
have a lower hydraulic conductivity when compared by the Ebonyi Formation, the estimated hydraulic
with the Ebonyi Formation, which has an alternat- conductivity ranges from 0.04 to 0.61 m/day, with
ing sequence of sandstones, siltstones, and shales. an average of 0.25 m/day. Areas with higher aquifer
Using the Niwas and Singhal (1981) empirical equa- hydraulic conductivity usually have higher hydrau-
tions, aquifer hydraulic conductivity was estimated lic connectivity and permeability and are generally

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 Table 1  Summary of interpreted layer parameters from the study area
VES Location Longitude Latitude Resistivity values of the layers(ohm-m) Layer depth (m) Curve No of Geologic
type layers formation
p1 p2 p3 p4 p5 p6 p7 d1 d2 d3 d4 d5 d6

1 Ekka 7°58′32.21″ 6°10′58.67″ 662.2 196.9 102.3 84.6 744 0.69 11.99 22.92 34.28 QQH 5 Ebonyi
E N Fm
2 Onueke Mar- 8°01′45.10″ 6°10′ 13.13″ 915.2 825.5 275.6 850.4 2.9 12.5 20.6 QH 4 Ebonyi
ket E N Fm
3 Abiaji 8°4′31.07″ 6°7′31.36″ 780.4 428.8 219.6 944.5 11.4 33.1 42.3 QH 4 Ebonyi
Village E N Fm
Environ Monit Assess (2022) 194:719

Square,
Nganbo-
Ogele
4 Amuzu 8°4′19.59″ 6°12′20.64″ 830 58.1 16.75 50 5.4 1.45 1.7 19.7 28.2 QHK 5 Ebonyi
Primary E N Fm
School
5 Ndiuhu 8°5′44.10″ 6°8′19.93″ 300 60 22.5 130 11.4 20.8 1.8 4.14 22.99 31.39 48.99 QHKH 6 Ebonyi
Amana E N Fm
6 Nganbo Ndi- 8°2′27.72″ 6°5′51.29″ 440 286 36.5 12 45.5 2.55 3.7 13.7 220.7 QQH 5 Ebonyi
agu Amagu E N Fm
7 Nganbo Agu 8°1′11.86″ 6°7′58.73″ 870 60.9 24.5 84 116 6.6 1.4 1.67 21.83 25.5 30.57 QHAK 6 Ebonyi
E N Fm
8 Sacred Heart 8°1′18.34″ 6°7′54.51″ 720 360 57 107.5 65 2 13.6 44.85 53.75 QHK 5 Ebonyi
Catholic E N Fm
Church
Onueke
9 Ndufu 7°58′11.20″ 6°7′42.75″ 825 330 68 106 65 1.9 13.3 56.5 12.3 QHK 5 Ebonyi
Idembia E N Fm
Commu-
nity Hall
10 Nganbo 7°58′37.08″ 6°9′2.18″ N 320 48 3.85 58 24 1.9 10.64 11.54 35.77 QHK 5 Ebonyi
Ohainya E Fm
Ezzama
11 Nganbo 8°4′24.74″ 6°7′34.57″ 280 560 40 273 210 1.75 3.76 22.76 35.26 KHK 5 Ebonyi
Amaeze- E N Fm
kwe
12 Ezeugwu 8°0′37.27″ 6°5′40.06″ 2151.7 814 14.1 35.8 8.25 12.3 31 QH 4 Ebonyi
Okofia E N Fm
13 Oriegu- 7°58′6.48″ 6°7′1.63″ N 345 205 103 36 198 3125 0.5 1.2 4 12 18 QQHK 6 Ebonyi
Market E Fm

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Square 1
 Table 1  (continued)
719

VES Location Longitude Latitude Resistivity values of the layers(ohm-m) Layer depth (m) Curve No of Geologic
type layers formation

13
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p1 p2 p3 p4 p5 p6 p7 d1 d2 d3 d4 d5 d6

14 Oriegu-Mar- 7°58′11.45″ 6°6′59.67″ 45 26 25 98 458 4578 0.8 1.5 3 8 18 QHAK 6 Ebonyi

Page 10 of 23

ket Square E N Fm
11
15 Azu Ugbo 8°0′14.57″ 6°5′20.43″ 939.1 443.3 174.8 789.5 9.6 21.3 38.4 QH 4 Ebonyi
Village E N Fm
Square
16 Ohiya Imea- 8°00′06.85″ 6°08′54.33″ 461.8 365.5 701.5 383.6 2.2 5.6 14.4 HK 4 Ebonyi
bali E N Fm
17 Ishieke 8°1′17.84″ 6°2′54.55″ 910 974.5 160 603.1 3.4 18 34 QH 4 Ebonyi
Ndufu E N Fm
Igbudu
18 Oguwekwe 8°1′43.34″ 6°9′16.93″ 299.5 21 12.6 256 2.4 8.7 48.9 QH 4 Ebonyi
Village E N Fm
Hall
19 Our Lady 7°58′55.33″ 6°9′19.40″ 1232.6 1199 173 765.3 2.4 6.6 105.8 QH 4 Ebonyi
Fatima E N Fm
Catholic
Church
20 Ochufuagba 7°59′13.05″ 6°7′23.66″ 1300 195 38 240 1.8 5 77 QH 4 Ebonyi
Com- E N Fm
munity
Primary
School
21 Community 7°57′48.36″ 6°7′0.94″ N 2100 630 95 150 2.5 9.8 52 QH 4 Ebonyi
Primary E Fm
School
Ugwuogo
22 Amuzu 8°1′19.89″ 6°10′5.03″ 1500 105 230 3000 2.3 32 37 HA 4 Ebonyi
Townhall E N Fm
23 Ndechi 8°8′4.84″ E 6°8′31.50″ 983.1 928.8 172.9 1329 8.3 17.3 33.2 QH 5 Abakaliki
Ndufu N Fm
achara
24 Ishieke, 8°1′17.84″ 6°2′54.55″ 910 974.5 160 603.1 3.4 18 34 QH 4 Abakaliki
Ndufu E N Fm
Igbudu
Environ Monit Assess (2022) 194:719
 Table 1  (continued)
VES Location Longitude Latitude Resistivity values of the layers(ohm-m) Layer depth (m) Curve No of Geologic
type layers formation
p1 p2 p3 p4 p5 p6 p7 d1 d2 d3 d4 d5 d6

25 Elegu 8°9′34.99″ 6°4′0.76″ N 921.1 835 319 839.1 2.9 15.5 31.1 QH 4 Abakaliki
Ndiechi E Fm
Ekpomaka
26 Elegu Ettem 8°10′51.80″ 6°5′50.93″ 2205 150 29.1 200 14.3 0.76 6.6 23 82.8 QH 5 Abakaliki
E N Fm
27 Ekpelu 6°2′52.88″ 8°8′11.30″ 733 340 32.1 46.9 458 1.8 5.03 22.1 46 QHK 5 Abakaliki
Environ Monit Assess (2022) 194:719

N E Fm
28 Ndiofeke 6°9′12.20″ 8°10′7.62″ 84.1 459 17.4 24.5 12.8 0.75 2.15 6.18 17.7 KHK 5 Abakaliki
N E Fm
29 Enyacha- 6°7′11.88″ 8°7′59.73″ 293 105 330 26.6 279 0.924 2.81 15.8 59.4 HK 5 Abakaliki
rigne N E Fm
(Ndiagu
Amagu)
30 Ndiagu 6°4′30.02″ 8°5′19.26″ 11.5 72.9 51.6 11.7 44.7 1.13 2.76 5.43 40.1 QHK 5 Abakaliki
Amagu N E Fm
Primary
School
Enyibivhiri
1
31 Eke Ettam 6°8′51.77″ 8°7′19.04″ 158.1 12.9 4.36 25.2 14.8 127 604 2.18 2.21 6.02 17.67 50 115.4 QHK 7 Abakaliki
Market N E Fm
Square
32 Amainyima 6°10′14.64″ 8°8′39.24″ 190 184 312 17.7 112 348 1.58 3.16 7.47 25.5 68.5 HKA 6 Abakaliki
N E Fm
33 Ndiagu 6°4′30.02″ 8°5′19.26″ 129 57.1 831 23.2 141 17.9 1.58 1.83 5.64 51.6 98.4 HK 6 Abakaliki
Amagu N E Fm
Primary
School
Enyibivhiri
11
34 Ndufu 6°4′36.96″ 8°3′15.95″ 749.9 2533 86.24 330 94.1 1448 2617 0.75 2.15 6.055 17.78 50.98 167.1 QHK 7 Abakaliki
Inyiamagu N E Fm
Obeagu
playground
(1)

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 719 Page 12 of 23 Environ Monit Assess (2022) 194:719

associated with higher groundwater potential (Opara

formation

Abakaliki
Geologic
et al., 2020). The hydraulic conductivity map gener-
ated from the estimates predicted using the Niwas

Fm
and Singhal model is shown in Fig. 6b.
Also, Eqs. (11)–(12) which represent the new
layers
No of

model equations proposed and used in this work were

6

used to estimate the hydraulic conductivity values of

the Ebonyi and Abakaliki Formations within the study
Curve
type

area. Hydraulic conductivity values estimated using

KH

the new model for areas underlain by the Ebonyi

Formation range from 0.49 to 1.5735 m/day with a
d6

mean value of 0.9205 m/day, while those underlain

by the Abakaliki Formation have hydraulic conduc-
113
d5

tivity values that vary from 0.0775 to 1.3023 m/day,

59.4

with a mean value of 0.2883 m/day. There is a high

d4

level of agreement between the hydraulic conductiv-

ity estimated from the pumping test and that from the
14.6
d3
Layer depth (m)

new model derived from the present study when com-

pared with Niwas and Singhal and Heigold model as
2.58
d2

shown in Table 2. This shows that the model equation

proposed and used in the present study which is geo-
0.75
d1

logically constrained is more effective in estimating

aquifer hydraulic parameters across the study area.
p7

From the hydraulic conductivity contour map of the

study area generated from values estimated using the
p6
15.4 50
Resistivity values of the layers(ohm-m)

new model (Fig. 6c), there exists a hydrogeological

p5

divide with the Ebonyi Formation in the western axis

of the study area having higher hydraulic conductiv-
20.7
p4

ity values and therefore a more prolific aquifer system

than the Abakaliki Formation which is in the eastern
13.9

axis of the study area with lower hydraulic conduc-

p3

tivity values. These findings are in agreement with

270

previous works done in the study area (Agumanu,

p2

1989; Ekwe et al., 2015; Oli et al., 2020). Within

23.1

the Abakaliki Formation, areas with hydraulic con-

p1

ductivity greater than the surrounding formation are

believed to be associated with highly fractured shale
8°3′30.85″
Latitude

zones which improved the porosity and permeability

of the formation.
E

Estimation of aquifer transmissivity (T) of the study

6°4′39.96″
Longitude

area
N

Aquifer transmissivity estimated across the study

Table 1  (continued)

playground
Inyiamagu

area using the new model ranges between 0.29 and

Obeagu
VES Location

57.27 ­m2/day with a mean value of 6.59 ­m2/day.

Ndufu

(11)

The transmissivity values within the area underlain

by the Ebonyi Formation vary from 0.63 to 57.27
­m2/day with a mean value of 8.23m2/day, while
35

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 Table 2  Computed hydraulic conductivity and transmissivity values derived from different models
VES point Location K from K from new K from Niwas K″ from Transmissivity (T) Transmissivity Transmissivity Transmissivity Geologic
pumping test model m/ and Singhal m/ Heigold from pumping test (T) from Heigold (T) from new from Niwas formation
m/day day day m/day ­m2/day ­(m2/day) model ­(m2/day) Singhal (T)
­(m2/day)

VES 1 * Ekka 1.01 1.01 0.61 6.15 9.0662 69.9 9.09 6.93 Ebonyi Fm
VES 2 * Onueke Market 0.69 0.69 1.99 2.04 4.1457 16.6 4.16 16.09 Ebonyi Fm
VES 3 Abiaji Village 0.74 1.58 2.53 23.3 4.56 14.56 Ebonyi Fm
Square,
Nganbo-
Environ Monit Assess (2022) 194:719

Ogele
VES 4 Amuzu Pri- 1.19 0.36 10.05 85.4 19.39 3.06 Ebonyi Fm
mary School
VES 5 Ndiuhu Amana 0.88 0.94 4.12 34.6 8.08 7.87 Ebonyi Fm
VES 6 Nganbo Ndiagu 1.32 0.26 13.48 134.8 22.33 2.63 Ebonyi Fm
Amagu
VES 7 Nganbo Agu 0.91 0.84 4.58 23.2 14.34 4.24 Ebonyi Fm
VES 8 Sacred Heart 0.93 0.77 4.92 272.8 1.67 42.95 Ebonyi Fm
Catholic
Church
Onueke
VES 9 Ndufu Idembia 1.08 0.49 7.54 325.9 3.22 21.17 Ebonyi Fm
Community
Hall
VES 10 Nganbo 1.14 0.42 8.75 212.0 6.39 10.13 Ebonyi Fm
Ohainya
Ezzama
VES 11 Nganbo 0.69 1.97 2.06 25.8 2.81 24.60 Ebonyi Fm
Amaezekwe
VES 12 Ezeugwu 0.49 5.87 0.74 3.0 2.90 23.76 Ebonyi Fm
Okofia
VES 13 Oriegu-Market 0.77 1.43 2.78 16.7 7.47 8.56 Ebonyi Fm
Square 1
VES 14 Oriegu-Market 0.59 3.30 1.27 12.7 2.14 33.01 Ebonyi Fm
Square 11
VES 15 Azu Ugbo Vil- 0.80 1.26 3.13 53.5 3.17 21.54 Ebonyi Fm
lage Square
VES 16 Ohiya Imeabali 0.63 2.63 1.57 5.3 7.16 8.96 Ebonyi Fm
VES 17 Ishieke Ndufu 0.82 1.15 3.40 54.7 3.64 18.57 Ebonyi Fm

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Igbudu
 Table 2  (continued)
719

VES point Location K from K from new K from Niwas K″ from Transmissivity (T) Transmissivity Transmissivity Transmissivity Geologic
pumping test model m/ and Singhal m/ Heigold from pumping test (T) from Heigold (T) from new from Niwas formation

13
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m/day day day m/day ­m2/day ­(m2/day) model ­(m2/day) Singhal (T)
­(m2/day)
Page 14 of 23

VES 18 Oguwekwe Vil- 1.57 0.15 22.58 142.2 57.27 0.95 Ebonyi Fm
lage Hall
VES 19 Uur Lady 0.80 1.25 3.16 313.2 0.63 123.69 Ebonyi Fm
Fatima
Catholic
Church
VES 20 Ochufuagba 1.30 0.27 12.98 934.8 3.44 19.72 Ebonyi Fm
community
primary
school
VES 21 Community 0.93 0.68 5.52 233.1 2.42 28.89 Ebonyi Fm
Primary
School
Ugwuogo
VES 22 Amuzu Town 0.94 0.76 5.03 149.4 3.05 22.48 Ebonyi Fm
hall
VES 23* Ndechi Ndufu 0.63 0.63 0.61 3.16 5.6585 50.2 5.69 9.68 Abakaliki
achara Fm
VES 24* Ishieke, Ndufu 0.60 0.59 0.56 3.40 5.3789 54.7 5.40 9.07 Abakaliki
Igbudu Fm
VES 25* Elegu Ndiechi 1.02 1.02 1.12 1.78 9.1713 27.8 9.22 17.52 Abakaliki
Ekpomaka Fm
VES 26 Elegu Ettem 0.16 0.10 16.65 273.1 1.37 1.68 Abakaliki
Fm
VES 27 Ekpelu 0.17 0.11 15.20 259.8 1.54 1.93 Abakaliki
Fm
VES 28 Ndiofeke 0.11 0.06 26.90 108.4 0.29 0.25 Abakaliki
Fm
VES 29 Enyacharigne 0.15 0.09 18.11 791.3 2.83 4.09 Abakaliki
(Ndiagu Fm
Amagu)
Environ Monit Assess (2022) 194:719
 Table 2  (continued)
VES point Location K from K from new K from Niwas K″ from Transmissivity (T) Transmissivity Transmissivity Transmissivity Geologic
pumping test model m/ and Singhal m/ Heigold from pumping test (T) from Heigold (T) from new from Niwas formation
m/day day day m/day ­m2/day ­(m2/day) model ­(m2/day) Singhal (T)
­(m2/day)

VES 30 Ndiagu Amagu 0.08 0.04 38.96 1348.0 1.20 1.42 Abakaliki
Primary Fm
School Eny-
ibivhiri 1
VES 31 Eke Ettam 0.09 0.05 32.29 1043.0 1.38 1.68 Abakaliki
Market Fm
Environ Monit Assess (2022) 194:719

Square
VES 32 Amainyima 0.11 0.06 26.48 477.4 0.99 1.12 Abakaliki
Fm
VES 34 Ndiagu Amagu 0.13 0.08 20.57 945.5 2.64 3.75 Abakaliki
Primary Fm
School Eny-
ibivhiri 11
VES 34 Ndufu Inyia- 0.39 0.33 5.57 185.0 6.32 11.00 Abakaliki
magu Obeagu Fm
playground
(1)
VES 35 Ndufu Inyia- 0.12 0.07 22.88 1025.0 2.36 3.26 Abakaliki
magu Obeagu Fm
playground
(11)
* Pumping test and Vertical Electrical Sounding conducted

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Fig. 5  Pumping test curves analyzed using Cooper and Jacob method for a Ekka Ezza, b Onueke market, c Ndiechi Ndufu Achara, d
Ishieke Ndufu Igbudu

that of the Abakaliki Formation ranges from 0.29 has higher transmissivity values than the Abakaliki
to 9.22 ­m2/day with a mean value of 3.44 ­m2/day. Formation as shown in Fig. 7b. Finally, the aquifer
The contour map of the transmissivity values esti- transmissivity values estimated by multiplying the
mated using the new model is shown in Fig. 7a. hydraulic conductivity values estimated using the
Also, Niwas and Singhal’s model was also used Heigold model by the thicknesses of the aquifer for
to estimate transmissivity across the study area as the Ebonyi Formation range from 3.01 to 934 ­m2/
shown in Eq. (10) by using the product of the aqui- day with a mean value of 142 ­m2/day, while that of
fer hydraulic conductivity estimates made from the the Abakaliki Formation range from 50.2 to 1347
Niwas and Singhal (1981) equation and the aquifer ­m2/day with a mean value of 507 m ­ 2/day, with the
thickness. The estimated values for the Ebonyi For- map shown in Fig. 7c. Analysis of the transmissivity
mation therefore ranges between 0.95 and 124 ­m2/ contour map of the study area, estimated by using
day with a mean value of 20.19 m ­ 2/day, while that the Heigold model (Fig. 7c), suggests that areas
of the Abakaliki Formation ranges from 0.25 to underlain by the Ebonyi Formation have a lower
17.5 ­m2/day with an average of 5.54 m ­ 2/day. Based transmissivity than areas underlain by the Abakaliki
on these predictions, therefore, the Ebonyi Formation Formation. This in particular is not in agreement

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Table 3  A paired t test for the different models

Statistics K (m/day) from pumping tests K (m/day) from new model

Mean 0.7880 0.7860

Variance 0.0421 0.0431
St. deviation 0.2052 0.2076
Observations 5 5
Pearson correlation 0.9998
T value 0.698
Observed mean difference 0.002
Standard deviation difference 0.001
Statistics K (m/day) from pumping tests K m/day) from Niwas and Singhal
Mean 0.7880 0.9780
Variance 0.0421 0.3725
St. deviation 0.2052 0.6103
Observations 5 5
Pearson correlation −0.0252
T value 0.548
Observed mean difference 0.190
Standard deviation Difference 0.405
Statistics K (m/day) from pumping tests K(m/day) from Heigold model
Mean 0.7880 3.3060
Variance 0.0421 3.0125
St. deviation 0.2052 1.7356
Observations 5 5
Pearson correlation 0.2962
T value 0.029
Observed mean difference 2.518
Standard deviation difference 1.530

with the geology of the area, thereby showing that estimated from the new model equations when com-
the Heigold model is defective for the study area. pared with K values from the pumping test revealed a
Heigold et al. (1979) equation therefore typically Pearson correlation of 99%. This represents a strong
under-predicts areas which are not similar geologi- positive correlation. The other models (KNS and KHG)
cally to the study area from where the empirical presented a strong negative correlation with that from
equation was generated. the pumping test. The observed mean difference of
Statistical analysis was carried out to ascertain the hydraulic conductivity estimated from Niwas and
reliability of the different empirical equations/mod- Singhal (1981) equation, Heigold et al. (1979) equa-
els in estimating hydraulic conductivity by compar- tion, and the new model equation when compared
ing them with the values from the widely accepted with the values of the pumping test showed that the
pumping test technique. A paired t test was used to new model values have a lower observed mean differ-
compare the values of the standard deviation, mean, ence than the others (Table 3). This validates the effi-
variance, and Pearson correlation of the various ciency of the model derived from the present study
hydraulic conductivities estimated from other mod- in estimating hydraulic conductivity when there is
els with those from the pumping test as shown in dearth of pumping test data.
Table 3. From Table 3, it was observed that K values

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Fig. 6  Contour map of the study area showing hydraulic conductivity, m/day: a Heigold model, b Niwas and Singhal model, c model
derived from the present study

Groundwater potential aquifer potentials of the study area range from low
to intermediate. The groundwater potentials at two
The groundwater potential of the study area was (2) of the locations representing 6% of the study area
assessed based on the transmissivity of the aquifer at have groundwater potential which can only sustain
each sounding point estimated using the new model. limited consumption, with twenty-nine (29) of the
Krasny’s (1993) classification of transmissivity mag- locations which represent 83% of the study area capa-
nitude as shown in Table 4 was used to assign ground- ble of providing groundwater potentials that can serve
water supply potentials of the various locations in the for private consumption, while the remaining four (4)
study area. Based on Table 5, it was observed that the locations which represent 11% of the study area hold

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Fig. 7  Contour map of the study area showing transmissivity in ­m2/day: a model derived from the present study, b Niwas and Singhal
model, c Heigold model

Table 4  Classification of transmissivity magnitude (After Krasny, 1993)

Magnitude of transmissivity (m2/day) Designation Groundwater supply potential

> 1000 Very high Regional importance

100–1000 High Lesser regional importance
10–100 Intermediate Local water supply
1–10 Low Private consumption
0.1–1 Very low Limited consumption
< 0.1 Imperceptible Very difficult to utilize for local water supply

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Table 5  Transmissivity classification based on data collected in the study area

Location Transmissivity Designation of transmissivity Groundwater supply
(m2/day) magnitude potential

Ekka 9.09 Low Private consumption

Onueke Market 4.16 Low Private consumption
Abiaji Village Square, Nganbo-Ogele 4.56 Low Private consumption
Amuzu Primary School 19.39 Intermediate Local water supply
Ndiuhu Amana 8.08 Low Private consumption
Nganbo Ndiagu Amagu 22.33 Intermediate Local water supply
Nganbo Agu 14.34 Intermediate Local water supply
Sacred Heart Catholic Church Onueke 1.67 Low Private consumption
Ndufu Idembia Community Hall 3.22 Low Private consumption
Nganbo Ohainya Ezzama 6.39 Low Private consumption
Nganbo Amaezekwe 2.81 Low Private consumption
Ezeugwu Okofia 2.90 Low Private consumption
Oriegu-Market Square 1 7.47 Low Private consumption
Oriegu-Market Square 11 2.14 Low Private consumption
Azu Ugbo Village Square 3.17 Low Private consumption
Ohiya Imeabali 7.16 Low Private consumption
Ishieke Ndufu Igbudu 3.64 Low Private consumption
Oguwekwe Village Hall 57.27 Intermediate Local water supply
Uur Lady Fatima Catholic Church 0.63 Low Private consumption
Ochufuagba community primary school 3.44 Low Private consumption
Community Primary School Ugwuogo 2.42 Low Private consumption
Amuzu Town hall 3.05 Low Private consumption
Ndechi Ndufu achara 5.69 Low Private consumption
Ishieke, Ndufu Igbudu 5.40 Low Private consumption
Elegu Ndiechi Ekpomaka 9.22 Low Private consumption
Elegu Ettem 1.37 Low Private consumption
Ekpelu 1.54 Low Private consumption
Ndiofeke 0.29 Very low limited consumption
Enyacharigne (Ndiagu Amagu) 2.83 Low Private consumption
Ndiagu Amagu Primary School Enyibivhiri 1 1.20 Low Private consumption
Eke Ettam Market Square 1.38 Low Private consumption
Amainyima 0.99 Very low Limited consumption
Ndiagu Amagu Primary School Enyibivhiri 11 2.64 Low Private consumption
Ndufu Inyiamagu Obeagu playground (1) 6.32 Low Private consumption
Ndufu Inyiamagu Obeagu playground (11) 2.36 Low Private consumption

a groundwater potential that can serve as a local water revealed a groundwater divide in line with the geology
supply. These areas that can sustain local water sup- of the study area with the Ebonyi Formation having a
ply are dominated by areas underlain by the Ebonyi higher groundwater potential than the Abakaliki For-
Formation. The aquifer potential map of the study mation. The findings of the present study are in agree-
area is shown in Fig. 8. ment with the results of previous studies within the
The results of this study have helped to delineate study area (Ekwe et al., 2020; Obiora et al., 2015; Oli
the groundwater potential zones within the study area. et al., 2020).
Evidently, the findings of the present study thus
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Environ Monit Assess (2022) 194:719 Page 21 of 23 719

Fig. 8  Groundwater poten-

tial map of the study area

Conclusion exploitation should be focused more on areas under-

lain by the Ebonyi Formation for a greater yield. The
The present study has clearly demonstrated the effec- study therefore clearly revealed a pronounced ground-
tiveness of the application of surficial resistivity data water divide between the Ebonyi and Abakaliki For-
in aquifer hydraulic estimation. Aquifer hydraulic mations of the study area.
parameters including aquifer hydraulic conductiv- The closeness of the estimated results obtained
ity and transmissivity were estimated using multiple from the interpretation of the vertical electrical
resistivity-based empirical equations even in areas sounding results with those obtained from pumping
with a paucity of pumping test data. These analyti- tests from available borehole locations has further
cal and empirical equations which have been used shown the validity of the present study. Electrical
with fairly high level of success were improved by resistivity method is therefore a useful tool for under-
adopting formation-specific equations which were standing the aquifer systems in the study area. The
constrained geologically. Statistical analysis of aqui- study has shown that direct current electrical resis-
fer hydraulic parameters estimated from the different tivity methods are not only useful in groundwater
models revealed that the new model proposed and exploration or delineation of aquifer geometry but can
used in the present study clearly showed values that also be effective in the estimation of aquifer hydraulic
have the closest relationship with values obtained parameters.
from the pumping test. Transmissivity estimated
from the new model suggested that areas under- Acknowledgements The authors are grateful to the man-
agement of the Federal University of Technology, Owerri, for
lain by the Ebonyi Formation have a greater aquifer supporting this research. The technical and data support of the
potential when compared with those areas underlain management and staff of Anambra-Imo River Basin Develop-
by the Abakaliki Formation. This can be explained ment Authority, Owerri, is deeply appreciated. Finally, we
by the geology, as areas within the Abakaliki For- appreciate with thanks the contributions of the anonymous
reviewers and editors who worked on the manuscript.
mation with higher aquifer potential are suspected to
be highly fractured shales. This is also validated by Data availability Data available on request.
Krasny’s groundwater potential classification of the
study area, with areas underlain by the Ebonyi Forma- Declarations
tion having greater groundwater prospects than those
Conflict of interest The authors declare no competing interests.
underlain by the Abakaliki Formation. Therefore,

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Okeke, I., Urom, O. O., Udeh, H. M., & Ezennubia, V.

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