# Integrated Approach to Investigate the Effect of Leachate on Groundwater around the Ikot Ekpene Dumpsite in Akwa Ibom State, Southeastern Nigeria

Authors: N. J. George; A. I. Ubom; J. I. Ibanga
Journal: International Journal of Geophysics
 (2014)

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## Abstract

Geophysical, geochemical, and hydrogeological measurements have been integrated to assess the effect of leachate on groundwater quality within the dumpsite in Ikot Epene Local Government Area of Akwa Ibom State, Southern Nigeria, and its environs. The resistivity values and depth of burial of the geomaterials, constrained by geology, were used in producing resistivity cross sections which show the geoelectric distribution of the subsurface near and away from the dumpsite. The observed high conductivity in subsurface layers closed to the dumpsite is symptomatic of the leachate-loaded conductive fluid leached and drained into the subsurface. The hydrochemical results of some species conform to WHO standards, while some were found to be relatively higher due to dissolution, leaching, and draining of leachate related contaminants in the soil. The correlation indices of the ion pairs show no significant effect on the paired ions, indicating that the significant value of some of the individual ions is not geologic but due to precipitation from the leachate residue. In general, the effect of leachate is more dominant in the immediate groundwater pathway near the dumpsite than aquifer repositories away from it. The crossplots of the water resistivity and bulk resistivity show exponential increase for the different layers.


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## Body

## 1. Introduction

Environmental contamination is one of the main concerns of earth scientists and researchers worldwide. The accelerated pace of industrial development coupled with uncontrolled growth of the urban population has resulted in the increasing production of solid/liquid residues. Urban waste materials, mainly domestic garbage, are usually disposed without the appropriate measures of the effect of the released fluid (leachate) on groundwater resources. Groundwater pollution happens mostly due to percolation of pluvial water and the infiltration of contaminants through the soil. The contaminant fluid emanated from the decomposition of organic matter is rich in dissolved salts, containing substantial amount of polluting substances [1, 2]. When the contaminant liquid (leachate) diffuses into the groundwater table, it affects the potability of groundwater, putting the local community into serious health risk. Some of the most frequent demands of people in the metropolitan areas include the detection of the location and extent of contamination patches/plumes in areas such as dumpsites or landfill sites.Electrical resistivity of soils is dependent up various factors, including soil type, water content, saturation, and pore fluid property. This experimental work has been performed to investigate the relationship between electrical resistivity and surficial subsurface conditions with varying physical property and landfill leachate contamination. The moisture density can be the most effective indicator for describing the relationship between electrical resistivity and physical property of unsaturated subsurface.  Experiments by other authors show that the electrical resistivity of soil exponentially decreased as moisture density increased. The addition of leachate fraught with various ions decreases the electrical resistivity. Also, the formation factor can be described by the term of moisture density in unsaturated sand. The formation factor (ratio of bulk resistivity to water resistivity of a medium) is higher when soil and pore water are contaminated by higher concentration of leachate than when soil and pore water are uncontaminated, since the movement ions are restrained by electrochemical interactions between soil particles and leachate constituents.The study area is situated in the northwestern part of Akwa Ibom State in southern Nigeria (Figure1). In the study area, the primary source of potable water which is utilized for domestic, agricultural, and industrial purposes is groundwater. Shallow aquifers are overexploited through open wells and bore wells. There has been significant deterioration in groundwater quality due to the leachate emanated from dumpsite into the wells located within the radius of the study area. The impact of leachate in groundwater is stupendous. Although the tissue fluid (leachate) loaded with mobile ions is rich in mineral nutrients needed by plants for agricultural productivity, the main preoccupation of the dwellers in the area, this degraded groundwater is unsuitable for drinking.Outline map of (a) Nigeria showing the position of Akwa Ibom State, (b) map of the study area showing some of the LGAs and the generalized geology, and (c) sketch map of the dumpsite location and its environ, showing the VES profiles, boreholes, and VES location.
(a)
(b)
(c)To assess the effect of leachate on the quality of groundwater, geophysical, hydrogeological, and hydrochemical studies were carried out near and away from the dumpsite located in the study area. The dumpsite is composed of materials of mechanical, biological, and chemical sources. Since the leachate contaminant is associated with high salinity flows within the subsurface, electrical resistivity method can be the most suitable field method to determine the region of dominant influence of salinity through measurement of apparent electrical resistivity of the subsurface. Under many subsurface conditions, electrical resistivity method can quickly and economically delineate the general level of contaminant/plume and identify areas most feasible for sampling and monitoring. Many contaminants contain ionic concentrations considerably higher than the background level of native groundwater [3]. When such contaminants are introduced into an aquifer, the electrical resistivity of the saturated zone is reduced [4]. Electrical resistivity study across suspected areas of high conductivity or low resistivity can identify such areas as zones fraught with contaminations [5]. However, combining the results from geophysical, hydrogeological, and hydrochemical data of monitoring wells can improve the uniqueness of the results.Empirical relations between the site dependent earth resistivity (ER) and the measured electrical conductivity (EC) of groundwater can be used to predict the magnitude of contaminant within and away from the dumpsite [5]. The objective of this paper is to integrate geoelectric and physicochemical data in determining the effect of leachate on groundwater within the dumpsite location and its environs. It also attempts to show the relationship between bulk and water resistivity thereby predicting the level of diffusion of dissolved fluid from dumping refuse into the groundwater repositories within the dumpsite environment.


## 2. Location

The dumpsite and its environs located in Ikot Ekpene Local Government Area (Figure1) lie between latitudes 5.072°–5.140°N and longitudes 7.390°–7.458°E in Akwa  Ibom state, southeastern Nigeria. It spreads over an area of about 25 km2. The basin is characterized by gently undulating topography with hills located in the northern parts and is sloping towards southwest. The maximum elevation in the area is of the order of 40 m (amsl) in the north whereas the minimum elevation is of the order of 10 m (amsl) in the south. The region is highly drained by the inland coastal water.  Vegetation in the study area is of the rain forest type. It is sustained by the tropical climate characterized by high temperature with annual mean of 5.5°-6.5°C. The maximum daily temperature lies  between 28° and 30°C during March and the minimum  daily mean temperature  lies between 23° and 24°C during July and August [6]. High relative humidity (annual mean of 83%) and high precipitation (250 mm per annum) are prevalent in the area.


## 3. Geological Setting and Hydrogeology

The area which is subjected to constant inundation by the water of coastal flank is geologically characterized by the Miocene Akata Formation (shales, intercalated sands, and silestone), Miocene-Pliocene Agbada Formation (sands and sandstones, intercalated with shales) and the Pliocene Benin Formation (coarse-grained sand, gravelly sands with minor intercalation of clays and shales) from top to bottom, respectively. The middle and the upper sand units of the Benin Formation constitute the major aquiferous units in the area [7, 8]. Typical boreholes in the area have 42–172 m depth, 1–55 m static water level (swl)  (depth from the surface to water level in the borehole), and 39–100 m saturated thickness. Other hydrological data are 216–5304 m2/day transmissivity, 1.2–42.5 m drawdown, and storage coefficient of 0.10–0.30 [9]. The water table varies from 1.3 m to 52 m according to [10].


## 4. Surface-Geophysical Method and Data Collection

Geophysical methods provide an efficient tool for characterizing subsurface geology and hydrology. The geophysical method used in this work measured the electrical resistivity using the Vertical Electrical Sounding (VES) method [11]. This was performed by using SAS 4000 ABEM Terrameter and its accessories. The apparent resistivity (ρa) was measured in ten locations using the following:
(1)(ρa)=π·[(AB/2)2-(MN/2)2MN]·Ra.
The equation can be simplified as in the following:
(2)(ρa)=K·Ra,
where the geometric factor K=π·([(AB/2)2-(MN/2)2/MN]), AB and MN are the current and potential electrode separations, respectively, and Ra is the resistance measured by the equipment. The potential and current electrode separations ranged between 1–40 m (MN/2=0.5 to 20 m) and 2–1000 m (AB/2=1.0 to 5000 m), respectively. Since the area has good access with avoidable obstructions, the cable spread was extended up to 1 km in order to ensure that depths  above 150 m  were sampled  assuming that the penetration depth varies between 0.25AB and 0.5AB [12, 13]. The coordinates and elevations of the locations were taken using the Global Positioning System (GPS).  The processing of apparent resistivity values with Resist Software constrained by drilled borehole lithologic information led to the determination of the model curves used in this work. From the curves, depth, thickness, and resistivity values of different layers that the current penetrated were obtained. The measured VES in the entire area was characterized by spatial variability due to inhomogeneity of the subsurface [14–16]. The smoothening process involved averaging of the observed electrical resistivity data at crossover points or outright deleting of one of the two data sets at crossover points and other outliers that fall significantly outside the dominant trend of the curve. Any discontinuity observed after the smoothening was assumed to be geologic. The bulk water conductivity, the reciprocal of bulk resistivity, was computed from the measured resistivity.


## 5. Physical and Chemical Sampling and Analytical Techniques

Field sampling was carried out in the month of May 2011 and water samples were collected with a new plastic bucket and poured into l litre polythene bottles after measuring physical parameters such as temperature, pH, and electrical conductivity (EC) (that change rapidly with time). The EC of the unsaturated layers was estimated by saturating drilled core samples with distilled water. The parameters (pH, temperature, and water conductivity) were measured in the field using 09 Kion pH, temperature, and conductivity meter, respectively. After sampling, the bottle was capped immediately to minimize oxygen contamination and the escape of dissolved gases. The hydrochemical analysis was carried out at the Ministry of Science and Technology Central Laboratory and Aluminum Smelter Company (ASCON) Chemical Laboratory, both in Akwa Ibom State, Nigeria. The cations (Na+, K+, Ca+, Mg2+, Fe2+, and Mn2+) were determined using Atomic Absorption Spectrophotometer (UNICAM 969AAS), while the anions(Cl− and SO42-) were analyzed using DR 2000 Spectrophotometer at wavelength 455 nm and 450 nm. Carbonates and bicarbonates (CO32- and HCO3-) were determined titrimetrically using phenolphthalein and methyl orange indicator method [17]. Water samples meant for anion determination were acidified and the choice of acid depended on the anion. For example, water sample meant for ions determination was primed with 0.5 M solution of nitric acid to keep the ions in solution.


## 6. Data Analysis, Interpretation, and Discussion of Results

### 6.1. Geophysical Data Analysis and Results

Smoothing of field data by manual plotting on a bilogarithmic graph for curve matching and computer modelling of the result from manual plotting were employed in the reduction of field data [18–20] to their equivalent geological models. Transformation of the measured apparent resistance Ra to their corresponding apparent resistivity ρa  was achieved using (1). The manual procedure involves plotting the computed apparent resistivity data on a bilogarithmic graph and, where necessary, the curves generated were smoothened to remove the effects of lateral inhomogeneities and other forms of noisy signatures in the smoothened curve were attributed to vertical variation of electrical resistivity with depth. The smoothened curves were quantitatively interpreted in terms of true resistivity and thickness by a conventional manual curve matching procedure using master curves and auxiliary chart [18, 21]. The conventional curves  and auxiliary charts (theoretical curves)  used in the interpretation  aided in obtaining a good fit between the observed field curves and the theoretical curves during total and partial matching. Software programs were later used to improve upon the manually interpreted results. Since the data were acquired at different times, several VES modelling Software programs including Resist [22], Ato [23], and Res1D [24] were used in modelling the data and the results were later transformed to their equivalent geological models. The primary layer parameters comprising resistivity, thicknesses, and depths obtained from the manual interpretation stage were keyed as inputs into some of the computer modelling Software programs (Resist and Res1D only). The computer Software used these parameters to generate data for the estimated model and compared the computed data with their measured counterpart. The extent of fit between the calculated and the measured data sets was assessed using the root mean square error (RMS) technique in which 10% was set as the maximum accepted value. Representative examples of modelled VES curves obtained within the dumpsite and its environs after the smoothing and modelling exercises are shown in Figures 2, 3, and 4 for the three transects considered. For VES far from the dumpsite, a good correlation was observed between the electrical resistivity derived 1D subsurface model and the geology model, while some disconformities  were noticed in VES closed to the dumpsite  as shown in Figures 2, 3, and 4. The observed variations are attributable to the leachate emanated from the garbage in the dumpsite. Table 1 shows the inferred bulk resistivity values and their layers as well as the corresponding water resistivities. Table 1 also shows the bulk and fluid conductivities of the penetrated layers and the borehole depths in the study area.Table 1
Summary of measured geoelectric parameters and depths of boreholes used as constraints in the study area.
Location
Bulk resistivity (Ωm)
Water resistivity (Ωm)
Bulk conductivity (Ω−1m−1)
Water conductivity (Ω−1m−1)
depth (m)
Boreholedepth (m)
ρ
b
1
ρ
b
2
ρ
b
3
ρ
1
w
ρ
2
w
ρ
3
w
σ
b
1
σ
b
2
σ
b
3
σ
1
w
σ
2
w
σ
3
w
d
1
d
2
Agric. secretariat [A]
169.4
159.1
17.7
14.8
14.1
5.9
0.0059
0.0063
0.1695
0.067
0.071
0.0709
0.8
76.7
78.0
IK. Club [B]
74.5
210.6
38.4
10.9
13.3
9.9
0.0134
0.0047
0.10101
0.092
0.075
0.0752
2.4
39.1
85.0
Local. G. Areasecretariat [C]
52.3
280.5
11.6
15.1
11.5
6.7
0.0191
0.0036
0.14925
0.066
0.087
0.0867
4.1
11.4
58.6
Queen street
68.5
260.1
836.9
11.9
11.9
26.0
0.0146
0.0038
0.03846
0.084
0.084
0.0840
3.9
14.9
—
FRS office [D]
1551.9
2504.6
1148.2
39.9
29.9
12.6
0.0006
0.0004
0.00090
0.025
0.033
0.0334
3.3
110.5
95.0
FCMB [F]
1826.8
97.9
973.9
43.9
35.6
28.2
0.0005
0.0102
0.07752
0.023
0.028
0.0280
3.6
40.1
68.9
Theological college [I]
736.1
670.7
2230.4
14.9
18.4
12.9
0.0014
0.0015
0.00045
0.065
0.054
0.0543
4.6
59.4
54.0
IK. hospital [E]
141.3
2450.3
470.0
12.9
16.6
19.4
0.0071
0.0004
0.04367
0.078
0.060
0.0602
2.0
91.8
75.0
Akwa savings and loans [G]
220.4
1905.2
789.7
11.6
22.9
22.9
0.0045
0.0005
0.04367
0.086
0.043
0.0437
4.9
117.5
80.0
Fire service station [H]
744.1
500.3
900.2
14.9
23.7
26.8
0.0013
0.0020
0.0011
0.067
0.042
0.0709
5.3
38.1
52.5Figure 2
Typical VES curves and modelled results obtained along A-A1 profile (A Agric. secretariat, B IK. club, and C Local G. Area secretariat).Figure 3
Typical VES curves and modelled results obtained along B-B1 profile (D FRS Office, E Ik. Club and F FCMB).Figure 4
Typical VES curves and modelled results obtained along C-C1 profile (G Akwa Savings & Loans  H  Fire service station and I Theological College).Resistivity cross sections were constructed for each of the transects with the aid of  Surfer  Golden Software Inc., USA, by combining the inverted results of the Schlumberger soundings as shown in Figures5, 6, and 7. To construct the resistivity cross sections, the inverted electrical resistivities were sampled with depths. The vertical variation in electrical resistivity with depth was gridded using the kriging gridding technique available in the Surfer package [25]. The interpolated electrical resistivities were imaged along the profile.Figure 5
Resistivity cross section along a profile from Agric. secretariat to Local G. Area Secretariat (A-A1).Figure 6
Resistivity cross section along a profile from FRS Office to FCMB (B-B1).Figure 7
Resistivity cross section along a profile from Agric. secretariat to Local G. Area    Secretariat (C-C1).


## 6.1. Geophysical Data Analysis and Results

Smoothing of field data by manual plotting on a bilogarithmic graph for curve matching and computer modelling of the result from manual plotting were employed in the reduction of field data [18–20] to their equivalent geological models. Transformation of the measured apparent resistance Ra to their corresponding apparent resistivity ρa  was achieved using (1). The manual procedure involves plotting the computed apparent resistivity data on a bilogarithmic graph and, where necessary, the curves generated were smoothened to remove the effects of lateral inhomogeneities and other forms of noisy signatures in the smoothened curve were attributed to vertical variation of electrical resistivity with depth. The smoothened curves were quantitatively interpreted in terms of true resistivity and thickness by a conventional manual curve matching procedure using master curves and auxiliary chart [18, 21]. The conventional curves  and auxiliary charts (theoretical curves)  used in the interpretation  aided in obtaining a good fit between the observed field curves and the theoretical curves during total and partial matching. Software programs were later used to improve upon the manually interpreted results. Since the data were acquired at different times, several VES modelling Software programs including Resist [22], Ato [23], and Res1D [24] were used in modelling the data and the results were later transformed to their equivalent geological models. The primary layer parameters comprising resistivity, thicknesses, and depths obtained from the manual interpretation stage were keyed as inputs into some of the computer modelling Software programs (Resist and Res1D only). The computer Software used these parameters to generate data for the estimated model and compared the computed data with their measured counterpart. The extent of fit between the calculated and the measured data sets was assessed using the root mean square error (RMS) technique in which 10% was set as the maximum accepted value. Representative examples of modelled VES curves obtained within the dumpsite and its environs after the smoothing and modelling exercises are shown in Figures 2, 3, and 4 for the three transects considered. For VES far from the dumpsite, a good correlation was observed between the electrical resistivity derived 1D subsurface model and the geology model, while some disconformities  were noticed in VES closed to the dumpsite  as shown in Figures 2, 3, and 4. The observed variations are attributable to the leachate emanated from the garbage in the dumpsite. Table 1 shows the inferred bulk resistivity values and their layers as well as the corresponding water resistivities. Table 1 also shows the bulk and fluid conductivities of the penetrated layers and the borehole depths in the study area.Table 1
Summary of measured geoelectric parameters and depths of boreholes used as constraints in the study area.
Location
Bulk resistivity (Ωm)
Water resistivity (Ωm)
Bulk conductivity (Ω−1m−1)
Water conductivity (Ω−1m−1)
depth (m)
Boreholedepth (m)
ρ
b
1
ρ
b
2
ρ
b
3
ρ
1
w
ρ
2
w
ρ
3
w
σ
b
1
σ
b
2
σ
b
3
σ
1
w
σ
2
w
σ
3
w
d
1
d
2
Agric. secretariat [A]
169.4
159.1
17.7
14.8
14.1
5.9
0.0059
0.0063
0.1695
0.067
0.071
0.0709
0.8
76.7
78.0
IK. Club [B]
74.5
210.6
38.4
10.9
13.3
9.9
0.0134
0.0047
0.10101
0.092
0.075
0.0752
2.4
39.1
85.0
Local. G. Areasecretariat [C]
52.3
280.5
11.6
15.1
11.5
6.7
0.0191
0.0036
0.14925
0.066
0.087
0.0867
4.1
11.4
58.6
Queen street
68.5
260.1
836.9
11.9
11.9
26.0
0.0146
0.0038
0.03846
0.084
0.084
0.0840
3.9
14.9
—
FRS office [D]
1551.9
2504.6
1148.2
39.9
29.9
12.6
0.0006
0.0004
0.00090
0.025
0.033
0.0334
3.3
110.5
95.0
FCMB [F]
1826.8
97.9
973.9
43.9
35.6
28.2
0.0005
0.0102
0.07752
0.023
0.028
0.0280
3.6
40.1
68.9
Theological college [I]
736.1
670.7
2230.4
14.9
18.4
12.9
0.0014
0.0015
0.00045
0.065
0.054
0.0543
4.6
59.4
54.0
IK. hospital [E]
141.3
2450.3
470.0
12.9
16.6
19.4
0.0071
0.0004
0.04367
0.078
0.060
0.0602
2.0
91.8
75.0
Akwa savings and loans [G]
220.4
1905.2
789.7
11.6
22.9
22.9
0.0045
0.0005
0.04367
0.086
0.043
0.0437
4.9
117.5
80.0
Fire service station [H]
744.1
500.3
900.2
14.9
23.7
26.8
0.0013
0.0020
0.0011
0.067
0.042
0.0709
5.3
38.1
52.5Figure 2
Typical VES curves and modelled results obtained along A-A1 profile (A Agric. secretariat, B IK. club, and C Local G. Area secretariat).Figure 3
Typical VES curves and modelled results obtained along B-B1 profile (D FRS Office, E Ik. Club and F FCMB).Figure 4
Typical VES curves and modelled results obtained along C-C1 profile (G Akwa Savings & Loans  H  Fire service station and I Theological College).Resistivity cross sections were constructed for each of the transects with the aid of  Surfer  Golden Software Inc., USA, by combining the inverted results of the Schlumberger soundings as shown in Figures5, 6, and 7. To construct the resistivity cross sections, the inverted electrical resistivities were sampled with depths. The vertical variation in electrical resistivity with depth was gridded using the kriging gridding technique available in the Surfer package [25]. The interpolated electrical resistivities were imaged along the profile.Figure 5
Resistivity cross section along a profile from Agric. secretariat to Local G. Area Secretariat (A-A1).Figure 6
Resistivity cross section along a profile from FRS Office to FCMB (B-B1).Figure 7
Resistivity cross section along a profile from Agric. secretariat to Local G. Area    Secretariat (C-C1).


## 7. Interpretation and Discussion of VES Results

The VES results from the study area are generally characterised with high and low conductivities at various depths and locations (see Figures2, 3, and 4). This is conveyed in the geoelectric cross sections that strategically show zones that have high resistivity (low conductivity) and zones that have low resistivity (high conductivity) (see Figures 5, 6, and 7). The conductive zones have geologic formations that are associated with leachate contaminations.   Figure 5 (A-A1 profile) shows on the average transitions of resistivity variations from resistive zone to conductive zone. The resistivity increases diagonally downward from Agric. Secretariat (closed to dumpsite) to the Local G. Area Secretariat (away from dumpsite). Similarly, conductivity increases diagonally from the deeper layer of VES at the Local G. Area Secretariat to the surficial layer at the Agric. Secretariat. The observation in this profile explains the effect of massive percolation of tissue fluid (leachate) into the subsurface within the dumpsite environment. The borehole water at Agric. Secretariat appears to be influenced by fluid emanated from garbage dumped in the dumpsite. The distribution of the bulk and fluid conductivities as shown in the Table 1 changes from place to place and within the depths penetrated in the profile. In Figure 6 (profile B-B1) of resistivity cross section, the resistivity increases with depth at the various VES points except at FCMB where resistivity inversion is noticed at the second layer of the transition. Combining all the VES, the resistivity cross section traversing B-B1 profile shows higher resistivity which implies low conductivity at higher depths.  In Figure 7, the resistivity cross section traversing C-C1 profile shows, in average, higher values within the southwest-northeast diagonal trend. In this resistivity image cross section, three transitions are generally noticed. These are highly resistive, moderately resistive, and mildly conductive zones. Generally, for A-A1 profile which is nearer to the dumpsite the sampled depths appear to be conductive (less resistive) ranging from the topmost layer of Agric. secretariat-nearest to the dumpsite, to the deepest layer of Local G. Secretariat farther away from the dumpsite. This implies that the conductive tissue fluid from the dumpsite leaches the subsurface within its axis diagonally, from top to bottom. This is the reason for the observed trend in the resistivity image cross section of A-A1 profile. For B-B1 and C-C1 profiles which are about 1 km away from the dumpsite, resistivity inversion occurs as resistivity on the average increases with depth due to the assumed normal compaction or lithification of sediments at deeper depth of burial.


## 8. Interpretation of Water Resistivity and Bulk Resistivity Interactions

Water and bulk resistivities determined in Table1 were plotted as shown in the crossplots of Figures 8, 9, and 10 for first, second, and third layers, respectively. The plots generated site dependent generalised model given in the following:
(3)y=Aebx,
where y and x represent the water resistivity and bulk resistivity, respectively. A and b in (3) are site  dependent constants. The water resistivity y increases exponentially with bulk resistivity x. Specifically, A is the threshold or ambient water resistivity, which depends on the artificially induced conductivity of pore fluid of the layer considered. The parameter b is the fluid-soil matrix mixing dimensionless constant which depends on the bulk conductivity and the overall formation factor, the ratio of bulk resistivity to water resistivity of the medium. From the first layer, the equation generated in Figure 8 has the values A=11.183 Ωm and b=0.0007. These values, respectively, signify the inferred ambient water resistivity and fluid-soil matrix mixing constant for layer one. Similarly, for the second and third layers, A and b are, respectively, 11.3290 Ωm and 0.0005 and 7.6938 Ωm and 0.0007. The observed values on the average show that layers one and two are similar in terms of the ambient water resistivities and fluid-soil matrix mixing constants. However, while b  for the third layer conforms to the first two layers, A deviates significantly. Although the degree of mixing is approximately the same due to similarity in geologic formations, there is alteration in the threshold artificially induced water conductivity, on the average, from 0.0888 to 0.1300 Siemens between layer one and layer three. From this range, the artificially induced fluid that influences the natural conductivity is more significant on the deeper layers than the surficial layers. This could be attributable to the continuous accumulation of leachate that drains or leaches downwards from the topmost layer to the deeper layer. The observed unconformity of the resistivity image cross section to the borehole information obtained when the borehole was drilled is an indication of the effect of leachate on the sandy formations and within the layers of the subsurface. Since the aquifer protecting layer’s longitudinal conductance S (the ratio of top layer thickness to top layer resistivity) is generally less than 1Ω-1 (i.e., S≪1Ω-1), as observed from Table 1 for all the VES locations, the aquifers are poorly protected generally. The underlying layers also have S values that are  less than 1 and this paves the way for the conductive contaminated fluid from  the dumpsite  to  drain into the subsurface thereby affecting the  threshold natural resistivity or conductivity in the deeper layers.Figure 8
A graph of first layer water resistivity against bulk resistivity.Figure 9
A graph of second layer water resistivity against bulk resistivity.Figure 10
A graph of third layer water resistivity against bulk resistivity.


## 9. Interpretation of Physicochemical Properties of the Groundwater Samples Measured from the Study Area

The  parameters measured in the study area include pH, EC (μS/cm), and temperature (°C), for physical parameters  and Na+, K+, Ca2+, Mg2+, Fe2+, Cl−, SO42-, HCO3-, PO43-, NO3-, F−, As, Mn,  and Cu2+ all measured in (Mg/L) for hydrochemical parameters (see Table 2). The mean value for each of the parameters detectable was calculated except for ions that were below detectable limit (BDL). The mean values for ions were compared with the WHO standard values available. The available WHO standard conforms to some ions except K+ > 2.0, Mg2+> 1.0, F− > 0.01, Mn > 0.01, and Cu2+ > 0.01 Mg/L which are beyond the acceptable   WHO standard for drinking water. The high values of the above ions within the   dumpsite and its vicinity in Table 2, could be due to the hydrolysis and the resulting leaching from the contaminated sources. Hydrolysis and consequent leaching leads to the precipitation of the above ion species in water sample used. Correlation in Table 3 shows that though most of the ions are higher than the WHO standard, correlation indices between the anion and cation are significantly low. This implies that the concentration of the paired ions in Table 3 is insignificant in the water sample. In all the water samples chemically analysed, carbonate (CO32-) was below detection level (BDL). This further confirms that the dumpsite and its environs are devoid of normal carbonate-rich compounds. However, the availability of bicarbonate (HCO3-) up to 172 Mg/L suggests the dissolution of carbonates and reaction of silicates with carbonic acid which results in high concentration of HCO3- in the water samples obtained from the study.  Although the concentration of Ca2+ is low, the high value of Mg2+ suggests that the water samples within the dumpsite and its vicinity may be temporarily hard due to the possibility of formation of Mg(HCO3)2(aq).Table 2
Summary of measured hydrochemical and some physical parameters for water sample used.
S/N
Location
Temp.T  (°C)
pH
Cond.(µS/cm)
Na
+ (Mg/L)
K
+ (Mg/L)
Ca+ (Mg/L)
Mg+ (Mg/L)
Fe+ (Mg/L)
SO
4
2
- (Mg/L)
Cl− (Mg/L)
PO
4
3
-
(Mg/L)
CO
3
2
-
(Mg/L)
HCO
3
-
(Mg/L)
NO
3
- (Mg/L)
F− (Mg/L)
Mn (Mg/L)
As (Mg/L)
Cu (Mg/L)
BH1
IK. hospital
29.7
6.9
67
6.9
2.1
11.6
1.8
0.04
1.0
22.9
0.8
BDL
245
3.9
0.3
0.003
0.01
0.10
BH2
FRS office
28.6
7.6
88
7.8
4.0
3.0
2.0
0.11
6.0
17.9
1.2
BDL
156
1.9
0.7
0.004
0.01
1.20
BH3
IK. club
29.2
8.1
1183
11.9
18.5
15.9
3.5
0.03
1.0
76.9
2.1
BDL
209
41.0
0.4
0.001
0.01
0.08
BH4
Local. G. Area  secretariat
28.8
8.2
96
7.9
0.6
9.9
0.8
0.05
1.2
47.0
2.0
BDL
80
1.7
0.3
0.006
0.01
0.01
BH5
Akwa savings and Loans
29.0
7.5
34
4.9
1.9
7.2
0.4
0.07
3.0
58.9
1.3
BDL
215
1.8
0.6
0.003
0.01
0.01
BH6
FCMB
27.9
6.5
65
5.0
3.0
5.4
5.6
0.01
2.0
43.7
1.3
BDL
240
1.3
0.3
0.002
0.01
0.01
BH7
Theological college
29.8
6.7
77
6.5
1.7
3.9
2.3
0.09
3.2
30.9
0.9
BDL
221
4.6
0.5
0.007
0.01
0.08
BH8
Fire service station
28.9
7.8
129
8.1
2.5
9.0
3.5
0.06
2.0
55.6
1.5
BDL
171
34.0
0.3
1.001
0.01
0.06
BH9
Queen street
27.9
7.4
45
4.3
3.7
0.9
5.1
0.03
7.0
34.9
1.1
BDL
100
1.6
0.4
0.008
0.01
0.03
BH10
Agric secretariat
29.5
8.5
509
8.9
0.9
1.5
5.9
0.06
3.6
66.8
2.2
BDL
80
42.0
0.5
1.001
0.01
0.05
Minimum
27.9
6.7
34
4.9
0.6
0.9
0.4
0.01
1.0
17.9
0.8
BDL
80
1.3
0.3
0.001
0.01
0.01
Maximum
29.8
8.2
1183
11.9
18.5
15.9
5.9
0.11
7.0
76.9
2.2
BDL
240
42.0
0.7
1.002
0.01
1.20
Range
27.9–29.8
6.7–8.5
34–1183
4.9–11.9
0.6–18.5
0.9–15.3
0.4–5.9
0.01–0.11
1.0–7.0
17.9–76.9
0.8–2.2
BDL
80–240
1.3–42.0
0.3–0.7
0.001–1.002
0.01–0.01
0.01–1.20
Mean
28.9
7.5
229
7.2
3.9
6.8
3.1
0.06
3.0
45.6
1.4
BDL
172
13.4
0.4
0.204
0.01
0.16
WHO standard 2006/2010
NS
6.5–8.5
1400
200
2.0
250
1.0
1.0
40.0
200
NS
NS
NS
44.0
0.01
0.01
0.01
0.01Table 3
Calculated ion pair correlation indices.
Ion pair
Inferred correlation index for ion pair
Na+-SO42-
0.17
Na+-Cl−
0.26
Mg2+-SO42-
0.06
Ca2+-Cl−
0.14
K+-SO42-
0.04
SO
4
2
--Cu2+
0.24
SO
4
2
--As
0.00
NO
3
--As
0.00In terms of the physical parameters, temperature, pH, and electrical conductivity (EC) were measured for the water samples collected within and around the dumpsite. The measured temperature values ranged from 27.8 to 29.8°C and the mean value was 28.9°C. The temperature values were found to remain approximately constant throughout the duration of the field work. This is an advantage that groundwater has over surface water.  The pH values ranged from 6.5 to 8.5 and the mean value was 7.5. The mean pH value result suggests that the water quality is close to neutrality level with values varying from 6.7 to 8.5. These values fall within WHO acceptable standard range of 6.5–8.5 [26]. The slightly acidic nature of the water can be attributed to the dissolution and draining of decomposed vegetative materials and other biodegradable wastes from dumping refuse and its surroundings by runoff that are in hydraulic connection with the local groundwater system [27, 28]. The water conductivity ranged from 34 to 1183 µS/cm. The average value was 229 µ/cm. The relatively high values obtained at some locations are symptomatic of the abundance of free ions in the water which could be attributed to the existence of equilibrium between the water and the soluble leachate-loaded contamination plume that dissolves into the soil [29]. The conductivity values are below the WHO standard value of 1,400 µS/cm [30]. Despite the known dependence of EC on the mobility of free ions in the water, the EC of the water also depends on the amount of dissolved substances in the water. Several researchers including [31, 32] have discussed the influence of EC on water quality. Ordinarily, the EC will be low for good quality water with low total dissolved solids (TDS). Thus, high aquifer resistivities can be delineated with areas with low TDS. The relatively high concentration of K+, Mg2+, F−, Mn, and Cu2+ in the repository of groundwater can also be due to tectonically induced secondary structures like, divide, fault lineament, and fold within the sedimentary facies which jointly creates rooms for the leaching, precipitation, and their dissolution in the subsurface water [33]. These secondary structures also create room for the multiple aquifer units in the study area.


## 10. Conclusions

In the course of using integrated approach to investigate the effect of leachate on ground water repository of Ikot Ekpene dumpsite in Akwa Ibom State, Nigeria, the study area, information generated from vertical electrical sounding, geological and hydrogeochemical techniques have been integrated and used in mapping shallow subsurface electrostratigraphy. The results aided in identifying the aquiferous horizons and their geometry and assessing the effects of leachate on the groundwater within the axis of Ikot Ekpene dumpsite. From the primary geoelectrical parameters inferred, aquifers are generally open or unconfined in the area. They are anisotropic and localized in both lateral and vertical extents. The electrical resistivity values of the aquiferous horizon were observed to be lower (<300 Ωm) in the VES data close to the dumpsite (profile A-A1) and relatively higher than those VES away from the dumpsite (profiles B-B1 and C-C1) in the study area. Thus, the distribution of water conductivity in the area as shown in Table 1 follows the resistivity pattern.  The interpretation of resistivity data and its inferred section in profile A-A1 shows that the conductive fluid from the dumpsite has dominant effect on the subsurface for VES data closer to the dumpsite than those VES data relatively farther away from it. The effect is eminent as it is shown in the diagonal pattern of flow from top to bottom. For profiles B-B1 and C-C1 which are farther away from the dumpsite, the resistivity seems on the average to be increased downward as it is expected in a normal situation where variations in resistivity with depth of burial are only due to lithologic differentiation caused by age and cementation or compaction. From the resistivity data analysis and the pore water measurement, water resistivity increases exponentially with bulk resistivity in the different layers of the subsurface sampled. The threshold or ambient water resistivity depends on the artificially induced conductivity of pore fluid for the layers considered.  The high range of water conductivity (34–1183 µS/cm) in the borehole is attributable to the unequal draining of the subsurface by the conductive leachate-loaded plume which decreases with increasing distance from the dumpsite location. The parameters realised from the model generated from bulk and water resistivity can be used to explain the extent of dissolution of leachate in water repositories within and away from the dumpsite.Hydrochemical results show that repository of groundwater contains little or noCO32-. However, the subsurface is enriched with HCO3- due to the reaction of silicates with carbonic acid which results in the high concentration of HCO3- in groundwater in all the geologic formations. Although some ions were below the available WHO standards, some were above the acceptable standard. The high values of some hydrochemical species can be attributed to the dissolution and precipitation of the leachate-loaded contamination plume within the subsoil. This and other   tectonically induced secondary structures like divide, fault lineament, and fold within the sedimentary facies cause wide variations in resistivities and conductivities within the subsurface of the study area. In effect, this influences the resistivity and conductivity of groundwater in the study area. The chemical, physical, and geostatistical parameters generated in this work can be used in monitoring the water quality within the vicinity of the dumpsite from time to time.



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*Source: 174589-2014-01-28.xml*