The technique of vertical electrical sounding (VES) is used here to evaluate the influence of several geoelectrical parameters of reflection coefficient (RC), fractured constant (FC), anisotropy (λ) of the subsurface hydrogeological layers and protecting layers (hOverb) which affect the overburden protective capacity (OPC) of the Quaternary aquifer in the Khanasser Valley region, Northern Syria. RC varies between a minimum of −0.89 and a maximum of 0.92 with an average of −0.28. FC varies between a minimum of 0.057 and a maximum of 25 with an average of 1.89. λ varies between a minimum of 0.72 and a maximum of 2.31 with an average of 1.24. The overburden-protecting layer (hOverb) varies between a minimum of 1.1 m and a maximum of 28.9 m with an average of 5.36 m. OPC varies between a minimum of 0.01 Ω−1 and a maximum of 13.75 Ω−1 with an average of 0.94 Ω−1. The statistical correlation matrix computed for those parameters highlights the mutual relationships between them. Different empirical equations are consequently established between the mentioned treated parameters and the OPC one. Three different trends of negative exponential function are revealed between anisotropy λ and OPC, indicating the presence of different hydraulic systems. The alteration sequence of impermeable and permeable layers as proven by the available lithological descriptions control the mentioned parameters and their values. The presence of sufficiently thick overburden impermeable layer helps in protecting the Quaternary aquifer from the surficial contamination, and acts as a natural filter slowing and retarding the fluid percolation. The approach developed in this paper with its different established empirical relationships is applied for the first time in Syria, and can be easily undertaken worldwide to assess the different conditions controlling the aquifers protectivity.

  • A new VES approach is proposed to evaluate the hydrogeophysical characteristics of Quaternary aquifer in Khanasser region, Northern Syria.

  • Overburden protective capacity (OPC) of the Quaternary aquifer is discussed and documented.

  • the influence of reflection coefficient (RC), fractured constant (FC), anisotropy (λ) of the subsurface hydrogeological layers, and protecting layers (hOverb), affecting the (OPC) are evaluated.

  • Statistical correlation matrix is computed to describe the mutual relationships between RC, F,C, λ, hOverb and OPC.

  • The approach developed can be easily undertaken worldwide to assess the different conditions controlling the aquifers protectivity.

The groundwater contained beneath the Earth's surface in rocks and soil and stored underground in aquifers is subjected to the contamination of the surface (Ikpe et al. 2021). The groundwater quality can be negatively affected by anthropogenic activities such as poor waste disposal management, which leads to leakages from the surface and underground storage tanks, sewage from oil spillage, mining activities and latrines and the movement of leachates from dumpsites into subsurface hydrogeological units (Oseji et al. 2018).

The hydrogeological aquifer system can be subsequently protected by the above overlying earth layers depending on their thicknesses, hydraulic conductivities and permeabilities. The aquifer protectivity in such a case can measure the aquifer overburden layers to behave as natural boundaries to filter percolating surface contaminated fluid (Adeniji et al. 2014). The major factors affecting the protectivity of the underlying hydrogeological aquifer are essentially thickness, porosity, grain size and permeability of the overburden-protecting layers (Mogaji et al. 2011; Adeniji et al. 2014; Ekanem 2020; Ekanem et al. 2020; Ikpe et al. 2021).

The permeable overlying layers, such as gravels and sand having high hydraulic conductivity and high resistivity, facilitate the easy movement and infiltration of surface fluid contaminants into the aquifer system. On the contrary, the impervious overburden units such as shale and clay slow and retard the rate of infiltration of surface contaminants into the subsurface, due to their low hydraulic conductivity and low resistivity, where the protectivity aquifer is considerably enhanced (Adeniji et al. 2014; Ayuk 2019; Ekanem et al. 2021).

The one-dimensional (1D) VES resistivity sounding data interpretation allows us to obtain the thicknesses and real resistivities of the subsurface lithological units penetrated by the electrical current passage under each VES point. The parameters of thicknesses and real resistivities are thereafter used to estimate the secondary geoelectric indice parameters (SGIP). The analysis of the SGIP of longitudinal conductance, reflection coefficient (RC), fractured constant (FC) and anisotropy coefficient is important in qualifying the aquifer protectivity and characterizing the aquifer overburden layers.

The total longitudinal conductance of the aquifer-protecting layers is proportional to aquifer protectivity (Abiola et al. 2009; Asfahani 2023).

The impervious materials’ overburden layers characterized by a total longitudinal conductance greater than one have good/excellent protectivity characteristics. On the contrary, the previous overburden layers, characterized by a total longitudinal conductance of less than 0.1, have poor/weak protection characteristics to the underlying aquifer systems.

An impermeable low-resistivity layer, such as shale or clay overlying a permeable layer of high resistivity, such as gravels and sands, yields a positive reflection resistivity coefficient, which can be used to determine the protectivity of aquifer systems. Positive values of reflection resistivity coefficient indicate good/excellent protectivity and vice versa.

The FC is big as much as the overburden-protecting impervious layer resistivity is low, where an inverse relationship exists between them.

The resistivity anisotropy coefficient (λ) of bigger than 1 indicates the materials’ resistivity variations according to the directions (Asfahani 2007, 2023; Yeboah-Forson & Whitman 2013). A sand–clay intercalation sequence can create such an anisotropy phenomenon, particularly in sedimentological environments (Asfahani 2007, 2023; Bala & Cichy 2015). λ coefficient can be, therefore, used as one of the important parameters affecting the aquifer protectivity and is related directly to the infiltration of surface water into the subsurface.

The overburden protective capacity (OPC, Ω−1) of the Quaternary aquifer in the Khanasser Valley, Northern Syria has recently been assessed by analyzing the protecting layers and their longitudinal conductance of (Ω−1) according to the classification of Henriet (1976); Asfahani (2023).

This paper concentrates basically on studying and analyzing the influence of several geoelectrical parameters affecting the aquifer protectivity and the OPC. A statistical correlation matrix is applied to evaluate the different mutual relationships between OPC and the treated geoelectrical parameters. Those parameters are overburden thickness (hOverb), RC, FC and anisotropy coefficient (λ) of the subsurface hydrogeological layers.

Khanasser Valley is approximately 70 km southeast of Aleppo City and is located between two hills, Jabal Al Hoss in the west and Jabal Shbeith in the east (Figure 1). The drain of the northern and southern parts of the valley is toward Jaboul salt lake and the Adami depression respectively, as indicated in Figures 1 and 2.
Figure 1

Location of the Khanasser Valley study area, Northern Syria.

Figure 1

Location of the Khanasser Valley study area, Northern Syria.

Close modal
Figure 2

Geological map of the Khanasser Valley and its surroundings (after Ponikarov 1964), with the sounding VES points.

Figure 2

Geological map of the Khanasser Valley and its surroundings (after Ponikarov 1964), with the sounding VES points.

Close modal

In the Khanasser Valley, three main aquifers are used for groundwater extraction and the deepest one is the upper Cretaceous, located at 400 m under the ground level. The second low-productive aquifer of Paleocene-Lower Eocene limestone is found above the Maastrichtian (ACSAD 1984). The average hydraulic conductivity (k) of this aquifer is 0.0054 m/day (Schweers et al. 2002). The Paleogene strata of around 50 m of Paleocene and lower Eocene in the central part of the Khanasser valley are not sufficiently thick over the Maestrichtian formation. The Quaternary aquifer, the most transmissive structure in the study region, is located near the surface and covered by proluvial and alluvial sediments of about 10 m. The main direct recharge of this aquifer is provided by the rainwater, the infiltrating runoff and the subsurface flow from the Jabal Shbeith and Jabal Al Hoss slopes.

Resistivity survey

The geoelectrical vertical electrical sounding (VES) technique adopting the Schlumberger array (Figure 3) was applied to sample the resistivity distributions of the subsurface using the Indian resistivity meter (ACR1 G-unit) and its accessories. The injection of the electric current into the subsurface was carried out by planting two current electrodes, A and B, on the Earth's surface, while two planted potential electrodes, M and N, at the surface were used to measure the generated potential difference. The four current and potential electrodes in line were connected to the resistivity meter whose output display gave directly the apparent resistance (ΔV/I) of the earth layers penetrated by the electric current.
Figure 3

Schlumberger array in the field.

Figure 3

Schlumberger array in the field.

Close modal

The Schlumberger electrode configuration gradually increases the current electrode distance separation of AB and occasionally separates the potential electrode distance MN about the centre of the configuration to penetrate deeper layers and complete the field VES resistivity curve. AB/2 is ranged between 3 and 500 m, while MN is ranged between 0.5 and 20 m. The electrode spacing in all the VES sounding points was such as AB5 MN in accordance with the potential gradient assumption (Keller & Frischknecht 1966; Dobrin & Savit 1988).

Thirty-four VES sounding points were carried out in the study of the Khanasser area, as shown in Figure 2.

Some shallow available boreholes with their lithological descriptions close to some VES points are used to calibrate the VES sounding interpretations and help in the modeling interpretation stage of the acquired data.

Resistivity data processing

Field apparent resistivity (ρa) is computed for each VES location by multiplying the measured resistance (ΔV/I) by the corresponding geometric factor K, such as
formula
(1)
K for the Schlumberger configuration is given by Equation (2) as follows:
formula
(2)
where AB and MN are the separation distances of the current electrode and potential electrode, respectively.

The field apparent resistivity values a) computed and obtained for each VES sounding location were plotted against (AB/2) on a log–log scale to produce the complete VES sounding curves.

Figure 4 shows the field set-up for acquiring the VES measurements in the Khanasser area under study.
Figure 4

Field set-up of the VES technique.

Figure 4

Field set-up of the VES technique.

Close modal
The interpretative conventional curve matching approach was first used to interpret each of the smoothened VES field resistivity curves to generate an initial model of layer resistivity and thickness of the penetrated layers by the electrical current (Zohdy et al. 1974). The initial layer model was thereafter used as an input in the software program called WINRESIST (Vander Velpen & Sporry 1993). The WINRESIST is a 1D least square inverse modeling, which makes use of the input resistivity data to generate a theoretical inverted model and then establishes a fit between this inverted model and the measured field data to give the final 1D resistivity model curves. The goodness-of-fit is expressed in terms of the root-mean-square error (RMSE) (Bandani 2011), which ranged from 2.3 to 5.5%. Figure 5(a) shows the WINRESIST window snapshot during the computation of the theoretical inverted model, while Figure 5(b) shows the corresponding VES resist graph display.
Figure 5

(a) A snapshot WINRESIST window during its application. (b) VES resist graph display.

Figure 5

(a) A snapshot WINRESIST window during its application. (b) VES resist graph display.

Close modal

This ID inversion interpretative technique allows us to get the final optimum inverted model curves with their first-order geoelectric indices, which are the true layer resistivity, thickness and depth accordingly.

Five available shallow boreholes with their lithological descriptions in the Khanasser area were used to constrain the inversion schema.

The overlying materials controls mainly the protectivity of a given hydrogeological unit. The protectivity in this case research is the ability of the overlying layers to act as protecting layers to retard and filter percolating surface fluid (Ekanem et al. 2021). The key factors affecting the protectivity of the underlying hydrogeological units are the permeability, grain size, porosity and thickness of the protecting layers (Mogaji et al. 2011; Adeniji et al. 2014; Ekanem 2020; Ekanem et al. 2021). In fact, sufficient impermeable and thick overlying protecting layers with low hydraulic conductivity contribute largely to retarding the infiltration of water into the subsurface and hence improve the aquifer system protectivity (Adeniji et al. 2014; Ekanem et al. 2021).

The overburden layer resistivity and thickness are the two basic primary geoelectric parameters that can be used conjointly according to (Henriet 1976) to evaluate the longitudinal conductance (Ω−1), which is proportional to the aquifer protectivity (Henriet 1976; Abiola et al. 2009; Asfahani 2023).

The total longitudinal conductance for a stack of n layers covering an aquifer is given by Asfahani (2023) as
formula
(3)

The resistivity RC, the FC and the anisotropy coefficient (λ) are three main geoelectrical parameters that take into consideration the resistivity variations between the aquifer layer and its overlying protecting layers. The main targeting objective of this paper is to establish the mutual empirical relationships between those parameters and aquifer protectivity (OPC).

Reflection coefficient

RC is computed according to Equation (4) (Ibuot et al. 2019; Asfahani 2021).
formula
(4)
where ρn is the resistivity of the Quaternary aquifer in the Khanasser valley and ρn−1 is the overlaying layer resistivity (Ibuot et al. 2019; Asfahani 2021). RC can have positive or negative values depending on the mutual resistivities of the aquifer and overlying layers. When the overlying layer resistivity is greater than the lower layer resistivity, RC has a negative value, while the reverse is the case. Consequently, negative values of RC will be obtained when a high-resistivity permeable gravel and sand overlay a low resistivity of a clay and shale impermeable layer. Thus, negative RC values are a good indicator of a permeable and impermeable earth layers sequence, which retards and slows the water infiltration rate for protecting any underlying hydrogeological units.

Fractured contrast

FC is computed according to Equation (5) (Ibuot et al. 2019; Asfahani 2021).
formula
(5)

FC is inversely proportional to the overburden resistivity (ρn−1). The impervious shale and clay with low-resistivity values contribute to increasing FC.

Anisotropy coefficient (λ)

λ is evaluated by knowing the total transverse resistivity (ρt) and the total longitudinal resistivity (ρl) of the subsurface hydrogeological units penetrated by the electrical current passage (Asfahani 2023).

λ is, therefore, expressed as
formula
(6)
The transverse resistivity (ρt) and longitudinal resistivity (ρl) are expressed by Equations (7) and (8), respectively.
formula
(7)
formula
(8)
where ρi and hi are the layer resistivity and thickness of the ith layer in the treated hydrological section, respectively.

The permeable gravels and sands have high-resistivity values and low longitudinal conductance values. On the contrary, the impervious clay and shale have high longitudinal conductance and low-resistivity values (Adeniji et al. 2014; Ayuk 2019). The materials characterized by high values of longitudinal conductance greater than 1 are accompanied by good/excellent protectivity, while those characterized by longitudinal conductance of less than 0.1 are accompanied generally by poor/weak aquifer protectivity (Henriet 1976; Abiola et al. 2009; Asfahani 2023).

The anisotropy can be regarded as a result of a thin sequence of sand–clay intercalation (Asfahani 2007, 2023; Bala & Cichy 2015; Ekanem 2020).

The 34 points of VES sounding points measured in the study of the Khanasser Valley region, Northern Syria by using the Schlumberger array were quantitatively interpreted in terms of 1D structure, where the real thicknesses and resistivities of the corresponding layers were obtained. Different geoelectrical curves were observed, which attest to the non-uniformity of the research study area. Those geoelectrical curves are QH (32%), HH (26%), KHKH (5.88%), H (8.82%), KH (5.88%), HK (5.88%), HAK (5.88%), HKH (2.94%), QHKH (2.94%) and QQH (2.94%) as indicated by Figure 6.
Figure 6

Frequency distribution of the geoelectrical curves in the Khanasser Valley region.

Figure 6

Frequency distribution of the geoelectrical curves in the Khanasser Valley region.

Close modal
Figure 7 shows the quantitative interpretation (1D) of the VES at V6-3 point of HH geoelectrical curve type, with a comparison with the available lithological description of well No.108 located closely to this V6-3 point. The rammel aswad composed of sand and alluvial gravels in the study region is the source of the shallow Quaternary aquifer, where its high thickness offers high yields and transmissivity. The brutal change in the well's productivity and yields in the study region even in very short distances is due to brutal changes of rammel aswad from one place to another vertically and laterally (Asfahani 2016).
Figure 7

Quantitative VES interpretation of V6-3 point with a comparison with lithology of Well No: 108.

Figure 7

Quantitative VES interpretation of V6-3 point with a comparison with lithology of Well No: 108.

Close modal
The protectivity of the Quaternary aquifer in the Khanasser Valley region has been already analyzed and documented through the parameter of OPC (Asfahani 2023). OPC(Ω−1) has been already determined by analyzing the longitudinal conductance of the overburden-protecting layers (Ω−1) according to the classification of Henriet (1976) and by using the following equation:
formula
(9)
where hi is the thickness and ρi is the resistivity of each covering layer.
It was found that OPC(Ω−1) is classified as 56% poor, indicating high vulnerability to the contamination, 5.9% weak, 14.7% moderate, 20.6% good and 2.9% excellent (Asfahani 2023). This paper concentrates mainly on analyzing and studying the influence of several geoelectrical parameters that affect considerably the spatial distribution of the OPC. Figure 8 shows the OPC (Ω−1) obtained for the 34 VES points in the study region. The spatial variation of the OPC is shown in Figure 9 (Asfahani 2023).
Figure 8

OPC (Ω−1) characterizing the 34 VES points in the Khanasser Valley region.

Figure 8

OPC (Ω−1) characterizing the 34 VES points in the Khanasser Valley region.

Close modal
Figure 9

The spatial variations of OPC of the Quaternary aquifer in the Khanasser Valley region (Asfahani 2023).

Figure 9

The spatial variations of OPC of the Quaternary aquifer in the Khanasser Valley region (Asfahani 2023).

Close modal

Table 1 includes the resulting geoelectrical parameters of the RC, FC, anisotropy of the subsurface hydrogeological layers (λ) and the overburden-protecting layers (hOverb).

Table 1

Result interpretations of the different geoelectrical parameters for the 34 VES measured points in the Khanasser Valley region, Northern Syria

Locationρn (Ω.m)ρn−1 (Ω.m)Thickness of protecting layers (m)RCFCλOPC (Ω−1)
V6-1 8.5 32.41 3.7 −0.52 0.32 1.17 0.14 
V9-3 11 34.84 3.3 −0.8 0.125 1.12 0.037 
V2-5 9.6 33.56 3.9 −0.9 0.1 1.85 0.012 
V1-1 6.5 29.88 6.5 0.60 4.1 1.13 2.48 
Sh11 30 – 22.7 0.63 4.5 1.39 3.26 
Sh12 15.5 38.1 28.9 0.43 2.5 1.37 4.57 
Sh13 32.96 1.2 −0.61 0.24 0.033 
V8-3 17 38.94 3.3 −0.6 0.25 1.1 0.05 
V3-1 10 33.95 2.8 −0.63 0.23 1.58 0.09 
V3-2 15 37.69 5.3 0.40 2.34 0.91 0.6 
V7-2 16 38.38  – – 1.07 0.37 
V7-3 16 38.38  – – 0.72 0.37 
V3-5 19 39.98 −0.64 0.22 1.26 0.057 
V5-4 14 37.04 3.5 −0.7 0.2 1.18 0.047 
V6-2 23 41.75  – – 1.07 0.76 
V10-4 12 35 3.8 −0.64 0.22 1.22 0.07 
V10-3 36.17  – – 1.07 2.5 
V10-1 10 35.23 3.5 −0.8 0.12 1.74 0.094 
V10-2 15 36.1 8.7 0.92 25 1.4 13.75 
V9-1 15 37.21 1.2 −0.2 0.71 1.25 0.006 
V9-2 4.3 32.47 4.4 −0.7 0.2 1.4 0.21 
V9-4 36.13 2.8 −0.6 0.3 1.1 0.09 
V8-2 11 37.11 4.8 −0.7 0.2 1.3 0.09 
V6-3 17 36.67 9.2 0.6 3.7 1.06 1.29 
V5-3 15 37.98 1.5 −0.4 0.45 1.03 0.045 
V5-5 36 40.29 2.4 −0.3 0.6 1.14 0.04 
V4-3 22 42.1 1.1 – – 1.03 0.01 
V3-3 15 37.43 2.1 −0.8 0.11 1.45 0.015 
V3-4 26 39.75 1.5 0.41 2.41 1.05 0.14 
V2-1 43 40.73 7.2 0.7 5.1 1.06 0.49 
V2-2 6.6 38.47 4.2 −0.39 0.44 1.07 0.23 
V2-3 38.84 6.4 −0.9 0.1 2.31 0.061 
V2-4 11.5 37.68 1.9 −0.5 0.4 1.26 0.06 
V1-2 10 34.32 4.2 −0.84 0.1 1.41 0.04 
Locationρn (Ω.m)ρn−1 (Ω.m)Thickness of protecting layers (m)RCFCλOPC (Ω−1)
V6-1 8.5 32.41 3.7 −0.52 0.32 1.17 0.14 
V9-3 11 34.84 3.3 −0.8 0.125 1.12 0.037 
V2-5 9.6 33.56 3.9 −0.9 0.1 1.85 0.012 
V1-1 6.5 29.88 6.5 0.60 4.1 1.13 2.48 
Sh11 30 – 22.7 0.63 4.5 1.39 3.26 
Sh12 15.5 38.1 28.9 0.43 2.5 1.37 4.57 
Sh13 32.96 1.2 −0.61 0.24 0.033 
V8-3 17 38.94 3.3 −0.6 0.25 1.1 0.05 
V3-1 10 33.95 2.8 −0.63 0.23 1.58 0.09 
V3-2 15 37.69 5.3 0.40 2.34 0.91 0.6 
V7-2 16 38.38  – – 1.07 0.37 
V7-3 16 38.38  – – 0.72 0.37 
V3-5 19 39.98 −0.64 0.22 1.26 0.057 
V5-4 14 37.04 3.5 −0.7 0.2 1.18 0.047 
V6-2 23 41.75  – – 1.07 0.76 
V10-4 12 35 3.8 −0.64 0.22 1.22 0.07 
V10-3 36.17  – – 1.07 2.5 
V10-1 10 35.23 3.5 −0.8 0.12 1.74 0.094 
V10-2 15 36.1 8.7 0.92 25 1.4 13.75 
V9-1 15 37.21 1.2 −0.2 0.71 1.25 0.006 
V9-2 4.3 32.47 4.4 −0.7 0.2 1.4 0.21 
V9-4 36.13 2.8 −0.6 0.3 1.1 0.09 
V8-2 11 37.11 4.8 −0.7 0.2 1.3 0.09 
V6-3 17 36.67 9.2 0.6 3.7 1.06 1.29 
V5-3 15 37.98 1.5 −0.4 0.45 1.03 0.045 
V5-5 36 40.29 2.4 −0.3 0.6 1.14 0.04 
V4-3 22 42.1 1.1 – – 1.03 0.01 
V3-3 15 37.43 2.1 −0.8 0.11 1.45 0.015 
V3-4 26 39.75 1.5 0.41 2.41 1.05 0.14 
V2-1 43 40.73 7.2 0.7 5.1 1.06 0.49 
V2-2 6.6 38.47 4.2 −0.39 0.44 1.07 0.23 
V2-3 38.84 6.4 −0.9 0.1 2.31 0.061 
V2-4 11.5 37.68 1.9 −0.5 0.4 1.26 0.06 
V1-2 10 34.32 4.2 −0.84 0.1 1.41 0.04 

The statistical correlation matrix applied, as shown in Table 2, allows us to derive and establish the mutual empirical relationships between those different geoelectrical parameters and the OPC.

Table 2

Statistical correlation matrix between the treated geoelectrical parameters in the Khanasser Valley region, Northern Syria

VariablesOPCρnρn−1RCFCλhOverb
OPC 0.07 −0.36 0.62 0.95 0.06 0.47 
ρn  −0.21 0.50 0.19 −0.27 0.23 
ρn–1   −0.75 −0.39 0.59 0.31 
RC    0.66 −0.37 0.53 
FC     −0.02 0.27 
λ      0.13 
hOverb       
VariablesOPCρnρn−1RCFCλhOverb
OPC 0.07 −0.36 0.62 0.95 0.06 0.47 
ρn  −0.21 0.50 0.19 −0.27 0.23 
ρn–1   −0.75 −0.39 0.59 0.31 
RC    0.66 −0.37 0.53 
FC     −0.02 0.27 
λ      0.13 
hOverb       

ρn indicates the resistivity of the Quaternary aquifer; ρn-1 indicates the resistivity of the overlying layer; hOverb indicates the thickness of the protecting layers.

The spatial distribution of the RC in the study region is shown in Figure 10 (Asfahani 2021).
Figure 10

Spatial variation of RC parameters in the Khanasser Valley region, Northern Syria.

Figure 10

Spatial variation of RC parameters in the Khanasser Valley region, Northern Syria.

Close modal
RC varies between a minimum of −0.89 at VES 2-5 and a maximum of 0.92 at VES 10-2, with an average of −0.28. The negative reflection values shown in the study area at the VES 5-4 indicate a high water potential weathered area (Olayinka 1996; Asfahani 2021). The unconsolidated material of sands and alluvial gravel known by the farmers of the study area as rammel aswad is the main source of the Quaternary aquifer. RC parameter is controlled by the distribution of both resistivity of the aquifer (ρn) and resistivity of the overlying layer (ρn−1), as indicated by Equation (4) (Table 1). An exponential empirical equation is found between the OPC and the RC, as indicated in Figure 11.
Figure 11

Empirical relationship between OPC and RC.

Figure 11

Empirical relationship between OPC and RC.

Close modal
This equation has the following form:
formula
(10)
FC varies between a minimum of 0.057 at VES 2-5 and a maximum of 25 at VES 10-2, with an average of 1.89, as shown in Figure 12.
Figure 12

FC of the Quaternary aquifer in the Khanasser Valley region.

Figure 12

FC of the Quaternary aquifer in the Khanasser Valley region.

Close modal
Figure 13

Empirical relationship between OPC and FC.

Figure 13

Empirical relationship between OPC and FC.

Close modal

The higher FC values are concentrated on VES 10-2 in the extreme northern part of the study area as for RC. The area with lower FC values is regarded as a good indicator of a high water potential weathered area (Olayinka 1996; Asfahani 2021).

An empirical linear equation is found between the OPC and the FC, as indicated in Figure 13.

This equation has the following form:
formula
(11)

FC is bigger as the overlying layer resistivity is low, as indicated by Equation (5).

Figure 14 shows the spatial variations of the λ anisotropy coefficient. It ranges between a minimum of 0.72 at V7-3 and a maximum of 2.31 at V2-3, with an average of 1.24 (Asfahani 2023).
Figure 14

Anisotropy coefficient (λ) variations (Asfahani 2023).

Figure 14

Anisotropy coefficient (λ) variations (Asfahani 2023).

Close modal
Although the correlation matrix carried out in this paper does not show a significant correlation between OPC and λ (0.06), the cross-plot of those two parameters indicates the presence of three negative exponential trends between them, as shown in Figure 15.
Figure 15

Empirical relationships between OPC and λ.

Figure 15

Empirical relationships between OPC and λ.

Close modal

The three empirical trends are expressed by exponential equations as follows:

Trend-1:
formula
(12)
Trend-2:
formula
(13)
Trend-3:
formula
(14)

The negative trends indicate different hydraulic systems in the Khanasser Valley region and show that as much λ is bigger as the OPC is lower.

It is to be mentioned that similar three positive trends have been already found between the anisotropy ) and the transmissivity (T) of the Quaternary aquifer (Asfahani 2023), indicating different hydraulic systems in the Khanasser Valley region. The overburden thickness (hOverb) with a sufficient thick clayey column protects the Quaternary aquifer in the study area from the contamination originating from the surface polluting fluid, where the spatial variation of this important parameter is shown in Figure 16 (Asfahani 2023).
Figure 16

Overburden thickness of the Quaternary aquifer in the Khanasser Valley region (Asfahani 2023).

Figure 16

Overburden thickness of the Quaternary aquifer in the Khanasser Valley region (Asfahani 2023).

Close modal
An empirical relationship is established between hOverb and the protectivity OPC of the Quaternary aquifer, as shown in Figure 17.
Figure 17

Empirical relationship between OPC and hOverb.

Figure 17

Empirical relationship between OPC and hOverb.

Close modal
This empirical equation has the following form:
formula
(15)

The correlation matrix shown in Table 2 indicates an acceptable correlation between hOverb and OPC (0.47). Table 3 summarizes the results of the geoelectrical parameters obtained by studying and analyzing the 34 VES points in the study region, for assessing the different parameters having their influences in affecting the protectivity of the Quaternary aquifer from the fluid contamination originating in the Khanasser Valley, Syria.

Table 3

Summary of the OPC of the Quaternary aquifer and the related geoelectrical parameters in the Khanasser Valley region, Syria

OPC (Ω−1)ρn (Ω.m)ρn–1 (Ω.m)RCFCλhOverb (m)
Min. 0.01 4.30 0.6 −0.89  0.057 0.72 1.1 
Max. 13.75 43.00 212 0.92 25 2.31 28.9 
Average 0.94 15.10 56 −0.28 1.89 1.24 5.36 
OPC (Ω−1)ρn (Ω.m)ρn–1 (Ω.m)RCFCλhOverb (m)
Min. 0.01 4.30 0.6 −0.89  0.057 0.72 1.1 
Max. 13.75 43.00 212 0.92 25 2.31 28.9 
Average 0.94 15.10 56 −0.28 1.89 1.24 5.36 

The VES technique is used in this paper to assess and evaluate the protectivity of the hydrogeological units of the Khanasser Valley region, Northern Syria. The influence of some geoelectrical variables that considerably affect the protectivity of the Quaternary aquifer in the study region is analyzed and documented.

The 34 VES points were interpreted quantitatively in terms of 1D structure by the curve matching technique to obtain an initial model of the corresponding thicknesses and resistivities. This model is thereafter used as an input in the WINRESIST computer software program to obtain the final geoelectrical inverted optimum model for every treated VES point.

The available shallow borehole lithological data in the study region and their correlations with the quantitative VES data interpretations confirm that the geoelectrical layers in the study area are mainly composed of sandy layers (fine, coarse and gravelly) with clay intercalations. Such a lithological sequence dominates the geoelectrical variables that control the OPC of the Quaternary aquifer. Those variables are the overburden-protecting layers (hOverb), RC, FC and anisotropy of the subsurface hydrogeological layers (λ). The OPC was already assessed by evaluating the longitudinal conductance of the overburden-protecting layers (Asfahani 2023). The study area has been classified according to the distribution of the longitudinal conductance and OPC(Ω−1) as 56% poor, indicating high vulnerability to contamination, 5.9% weak, 14.7% moderate, 20.6% good and 2.9% excellent (Asfahani 2023).

The statistical correlation matrix used in this paper allows us to obtain and establish different mutual empirical equations between (RC, FC, λ and hOverb). These empirical equations indicate the considerable influence of the mentioned geoelectrical variables on the spatial distribution of the OPC.

The different geoelectrical results obtained and documented provide useful information that largely helps in mapping out and locating the effectively protected groundwater area. The approach developed in this research paper is applied for the first time in Syria and can be easily practised worldwide with its different steps to assess the different protectivity conditions surrounding an aquifer.

The author would like to thank Dr I. Othman, General Director of the Syrian Atomic Energy Commission, for permission to publish this research work. The German Ministry of Economic Cooperation and Development (BMZ) and German Agency for Technical Cooperation (GTZ) are acknowledged for financial and administrative support to the Khanasser Valley Integrated Research Site (KVIRS) project. Prof. Late Rieser Armins (coordinator of the project) from Bonn University, Germany is deeply thanked for many useful discussions during the preparation stages of this project.

ICARDA is highly thanked for providing the facilities and the logistics during the realization of the Khanasser Valley project. Dr Fares Asfari from ICARDA is cordially thanked for his great help during the different stages of the project.

The three competent reviewers are cordially thanked for their professional remarks, critics and suggestions that considerably improve the final version of this paper. The Editor-in-Chief and the staff of WPT are cordially thanked for their assistance during the different stages of paper publication.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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