1. Introduction
The methods of surface geophysics offer prompt and inexpensive means for subsurface characterization [
1,
2,
3]. In addition, the surface geophysics technics provide information on subsurface properties, such as the layer’s thickness and saturation zones, depth to bedrock, fracture zones, location and orientation of bedrock fractures, and faults. New developments in recent years are the use of 2-D electrical imaging/tomography surveys for mapping areas with moderately complex geology [
4].
Agricultural geophysics is a modern discipline that applies noninvasive geophysical methods to obtain valuable soil surface and near-surface information. Geophysical techniques are becoming an important practical tool for many agricultural applications. Agricultural geophysical analyses are focused on delineating features over large areas within the soil profile (0 to 2 m depth) [
5]. The most common geophysical methods predominantly used for agricultural purposes are direct current (DC) resistivity and electromagnetic induction. With the recent advent of precision agriculture, the ability to generate a large amount of information rapidly is becoming more critical than ever [
5,
6]. Site infrastructure assessment, hydrologic monitoring, and environmental investigations are just a few current and potential uses of near-surface geophysical methods in agriculture applications. In addition, modern geophysical techniques are being incorporated within site-specific agriculture to detect soil horizons, soil compaction, soil salinity, mapping of hardpan layer, and soil texture [
6]. Today, with the advent of precision agriculture which employs data from multiple sources to enhance crop yields and assess soil quality to improve the cost-effectiveness of crop management strategies, it is necessary to advance the agricultural geophysics methods for clay-pan depth determination, soil hydrologic characterization, soil nutrient monitoring, crop/tree root biomass surveying, identification of subsurface flow pathways, subsurface irrigation, drainage systems infrastructure detection, and soil compaction evaluation [
7,
8,
9].
Electromagnetic (EM) instruments have been used extensively to determine the spatial distribution of soil attributes, including clay content [
10,
11], moisture [
12], and soil salinity [
13,
14,
15,
16]. In addition, different studies have used EM instruments to determine the depth of a clay layer [
17], soil types, and organic carbon fraction [
18]. Al-Ahsa Oasis is located 70 km to the west of the Arabian Gulf, and it is also one of the main agricultural areas in Saudi Arabia (
Figure 1).
The cultivated area in the Al-Ahsa oasis is about 12,000 hectares. Groundwater was considered the main water source, if not the only source, for the different purposes of Al-Ahsa Oasis. As a consequence of the overexploitation of groundwater resources, a decline in groundwater levels is observed. The famous springs in the Al-Ahsa oasis are running dry. Furthermore, deterioration of groundwater quality is occurring, caused by upconing of deeper saline groundwater [
19].
Due to groundwater depletion, treated wastewater is currently used to meet the shortage of irrigation water at Al-Ahsa Oasis. As a result, most groundwater is discharging from the Neogene aquifer. Today, due to excess overpumping, water depletion, and water deterioration, the signs of soil salinity at Al-Ahsa have become dominant [
20,
21].
Water and soil are the most critical factors that determine the success of agricultural activity in any location based on their characteristics. Some excavations at Al-Ahsa oasis indicated hardpan layers at different soil depths. Generally, hardpan is a term for a dense layer of soil below the uppermost topsoil layer. The negative impacts of the hardpan layer are that it is mainly impervious to water, restricts root growth, and makes it difficult for air, water, other gases, and organisms to move through the soil. Therefore, determining the existence of the hardpan layer nature and depth of its presence is very important in crop selection [
22].
Al-Ahsa soils are underlain by an impermeable marl layer (mixtures of clay and calcium carbonate) at zero to 2 m depth below the ground surface. Excess irrigation water accumulates on top of this layer, forming a shallow water table beneath the soils of the Al-Ahsa Oasis. The water table depth is affected by varying depths to the marl layer, the soil texture, and depth and spacing between field drainage canals [
23]. The irrigated arid zone of Al-Ahsa oasis faces twin problems of water scarcity and waterlogging accompanied by salinity. For more details about the studies related to the soil of Al Hassa, refer to [
24,
25,
26]. Al-Dakheel [
27] investigated the extent of soil salinity, irrigation water quality, and the relationship with the growth of vegetation, employing NDVI derived from Landsat satellite imagery. Al-Barrak and Al-Badawi [
28] reported that salt-affected soils in Al-Ahsa region represent as much as 20 % of the total area.
El Najem [
21] studied the degraded agricultural soils at Al-Ahsa Oasis and reported that the decline in the soil productivity distinguished the soil degradation at Al-Ahsa oasis. He attributed that to human activities and the marginal climatic conditions, which are considered the most important sources of soil degradation. The soil chemical properties exhibited slightly alkaline pH values, extending between 7.33 and 7.86, while the soil salinity data, as EC (electrical conductivity) values, varied across the Al-Ahsa Oasis. He found several values that exceeded 400 mS/m (i.e., the minimum value of saline soils), reaching 7.80 dS m
−1, implying the persistence of soil salinity conditions (i.e., saline soil) in the Oasis’s agricultural soils. It was also noticed that the soil EC values increased with increasing soil depths, signifying the inefficient drainage systems and, hence, salinization of the soil profile in the Oasis [
21].
Inland Sabkhas in Al-Ahsa area are salt-affected intermediate to dark brown soils found in relatively low relief areas. Sabkha in Al Hassa exists in very low relief areas, which are saturated with water (where groundwater rose and pushed salt to the surface).and may even have surface water [
27].
Al-Ahsa drainage water is collected by earthen lateral open canals having depths of about 1 m. The collected drainage water in the eastern part of Al-Ahsa oasis flows from the lateral’s canals to three sub-main drainage canals, which are connected to the main drainage canal D2 as shown in
Figure 2. The collected drainage water in this drainage flows towards an evaporation lake in Al Asfar 13 km to the east of the Oasis, while the drainage water in the northern sector flows from the lateral to the sub-main drainage canals that were connected to the main drainage canal D1. The drainage water in D1 flows towards an evaporation lake in Al Uyoun (see
Figure 2). The collected water in both lakes remains in the winter season to be a source for cattle to drink, as well for shallow aquifer recharge. From December until April, the agricultural drainage water overflows from Al Uyoun lake through small waterways into the Arabian Gulf [
23].
For more details about the hydrogeology and the hydrochemical characterization of the groundwater of the Al-Ahsa area, refer to [
19,
27,
29,
30,
31,
32].
Soil surveys require quick and, when possible, nondisturbing estimations of numerous soil properties, such as salinity, texture, stone content, groundwater depth, and horizon sequence in soil profiles; however, conducting soil measurements with a high sampling density is costly and time-consuming. Conventional methods of soil analysis mostly require disturbing soil, removing soil samples, and analyzing them in a laboratory. So, the traditional methods used to acquire soil information involve intensive field surveys and laboratory analyses. As a consequence, only limited amounts of data are collected. In addition, the low resolution of the spatial data used to provide indicators of the distribution of water/soil properties and soil conditions may lead to interpretation errors and possibly errors in soil management. On the contrary, geophysical methods allow rapid measurement of soil electrical properties, such as electrical conductivity, resistivity, and potential, directly from the soil surface to any depth without soil disturbance. Modern geophysical techniques are a very efficient and effective tool for the nonintrusive gathering of continuous agricultural field data on many soil types, soil conditions, soil salinity, and underground topographies.
The objectives of this study were to evaluate the effectiveness of modern geophysical techniques to study the agricultural aspects of Al Hassa oasis.
2. Materials and Methods
2.1. The Geophysical Investigations
Electrical resistivity tomography (ERT) and Electromagnetic (EM) induction were implemented to achieve the objectives of this study. The DC resistively method of geophysical exploration is popular, has proved to be successful, and has many implications in agriculture, environmental studies, and hydrogeology. Moreover, the conductivity meter is an inexpensive, rapid, and effective means for mapping soil salinity. In this study, 2-D electrical resistivity measurements were carried out using a SuperSting R8/IP 8 channel multielectrode resistivity (Advanced Geosciences (AGI), Inc. Geoscience Dr., Austin Texas, TX, USA) and IP imaging system with 112 electrodes manufactured by Advanced Geosciences, Inc., (AGI), (
Figure 3A), while the EM38-MK2 m (Geonics Limited, Meyerside Dr., Mississauga, Ontario, Canada) was used in vertical mode (
Figure 3B) to measure the electrical conductivity (EC) along the study area.
Ten profiles of 2-D (P-1 to P-10) electrical tomography using the SuperSting R8/IP 8 multielectrode channel resistivity and IP imaging system with 112 electrodes at one-meter electrode spacing were implemented. The locations of these profiles were chosen to cover different zones across the entire Al Hassa oasis. Moreover, 2240 measuring points using EM38-MK2 at vertical mode with the transmitter–receiver of 0.5 and one-meter spacing were measured with twenty electrical conductivity profiles.
Figure 4 shows the base map of the ten conducted 2-D profiles along the study area. It is worth mentioning that the EM38-MK2 measured electrical conductivity was measured at the 10 exact locations of the measured 2-D profiles to correlate soil conductivity/resistivity at near-surface (These lines are Labeled Line One-1, Line Two-1, etc.).
In contrast, the other ten EM38-MK2 electrical conductivities, each of them, were measured five meters away from the location of the 2-D transects. These EC lines are labeled Line One-2, Line Two-2, etc., to distinguish them on the data logger files from those measured at the exact locations of the 2-D transects. These ten EC lines (labeled Line One-2, Line Two-2, etc.) were measured for correlation with those measured at locations of the 2-D transects.
For more details about the irrigation water quality refer to, for example, Hussein et al. [
31]. For the soils of Al Hassa, refer to El Najem [
21].
2.2. Two-Dimensional Resistivity Description and Data Acquisition
The SuperSting R8/IP multielectrode resistivity provides apparent resistivity, induced polarization, and battery voltage. The measurement range is ±10 V, and the max measuring resolution is 30 nV, depending on the voltage level. The internal transmitter is 200 W and the external 15 kW. The output current ranges from 1 to 2000 mA continuous, and it can be measured with high accuracy. The output voltage is 800 V, and the actual electrode voltage depends on the ground resistivity and transmitted current. There are eight input channels.
The input gain ranges automatically and always uses the receiver’s full dynamic range. The input impedance is more than 50 MΩ. The system calibration is conducted digitally by the microprocessor, based on the correction values stored in the memory. The supported configurations in manual mode are resistance, Wenner, Schlumberger, pole–dipole, dipole–dipole, and pole–pole, and any configuration can be programmed in automatic mode. The operating system is stored in a reprogrammable memory. For each measurement, full-resolution readings of the mean value and error are stored along with the user-entered coordinates and time of the day.
The displayed and stored data in the memory are apparent resistivity (Ohm-m), current intensity (mA), and measured voltage (mV) for each measurement. In addition, the data can also be realtime displayed on an Android device with bright color, transmitter/receiver plot, IP curves, and contact resistance measurements. The internal SuperSting memory in the resistivity mode can store more than 79,000 measurements and can store more than 26,000 measurements in the combined resistivity/induced polarization mode. The RS-232C channel is available to dump the data from the instrument to a Windows-type computer based on the user command. The operating time of the SuperSting R8/IP depends on survey conditions and the used battery size. The internal circuitry in the auto mode can adjust the current to save energy. The operating temperature ranges from −5 to +50 °C.
The resistivity method depends on the injection of the electrical current (I) into the ground by using two current electrodes A (source) and B (sink), and two potential electrodes M and N, computing the resulting potential differences (ΔV) as illustrated in
Figure 5. Increasing the electrode spacing results in a deep depth of investigation, where the electric current passes through the investigated subsurface targets. By considering the subsurface structure, the depth of investigation represents about 20% to 40% of the spacing of the current electrodes [
33].
The following Equations (1) and (2) give the apparent electrical resistivity of the subsurface
where
G is the Geometrical Factor and is given by
where
d1,
d2,
d3, and
d4 are the distances of the potential electrodes M and N from the current electrodes (A and B), see
Figure 5.
For more details about resistivity and survey deployment basics, refer to Musset and Khan [
34] and Reynolds [
35]. In this study, the 2D electrical resistivity measurements were carried out using the SuperSting R8/IP 8 multielectrode channel resistivity and IP imaging system with 112 electrodes at one-meter spacing manufactured by AGI Advanced Geosciences, Inc., Austin, TX, USA (
Figure 3A).
A combination of dipole–dipole, Wenner-Schlumberger, and pole–dipole configurations at each transect of the conducted ten 2-D resistivity profiles was implemented and merged during the processing of the interpretation of resistivity data for each transect. The coordinates of the conducted 2-D profiles were measured using the GPS system. The quality of the data acquisition was entirely controlled by the computer software, which, before starting any measurement, checked the electrode connectivity to the soil and the magnitude of the contact resistances. The 1 m electrode spacing was chosen with an estimated investigation depth about 20 m below the ground. The apparent resistivity data were inverted to create a model of the resistivities of the subsurface using AGI Earthimager 2-D Software (after Advanced Geosciences, Inc., Austin, TX, USA). With this software, the data collected with the AGI SuperSting earth imaging resistivity instruments can be interpreted into easy-to-read 2-D earth sections (resistivity tomograms). A more accurate subsurface model is the two-dimensional (2-D) model, where the resistivity changes in the vertical and horizontal directions along the survey line are recorded. 2-D resistivity profiling was carried out by making many measurements at different profile locations and offsets. Finally, the 2-D resistivity profiling data were inverted using AGI Earthimager 2-D Software (after Advanced Geosciences, Inc., Austin, TX, USA) to create a tomogram-like resistivity model along a subsurface section that detected different salinity water zones [
4]. AGI EarthImager 2-D software (after AGI Inc., Austin, TX, USA) was used for resistivity data inversion. AGI EarthImager 2-D software is a two-dimensional inversion modeling software for affordable resistivity and induced polarization (IP) imaging. Using this software, any array or mixed data from Schlumberger, pole–pole, pole–dipole, dipole–dipole, or Wenner electrode arrays can be inverted.
2.3. EM38-MK2 Description and Data Acquisition
EM38-MK2 provides the measurements of in-phase (magnetic susceptibility) and quad-phase (conductivity) components within two different depth ranges without any requirement to contact with or penetration of the instrument into the soil. The maximum practical depth of exploration is 1.5 m. Therefore, the EM38-MK2 applications in general soil and agriculture sciences are typical. The EM38-MK2 contains two receiver coils, divided to 1 m and 0.5 m from the transmitter, supplying the data from the effective depth ranges of 1.5 m and 0.75 m, respectively when placed in the vertical dipole orientation. On the other hand, it supplies the data from the effective depth ranges of 0.75 m and 0.375 m, respectively at horizontal dipole orientation. Once the EM38-MK2 is positioned within the collapsible calibration stand, the instrument can be calibrated automatically within seconds, without any necessity for iterative adjustments. In addition, the EM38-MK2 is supported by temperature equilibrium circuitry to improve temperature-related drift aspects. The data can be collected by any appropriate field computer or the DAS70-AR Data Acquisition System, which can be connected by either Bluetooth wireless technology or RS-232 serial cable. The DAS70-AR provides an improved level of support for data collection, and it includes a rugged field computer with 8 GB storage memory. For more details about this instrument, refer to Geonics Ltd., Mississauga, ON, Canada.
The diagram of the EM38 and its related electromagnetic fields is described in
Figure 6. The primary magnetic field (Hp) is generated from the transmitting coil (Tx) at one end of the sensor, this field produces current loops in the ground below, and in turn, the current loops generate their own magnetic field (Hi). The generated secondary field is superimposed on the primary field, and both Hp and Hi are measured in a receiving coil (Rx) at the other end of the sensor [
36]. The meter is intended to be placed or held in either the horizontal or vertical orientation; this orientation position controls the signal penetration depth and depth weighting response pattern. In a homogeneous soil profile, the vertical (EMV) signal penetrates to a depth of 1.5–2 m, while the horizontal (EMH) signal primarily reflects the shallower soil zone (0.75–1.0 m); Manual of EM38-MK2, (Geonics Limited).
Therefore, the instrument works by emitting an alternating current through a transmitter coil, which induces a primary magnetic field to pass perpendicular to the coil orientation and into the adjacent media. Eddy currents are generated as these currents pass through the coil. This strength is a function of the (a) amount of negative charge on the clay particle; (b) clay content; (c) concentrations of salts in the soil solution; and (d) soil moisture content. The more conductive the soil, the greater the secondary magnetic field produced. The ratio of the primary and secondary magnetic fields determines the apparent electrical conductivity (ECa).
Electromagnetic induction sensors, such as EM38-MK2, are becoming more widely used for mapping relative differences in soil characteristics in agricultural fields, including soil salinity; see [
15]. In this study, EM38-MK2 was used in vertical mode to measure the electrical conductivity (EC) at 75 and 150 cm depths at about 2240 sites along the study area (see
Figure 4). The acquired data using the EM38-MK2 conductivity meter were processed using the DAT38MK2 Ver. 1.05 package (Geonics Limited) and exported to XYZ format for the twenty EC measured profiles.
4. Conclusions
Implementing electrical resistivity tomography (ERT) and modern electromagnetic induction techniques contributed to soil characterization salinity and mapping hardpan layer problems at Al-Ahsa Oasis, Eastern Province, Saudi Arabia. The tomograms of ten acquired 2-D resistivity profiles and data of the excavated soil pits judged by local farmers indicated the different geoelectrical layers. Information about the depth thickness of these geoelectric layers, including the topmost soil, was given. In some of the 2-D tomograms and at shallow depths, the hardpan layer was depicted, and this layer was composed of marl, clay, mudstone, or shale. This layer directly affects the level of soil water. Thus, the accumulation of salt in some locations results in some of the sites affected by the salt composed sabkha, especially if it is very shallow, which increases the soil conductivity. The 2-D tomographs measured at the southwest displayed resistivity values different to those those measured at the north and east of the study area, which were characterized by low resistivity values at greater depths due to effect of the sabkha and clayey soil and effects of both the Al Yuoun evaporation lake at the north of the Al-Ahsa Oasis and of the Al Asfar Lake at the east of the Oasis. The results of the twenty measured electrical conductivity profiles using the EM38-MK2 in the vertical mode were conducted at two different coil separations (1 m and 0.5 m) at the same locations of the measured 2-D profiles. The electrical conductivity results showed that the salinity variation along the measured profiles changed laterally and vertically due to changes in soil type/texture, soil moisture, and the existence of sabkha. The measured conductivity at most lines indicated high values of conductivities at coil separation of 1 m (greater depth); these profiles were located at the north and east of the study area, while only a few lines showed high values of conductivities measured at a coil separation of 0.5 m (shallow depth) compared to those at 1 m coil separation, these lines were located at the southwest of the study area. Moreover, it is found that the farms located in the southwest of the study area were characterized by low conductivities, while relatively high conductivities characterized the farms located to the north and east in the Al-Ahsa oasis. Thus, modern geophysical techniques proved to be efficient and effective tools for the nonintrusive gathering of continuous agricultural field data on many soil types, soil conditions, soil salinity, and near-surface conditions. Monitoring data about both soil and irrigation water was very important to prevent the degrading of agricultural soils in Al-Ahsa oasis. Degrading of agricultural soils will lead to poor agricultural productivity. The productivity limiting factors of these soils were mainly integrated into their chemical properties represented by the increased salinity. Such contribution provides technical support for planners, decision makers, and researchers in the field of agricultural sciences for ensuring agriculture sustainability in this Oasis.