Electromechanical Behavior of Afyonkarahisar Clay Under Varying Stress and Moisture Conditions

Abstract

Clay is a widely used material with unique properties that vary depending on water content and applied pressure. In this study, the electromechanical behavior of clay samples from Afyonkarahisar, Turkey, is investigated by examining the relationship between electrical resistivity, water content, and mechanical loading under uniaxial pressure. The samples with a water content of 10%, 20%, and 30% were tested using a uniaxial loading machine in accordance with ASTM D 2216 and the Turkish standard TS 1900-1. The analysis included measurements of stress, deformation, and electrical conductivity of the soil. A comparative assessment of samples with varying water content revealed that at low moisture levels (10%), the specific electrical resistivity initially decreases due to soil compaction and reduced porosity. However, as stress increases further, resistivity rises significantly as microcracks begin to develop, disrupting conductive pathways. In contrast, at higher water contents (20% and 30%), resistivity consistently decreases with increasing stress, while conductivity increases markedly. This indicates that at elevated saturation levels, the presence of water facilitates charge carrier mobility through ionic conduction, resulting in lower resistivity and higher conductivity. Comparisons with previous studies on clays such as bentonite and kaolinite reveal similar qualitative trends, although differences in the rate of resistivity change suggest a distinct mineralogical influence in Afyonkarahisar clay. This study contributes to a deeper understanding of the geotechnical behavior of this regional clay and supports more accurate performance predictions in engineering and construction applications.

1. Introduction

Understanding the behavior of clay under varying water content and its effect on electrical resistivity and conductivity is crucial [1], particularly in regions like Afyonkarahisar, where groundwater plays a significant role [2]. The behavior of clays in response to changes in water content directly impacts their geotechnical properties [3], which is vital for infrastructure and engineering projects. Variations in water content can influence key factors such as compressibility, shear strength, and permeability, all of which are critical for construction and stability assessments.

Previous studies have investigated the relationship between geotechnical properties and the electrical resistivity of soils and rocks. For example, Fallahsafar et al. (2013) [1] found that higher water content in clay soils leads to lower resistivity, whereas a higher proportion of air voids increases it. Sun and Xue (2014) [4] observed that in sedimentary rocks such as mudstone, sandstone, and limestone, changes in resistivity correlate with crack development during uniaxial compression. These results highlight the influence of moisture content and internal structural changes on resistivity, providing a foundation for further studies aimed at predicting the failure of geomaterials under stress.

In China, another relevant study conducted by Qiang Sun and Lei Xue (2014) [4] focused on the relationship between resistivity and water content in mudstones, sandstones, and limestone. The study used uniaxial compression tests to assess resistivity changes under load, measuring resistivity. Their findings revealed that resistivity variation correlates with crack development during uniaxial compression, with sharp resistivity changes occurring as cracks form and grow in the soil. These findings suggest a threshold for crack coalescence, which starts at 75–85% of the peak strength, and the study emphasizes the need for further validation of these results to confirm their applicability in predicting soil failure under various conditions.

In geotechnical engineering, electro-osmosis is frequently used to manage soils with high water content. Electrical conductivity is a key parameter for monitoring these processes, as the presence of water and dissolved ions significantly enhances the soil’s ability to conduct electric current. This allows for real-time monitoring of soil moisture variations.

Geophysical techniques such as Electrical Resistivity Tomography (ERT) enable spatial and temporal monitoring of water content in soils at various depths. Electrical conductivity is a crucial factor in these investigations, allowing for the assessment of dynamic changes in soil properties due to external influences such as rainfall, drought conditions, or mechanical loading.

Numerous studies have demonstrated a strong correlation between electrical conductivity and soil moisture. Higher water content increases the number of mobile ions in pore water, lowering the soil’s electrical resistivity. Due to this relationship, electrical conductivity monitoring has become a valuable tool in geotechnical site investigations and infrastructure projects, including embankments, road foundations, and other structures where controlling soil moisture is essential for ensuring long-term stability and safety.

Loke and Barker (1996) [5] conducted foundational research using electrical tomography to determine water content and infer mechanical characteristics of soils at various depths. Santamarina and Cho (2004) [6] studied the effect of soil moisture on mechanical properties and electrical conductivity, identifying significant interdependence. The article by Ramos et al. (2019) [7] explores the use of path coefficient analysis as an alternative method to identify soil quality indicators. The authors applied this statistical technique to evaluate the direct and indirect effects of various physical and chemical soil properties on overall soil quality. Their findings show that path analysis provides deeper insight into the relationships among soil parameters—such as texture, compaction, organic matter, pH, and cation exchange capacity—helping to identify which variables most significantly influence soil quality. This approach offers a more structured and informative evaluation than traditional correlation analysis. The study highlights the method’s potential for improving soil monitoring and management, especially in agricultural and environmental contexts. The study “Quasi-3D mapping of soil moisture in agricultural fields using electrical conductivity sensing” by Shaukat et al. (2022) [8] explores the use of electromagnetic induction surveys to predict soil moisture across agricultural fields. The researchers established electrical resistivity–soil moisture calibrations at two depths, which were then used to convert soil conductivity data into volumetric moisture content. This approach allowed for the accurate prediction of soil moisture at three depths during both dry and wet seasons. Furthermore, the application of quasi-3D inversion techniques significantly improved the estimation of soil moisture distribution throughout the soil profile. The study highlights the effectiveness of EMI-based sensing combined with inversion modeling as a practical and non-invasive method for high-resolution soil moisture monitoring in agricultural settings.

Khosravi et al. (2019) [9] conducted a comparative analysis of various models, including artificial neural networks, for predicting soil electrical resistivity based on mechanical properties. Zohra-Hadjadj et al. (2019) [10] developed a system for automated sampling and weighing of soil specimens using microwave drying, enabling rapid and accurate determination of soil density. Zhang et al. (2019) and Yang et al. (2024) [11,12] explored the use of piezoelectric sensors to detect changes in the mechanical properties of soils caused by freeze–thaw cycles.

Butterfield (1979) [13] introduced a mechanical behavior model for natural clays based on critical state soil mechanics, emphasizing the differences between naturally consolidated and laboratory-prepared samples, as well as the long-term response of clays under loading. Craig (2004) [14], in his widely used textbook, provides a systematic overview of both fundamental and advanced concepts in soil mechanics, including classification, permeability, consolidation, shear strength, and slope and foundation stability, making it a key reference in both education and engineering practice. Similarly, Das (2016) [15] offers a comprehensive treatment of geotechnical engineering, with a strong focus on the mechanical behavior of soils, investigation methods, foundation design, and settlement analysis, all presented with a clear practical orientation. Ladd and Foott (1974) [16] developed the SHANSEP method (Stress History and Normalized Soil Engineering Properties) as an improved approach for evaluating the stability of soft clays, allowing for a more realistic assessment of safety factors by accounting for stress history. Mesri (1975) [17] further advanced design procedures for soft clays, focusing on settlement and long-term stability, and providing experimentally supported methods essential for the reliable design of structures on weak soils.

While these studies provide valuable insights, this research focuses specifically on Afyonkarahisar clay, which has a unique geotechnical profile. Unlike the previous studies, which used a broader range of water content values, this study focuses on water content levels of 10%, 20%, and 30%, which are more relevant to the local conditions in Afyonkarahisar.

The primary contribution of this research is to deepen the understanding of Afyonkarahisar clay’s behavior, particularly how its resistivity and conductivity change as water content varies, and how these properties interact with stress and strain. This study provides valuable insights into the physical properties of the clay, which can significantly impact the performance of the material in real-world applications. By observing these changes under stress and strain, the research offers a more comprehensive view of the clay’s behavior under different conditions. This can help inform us about the design of more effective infrastructure projects in the region. Furthermore, the findings can guide future studies by offering a foundation for further exploration of local soil properties, ultimately leading to better material selection, construction methods, and long-term stability in engineering projects involving Afyonkarahisar clay. This study aims to (1) investigate the influence of water content on the electrical resistivity of Afyonkarahisar clay, (2) examine the correlation between resistivity changes and mechanical behavior under uniaxial compression, and (3) compare the results with previous findings on other clay types to assess generalizability.

The research aims to explore three fundamental questions, each addressing a critical aspect of the relationship between electrical resistivity, water content, and mechanical behavior of soils under stress.

The first key question: How does electrical resistivity change with varying water content? This question seeks to investigate the extent to which water content affects the electrical resistivity of the soil. Given that water plays a crucial role in soil conductivity, this question is focused on understanding the physical and chemical mechanisms by which moisture influences resistivity and how these changes can be measured and quantified across different moisture levels.

The second question: What is the relationship between resistivity variation and mechanical behavior under uniaxial compression? Here, the goal is to examine how changes in electrical resistivity correlate with soil behavior when subjected to mechanical stress, specifically under uniaxial compression. This includes evaluating whether variations in resistivity can be used to predict or explain changes in the soil’s mechanical properties, such as strength, stiffness, and deformation. Understanding this relationship is crucial for determining how soil conductivity can serve as an indirect measure of its mechanical performance, particularly in geotechnical applications like foundation design or slope stability.

Finally, the third question: How do the findings compare with previous studies on other clay and soil types? This question places the current research within the context of existing literature, seeking to identify similarities or differences in findings when compared to other studies on various soil types, especially clays. By drawing comparisons with previous research, the study aims to evaluate whether the observed relationships between resistivity, water content, and mechanical behavior hold true across different soil compositions and environmental conditions, thereby contributing to a broader understanding of soil mechanics and resistivity in geotechnical practice.

By investigating these factors, this study provides a more detailed understanding of local soil properties, contributing to improved foundation designs, geophysical monitoring, and long-term infrastructure stability in regions with similar geological conditions. Section 2 describes the materials and methods, including sample preparation, testing procedures, and the standards followed. Section 3 presents the experimental results, focusing on resistivity variations under different water content levels and uniaxial compression. Section 4 discusses these findings in relation to previous studies, highlighting key differences and implications for geotechnical applications. Section 5 concludes with the study’s main contributions, limitations, and recommendations for future research.

2. Materials and Methods

2.1. Afyonkarahisar Clay Characterization

The clay soil used in this study was collected from the center of Afyonkarahisar, Turkey, at a depth of approximately 1–1.5 m. The collection method could be classified as disturbed soil. The clay soil was classified as high-plasticity clay (CH) according to the Unified Soil Classification System (USCS) [18], ISO 14688-1 [19], and ISO 14688-2 [20]. The properties of the clay include a specific gravity of 2.62, a unit weight of 16.5 kN/m³, a shrinkage limit of 5.8%, a maximum dry density of 1.58 g/cm³, and an optimum water content of 21.9%. The liquid limit (LL) is 48.6%, and the plastic limit (PL) is 23%, resulting in a plasticity index (PI) of 25.6%. According to the USCS, soils with a PI greater than 7 and a liquid limit above 50% are classified as high-plasticity clay (CH). While the liquid limit in this case is just below the 50% threshold, the high PI value strongly supports the classification as CH, as the plasticity index is a key determinant in this classification. The PI indicates that the soil is more prone to significant volume changes with moisture variations, which is characteristic of high-plasticity clays.

Soil identification tests were carried out in accordance with several internationally recognized standards. The Unified Soil Classification System (USCS) [18] is a widely used system in geotechnical engineering for categorizing soils based on their particle size distribution and Atterberg limits (liquid limit, plastic limit, and plasticity index). According to USCS, a soil with a liquid limit greater than 50% and a plasticity index greater than 7 is classified as CH (high-plasticity clay), which is consistent with the high PI value observed in this sample.

Additionally, ISO 14688-1 [19] and ISO 14688-2 [20] provide international standards for the classification and identification of soils. ISO 14688-1 specifies the principles for identifying soil types based on their physical properties, including the limits for liquid and plasticity indices, while ISO 14688-2 focuses on the detailed classification criteria, ensuring consistent soil identification worldwide.

The soil tests were also conducted in compliance with several standards, such as Turkish Standard TS 1900 [21], ASTM D 854 [22] for determining specific gravity, ASTM D 422 [23] for grain size analysis, ASTM D 4318 [24] for liquid and plastic limits, and ASTM D 2216 [25] for determining the moisture content of soils. These standards are essential for ensuring the accuracy and reliability of soil classification, providing a standardized approach to assessing the physical properties that influence soil behavior in geotechnical applications.

2.2. Specimen Preparation and Test Methods

In this study, the low-plasticity clay samples were dried in an oven at 105 °C for 24 h to remove all moisture and ensure they were completely dry. For the experimental study, samples were produced by performing a standard compression at the optimum water content (20%) determined beforehand, and at two different water contents (10% and 30%). The standard compression test was carried out according to ASTM D 2216 [25] and Turkish Standard TS 1900-1 guidelines [21], using different water content ratios. Water was mixed into the samples to achieve the desired moisture levels for the test. The samples were compressed into three layers of approximately equal mass within a standard compression mold (diameter: 105 mm; height: 115.5 mm). Each layer received 25 impacts from a 2.5 kg hammer dropped from a height of 305 mm to achieve the proper compaction. For uniaxial compressive strength testing, three samples were prepared for each of the three water contents (10%, 20%, and 30%). All samples were compacted using standard Proctor energy to ensure uniform density and structure across all specimens. Three different samples were taken for each mixture using standard mold samplers. The diameter of the samples is 38 mm, and the height is 76 mm.

Analysis of the Relationship Between Moisture Content and Bulk Density for a Given Dry Density. In this analysis, the dry density of the soil is known and taken as 1.58 g/cm³. To investigate the influence of moisture content on the bulk density, three levels of moisture content are selected: 10%, 20%, and 30%. The specific gravity of the soil solids is 2.62, although it is not required for the bulk density calculation directly.

The relationship between moisture content ($w$) and bulk density ($\mathsf{\rho }$) for each selected value of w is determined using the following Equation (1):

$$\mathsf{\rho }={\mathsf{\rho }}_d·(1+w),$$

(1)

where:

• $\mathsf{\rho }$ = bulk (wet) density [g/cm³]
• ${\mathsf{\rho }}_d$ = dry density [g/cm³]
• $w$ = water content

Using this equation, the bulk density is calculated for each selected moisture content. The basic geomechanical properties of Afyonkarahisar Clay samples are presented in

Table 1. Geomechanical properties of Afyonkarahisar Clay samples.

Property	Value
Soil classification	High plasticity clay (CH)
Specific gravity (Gs)	2.62
$\mathrm{Maximum} \mathrm{dry} \mathrm{density} ({\mathsf{\rho }}_d$)	1.58 g/cm3
Optimum water content (wopt)	21.9%
Liquid limit (wL)	48.6%
Plastic limit (wP)	23.0%
Plasticity index (PI)	25.6%
Shrinkage limit	5.8%
Moisture content (w)	10%, 20%, 30%
$\mathrm{Bulk} \mathrm{density} \mathsf{\rho }$(w)	1.738, 1.896, 2.054 g/cm3

.

2.3. Schematic Diagram of Experimental Systems

The experimental setup used for measuring the electrical resistivity is illustrated in Figure 1. The system consists of two copper plates serving as electrodes, two wooden plates providing insulation, a direct current (DC) power supply with constant voltage output, a data acquisition unit, and the test specimen. The copper and wooden plates were placed on the top and bottom surfaces of the clay specimen, respectively, and the assembly was fixed within a uniaxial compression testing machine.

A constant voltage of 60 V was applied to the system using the DC power source, with the positive and negative terminals connected to separate copper electrodes, thereby completing the circuit. During the uniaxial compression test, voltage values across a 10 Ω resistor were recorded at one-second intervals using the data acquisition system. The recorded voltage values were divided by the 10 Ω resistance to determine the current passing through the clay specimen.

Using Equation (2), the resistance (R) of the clay sample was calculated by taking the ratio of the fixed voltage (60 V) to the measured current (I). Subsequently, the electrical resistivity (${\mathsf{\rho }}_s$) of the clay specimen was determined using Equation (3).

Furthermore, throughout the uniaxial compression test, the change in electrical resistivity (${\mathsf{\rho }}_s$) of the clay sample was monitored in real time, and the temporal variation in resistivity was recorded at one-second intervals by the data acquisition system. The resulting data were then used to plot the resistivity change over time.

Finally, the electrical conductivity (EC) of the clay specimen was calculated using Equation (4).

$$\mathrm{R}={\displaystyle \frac{V}{I}},$$

(2)

$${\mathsf{\rho }}_s=Rx{\displaystyle \frac{A}{L}},$$

(3)

$$E\mathrm{C}={\displaystyle \frac{1}{{\rho }_s}},$$

(4)

In the equations, (I) represents the electrical current flowing through the circuit (A); V denotes the potential difference between the electrodes (V); R is the measured electrical resistance of clay sample (Ω); $\mathsf{\rho }$ represents the electrical resistivity of clay sample (Ω·cm); L denotes the distance between the copper electrodes (cm); and A refers to the cross-sectional area of the clay sample (cm²). To determine the electrode spacing, the specimen height was measured at three different points, and the average value was taken as L. A deformation gauge was used to monitor the changes in specimen height during testing. Simultaneous measurements of load and electrical conductivity were recorded at regular time intervals, and this process continued until the clay specimen failed under uniaxial compression.

Figure 2 presents a schematic diagram of the experimental setup illustrating the interaction between mechanical loading and electrical resistance measurements. The configuration enables the simultaneous acquisition of electrical resistance data during mechanical loading, thereby allowing for a comprehensive analysis of the relationship between the mechanical and electrical behavior of the clay specimen.

3. Test Results and Discussions

In this study, the clay soil under investigation was thoroughly analyzed in a laboratory setting with respect to its physical and mechanical properties. The soil was classified as a high plasticity clay (CH), and its fundamental engineering characteristics were determined through a series of tests conducted in accordance with relevant standards. The data obtained enabled a combined evaluation of both the mechanical behavior and electrical properties of the soil, thereby offering a novel approach for monitoring the electrical responses of soils under deformation.

To determine the mechanical strength properties of the soil, unconfined compression tests were conducted. The unconfined compression test is a fundamental laboratory method widely used to determine the undrained shear strength of cohesive soils. In this test, a cylindrical soil specimen is subjected to axial loading without any lateral confinement. As the specimen deforms under the applied load, its peak compressive strength and deformation characteristics are recorded. The results provide essential data for assessing the engineering behavior of the soil, conducting bearing capacity analyses, and evaluating soil stability.

Through this integrated approach, it becomes possible to monitor variations in the mechanical behavior of soils via electrical resistance data. This highlights the potential of electrical measurement techniques as an alternative monitoring method in geotechnical engineering for evaluating soil properties.

The samples were subjected to uniaxial compression testing to investigate the relationship between water content and changes in electrical resistivity. The behavior of resistivity varied depending on the applied stress level, highlighting the complex interaction between mechanical and electrical properties of the clay. During the experiment, stress, strain, and electrical conductivity values were measured simultaneously to capture the full spectrum of variations occurring during compression.

3.1. Electrical Resistivity and Conductivity

Figure 3 illustrates the variations in stress and strain levels, along with corresponding changes in electrical resistivity and conductivity. These measurements provide a detailed understanding of how clay with different water contents responds to mechanical loading and how its electrical properties evolve throughout the compression process.

At lower initial water content, the early stage of loading led to a reduction in porosity due to compression, which in turn influenced soil conductivity and caused a decrease in electrical resistivity. This initial decline in resistivity is attributed to the closer packing of soil particles, reducing the void spaces and altering the conductive pathways. However, as the compression progressed, the material reached a critical stress level where microcracks began to form. These cracks disrupted the continuity of conductive pathways, leading to an increase in electrical resistivity. In the later stages of loading, as the crack density increased significantly, a rapid rise in resistivity was observed, indicating a sharp transition in the material’s electrical response.

These findings emphasize the nonlinear nature of electrical resistivity behavior under uniaxial compression, particularly in cohesive soils with varying water content. The results provide valuable insights for geotechnical engineering, especially in applications related to soil stability analysis, foundation design, and the assessment of soil behavior under different loading and moisture conditions.

When the above graphs are examined in general, it is seen that the electrical resistivity values under stress decrease with the increase in the amount of water in the clay samples. On the other hand, it is seen that the electrical conductivity values increase.

3.2. Stress–Strain and Conductivity Through Uniaxial Compression Test

The strain–stress data were obtained through uniaxial compression tests, where an increasing axial load was applied to the clay sample until failure. The corresponding strain was recorded using a displacement sensor, while stress values were derived from the applied force divided by the initial cross-sectional area of the sample.

Simultaneously, electrical conductivity was measured using electrodes, which recorded resistivity changes in real time as the sample was compressed. The graph shows that both curves exhibit a similar trend, indicating a correlation between mechanical deformation and electrical conductivity changes. In the initial loading phase, both stress and conductivity increase gradually with strain. As strain progresses, the stress–strain curve exhibits a nonlinear increase, while the conductivity–strain curve follows a comparable pattern. This suggests that changes in microstructure (such as pore compression and particle rearrangement) influence both mechanical and electrical properties.

The slopes of both curves are notably close, implying a strong relationship between stress development and conductivity variation in clay with moderate water content. These findings suggest that electrical conductivity measurements could serve as an indirect method for monitoring strain-induced changes in clay under compression.

Figure 4 illustrates the Stress–Strain and Conductivity–Time responses obtained from uniaxial compression and electrical resistance tests conducted at different water contents. These measurements provide insight into how clay with varying water contents responds to mechanical loading and how its electrical resistance evolves during the compression process.

When the graphs in Figure 4 are analyzed overall, it can be concluded that the stress–strain graphs and the time-dependent electrical conductivity graphs exhibit similar behavior across all three water content levels. For instance, in clay samples with 10% water content, electrical conductivity increases as stress rises and decreases as stress reduces.

In Figure 5, strain–stress and strain–conductivity relationships are shown for clay samples with 10–20–30% water content. In addition, since the experiments were conducted in the same time interval, time–stress and time–conductivity relationships are also shown. When Figure 5 is examined, it is concluded that the strain–stress and strain–conductivity graphs are similar to each other. In addition, when the time–stress and time–conductivity relationships are examined, it is seen that similar curves are obtained.

3.3. Electrical Conductivity Under Different Water Contents and Varying Stress–Strain Conditions

The analysis of the results indicates a similarity between the temporal evolution of stress and strain and the temporal variation of electrical conductivity under changing stress–strain conditions during the uniaxial compression test, across all three levels of water content. The values of electrical conductivity (EC) vary with the applied stress state and water content according to a trend that can be described using a simple exponential form, see Equation (5).

$$EC=a·e^{b·(w/w_L)},$$

(5)

Figure 6 illustrates the variation in electrical conductivity under different stress–strain conditions (for σ_u = 50, 75, 100, and 200 kPa) during uniaxial compression tests, and for different initial water contents (w = 10%, 20%, and 30%). A good agreement between the measurements is observed when the results are expressed in exponential form, suggesting a consistent relationship between electrical conductivity and applied stress across different moisture conditions. The values of the parameters a and b for different applied stress levels are summarized in

Table 2. Parameters a and b in Equation (4) for different stress levels.

Stress σ (kPa)	a	b
50	0.0011	0.1428
75	0.0012	0.1405
100	0.0020	0.1227
200	0.0038	0.1068

.

The relationships between electrical conductivity (EC) and water content (w) of soil samples subjected to varying stress–strain conditions during uniaxial compression tests are characterized by two parameters, a and b, as expressed in Equation (6).

Equations (5) and (6) are derived from the integration of laboratory test data and established findings from the literature on shear strength and soil behavior, with particular reference to Budhu (2015) [26].

$$EC=a· e^{b·w},$$

(6)

These parameters capture the influence of applied stress levels on the dependence of electrical conductivity on moisture content. The specific values of parameters a and b for different applied stress levels are summarized in Table 2, providing insight into how mechanical loading affects the soil’s electrochemical behaviour.

3.4. Influence of Relative Moisture Content on the Uniaxial Compressive and Undrained Shear Strength of Clay

This section examines the influence of relative moisture content on the uniaxial compressive strength of clay (q_u) and the undrained shear strength (c_u). The focus is on the empirical relationship between cu/qu as a function of the relative water content w/w_L (where w is the water content and w_L the liquid limit), and its comparison with experimentally determined strength values. The findings indicate that cu/qu decreases significantly with increasing relative moisture content, reflecting a reduction in shear resistance due to the higher water content. For the investigated high-plasticity clay (CH), the variation in the internal friction angle with increasing moisture content was also analyzed, while cohesion was found to be negligible.

In practical applications, a simplified empirical relationship is often used:

$${\mathrm{c}}_u={\mathrm{q}}_u/2,$$

(7)

This relationship was first proposed in the works of Skempton (1957) [27] and Terzaghi and Peck (1967) [28]. However, it is only valid for consolidated, saturated clays under undrained conditions. The relationship becomes less reliable when the moisture content or plastic properties of the soil change. Therefore, the concept of relative humidity w/wL was later introduced, which allows comparison of different clays regardless of their absolute water content.

Since moisture content strongly affects consistency and thus mechanical properties, normalization with relative humidity w/w_L was introduced, which allows a more universal comparison of clays. Wroth and Wood (1978) [29] examined the correlation between soil index properties and fundamental engineering properties. Based on experimental data, they demonstrated that basic mechanical characteristics of soils, such as strength and stiffness, can be reliably estimated from easily measurable index parameters, including water content, plastic limit, and density. This makes their findings especially useful for preliminary design and site characterization. Holtz et al. (2011) [30], in their comprehensive textbook, An Introduction to Geotechnical Engineering, cover a broad range of geotechnical topics, from soil classification and behavior to the principles of foundation design, settlement, bearing capacity, and slope stability. Mitchell and Soga (2005) [31], in Fundamentals of Soil Behavior, focus on the microscopic and physicochemical understanding of soil behavior, discussing the influence of mineralogy, particle interactions, and pore fluid chemistry on macroscopic mechanical properties. ASTM Standard D2487-17e1 (2017) [32] defines the Unified Soil Classification System (USCS), which provides a standardized framework for classifying soils for engineering purposes and ensures consistency in communication and interpretation among practitioners. Grim (1968) [33], in Clay Mineralogy, offers a detailed examination of clay minerals, discussing their structure, physical and chemical properties, and their significance in both natural and engineered environments.

Terzaghi and Peck (1967) [28] emphasized that for saturated, purely cohesive soils with no internal friction, the undrained shear strength (c_u) can be estimated as one-half of the unconfined compressive strength (q_u), as expressed in Equation (7).

Das (2007) [34] confirms the validity of this classical relationship but notes that deviations are frequently observed in practice. He attributes lower c_u values to factors such as partial saturation, the presence of internal friction, sample heterogeneity, and experimental errors in laboratory testing. In such cases, the ratio of c_u to q_u may fall below 0.5.

Craig (2004) [35] further stresses that natural soils often deviate from idealized models, highlighting the importance of understanding the specific behavior of each tested sample.

3.5. Uniaxial Compressive Strength of CH Clay

The CH clay exhibits high compressive strength at low moisture content, which decreases significantly with increasing water content. At a moisture content of w = 10%, the measured uniaxial compressive strength is q_u = 1200 kPa, which, based on the simplified empirical correlation, corresponds to an undrained shear strength of c_u = 600 kPa. At w = 20%, the compressive strength is slightly lower, with q_u = 900 kPa, while at w = 30%, the uniaxial compressive strength drops sharply to only q_u = 120 kPa.

Within the range of relative water content w/w_L = 0.20 to 0.60, the ratio c_u/q_u ≈ 0.5 is considered realistic. However, at higher relative water contents—closer to saturation—a significant reduction in this ratio is expected, indicating a loss of shear resistance with increasing pore water content.

An empirical exponential relationship proposed by O’Kelly (2013) [35] is used to describe the dependency of the undrained shear strength on the unconfined compressive strength ratio on the normalized water content:

$$c_u/q_u=A·e^{-B·(w/w_L)},$$

(8)

where:

• c_u = undrained shear strength,
• q_u = unconfined compressive strength,
• w = natural water content of the soil (%),
• w_L = liquid limit (%),
• A = empirical coefficient representing the maximum value of the c_u/q_u ratio at very low water content,
• B = empirical exponent controlling the rate at which the ratio decreases with increasing normalized water content (w/w_L).

This relationship captures the exponential decay of shear strength relative to compressive strength as water content increases, and it enables better comparison between soils with different plasticities.

The parameters A and B must be determined empirically based on tests conducted on the specific soil type under investigation. The form of the relationship used in this study is summarized in Equation (9).

$$c_u/q_u=0.55·e^{-1.5·(w/w_L)},$$

(9)

This equation effectively captures the reduction in strength for different clay types. It has been validated against experimental data and shows good agreement with observations for CH clays, where a sharp decrease in strength is evident at higher values of normalized water content (w/w_L).

Figure 7 illustrates the decrease in the c_u/q_u ratio as a function of increasing relative water content (w/w_L), in accordance with Equation (9).

3.6. Sensitivity Assessment

The maximum range of soil sensitivity can be estimated as follows:

$$S_t=c_{u,max}/c_{u,min},$$

(10)

This result (S_t ≈ 1200/120 = 10) indicates that the clay exhibits a sensitivity of approximately 10, which classifies it as a highly sensitive material. Such behavior is characteristic of montmorillonitic clays or quick clay–type soils, where even slight disturbances or increases in moisture content can cause a significant reduction in shear strength.

In practice, this means that the soil, when dry, may present a misleadingly high bearing capacity. However, even a small change in moisture content can lead to a substantial loss of strength. This reflects the high sensitivity of the studied clay, quantified by a sensitivity index of approximately St ≈ 10, indicating that the undrained shear strength decreases sharply with minor increases in moisture content. Such behavior is characteristic of high plasticity clays (CH), especially montmorillonitic and quick clays, where small moisture variations weaken particle bonding and disrupt soil structure.

As the pore water content increases, the resulting rise in pore water pressure reduces the effective stress in the soil—a key factor controlling its mechanical performance. This reduction directly leads to lower shear resistance and bearing capacity, making the soil vulnerable to settlement, swelling, and slope instability. Therefore, strict control of drainage and hydrological conditions is crucial to ensure the long-term stability and reliability of structures built on or within such soil.

Figure 8 illustrates the correlation between undrained shear strength (c_u) and electrical conductivity. The observed relationship is clearly nonlinear, indicating that changes in electrical conductivity do not correspond to proportional changes in shear strength. Instead, the correlation suggests a more complex interaction, where shear strength decreases more rapidly at higher conductivity levels, particularly in the moisture range approaching saturation. This nonlinear trend may be attributed to the increase in pore water content, which raises electrical conductivity due to enhanced ion mobility. As saturation is approached, pore water pressure increases, leading to a significant reduction in effective stress. Both effects contribute to the observed decrease in undrained shear strength and reflect the complex interaction between moisture content, pore pressure, and soil structure.

The curve (see Equation (11)) implies that electrical conductivity can serve as an indirect indicator of shear strength, but only when its nonlinearity is properly accounted for through empirical or calibrated models.

c_u = −114,000 EC² + 7200 EC + 371.25,

(11)

Figure 9 illustrates the reduction in undrained shear strength (c_u) as a function of relative water content (w/w_L). The data clearly show that as the relative water content increases, the shear strength of the clay decreases significantly. This trend reflects the progressive weakening of the soil structure due to higher moisture levels, which reduce interparticle bonding and effective stress. The decline is nonlinear, with a particularly steep drop observed as the relative water content approaches or exceeds the plastic limit. This behavior highlights the sensitivity of high-plasticity clay to moisture changes and underscores the importance of monitoring water content in assessing the mechanical stability of such soils. The curve (see Equation (12)) presented in Figure 9 emphasizes the critical threshold beyond which the soil loses a substantial portion of its shear resistance.

c_u = −1102.2·(w/w_L) + 712.4,

(12)

Figure 10 illustrates the correlation between electrical conductivity and the measured uniaxial compressive strength (q_u) at different levels of relative water content (w/w_L). The results demonstrate that electrical conductivity, which increases with higher moisture content, is inversely related to the uniaxial compressive strength of the clay. As relative water content rises, the electrical conductivity of the soil increases due to enhanced ionic mobility and pore water connectivity, while the compressive strength decreases due to the softening and loss of interparticle cohesion. The correlation is nonlinear and reflects the complex interaction between the soil’s hydraulic and mechanical properties (see Equation (13)). This relationship suggests that electrical conductivity measurements could potentially serve as a proxy for estimating strength parameters in situ, especially in conditions where direct mechanical testing is not feasible. However, the variability introduced by different moisture levels must be carefully considered in predictive models.

EC = −0.3543·(w/w_L)² + 0.4617·(w/w_L) − 0.055,

(13)

The results also show that the relationship between electrical conductivity (EC) and relative water content (w/w_L) is not linear but follows a decreasing trend. This indicates that as relative moisture increases, the electrical conductivity initially rises but eventually stabilizes or declines at a slower rate, reflecting saturation effects and changes in ion mobility at high water contents. For practical applications, a more suitable correlation is provided in Figure 11, which presents an exponential equation (see Equation (14)) fitted to the experimental data. This empirical model offers improved predictive capability for estimating conductivity based on moisture content, particularly in field conditions where accurate and rapid assessments are required.

$$w=6.7·e^{15.342·EC},$$

(14)

The results confirm that the use of relative humidity w/w_L is crucial for a realistic assessment of clay strength under different hydrological conditions. The empirical nonlinear relationship allows the engineer to easily assess the safety state even under variable conditions. The use of index consistency, together with laboratory data, allows for more reliable prediction of soil behavior.

4. Implementation

In this study, a methodology was developed that integrates laboratory analysis of clay soils with advanced field measurement techniques to monitor physical changes in soils, particularly moisture content, porosity, and mechanical resistance. This approach is highly relevant for various branches of geotechnical and environmental engineering, where accurate information on soil conditions is essential for stability assessment, design, and environmental impact monitoring.

The laboratory investigations focused on quantifying the relationship between the electrical resistivity of soils and their mechanical properties. Measurements on samples taken from boreholes included gravimetric determination of water content, electrical resistivity measurements using a two-electrode method, and mechanical tests such as strength, cohesion, and elastic modulus. The results consistently demonstrated a correlation between moisture content and electrical resistivity, with higher saturation corresponding to lower resistivity values. This finding aligns with the observations of Rembert et al. (2020) [36], who studied transport properties in unsaturated soils.

Based on these results, empirical correlations were established to enable the transfer of laboratory findings to field conditions. This calibration forms the foundation for interpreting field measurements, where electrical resistivity tomography (ERT) was selected as a key method, supported by the installation of moisture sensors (e.g., TDR, FDR) and local meteorological stations to record precipitation, temperature, and evapotranspiration data.

Field monitoring using ERT and sensors enables time-lapse (4D) observation of infiltration, saturation, and soil drying processes, allowing the detection of mechanical property changes such as reduced shear strength due to increased moisture.

Using correlation functions derived from laboratory measurements, field-acquired resistivity data can be converted into estimates of soil moisture content and, in some cases, approximate mechanical properties of the soil. This interpretation is especially valuable in geotechnical site investigations, including assessments of slope stability and landslide risk.

One of the key applications of this methodology is detecting the impacts of climate change on soils. The increasing frequency of extreme weather events (e.g., prolonged rainfall, droughts) alters the soil’s water balance, affecting shear strength and potentially causing subsidence, cracking, or even triggering landslides. Early detection of these changes through ERT and sensor networks allows timely, targeted interventions such as drainage improvements or soil reinforcement.

Moreover, the methodology is not limited to geotechnical stability but also provides effective support for geothermal applications. Electrical resistivity is directly related to soil temperature and saturation, which are critical parameters for the design and operation of shallow geothermal systems such as ground-source heat pumps.

Overall, the combined use of laboratory and field methods represents a robust, non-invasive, and adaptable tool for early detection of soil changes, risk management under climate change, and the development of sustainable energy solutions.

The tested material corresponds to high-plasticity clays (CH group, USCS), exhibiting electromechanical behavior typical of soils rich in montmorillonite and illite. Comparative data confirm that this behavior is representative of similar clay types (see

Table 3. Comparative Characteristics of Different Clay Types.

Clay Type	USCS Symbol	Liquid Limit (LL)	Plasticity Index (PI)	Consistency at Low Moisture	Behavior at High Moisture	Typical Mineral Composition
Low plasticity clay	CL	<50%	7–17	Stiff to firm	Gradual loss of strength	Mainly kaolinite, some illite
High plasticity clay	CH	>50%	>17	Very stiff at low moisture	Rapid strength loss	Dominantly montmorillonite or illite
Silt (lean clay/ML)	ML	25–50%	<7	Soft	Slight strength reduction	Fine quartz, mica, and minor clay minerals
Montmorillonitic clay (e.g., bentonite)	CH	60–100%	>30	Extremely stiff when dry	Extreme sensitivity and swelling	Predominantly montmorillonite
Kaolinitic clay	CL	30–50%	10–20	Stiff	Moderate change in strength	Primarily kaolinite
Illitic clay	CL/CH	30–60%	10–25	Firm to stiff	Moderate strength loss	Primarily illite, minor kaolinite/montmorillonite
Organic-rich marine clay	OH/OL	40–100%	7–17	Soft to firm	Low strength	Clay minerals with significant organic content

).

Compared to other clay types presented in Table 3, the clay from the Afyonkarahisar region exhibits characteristics typical of high-plasticity clay (CH), with a pronounced presence of montmorillonite, which strongly influences its mechanical and electrical behavior. Laboratory tests have shown that this clay is highly sensitive to moisture content changes, exhibiting a rapid decrease in shear strength with increasing water content. This behavior is characteristic of montmorillonite-rich clays and contrasts with lower-plasticity clays such as kaolinitic clays, which show moderate strength variations, or illitic clays, which exhibit intermediate strength losses. Afyonkarahisar clay is notable for its high stiffness in dry conditions; however, it undergoes significant strength loss and increased electrical conductivity as saturation increases. Understanding these distinctions is essential for the proper application of empirical models and for reliably extrapolating findings to other geological contexts.

Afyonkarahisar clay falls within the high plasticity (CH) classification, with a liquid limit close to the 50% threshold and a relatively high plasticity index of 25.6%. These characteristics place it near a borderline classification, distinguishing it from other regional clays. Additionally, engineering parameters such as specific gravity, optimum water content, and dry density suggest that this clay may require specialized soil improvement techniques. Consequently, Afyonkarahisar clay represents a unique and important case study for both local engineering projects and comparative soil research.

5. Conclusions and Recommendations

This study demonstrates a strong and consistent coupling between water content, mechanical behavior, and electrical resistivity in clayey soils. Laboratory tests under uniaxial compression showed that resistivity is influenced by both moisture level and stress stage. At low moisture content (10%), resistivity initially decreased due to compaction and then increased as microcracks formed. At higher moisture levels (20% and 30%), resistivity decreased steadily with increasing stress, reflecting improved ionic mobility and higher conductivity. The tested material, classified as high-plasticity clay (CH group, USCS), exhibits electromechanical responses typical of montmorillonite- and illite-rich soils, and the results are consistent with similar clay types.

Furthermore, the shear strength of unsaturated Afyon clay was found to decrease linearly with increasing moisture content, confirming the dominant role of water in controlling strength parameters. This trend aligns with established literature and reflects the high sensitivity of such soils to saturation. However, the empirical relation shows limited validity at high moisture levels, where it may predict unrealistically low strength values.

Although the empirical models used are based on the USCS classification system, their interpretation remains valid in practice. Nonetheless, when working within the ISO 14688 framework, it is essential to verify the compatibility of classification parameters to ensure accurate application of such models.

Electrical resistivity was confirmed as a practical, non-destructive indicator of mechanical changes, with clear potential for use in monitoring soil behavior during compaction, infiltration, and slope deformation. When combined with techniques such as electrical resistivity tomography (ERT) or electrical impedance tomography (EIT), it enables spatially resolved, real-time observation of moisture dynamics.

Based on these findings, we propose a site-specific monitoring system that integrates calibrated electrical resistivity measurements with in situ moisture sensors and meteorological data. Periodic ERT surveys and borehole-based measurements would enable continuous tracking of subsurface moisture and its impact on mechanical stability.

This study was limited to the clay from the Afyonkarahisar region. The findings are consistent with previous research on montmorillonite- and illite-rich clays, highlighting the strong influence of moisture content on the mechanical behavior and electrical resistivity of soils. Similar to Budhu (2015) [26], Das (2007) [34], and Craig (2004) [14], our results show a rapid decrease in shear strength with increasing water content, which is characteristic of high-plasticity clays. We also observed a decrease in electrical resistivity with increasing moisture and loading, aligning with prior findings on enhanced ionic mobility and microstructural changes. Differences arise when compared to clays with lower plasticity or different mineralogical compositions, such as kaolinitic or organic-rich clays, where changes in mechanical and electrical properties are typically more moderate or driven by different mechanisms. This underscores the critical role of mineral composition and plasticity in determining the electromechanical behavior of soils.

Overall, this study contributes to a broader understanding of soil mechanics by confirming the utility of electrical resistivity as a non-invasive indicator of moisture and mechanical changes in specific clay types. For future research, it is recommended to test a wider range of soils with varying mineralogical compositions and environmental conditions to develop more generalized models applicable across diverse geotechnical scenarios.

Future research should also explore other clay types with varying mineralogy and structure to generalize the observed relationships. Additional studies are needed on the effects of cyclic loading and environmental variability on electromechanical coupling. Developing coupled hydro-mechanical-electrical models, validated through empirical data, will be critical for scaling these approaches to real-world geotechnical applications.

In summary, integrating electrical monitoring into geotechnical engineering offers a robust and non-invasive approach for early detection of instability in clay-rich formations. It supports safer design, better risk management, and improved resilience of infrastructure in the face of moisture-driven failures.

6. Limitations

Despite its strengths, this study acknowledges several limitations that should be considered when interpreting and applying the results to broader contexts.

Firstly, based on geomechanical characteristics and laboratory test data, the investigated clay from Afyonkarahisar most closely corresponds to the CH classification (high plasticity clay) according to the Unified Soil Classification System (USCS) and to ClH according to the Classification System ISO 14688-1. While this provides a consistent basis for analysis, it inherently limits the generalizability of the findings. To broaden the applicability of the research outcomes, future studies should include other clay types with varying mineralogical compositions and plasticity characteristics, as outlined in Table 2.

Secondly, the experimental program was limited to uniaxial compression tests. Although these tests are valuable for initial material characterization, they do not fully represent the complex stress conditions encountered in situ. For a more comprehensive understanding of clay behavior under realistic geotechnical conditions, future investigations should incorporate direct shear and triaxial tests. The integration of these methods with electromechanical measurements could reveal important interdependencies between mechanical loading modes and electrical responses.

Thirdly, while laboratory testing allows for controlled experimental conditions, it cannot fully replicate field environments. Therefore, to assess the practical relevance and predictive value of the laboratory results, complementary field investigations are essential.

Additionally, the empirical equation used to describe the dependency of the undrained shear strength to unconfined compressive strength ratio on the normalized water content involves material-specific parameters. These parameters must be calibrated individually for each representative soil type to ensure accurate and meaningful predictions. Without such calibration, the applicability of the empirical relationship to different soils remains limited and may lead to misleading interpretations.

Lastly, it should be noted that Figure 8, Figure 9, Figure 10 and Figure 11 present results based on only three data points, each corresponding to uniaxial compression tests conducted at carefully selected moisture contents (10%, 20%, and 30%). These moisture levels were chosen based on preliminary material characterization and represent typical field-relevant conditions for high-plasticity clays. While a larger dataset could enhance the statistical robustness of the fitted curves, the primary aim here was to illustrate the general trends and qualitative relationships between moisture content, shear strength, and electrical resistivity. Future work will consider denser sampling of moisture conditions to improve the resolution and reliability of the fitting analysis.

These limitations point to key areas for future research. Expanding the study to include different clay types, employing a wider range of mechanical testing methods, and validating findings under field conditions are crucial steps toward a more complete understanding of the electromechanical behavior of clays in engineering contexts.