Theoretical analysis and application of the telluric electric field frequency selection method for shallow groundwater exploration

The telluric electric field frequency selection method (TEFSM) measures horizontal electric field components at discrete frequencies of naturally occurring electromagnetic (EM) fields. Developed as an extension of magnetotellurics (MT) and audio-frequency magnetotellurics (AMT), TEFSM offers potential for shallow groundwater exploration, yet its underlying mechanisms and practical effectiveness remain underexplored. Here, we combine theoretical analysis, forward modeling, and field validation to assess its performance. A conductive sphere model subjected to magnetotelluric and stray current fields was used to compute secondary surface responses, revealing low-potential anomalies directly above the target. The anomaly amplitude decreases with increasing burial depth and decreasing sphere radius. Field validation under the Rural Drinking Water Safety Project in Guangxi Province, China, involved 131 TEFSM-guided wells drilled to depths of up to 142.8 m. Of these, 114 yielded >1 m³/h, corresponding to an ∼87% success rate. The close agreement between simulations and field outcomes demonstrates that TEFSM reliably detects shallow conductive structures and is an effective tool for groundwater exploration.

1 Introduction

Groundwater plays a crucial role in sustaining human survival and socioeconomic development (Rahman et al., 2025), yet it can also contribute to geological hazards (Yang et al., 2021). Consequently, accurate detection and exploration of groundwater are both significant and necessary. Geophysical techniques commonly employed in groundwater exploration include seismic methods (Wei et al., 2025), potential-field approaches (Adiat et al., 2013), geoelectric and electromagnetic methods (Agyemang, 2022; Song et al., 2021), self-potential measurements (Robert et al., 2011), and surface nuclear magnetic resonance techniques (Li et al., 2015). The telluric electric field frequency selection method (TEFSM), also known as the frequency selection method (FSM), was developed by Chinese researchers in the 1980s, drawing on the principles of magnetotellurics (MT) and audio-frequency magnetotellurics (AMT) (Yang, 1982; Han and Wu, 1985; Gomo, 2024). TEFSM is a passive-source electromagnetic (EM) technique that exploits differences in subsurface conductivity. Unlike MT and AMT, TEFSM measures only the horizontal electric field components of the magnetotelluric field at the Earth’s surface. The method is valued for its simplicity, portability, and efficiency, and it has been successfully applied in shallow groundwater exploration (Alabi et al., 2020; Isah et al., 2023; Bassey et al., 2024) as well as in disaster detection (Adagunodo et al., 2023; Melchinov and Pavlov, 2022; Yang et al., 2024). Its operational frequency typically ranges from 10 to 2,000 Hz, with an exploration depth generally limited to about 300 m. Because TEFSM relies on naturally occurring electromagnetic fields, its source characteristics are inherently complex. Multiple factors can contribute to the primary field source, and their relative influence may vary considerably across different exploration environments. Given that TEFSM employs measurement principles similar to those of MT and AMT, their field sources are generally comparable in areas with minimal cultural interference (Kingston et al., 2022; Yang et al., 2023; 2025), although these studies only consider the influence of the natural magnetotelluric field. Moreover, certain exploration results were obtained under conditions where power supply across the entire survey area had been disconnected (Yang et al., 2023). In contrast, in anthropogenic environments such as villages, towns, and industrial zones, stray currents can significantly distort TEFSM measurements (Yang, 1982; Bao et al., 1994), and such investigations typically focus solely on the effects of stray current. Lu et al. (2023) further studied TEFSM sounding from the perspective of stray current interference. However, it is important to distinguish between TEFSM sounding and TEFSM profile exploration. The former involves a fixed observation point with progressively increasing electrode spacing (MN) to analyze how the potential difference (ΔV_MN) varies with electrode separation. The latter maintains a constant MN distance while moving both electrodes forward synchronously along survey lines to map lateral variations in ΔV_MN. Previous studies (Yang and Zhang, 2013; Yang et al., 2016; Yang et al., 2017) have analyzed the origins of anomalies in TEFSM profiles using both stray current and magnetotelluric theories, respectively, showing that each framework provides valuable perspectives for interpretation. This study evaluates the effectiveness of TEFSM for shallow groundwater exploration, with particular attention to the combined action of stray currents and magnetotelluric fields. This study focuses specifically on analyzing the origins and exploration implications of anomalies in TEFSM profile data. Specifically, it investigates the causes of profile anomalies from a three-dimensional perspective, incorporating the complexity of natural field sources. In addition, the contributions of horizontal electric and magnetic field components associated with stray currents and magnetotelluric field to TEFSM anomalies are systematically assessed.

2 Methodology

2.1 Basic theory of TEFSM

TEFSM operates as a passive-source method in which the generation of anomalous electric fields is inherently complex. In this study, we consider the primary field source of TEFSM to consist of two components. The first is the alternating electromagnetic field induced by external geophysical processes, analogous to the field source in MT. The second originates from anthropogenic activities at the Earth’s surface, including industrial stray currents and human-induced electromagnetic interference (Yang et al., 2017). In practice, TEFSM commonly employs three frequencies (25, 67, and 170 Hz) for rapid exploration. Among these, the 67 Hz signal is typically the most prominent (Liang et al., 2016), likely due to its proximity to China’s industrial power frequency of 50 Hz, which coincides with the frequency of underground stray currents. Numerous studies have shown that TEFSM generally achieves exploration depths of less than 300 m in groundwater surveys. According to the controlled-source audio-frequency magnetotelluric (CSAMT) principle, an observation station resides in the far-field zone when the distance between the receiver and transmitter exceeds three times the skin depth (Zhang et al., 2025). In our TEFSM applications, proactive measures are taken to reduce anthropogenic interference, allowing alternating electromagnetic fields generated by surface activities to be effectively treated as far-field contributions. Consequently, the TEFSM field source can be conceptualized as a vector superposition of magnetotelluric fields and anthropogenic electromagnetic interference. Although other underground electromagnetic signals from human activities may exist, they are beyond the scope of this study. Based on this framework and the far-field characteristics of CSAMT, the natural alternating primary field source signal at depth can be described within a rectangular coordinate system (Figure 1) as comprising horizontal electric field components (Ex and Ey), horizontal alternating magnetic field components (Hx and Hy), and the vertical alternating electric field component (Ez). These represent the vector sum of all natural electromagnetic and stray current fields. The vertical magnetic field component (Hz) is assumed negligible. Because observation stations are located in remote far-field zones with minimal anthropogenic disturbance, stray currents are considered to contribute only horizontal components. Likewise, the geomagnetic field, propagating nearly perpendicular to the Earth’s surface, is treated as having only horizontal components (Yang et al., 2016). Moreover, TEFSM records solely the horizontal electric field components; the vertical electric field (Ez) does not influence measurements and can be disregarded. Assuming harmonic behavior of all electromagnetic field components, a coordinate system can be established (Figure 2) for the case of a highly conductive sphere embedded in a homogeneous half-space.

Figure 1

Figure 1. Schematic diagram of underground natural alternating electromagnetic field components.

Figure 2

Figure 2. A sphere in a natural alternating electromagnetic field within a homogeneous half-space.

From the preceding analysis and as illustrated in Figure 2, it is evident that, during TEFSM-based surface exploration, only the natural primary electromagnetic field components Ex, Ey, Hx, and Hy interact with the conducting sphere. Because free charges cannot accumulate in a medium with finite conductivity (σ ≠ 0), the propagation of the magnetotelluric field is governed by Maxwell’s equations. Accordingly, the electric field E, magnetic field H, electric displacement D, and magnetic flux density B satisfy the following fundamental relations:

$\nabla \times \mathit{E}=-\mu ·\frac{\mathit{\partial }\mathit{H}}{\mathit{\partial }t}(1)$

$\nabla \times \mathit{H}=\sigma ·\mathit{E}+\epsilon ·\frac{\mathit{\partial }\mathit{E}}{\mathit{\partial }t}(2)$

$\nabla ·\mathit{D}=\mathbf{0}(3)$

$\nabla ·\mathit{B}=\mathbf{0}(4)$

Equations 1– 4 are the Maxwell equations. By applying the method of separation of variables (Ward, 1971; He, 2012), the components of the secondary electric field (E₂) generated by the primary magnetic field component H_x in Figure 2 are expressed in Equations 5, 6.

$E_{2y}=-\left[C_1{J}_{3/2}\left(k_{2}r\right)+D_1{J}_{-3/2}\left(k_{2}r\right)\right]\frac{1}{\sqrt{k_{2}r}}\frac{z}{\sqrt{x^2+y^2+z^2}}(5)$

$E_{2z}=\left[C_1{J}_{3/2}\left(k_{2}r\right)+D_1{J}_{-3/2}\left(k_{2}r\right)\right]\frac{1}{\sqrt{k_{2}r}}\frac{y}{\sqrt{x^2+y^2+z^2}}(6)$

Similarly, the secondary electric field components induced by the primary magnetic field component H_y can be computed using Equations 7, 8.

$E_{2z}=-\left[C_1{J}_{3/2}\left(k_{2}r\right)+D_1{J}_{-3/2}\left(k_{2}r\right)\right]\frac{1}{\sqrt{k_{2}r}}\frac{x}{\sqrt{x^2+y^2+z^2}}(7)$

$E_{2x}=\left[C_1{J}_{3/2}\left(k_{2}r\right)+D_1{J}_{-3/2}\left(k_{2}r\right)\right]\frac{1}{\sqrt{k_{2}r}}\frac{z}{\sqrt{x^2+y^2+z^2}}(8)$

where J_3/2 (kr) and J_-3/2 (kr) denote Bessel functions of complex arguments, and k₂ represents the wave number of the surrounding rock, defined as k₂² = ω²ε₂μ₂-iωμ₂σ₂, where i is the imaginary unit with i² = −1. The coefficients C₁ and D₁ are formulated as follows:

$C_1=-\frac{\mathrm{i}\omega 3\sqrt{\mathrm{\pi }}{\mu }_1{\mu }_2{H}_{\mathrm{P}}{k}_1^2{a}^3}{2\sqrt{2}\left\{\left({\mu }_2-{\mu }_1\right)p_1\cos p_1-\left[{\mu }_2\left(1-p_1^2\right)-{\mu }_1\right]\sin p_1\right\}}(9)$

$D_1=-\frac{a^3}{2\sqrt{2}}\frac{\left(2{\mu }_1+{\mu }_2\right)p_1\cos p_1-\left[{\mu }_2\left(1-p_1^2\right)+2{\mu }_1\right]\sin p_1}{\left({\mu }_2-{\mu }_1\right)p_1\cos p_1-\left[{\mu }_2\left(1-p_1^2\right)-{\mu }_1\right]\sin p_1}\mathrm{i}\omega \sqrt{\mathrm{\pi }}{\mu }_2{k}_2^2{H}_{\mathrm{P}}(10)$

where p₁ = k₁a, and k₁ is the wave number of the spherical medium. If the displacement current is neglected, k₁² = -iωμ₁σ₁ (Equations 9, 10).

When considering the two horizontal components E_x and E_y of the alternating electric field in Figure 2, an approximate solution can be derived by referencing the analytical solution for a conducting sphere in a uniform electrostatic field (Ward, 1971; Yang, 1982). If the focus is solely on the anomalous field, the potential of this anomalous field on the surface is described by the following expression:

$U_p=2\frac{{\sigma }_1-{\sigma }_2}{{\sigma }_1+2{\sigma }_2}{\left(\frac{a}{r}\right)}^3\frac{j_0}{{\sigma }_2}r\sin \theta {\mathrm{e}}^{\mathrm{i}\omega t}(11)$

In electrical prospecting, the measured quantity is typically the potential gradient, which corresponds to the electric field intensity of the anomalous field. Based on Equation 11, the induced secondary electric field components E_2y and E_2x along the main surface profile aligned with the y-axis (x = 0) can be calculated using Equations 12, 13, respectively:

$E_{2y}=2\frac{{\sigma }_1-{\sigma }_2}{{\sigma }_1+2{\sigma }_2}{a}^3\frac{j_0}{{\sigma }_2}\frac{2y^2-h_0^2}{{\left(y^2+h_0^2\right)}^{5/2}}{\mathrm{e}}^{\mathrm{i}\omega t}(12)$

$E_{2x}=2\frac{{\sigma }_1-{\sigma }_2}{{\sigma }_1+2{\sigma }_2}{a}^3\frac{j_0}{{\sigma }_2}\frac{-1}{{\left(y^2+h_0^2\right)}^{3/2}}{\mathrm{e}}^{\mathrm{i}\omega ·t}(13)$

where, h₀ represents the depth of the center of the sphere, and j₀ = E₀/ρ₂.

According to electromagnetic field theory, the electric and magnetic components of a time-harmonic uniform plane electromagnetic wave propagating along the negative z-axis (as shown in Figure 2) are mutually dependent. If one component (electric or magnetic) is known, the orthogonal counterpart can be derived (Ward, 1971). Assuming E₀ = be^iΨ, where b and Ψ are real-valued quantities and Ψ is referred to as the phase angle, the electric field components propagating along the negative z-direction are expressed as:

$E_x=E_y=E_0{\mathrm{e}}^{-\mathrm{i}\left(kz-\omega t\right)}=b{\mathrm{e}}^{\mathrm{i}\psi }{\mathrm{e}}^{\mathrm{i}\left(\omega t-kz\right)}(14)$

where e^-i(kz−ωt) represents propagation in the negative z-direction (Equation 14). The corresponding primary magnetic field components are then derived according to the electromagnetic wave theory and are given in Equation 15.

$H_y=b{\mathrm{e}}^{\mathrm{i}\mathrm{\Psi }}{\mathrm{e}}^{-\mathrm{i}\left(kz-\omega t\right)}\times k/\left(\omega \mu \right)\text{\hspace{0.17em}and\hspace{0.17em}}{H}_x=-b{\mathrm{e}}^{\mathrm{i}\mathrm{\Psi }}{\mathrm{e}}^{-\mathrm{i}\left(kz-\omega t\right)}\times k/\left(\omega \mu \right)(15)$

2.2 FSM method

In practical exploration, the TEFSM primarily measures horizontal electric field components along the survey line at the surface (Figure 3a). The potential electrodes, M and N, are placed along measuring lines or profiles with fixed spacing, while point O, located at the midpoint of MN, serves as the recording station. Typically, the electrode spacing MN is set to 10 m or 20 m. At each observation point, potential differences (△V) are recorded across multiple frequencies, producing potential difference curves along the profile (Figure 3b). Variations in these curves are used to infer the horizontal position of anomalous bodies. The TEFSM sounding configuration is analogous to conventional vertical electrical sounding methods, particularly the Schlumberger array, but differs in that it does not require power supply electrodes A and B. Measurements are taken at point O—the midpoint of MN—as shown in Figure 3b. The potential electrodes M and N are expanded outward synchronously, typically in 10 m increments, although this may be reduced to 2 m under specific conditions. As the spacing MN increases (Figure 3b), the exploration depth also increases, allowing potential difference variations with depth to be resolved at specific sounding points. This enables the estimation of anomalous body burial depths from TEFSM sounding curves (Yang et al., 2020).

Figure 3

Figure 3. (a) Schematic diagram of a profile survey device; (b) schematic diagram of a TEFSM sounding device.

3 Simulation analysis

Assuming that the resistivity (ρ₁) of a water-filled sphere depicted in Figure 2 is measured at 50 Ω m with its center buried at a depth (h₀) of 40 m and possessing a radius (a) of 2.0 m while surrounding rock has a resistivity (ρ2) of approximately 3000 Ω m—both materials being non-magnetic—the values for dielectric constants (ε₁ and ε₂) can be disregarded when displacement current effects are neglected. It is assumed that equal-sized alternating electric fields exist in the underground half-space along both the x and y directions, specifically represented as E₀ = be^iψ = 0.3e^iψ V/m. The phase angle ψ is set to 0, as variations in ψ do not affect the amplitude of the potential. Furthermore, the corresponding magnitudes of the alternating magnetic field in both x and y directions can be determined using Equation 15.

The secondary anomalous electric field |E_2y| along the surface main profile in the y direction, illustrated in Figure 4a, can be calculated using Equations 5, 12 when the frequency f of the alternating magnetic field is set at 25 Hz. Similarly, |E_2x| for the surface main profile along this same direction can be derived from Equations 8, 13. Given that in-situ exploration typically measures only those components of electric fields aligned with survey lines (as shown in Figure 2a), subsequent calculations will focus exclusively on values pertaining to |E_y|.

Figure 4

Figure 4. Forward modelling results of |E_y| along the y-axis of the survey line at the surface. (a) f = 25 Hz (b) f = 170 Hz.

Figure 4a presents results for three different burial depths of a sphere when f equals 25 Hz. These results indicate that |E_y| diminishes with increasing burial depth while also showing a significant reduction in relative anomaly amplitude. Figure 4b illustrates how |E_y| varies with sphere radius; notably, anomaly amplitude increases alongside sphere radius. The forward response curve is symmetric, characterized by a distinct minimum directly above the sphere and flanked by local maxima. This minimum coincides with the center of the low-resistivity sphere, offering a reliable indicator for locating subsurface conductive materials.

4 Case studies

As a primary geophysical exploration technique, the telluric electric field frequency selection method (TEFSM) has played a vital role in shallow groundwater prospecting within Guangxi Province’s Rural Drinking Safety Project under China’s 12th Five-Year Plan (Liang et al., 2016; Yang et al., 2020). Based on TEFSM survey results, a total of 131 wells were drilled (Table 1), with a maximum depth of 142.8 m. Of these, 17 wells were unsuccessful, yielding ≤1 m³/h, while 29 wells produced between one and <5 m³/h. The remaining 85 wells yielded ≥5 m³/h and were classified as successful. This corresponds to an overall success rate of approximately 64.9%. When wells producing 1–5 m³/h are also considered successful, the rate increases to about 87.0%. These results demonstrate that TEFSM is an effective tool for shallow groundwater exploration. Additionally, the instrument used in the groundwater explorations is the JK-E frequency selector manufactured by Beijing Jieke Entrepreneurship Co., Ltd.

Table 1

Table 1. Applications of TEFSM in the rural drinking water safety project of the 12th five-year plan in Guangxi province.

The application examples discussed herein are primarily conducted in rural areas and adjacent zones, where spatial constraints are common. Additionally, conventional resistivity methods are often too time-consuming to meet the urgent demands of groundwater exploration. Hence, TEFSM was selected as the primary exploration technique.

To illustrate the specific application effects of TEFSM, this paper will discuss the exploration results from two villages mentioned above: Geshuitang Village and Qingshui Village, both located in Guangxi Province, China (as shown in Figure 5).

Figure 5

Figure 5. Geological overview and schematic layout of geophysical survey lines in (a) Geshuitang Village and (b) Qingshui Village.

4.1 Geshuitang Village

Geshuitang Village is located between latitudes 24°45′34″and 24°46′33″N and longitudes 110°39′03″and 110°40′08″E, covering an area of approximately 3 km² (Figure 5a). The region has a mean annual temperature of 19.9 °C and receives 1,355–1,865 mm of rainfall annually. The village lies on the west bank of the Gongcheng River, where the geology is dominated by calcareous rocks with well-developed karst features. The terrain is relatively flat, with elevations ranging from 97 to 107 m above mean sea level (a.m.s.l.) in the plains and from 187 to 342 m in the surrounding hills. Relative relief varies between 91 and 235 m. The bedrock consists primarily of Upper Devonian (D3) limestone with shallow weathered rock fissures. Although no bedrock outcrops are exposed at the surface, subsurface karst features—including sinkholes, caves, and voids—are present. Borehole data confirm the existence of deep karst fissures within the limestone bedrock. The upper soil layer (Qh) generally comprises clayey sand and loam, underlain by sandy gravel deposits containing pore water. The thickness of the upper soil typically ranges from 3.5 to 7.0 m. On the northwestern and northeastern sides of Geshuitang Village, Upper Devonian (D3) thick-bedded limestone and gray-black thin-bedded siliceous rock are predominant, with formation thicknesses ranging from 119.0 to 410.0 m.

Figures 6a,b present the three-frequency prospecting results obtained using the telluric electric field frequency selection method (TEFSM) along survey line BB′, together with the sounding results at point 20/BB′. For both profile prospecting and point sounding, electrode spacing (MN) during in-situ surveys was set at 10 m intervals, with incremental increases in MN also measured at 10 m intervals during TEFSM soundings. Previous research by Lu et al. (2023) has specifically investigated anomaly mechanisms in TEFSM sounding, for which the effective exploration depth is approximately equal to the MN electrode spacing.

Figure 6

Figure 6. (a) Profile BB’ survey results; (b) TEFSM sounding results at point 20/BB’ in Geshuitang Village; (c) schematic geological section along BB’.

As shown in Figure 6a, apparent low-potential anomalies were identified at measuring points 11 and 20 on survey line BB′. However, no anomalies were observed near measuring point 11 on the adjacent parallel profile CC′ during follow-up exploration. Consequently, measuring point 20 was selected for sounding. The resulting TEFSM sounding curves reveal a distinct V-shaped valley anomaly at MN = 50 m (Figure 6b). Based on prior experience, this anomaly suggests that groundwater is likely present at a depth of approximately 50 m. Drilling was therefore conducted at location 20/BB′, with a final borehole depth of 102.20 m. Drilling data indicate that the first 10 m comprise yellow-brown residual clay with minor fine sand and pebbles. Below this depth, gray, fine-grained, medium-to thick-bedded limestone is encountered, characterized by well-developed joints and dissolution features. The recovered core is predominantly columnar, ranging from short to long fragments. Karst cavities filled with clay were observed between 15.20 and 16.40 m. Between 54.00 and 62.00 m, fissures are highly developed, and water inflow occurred during drilling, indicating that this interval constitutes the main aquifer tapped by borehole PL10 (Figure 6c). The well yields more than 5 m³/h of water, with a maximum drawdown of only 5 cm under pumping with a 5-ton pump. Thus, the aquifer depth determined from drilling is approximately 58.0 m. The ratio of the anomalous electrode spacing (MN = 50 m) to the aquifer depth (58.0 m) is approximately 0.86.

4.2 Qingshui Village

Qingshui Village is located between latitudes 23°35′52″and 23°36′51″N and longitudes 109°41′23″and 109°42′16″E, covering an area of approximately 8.4 km² (Figure 5b). The region has an average annual temperature of 21.2 °C and an average annual rainfall of 1,291.7 mm. The village lies in the south-central part of a karstic quasi-plain on the eastern bank of the Qianjiang River. The terrain is relatively flat, with elevations ranging from 39 to 63 m above mean sea level. The underlying bedrock is primarily Carboniferous (C) limestone, although no outcrops are exposed at the surface. Borehole data reveal that solution pores, caves, and fissures are well-developed in parts of the bedrock, some of which are filled with clay and calcite veins. Preliminary drilling from earlier investigations further confirms significant karst development in the subsurface strata. The overburden comprises an upper layer of brownish-yellow clay and a lower clayey soil with gravel, with a combined thickness of 10–30 m. Beneath the Quaternary cover, the Middle Carboniferous Dapu Formation (C2d) is predominantly distributed, consisting of medium-to thick-bedded dolomite interbedded with limestone and dolomitic limestone, with a thickness ranging from 345 to 660 m.

As illustrated in Figure 7a, a relatively low-potential anomaly occurs at measuring point 20/FF′, with the most pronounced low-value anomaly observed at 67 Hz. TEFSM sounding at this location shows that the curves for the three frequencies follow nearly identical trends, characterized by a steady increase with increasing MN spacing, except for a plateau at MN = 50 m (Figure 7b). This feature suggests a groundwater depth of approximately 50 m. Drilling results at point 20/FF′ confirm groundwater occurrence at 54.5–55.0 m depth. The overlying formation from 0 to 13.5 m consists of yellow clay, while the underlying section from 13.5 to 84.4 m is composed of dark-gray, fractured, and jointed limestone. The well yields more than 5 m³/h of water (Figure 7c). Accordingly, the ratio of the anomalous electrode spacing (MN = 50 m) to the groundwater depth (54.75 m) is approximately 0.91.

Figure 7

Figure 7. (a) Profile FF’ survey results; (b) TEFSM sounding results in Qingshui Village; (c) schematic geological section along FF’.

5 Discussion

The research work demonstrates the effectiveness of TEFSM in shallow groundwater exploration. By considering the combined effects of the magnetotelluric field and the stray current field, the influence of the horizontal electric and magnetic field components of the natural electric field on a low-resistivity water-bearing anomaly was analyzed. Based on this analysis, the mechanisms responsible for TEFSM profile anomalies were investigated.

The exploration depth of TEFSM is relatively shallow, mostly less than 300m burial depth, and is often applied in complex environmental conditions. Its primary field source is similarly complex and closely tied to the surrounding working environment. Previous studies have shown that when the magnetotelluric field is dominant, the observed anomalies are primarily attributed to the static effects commonly associated with frequency-domain electromagnetic methods (Yang et al., 2023). However, in areas near high-voltage transmission lines, the electromagnetic field signals generated by these lines may become the dominant field source (Yang et al., 2023). Or in areas with significant human interference, such as industrial zones, stray currents were traditionally considered the dominant factor (Yang, 1982). In certain cases, the field source may originate from both the geomagnetic field and the stray current field, as considered in this study. Consequently, differing interpretations of the field source leads to divergent views on the origins of observed anomalies. The practical effectiveness of the TEFSM cannot be overlooked; it has demonstrated a higher success rate and lower exploration cost in shallow groundwater detection within 300 m compared to conventional geophysical techniques. However, the complexity of its field source and the relatively limited theoretical foundation contribute to ongoing challenges. It is understandable that some scholars, particularly those without direct experience in applying TEFSM, may express skepticism. Nevertheless, continued discussion and research by the scientific community will undoubtedly facilitate the method’s advancement and refinement. Given the promising performance of TEFSM in shallow groundwater exploration, further in-depth theoretical research on this method is warranted.

Currently, there is growing interest in applying TEFSM for detecting groundwater at depths close to or even exceeding 1 km. The author argues that reducing the operating frequency is essential for achieving deeper penetration in TEFSM surveys. Under such conditions, the characteristics of the deep subsurface field source will change, leading to a reduced signal-to-noise ratio. Further theoretical analysis and experimental validation are therefore required to address these challenges.

6 Conclusion

Theoretical forward modeling results indicate that, under the influence of magnetotelluric and stray current fields, TEFSM prospecting produces distinct low-potential anomalies directly above water-bearing structures. This feature can be effectively applied in practical groundwater identification. Field applications demonstrate that TEFSM profile anomalies consistently exhibit relatively low potentials at groundwater-bearing locations, typically forming V- or U-shaped patterns. When TEFSM sounding curves display such patterns, they generally signify the presence of groundwater, with the electrode spacing (MN) at the inflection point approximating the groundwater depth. In Figures 6, 7, the 67 Hz signal is consistently the strongest, likely influenced by industrial stray currents. Moreover, the close similarity between measured groundwater anomaly curves and theoretical forward modeling results further validates the method’s reliability for groundwater exploration.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

DW: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing. TY: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing. AI: Writing – review and editing. QQ: Data curation, Investigation, Methodology, Software, Writing – original draft, Writing – review and editing. MZ: Funding acquisition, Project administration, Resources, Visualization, Writing – original draft, Writing – review and editing.

Funding

The authors declare that financial support was received for the research and/or publication of this article. This research was supported by the Science and Technology Program of the Geological Institution of Hunan Province under grant number HNGSTP202417.

Acknowledgements

We gratefully acknowledge the editors and reviewers for their insightful and constructive feedback, which has significantly contributed to improving the quality of this manuscript.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Adagunodo, T. A., Ojoawo, A. L., Anie, N. O., and Edukugho, P. O. (2023). Application of frequency selection and geoelectrical sounding methods for mapping of leachate’s pathways in an active dumpsite. SN Appl. Sci. 5, 352. doi:10.1007/s42452-023-05557-8

CrossRef Full Text | Google Scholar

Adiat, K. A. N., Nawawi, M. N. M., and Abdullah, K. (2013). Application of multi-criteria decision analysis to geoelectric and geologic parameters for spatial prediction of groundwater resources potential and aquifer evaluation. Pure Appl. Geophys. 170 (3), 453–471. doi:10.1007/s00024-012-0501-9

CrossRef Full Text | Google Scholar

Agyemang, V. O. (2022). Groundwater exploration by magnetotelluric method within the birimian rocks of mankessim, Ghana. Appl. Water Sci. 2022, 26. doi:10.1007/s13201-022-01576-9

CrossRef Full Text | Google Scholar

Alabi, A. A., Popoola, O. I., Olurin, O. T., Ogungbe, A. S., Ogunkoya, O. A., and Okediji, S. O. (2020). Assessment of groundwater potential and quality using geophysical and physicochemical methods in the basement terrain of Southwestern, Nigeria. Niger. Environ. Earth Sci. 79, 364. doi:10.1007/s12665-020-09107-y

CrossRef Full Text | Google Scholar

Bao, G., Li, D., and Zhang, Y. (1994). Research on the interfering electric field instrument. Chin. J. Nonferrous Metals 4 (4), 9–13.

Google Scholar

Bassey, E. N., Ajani, O. O., Isah, A., and Adeniji, A. A. (2024). Geophysical investigation of groundwater potential in iwo, Osun state, Southwestern Nigeria using audiomagnetotelluric method. Results Geophys. Sci. 16, 100066. doi:10.1016/j.ringps.2023.100066

CrossRef Full Text | Google Scholar

Gomo, M. (2024). Exploring deeper groundwater in a dolomite aquifer using telluric electric frequency selection method geophysical approach. Groundw. Sustain. Dev. 26, 101265. doi:10.1016/j.gsd.2024.101265

CrossRef Full Text | Google Scholar

Han, R., and Wu, M. (1985). Application of natural electric field frequency selection method in engineering geology. Geotechnical Investigation and Surv. 13 (3), 76–79.

Google Scholar

He, J. (2012). Principles of marine electromagnetic method. Beijing: Higher Education Press.

Google Scholar

Isah, A., Akinbiyi, O. A., Ugwoke, J. L., Ayajuru, N. C., and Oyelola, R. O. (2023). Detection of groundwater level and heavy metal contamination: a case study of Olubunku dumpsite and environs, Ede North, Southwestern Nigeria. J. Afr. Earth Sci. 197, 104740. doi:10.1016/j.jafrearsci.2022.104740

CrossRef Full Text | Google Scholar

Kingston, V. J., Ravindran, A. A., Abishek, R. S., Aswin, S. K., and Antony Alosanai Promilton, A. (2022). Integrated geophysical and geochemical assessment of submarine groundwater discharge in coastal terrace of Tiruchendur, Southern India. Appl. Water Sci. 12, 9. doi:10.1007/s13201-021-01553-8

CrossRef Full Text | Google Scholar

Li, T., Feng, L. B., Duan, Q. M., Jun Lin, , Xiao-Feng Yi, , Chuan-Dong Jiang, , et al. (2015). Research and realization of short dead-time surface nuclear magnetic resonance for groundwater exploration. IEEE Trans. Instrum. Meas. 64 (1), 278–287. doi:10.1109/tim.2014.2338693

CrossRef Full Text | Google Scholar

Liang, J., Wei, Q., and Hong, J. (2016). Application of self-potential method to explore water in karst area. Geotechnical Investigation and Surv. 44 (2), 68–78.

Google Scholar

Lu, Y., Yang, T., and Tizro, A. T. (2023). Fast recognition on shallow groundwater and anomaly analysis using frequency selection sounding method. Water 15, 96. doi:10.3390/w15010096

CrossRef Full Text | Google Scholar

Melchinov, V. P., and Pavlov, A. A. (2022). Experience with a water detector in the study of the permafrost structure. Geomagnetism Aeronomy 62 (3), 271–277. doi:10.1134/S0016793222030100

CrossRef Full Text | Google Scholar

Rahman, M., Woods, R., Pianosi, F., Wagener, T., and Hartmann, A. (2025). Application of a parsimonious large-scale distributed groundwater flow model to quantify inter-catchment groundwater flow. J. Hydrology 662, 133900. doi:10.1016/j.jhydrol.2025.133900

CrossRef Full Text | Google Scholar

Robert, T., Dassargues, A., Brouyère, S., Kaufmann, O., Hallet, V., and Nguyen, F. (2011). Assessing the Contribution of electrical resistivity tomography (ERT) and self-potential (SP) methods for a water well drilling program in fractured/karstified limestones. J. Appl. Geophys. 75 (1), 42–53. doi:10.1016/j.jappgeo.2011.06.008

CrossRef Full Text | Google Scholar

Song, W., Li, Z., Jin, Y., Zhang, B., and Zheng, T. (2021). Comprehensive application of hydrogeological survey and in-situ thermal response test. Case Stud. Therm. Eng. 27, 101287. doi:10.1016/j.csite.2021.101287

CrossRef Full Text | Google Scholar

Ward, S. H. (1971). Electromagnetic theory for geophysical applications. Min. Geophysics vol. Ⅱ, 13–196.

Google Scholar

Wei, A., Feng, C., and Hong, H. (2025). Development of design factors for seismic liquefaction hazard-consistent design and evaluation. Soil Dynamics and Earthquake engineering, 199. 109715. doi:10.1016/j.soildyn.2025.109715

CrossRef Full Text | Google Scholar

Yang, J. (1982). Experimental results and theoretical study of the stray current method in karst area. Geophys. Geochem. Explor. 6 (1), 41–54.

Google Scholar

Yang, T., and Zhang, H. (2013). A study of the anomaly genesis for the frequency selection method in a natural electric field of a karst body. Hydrogeology and Eng. Geol. 40 (5), 22–28.

Google Scholar

Yang, T., Zhang, Q., and Wang, Q. (2016). Study on the anomaly genesis of the frequency selection method for a sphere under natural electromagnetic field. J. Hunan Univ. Sci. and Technol. Nat. Sci. Ed. 31 (2), 58–65. doi:10.13582/j.cnki.1672-9102.2016.02.010

CrossRef Full Text | Google Scholar

Yang, T., Xia, D., and Wang, Q. (2017). Theoretical research and application of frequency selection method for telluric electricity field. Changsha: Central South University Press.

Google Scholar

Yang, T., Chen, Z., and Liang, J. (2020). Theoretical analysis of sounding anomaly and field application of the natural electric field frequency selection sounding method in groundwater exploration. Earth Sci. Front. 27 (4), 302–310. doi:10.13745/j.esf.sf.2020.6.34

CrossRef Full Text | Google Scholar

Yang, T., Wang, D., and Zhang, Y. (2021). Application research of comprehensive geophysical method to karst investigation in a productive mine. Prog. Geophys. 36 (3), 1145–1153. doi:10.6038/pg2021EE0275

CrossRef Full Text | Google Scholar

Yang, T., Gao, Q., Li, H., Fu, G., and Hussain, Y. (2023). New insights into the anomaly genesis of the frequency selection method: supported by numerical modeling and case studies. Pure Appl. Geophys. 180, 969–982. doi:10.1007/s00024-022-03220-8

CrossRef Full Text | Google Scholar

Yang, T., Zhu, D., and Fu, G. (2024). Shallow groundwater exploration by frequency selection method of telluric current in interference environment of high voltage transmission lines. China Sci. Pap. 19 (10), 1065–1072. doi:10.3969/j.issn.2095-2783.2024.10.002

CrossRef Full Text | Google Scholar

Yang, T., Zhu, D., Hussain, Y., Huang, R., Yu, Q., and Ding, Q. (2025). Feasibility study of telluric magnetic field frequency selection method in groundwater exploration. J. Appl. Geophys. 233, 105608. doi:10.1016/j.jappgeo.2024.105608

CrossRef Full Text | Google Scholar

Zhang, K., Zhang, R., Wang, M., Lin, Z., Zhang, Q., Jing, J., et al. (2025). Controlled source ultra-audio frequency magnetotellurics transmitter for high-resolution detection of urban shallow underground space. Measurement 256 (Part), 118144. doi:10.1016/j.measurement.2025.118144

CrossRef Full Text | Google Scholar