Introduction

The recognition of landslide behaviour in various geological conditions is crucial in landslide hazard evaluation (Aleotti and Chowdhury 1999; Anbarasu et al. 2010; Guzzetti et al. 1999; Dai et al. 2002; Barla et al. 2013; Bonnard and Corominas 2005; Cascini et al. 2005; Fukuoka et al. 2005; Mansour et al. 2011; Sassa et al. 2004, Song and Kim 2014). In this sense, geophysical methods may be helpful in monitoring landslides and, consequently, in assessing the landslide hazard (Bichler et al. 2004; Bièvre et al. 2015; Brückl et al. 2013; Bogoslovsky and Ogilvy 1977; Frasheri et al. 1998; Hack 2000; Méric et al. 2005; Jongmans and Garambois 2007; Jongmans et al. 2009; Lundström et al. 2009; Hibert et al. 2011; Reynolds 2011, Salas-Romero et al. 2015; Singh et al. 2013; Travelleti et al. 2013; Zarroca et al. 2014). In recent years, a new seismic method based on ambient noise has been intensively developed, known as seismic interferometry, which may be demonstrated to be useful in monitoring mass movements (Jongmans and Garambois 2007; Méric et al. 2007; Jongmans et al. 2009; Renalier et al. 2010a, 2010b; Mainsant et al. 2012b; Del Gaudio et al. 2013; Pilz et al. 2013).

Seismic interferometry is a method enabling the use of local seismic noise for analysis of changes of elastic properties within the geological medium. It is originated from the phenomenon of interference of seismic signals (Curtis et al. 2006; Schuster 2009). The principles and applications of seismic interferometry were broadly explained by Schuster (2009) and Wapenaar et al. (2010a, 2010b).

Seismic interferometry consists of retrieving the impulse response of the medium, the so-called Green’s function, between a pair of receivers using the operations of cross-correlation, deconvolution or cross-coherence of seismic signals registered at the receivers. The method assumes a Rayleigh surface wave, which is dispersive, i.e., its velocity strictly depends on the frequency. Rayleigh waves are described by dispersion curves, which demonstrate the dependence of a phase velocity on wave frequency. Shear wave (S-wave) velocities have the dominant influence on the dispersion curve in a high-frequency range (>5 Hz) (Xia et al. 1999). As a result of inversion of a Rayleigh wave’s phase velocity, an image of the changes in S-wave velocities is obtained. The S-wave velocity is sensitive to changes in properties of the ground medium, especially to changes in its rigidity, which could be also the consequence of changes in water content in the medium.

Seismic interferometry has increasing geo-engineering applications. Larose et al. (2015) presented recent developments in ambient seismic noise methods to monitor the variations in the mechanical properties of the subsurface and to identify new sources of seismic signals that occur outside the solid Earth. The authors demonstrated the use of seismic noise in marking the thermal variations in the subsoil, in buildings or in rock columns, the temporal and spatial evolution of a water table and the changes of the rigidity of the soil constituting a slope prone to mass movements.

Seismic interferometry studies analysing changes in the S-wave velocity preceding major landslide movements were broadly undertaken by Mainsant et al. (2012b). These researchers concluded that the observed changes in the S-wave velocity decreased two or even threefold before mass movement. The drop in S-wave velocities was correlated with the measurements of displacement performed on the terrain surface. Moreover, Mainsant et al. (2012a) studied the S-wave velocity in terms of rheological changes in clay-rich geological formations, which are responsible for many landslides. These researchers conducted rheometrical laboratory experiments to investigate the solid-fluid transition, which affects derangement of the particle network and is associated with a loss in rigidity. The results indicated that the S-wave velocity significantly varies with rheological changes in the clay, supposedly caused by the disorganization of the particle network. According to the outcomes of their investigations, the authors concluded that measuring the S-wave velocity could be applicable to monitoring rheological changes in landslides in clayey deposits and that the time-dependent variation in this parameter could be a beneficial indicator for earthflows. The authors continued laboratory experiments (Mainsant et al. 2015) in order to examine the physical origin of the S-wave velocity decreases which occur prior to the onset of mass movements. Additional rheometrical studies indicated that it is probably caused by a complex transient rheological response of the clay. These researchers supposed that such response is connected to the existence of the so-called “delayed fluidization” phases in which the shear modulus quickly decreases while the apparent viscosity varies more slowly and requires more time to reach its fluid level. The results are comparable with a real in-field situation of a landslide movement.

Renalier et al. (2010a) applied ambient seismic measurements to determine the deepest slip surface of a landslide in clayey deposits, which had not been detected by active seismic methods. This surface was found by obtaining the dispersion curves at lower frequencies than 3 Hz. During a 30-month period of seismic noise observations, they detected a slight but significant decrease in the surface wave velocities. Moreover, authors observed both lateral and vertical variations of the S-wave velocity which have been related to landslide activity and the location of slip surfaces. Additionally, Renalier et al. (2010b) successfully applied an ambient noise cross-correlation to obtain a 3D model of the S-wave velocity of a landslide affecting clayey deposits. They computed cross-correlations between the vertical components of recording stations which allowed them to retrieve the Rayleigh wave Green’s functions and estimate their group velocity dispersion curves in the 1.7–5 Hz frequency range. The dispersion curves were then inverted with a neighbourhood algorithm which resulted in the 3D model of the S-wave velocity of the studied landslide.

The results of seismic studies described in this paper are a continuation of the work by Pilecki and Harba (2015) who presented the usefulness of the seismic interferometry method in mapping the structure and properties of the near-surface geological medium in the area of the active Just-Tegoborze landslide (southern Poland). Their preliminary results are based on the measurements carried out along single seismic profile in two measurement series. In this paper, we present the results developed with one additional series. Moreover, the results were extended with data from transverse seismic profiles. We also describe the geological conditions of the Just-Tegoborze landslide and the measurement methodology, as well as the methodology of seismic data processing and interpretation. The changes of elastic properties of geological medium are characterized by the changes in the S-wave velocity. The recognized seismic boundaries are correlated to lithological ones shown on the geological engineering cross-section.

Geological and geomorphological setting

Geographically, the Just-Tegoborze landslide is located in Swidnik and Tegoborze villages, in Nowy Sacz county in the southern part of Poland. It is situated on a slope of Jodlowiec Wielki Mountain and St. Just Mountain, slightly below St. Just pass of the Beskid Wyspowy range (Fig. 1).

Fig. 1
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Geographic location map of the study area of the Just-Tegoborze landslide (on the basis of Google Maps)

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From the geological point of view, the Just-Tegoborze landslide lies in Magura Nappe in the Outer (Flysch) Carpathians (Fig. 2). On the study area, Magura Nappe is represented by hieroglyphic beds, Magura beds and Sub-Magura beds. Hieroglyphic beds are mainly built of thin-bedded sandstones and shales. They are interbedded with medium and thick-bedded sandstones in the upper part, whereas shales constitute a majority in the lower part. Magura beds consist of muscovitic sandstones of 0.7 to 2 m thickness. Sub-Magura beds are built of sandstones and shales. Flysch formation, according to data from the 3I/P borehole located on the study area (Fig. 3), dips at angles from 60° to 84° toward the North.

Fig. 2
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Geological map of the surrounding area of the Just-Tegoborze landslide with elevation contour lines marked (based on Cieszkowski and Waskowska 2010)

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Fig. 3
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A part of the Just-Tegoborze landslide sketch on a base topographic map, including projection of a geological engineering cross-section with boreholes and seismic profiles (based on Chowaniec and Wojcik 2012)

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Quaternary colluvial deposits cover discordant flysch bedrock on the study area. Strongly cohesive clayey colluvium has a thickness of 10 to 12 m (Fig. 4). It is very heterogenous and consists of clay, humic clay, silty clay, sandy clay, silts, clayey debris, clasts of sandstones, mudstones and shales. Soft clayey colluvium with relocated fragments of soft shales, locally interbedded with hard shales, mudstones and sandstones forms a layer of 3 to 5 m thickness below the near-surface clayey colluvium (Czudec 2012, unpublished data).

Fig. 4
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A part of the geological engineering cross-section of the study area with the A-A′ projected seismic profile (based on Pilecki and Harba 2015)

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Several failure surfaces of the landslide were distinguished as a result of archival geological works (Chowaniec and Wojcik 2012). Failure surfaces were investigated on the study area within colluvial deposits at approximately 10 and 12 m depth and between colluvial deposits and the flysch bedrock at approximately 14 to 17 m depth (Fig. 4).

The Just-Tegoborze landslide developed on the contact between shale and shale-sandstone complexes of Sub-Magura and hieroglyphic beds, and Magura sandstones. Shale and shale-sandstone complexes are less resistant and more susceptible to weathering than Magura sandstones. Magura sandstones have uniaxial compressive strength (UCS) from 19 to 91 MPa, whereas shales from hieroglyphic beds have UCS from 0.25 to 2.9 MPa (Czudec 2012, unpublished data). Other factors, which have an influence on the development of the Just-Tegoborze landslide, include the occurrence of weak variegated shales prone to swelling and complicated tectonics between Magura, Sub-Magura and hieroglyphic beds.

The Just-Tegoborze landslide has southeastern exposure and descends to the Roznow Lake (Fig. 1). The azimuth of its movement is 130°, and its average slope angle is 11.8° (Chowaniec and Wojcik 2012). From a geomorphological point of view, it consists of a number of mass movement areas, however, with no clear boundaries between them. Its slopes are of convex-concave type, and the terrain relief is strongly diversified. Slopes are mostly cut by small coomb valleys, dells and gullies. There are numerous scarps and landslide niches on the upper part of the landslide. On the study area, levels of water filtration were examined on 0.7, 2.0, 4.7 and 5.8 m. Water seepages are observed on the terrain surface close to the 3I/P (Fig. 3). Water level in a dug well, which is located on the study area, is 1.2 m deep, however, it reaches terrain surface during intense rainfalls and spring thaw. It leads to the conclusion that there are weakly permeable deposits which limit the infiltration of water deep into the geological medium. The analysis of the core from 3I/P borehole indicates the presence of low permeable, weakly and medium fractured shales and variegated shales at the depth of 13 m. Above them, there are very fractured shales and previously described colluvial deposits which have a water content up to 35% (Czudec 2012, unpublished data).

Methodology

Seismic acquisition

A local high-frequency seismic noise was used in the study with seismic interferometry, generated mainly by intense vehicle traffic on a state road no. 75 present in the immediate vicinity. Data acquisition was carried out by 12 Güralp CMG-6TD broadband seismometers working autonomously. They were installed along two profiles with lengths of 75 and 95 m, which crossed at the 3I/P borehole (Fig. 3). Distances between seismometers were from 10 to 20 m. Data recording lasted for 60 min with 10 ms sampling. Signals were recorded in the frequency band of 0.03–100 Hz. Figure 5a shows an example of a seismogram of the seismic noise recorded, which is characterized by the strongest seismic energy within a frequency band between 5 and 22 Hz (Fig. 5b). A similar frequency band of vehicle traffic, used as a source for near-surface passive imaging, was studied by Kuzma et al. (2009).

Fig. 5
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An example of a seismogram (a) and an amplitude spectrum (b) of seismic noise recorded in a period of 60 min at the Just-Tegoborze landslide

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Measurements were carried out in three series in 2015: January 23rd (a dry period), March 9th (a period of an increased water content after the spring thaw) and July 9th (a period of an intense water infiltration during heavy rainfalls). Figure 6 shows a daily average precipitation and temperature measured at nearby meteorological stations from July 2014 to July 2015. In each seismic measurement series, the seismometers were installed at the same place. The recognition depth range of the geological medium was up to 20 m.

Fig. 6
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Daily average precipitation and daily average temperature data measured at the two meteorological stations in the vicinity of the Just-Tegoborze landslide from 1st July 2014 to 31st July 2015. Black vertical lines correspond to measurement series: 1, 2 and 3 respectively

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Processing and interpretation

The data processing and interpretation scheme was similar to those of Bensen et al. (2007) and Cheng et al. (2015).

The measured amplitude records of vertical velocity of ground vibrations on the Just-Tegoborze landslide were first band-pass filtered in the 7 to 35 Hz frequency band for smoothing amplitude spectra. Next, 1-bit normalization and cross-correlation were applied. Cross-correlation functions were computed between all available receiver pairs. As a result, series of empirical Green’s functions were obtained and sorted afterwards into the so-called common virtual source gathers for every receiver. Each virtual source was considered as a bidirectional shot with two common virtual source gathers as the causal and acausal signal parts (Fig. 7).

Fig. 7
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An example of a common virtual shot gather of the virtual source located at the 75 m point of the B-B′ seismic profile with acausal and causal parts indicated

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The frequency–wavenumber (f–k) transform was subsequently computed to separate surface wave energy from those of body waves. Muting was applied (Fig. 8a) in order to improve the signal to noise ratio. Finally, the dispersion curve of the Rayleigh wave was extracted (Fig. 8b).

Fig. 8
figure 8

An example of a seismic noise cross-correlogram with a muting window (a) and a dispersion image with a picked fundamental mode (M0) (b)

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Data interpretation was based on the first picking fundamental modes of the Rayleigh wave from the dispersion curves. They were inverted afterwards to obtain 1D shear wave velocity models (Fig. 9). Inversion was conducted by means of a genetic algorithm. Finally, a 2D shear wave velocity section was constructed on the basis of the 1D information. Data processing and interpretation were carried out using own algorithms written in Matlab and supported by Geogiga Seismic Pro software.

Fig. 9
figure 9

An example of a 1D S-wave velocity profile inverted from the dispersion curve

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Results and analysis

The seismic sections developed for the three measurement series are presented in Fig. 10 for longitudinal sections and in Fig. 11 for section transverse to the landslide axis.

Fig. 10
figure 10

S-wave velocity section along the A-A′ seismic profile measured on 23rd January 2015 (a), 9th March 2015 (b) and 9th July 2015 (c)

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Fig. 11
figure 11

S-wave velocity section along the B-B′ seismic profile measured on 9th March 2015 (a) and 9th July 2015 (b)

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The 1st measurement series was carried out in the winter period in conditions which may be assumed to be dry (Fig. 6). Evident in this section are three layers with varied S-wave velocities (Fig. 10a). In the near-surface layer, with the lowest velocities ranging from 220 to 270 m/s, there is also a local minimum value in the central part. This layer is most likely connected with the increased water content in the medium, as demonstrated by the observed water table when executing borehole 3I/P and the visible dampness of the terrain surface while taking the measurements. The first layer is characterized by a thickness amounting to approximately 5 m along the entire length of the profile. The next, middle layer is characterized by the S-wave velocity ranging from 270 to 340 m/s. Its thickness is variable and primarily is approximately 8 to 10 m, locally decreasing to 5 m in the 70 to 75 m of the seismic profile (Fig. 10a). Thickness of the second layer is the largest in the central part of the profile. The deepest-located layer is characterized by the S-wave velocity values in the range of 340 to 400 m/s. The roof of this layer occurs at the depth of 10 to 15 m.

The trough-like shape of the seismic boundary between the second and third layers occurs in the zone of the weaker rock mass of the hieroglyphic beds made of clayey variegated shales and shales with instances of minor sandstone interbedding. A harder sandstone-shale rock mass of Sub-Magura beds lies in the vicinity (Fig. 4). The roof of the third layer likely constitutes the surface of a less weathered bedrock.

The 2nd measurement series was carried out in the spring period with a melting snow cover. The near-surface ground might have not yet been fully thawed (Fig. 6). The longitudinal (Fig. 10b) and transverse (Fig. 11a) sections are characterized by a significant decrease in the S-wave velocity in the two surface layers of the medium. In order to emphasize the differences, layer boundaries were marked in the longitudinal section according to contour lines interpreted in Fig. 10a. The zone of weakened elastic properties stretched toward the drop in the terrain surface of the area. The velocity value of the seismic boundary of the bedrock was very slightly changed. It should be noted that the depth of this boundary was maintained.

The 3rd measurement series was conducted in the summer period directly after storm rainfalls (Fig. 6, Fig. 10c, Fig. 11b). Increased infiltration into the medium caused a greater weakening of elastic properties, especially in the first layer, compared to the 2nd series. The velocity value of the seismic boundary of the bedrock again only slightly changed. The depth of this boundary was also maintained. A similar effect may be observed in the transverse sections (Fig. 11a, b).

In relation to the geological engineering cross-section of the research area (Fig. 4), one may notice that the first two near-surface seismic layers correspond to clayey colluvium formations. The seismic boundary occurring at a depth of approximately 10 to 15 m may be correlated to the roof of the less weathered rock mass of the shale and shale/sandstone series. In the seismic image, the bedrock (third layer) did not undergo significant changes as a result of infiltration, which confirms lesser disturbance by landslide processes in comparison with colluvium layers. Presumably, the bedrock roof boundary is one of the most important failure surfaces of the landslide. The trough-like shape of this seismic boundary in the central part of the seismic section may be connected with the greater range of weathering in the zone of weaker hieroglyphic beds.

Conclusions

This study has demonstrated that it is possible to monitor the changes of shear wave velocities of a geological compound medium, as it is monitored in the Just-Tegoborze landslide by the seismic interferometry method using a local high-frequency ambient noise. The results clearly show changes of the S-wave velocity which are most likely caused by various conditions of infiltration and water content in the geological medium. Generally, an increasing water content in the medium results in the decrease of the S-wave velocity value and also the medium’s rigidity.

The interpreted seismic boundaries may be correlated to lithological boundaries shown in a geological engineering cross-section. In the seismic image, the course of the bedrock boundary is more complex in comparison with the geological engineering cross-section. The trough-like shape of this seismic boundary in the central part of the seismic section may be related to the decrease of rigidity of weak hieroglyphic beds compared to the stronger surrounding rock mass, however, it requires further detailed studies. The investigated bedrock boundary is presumably one of the failure surfaces.

The complicated course of the bedrock boundary may also have an influence on the water flow paths in the colluvium layer affected by mass movements. In consequence, it has an influence on the stability of the state road structure.

The presented results of seismic interferometry may be helpful in evaluating the behaviour of the Just-Tegoborze landslide. These findings can be also used in designing protections against mass movements.