‘Seismic and electrical investigations of the San Vito Romano landslide: preliminary analysis in a multi-hazard framework

Summary This study presents a multidisciplinary investigation of the San Vito Romano landslide, an active, retrogressive movement affecting turbiditic deposits of the Flysch Formation in central Italy. In addition to preliminary geophysical surveys—including HVSR, ERT, MASW, and SRT—an advanced seismic monitoring system was deployed to explore the dynamic response of the landslide to external triggers. A permanent network of four seismometers (SARA instruments, 2.5 Hz eigenfrequency) has been recording ambient seismic noise since February 2024, with two sensors installed within the landslide body and two outside. The monitoring system enables continuous tracking of resonance frequency variations over time and their correlation with rainfall events, observed through an on-site weather station. Seismic events were selected using the INGV database, considering earthquakes within a 100 km radius and magnitude above M2. From this data, Spectral Standard Ratios (SSR) were computed to derive site amplification functions, which are used to calibrate a 2D numerical model of the landslide's seismic response. The study further applies the characteristic periods-based (CPB) approach, analyzing Ts/Tm and Tl/Tm ratios to assess resonance conditions and predict maximum seismic displacements. This integrated method provides key insights into slope–seismic wave interactions and contributes to improved hazard assessment in complex landslide settings. All mountainous areas are affected by gravitational mass movements of various types, sizes and velocities, which could have a major impact on life and property (Mainsant et al., 2011). In-depth knowledge of the possible evolutionary scenarios of the slopes is fundamental to the management of the degree of danger for structures, especially for people. Moreover, it was shown once again how a multi-source approach, with different investigation techniques, cannot be ignored for the study of the evolution of complex landslides (Mangifesta et al., 2024). The interaction between seismic waves and slopes is an important topic to provide reliable scenarios for earthquake-(re)triggered landslides. The physical properties of seismic waves as well as slope topography and geology can significantly modify the local seismic response, influencing landslide triggering. (Martino et al., 2016). In a multihazard perspective, is the second global triggering factor of landslides (the first being rainfall) as local seismic amplification can promote the (re)activation of landslides even under unexpected far-field conditions, thus increasing hazard (Bourdeau et al, 2017). A characteristic period ratio Ts/Tm was introduced to describe such conditions, that is a maximum displacement is theoretically expected for a Ts/Tm ratio equal to 1. In particular, the landslide mass mobility is theoretically favoured (Hutchinson 1994) by the characteristic period of the seismic input (Tm), which is double with respect to the period (Tl) associated with the length of the landslide mass itself (i.e. for a characteristic period ratio Tl/Tm equal to 0.5). According to this characteristic periods-based (CPB) approach, the values of the expected earthquake-induced landslide displacements depend on a combination of 1-D and 2-D effects, these last ones related to the more complex interactions between the landslide mass and slope geometry (Martino et al., 2016). The selected case study focuses on the San Vito Romano landslide, located in the province of Rome. This is an active, retrogressive landslide affecting the turbiditic deposits of the Flysch Formation. The geological structure of the slope has been identified as the main predisposing factor, while rainfall and soil moisture are considered significant preparatory factors. The primary triggering mechanisms include cumulative rainfall and seismic events. The landslide exhibits a slow-moving dynamic, with its most recent reactivation occurring in 2011, resulting in substantial damage, particularly in the northern sector of the landslide body. For the geophysical characterization of the landslide, a preliminary ambient seismic noise survey was conducted. A total of 31 HVSR measurements were acquired both inside and outside the landslide area. Each recording lasted approximately 45 minutes and was performed using the seismometers (SARA electronic instruments) with eigenfrequency of 2.5 Hz. The analysis of these data allowed the identification of the site's resonance frequency, which is crucial for estimating the depth of the slip surface. Subsequently, two investigation lines were selected. The first profile (Line 1) was positioned upslope, outside the landslide perimeter and close to the crown area. Along this line, an 800-meter-long Electrical Resistivity Tomography (ERT) survey was conducted, employing 81 electrodes spaced at 10 meters in a multi-gradient array using the ABEM Terrameter LS2 system (Guideline Geo). This ERT survey was integrated with two MASW profiles, conducted along the same line, using 48 geophones spaced 1.5 meters apart and two Geode (Geometrics) seismographs, with the goal of retrieving the shear-wave velocity profile of the shallow subsurface (DOI ~ 30 m). The resulting resistivity section offered a detailed image of the subsurface, reaching investigation depths of about 150 meters and revealing the contrast between the conductive marly layers and resistive sandstone facies of the Flysch Formation (Fig. 2). Fig2. Intercepting a deep layer due to the transition between two facies of the marly-arenaceous bedrock: clayey marls and sandstone The second survey line (Line 2) is located within the landslide body. Here, a combination of ERT and Seismic Refraction Tomography (SRT) was performed along a profile using 48 sensors spaced at 1.5 meters, in conjunction with MASW profiling and a down-hole seismic test to characterize the near-surface geophysical properties within the landslide area. The ERT and SRT data were processed using the pyGIMLi inversion software (Rücker et al., 2017), while the MASW data were inverted using the code developed by Cercato (2009). In addition to the previously described geophysical investigations, a seismic monitoring network has been installed, consisting in this case of 4 seismometers (SARA instruments with an eigenfrequency of 2.5 Hz), two of which are positioned within the landslide body and two outside. The instruments have been continuously recording ambient seismic noise since February 2024. The monitoring setup allows for continuos tracking of resonance frequency variation and their correlation with rainfall events, which are also continuously monitored through the presence of a weather station installed on-site. From the seismic noise monitoring, seismic events were identified using the INGV (National Institute of Geophysics and Volcanology) database, considering earthquakes within a 100 km radius and with a magnitude greater than M2. Spectral Standard Ratios (SSR) were derived from this data, which allow for obtaining amplification functions. These functions can be used to calibrate a 2D numerical model of the landslide’s seismic response under different loading scenarios. Finally, the method of characteristic periods of the landslide will be applied, analyzing the ratios Ts/Tm and Tl/Tm, in order to gain a deeper understanding of the interactions between seismic waves and the landslide body. This approach helps identify the conditions under which resonance phenomena may occur, determining the critical characteristic period (Tm critical) associated with the maximum expected seismic displacement. This information represents a fundamental tool for assessing the local seismic response and for defining risk mitigation strategies in unstable areas, particularly in mountainous contexts with high vulnerability. References - Bourdeau, C., Lenti, L., Martino, S., Oguz, O., Yalcinkaya, E., Bigarrè, P., & Coccia, S. (2017). Comprehensive analysis of the local seismic response in the complex Büyükçekmece landslide area (Turkey) by engineering-geological and numerical modelling. Engineering Geology, 218, 90–106. - Cercato M. (2009): Addressing non‐uniqueness in linearized multichannel surface wave inversion. Geophysical Prospecting, 57(1), 27-47. - Main¬sant, G., Larose, E., Brönnimann, C., Jongmans, D., Michoud, C., & Jaboyedoff, M. (2012). Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. Journal of Geophysical Research: Earth Surface, 117(F1). - Mangifesta, M., Aringoli, D., Pambianchi, G., Giannini, L. M., Scalella, G., & Sciarra, N. (2024). A Methodologic Approach to Study Large and Complex Landslides: An Application in Central Apennines. Geosciences, 14(10), 272. - Martino, S., Lenti, L., Delgado, J., Garrido, J., & Lopez-Casado, C. (2016). Application of a characteristic periods-based (CPB) approach to estimate earthquake-induced displacements of landslides through dynamic numerical modelling. Geophysical Journal International, 206(1), 85–102. - Rücker C., Günther T., Wagner F.M., (2017): pyGIMLi: An open-source library for modelling and inversion in geophysics. Computers and Geosciences, 109, 106-123.