The development of tools for quantitative scenarios of ground instability effects is a challenge for risk mitigation, particularly in landslide risk management. In the RETURN project framework, the case study of the San Vito Romano earth-slide has been selected for PhD research as learning example for experiencing an integrated approach of passive geophysics and satellite interferometry. Such an approach is promising in managing urban plans and protecting historical heritage. It is also an effective tool for detecting and monitoring seasonal ground instability effects, while providing a useful instrument to calibrate numerical models aimed at predicting multi-hazard scenarios. The village of San Vito Romano is a historic location representative for the rural areas surrounding the city of Rome (Central Italy). The village is primarily built on an active earth-slide covering nearly 1 km², characterized by a roto-translational mechanism and slow kinematics. The landslide affects silico-clastic deposits from the Frosinone Formation (Upper Tortonian), consisting of alternating layers of clayey and arenaceous marls. This geological structure predisposes the area to slope instability. Preparatory factors such as cumulative precipitation, which influences soil moisture, and triggering events such as seismic activity and heavy rainfall, can contribute to the current landslide activity. Evidence of this ongoing movement is found in the fractures present in buildings, which have been declared unsafe for use. The project aims to develop a quantitative tool that correlates satellite displacements with proxies from passive seismic techniques (LSMI) to highlight the role of preparatory and triggering factors in landslide activity, specifically dealing with rainfalls and earthquakes. This information will be used to train a model for forward analysis of scenarios in a multi-hazard perspective. This research integrates ambient seismic noise techniques, with a specific focus on seismic interferometry, and Differential Interferometry SAR (DInSAR) techniques, particularly employing the Smal Baseline Subset approach. To conduct passive seismic studies, four short-period three-component velocimeters (VelBox, model SL06 2Hz sensor) have been installed on the landslide to continuously record ambient seismic noise. From ambient noise correlation, we can approximate the impulse response of a medium to an excitation (or Green’s function), that results in a cross-correlation function (CCF) that is representative of the direct and diffused propagation within the medium (Le Breton et al., 2021). This technique attracted interest after detecting for the first time a clear velocity drop five days before the catastrophic acceleration of a shallow clayey landslide, at Pont-Bourquin (Mainsant et al., 2012b). This kind of monitoring allows the calculation of landslide mobility indices (LSMI), such as natural period variation (dT/T), peak polarization variation (dP/P) and changes of Rayleigh waves velocity (dV/V) over time. In this way, we can continuously monitor changes in rigidity, amplification, and non-linear elastic properties of the soil to understand how the slope is prepared for possible instability. Furthermore, in relation to satellite techniques, SBAS approach creates maps of mean displacement rate and generates time series data of the displacements on specific points within the image. The processed data, which spans from 2022 to the present, reveals an increase in displacement rates, especially in certain sectors of the landslide. References - Le Breton, M., Bontemps, N., Guillemot, A., Baillet, L., & Larose, É. (2021). Landslide monitoring using seismic ambient noise correlation: challenges and applications. Earth-Science Reviews, 216, 103518. - Mainsant, G., Larose, E., Br¨onnimann, C., Jongmans, D., Michoud, C., Jaboyedoff, M., 2012b. Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. 117, F01030 https://doi.org/10.1029/2011JF002159.

Advancements in integrating passive geophysical surveys and satellite interferometry for multi-hazard monitoring / Marano, Simona; Yawar, Hussain; Grechi, Guglielmo; Rivellino, Stefano; Bozzano, Francesca; Martino, Salvatore. - (2024). (Intervento presentato al convegno Dissemination Workshop PE3 PNRR RETURN tenutosi a Bologna).

Advancements in integrating passive geophysical surveys and satellite interferometry for multi-hazard monitoring

Marano Simona;Guglielmo Grechi;Stefano Rivellino;Francesca Bozzano;Salvatore Martino
2024

Abstract

The development of tools for quantitative scenarios of ground instability effects is a challenge for risk mitigation, particularly in landslide risk management. In the RETURN project framework, the case study of the San Vito Romano earth-slide has been selected for PhD research as learning example for experiencing an integrated approach of passive geophysics and satellite interferometry. Such an approach is promising in managing urban plans and protecting historical heritage. It is also an effective tool for detecting and monitoring seasonal ground instability effects, while providing a useful instrument to calibrate numerical models aimed at predicting multi-hazard scenarios. The village of San Vito Romano is a historic location representative for the rural areas surrounding the city of Rome (Central Italy). The village is primarily built on an active earth-slide covering nearly 1 km², characterized by a roto-translational mechanism and slow kinematics. The landslide affects silico-clastic deposits from the Frosinone Formation (Upper Tortonian), consisting of alternating layers of clayey and arenaceous marls. This geological structure predisposes the area to slope instability. Preparatory factors such as cumulative precipitation, which influences soil moisture, and triggering events such as seismic activity and heavy rainfall, can contribute to the current landslide activity. Evidence of this ongoing movement is found in the fractures present in buildings, which have been declared unsafe for use. The project aims to develop a quantitative tool that correlates satellite displacements with proxies from passive seismic techniques (LSMI) to highlight the role of preparatory and triggering factors in landslide activity, specifically dealing with rainfalls and earthquakes. This information will be used to train a model for forward analysis of scenarios in a multi-hazard perspective. This research integrates ambient seismic noise techniques, with a specific focus on seismic interferometry, and Differential Interferometry SAR (DInSAR) techniques, particularly employing the Smal Baseline Subset approach. To conduct passive seismic studies, four short-period three-component velocimeters (VelBox, model SL06 2Hz sensor) have been installed on the landslide to continuously record ambient seismic noise. From ambient noise correlation, we can approximate the impulse response of a medium to an excitation (or Green’s function), that results in a cross-correlation function (CCF) that is representative of the direct and diffused propagation within the medium (Le Breton et al., 2021). This technique attracted interest after detecting for the first time a clear velocity drop five days before the catastrophic acceleration of a shallow clayey landslide, at Pont-Bourquin (Mainsant et al., 2012b). This kind of monitoring allows the calculation of landslide mobility indices (LSMI), such as natural period variation (dT/T), peak polarization variation (dP/P) and changes of Rayleigh waves velocity (dV/V) over time. In this way, we can continuously monitor changes in rigidity, amplification, and non-linear elastic properties of the soil to understand how the slope is prepared for possible instability. Furthermore, in relation to satellite techniques, SBAS approach creates maps of mean displacement rate and generates time series data of the displacements on specific points within the image. The processed data, which spans from 2022 to the present, reveals an increase in displacement rates, especially in certain sectors of the landslide. References - Le Breton, M., Bontemps, N., Guillemot, A., Baillet, L., & Larose, É. (2021). Landslide monitoring using seismic ambient noise correlation: challenges and applications. Earth-Science Reviews, 216, 103518. - Mainsant, G., Larose, E., Br¨onnimann, C., Jongmans, D., Michoud, C., Jaboyedoff, M., 2012b. Ambient seismic noise monitoring of a clay landslide: Toward failure prediction. J. Geophys. Res. 117, F01030 https://doi.org/10.1029/2011JF002159.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1754991
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