Journal
LANDSLIDES
Volume -, Issue -, Pages -Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s10346-023-02127-2
Keywords
Ground shaking; Coseismic landslides; Susceptibility; Hazard; Multi-hazard
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There are statistical and deterministic approaches to describe seismic triggering of rockfalls. Statistical approaches rely on the analysis of local terrain properties, while deterministic approaches model individual trajectories of boulders set in motion by seismic shaking. In this study, a new method for earthquake-triggered rockfall scenario assessment is proposed, using ground shaking estimates produced in near real-time by a seismological monitoring network. It applies a probabilistic source map and three-dimensional kinematic modeling to calculate rockfall trajectories.
Different approaches exist to describe the seismic triggering of rockfalls. Statistical approaches rely on the analysis of local terrain properties and their empirical correlation with observed rockfalls. Conversely, deterministic, or physically based approaches, rely on the modeling of individual trajectories of boulders set in motion by seismic shaking. They require different data and allow various interpretations and applications of their results. Here, we present a new method for earthquake-triggered rockfall scenario assessment adopting ground shaking estimates, produced in near real-time by a seismological monitoring network. Its key inputs are the locations of likely initiation points of rockfall trajectories, namely, rockfall sources, obtained by statistical analysis of digital topography. In the model, ground shaking maps corresponding to a specific earthquake suppress the probability of activation of sources at locations with low ground shaking while enhancing that in areas close to the epicenter. Rockfall trajectories are calculated from the probabilistic source map by three-dimensional kinematic modeling using the software STONE. We apply the method to the 1976 MI = 6.5 Friuli earthquake, for which an inventory of seismically-triggered rockfalls exists. We suggest that using peak ground acceleration as a modulating parameter to suppress/enhance rockfall source probability, the model reasonably reproduces observations. Results allow a preliminary impact evaluation before field observations become available. We suggest that the framework may be suitable for rapid rockfall impact assessment as soon as ground-shaking estimates (empirical or numerical models) are available after a seismic event.
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