Abstract

Scenarios of earthquake-induced landslides are necessary for seismic microzonation (SM) studies since they must be integrated with the mapping of instability areas. The PARSIFAL (Probabilistic Approach to pRovide Scenarios of earthquake‐Induced slope FAiLures) approach provides extensive analyses, over tens to thousands of square kilometers, and is designed as a fully comprehensive methodology to output expected scenarios which depend on seismic input and saturation conditions. This allows to attribute a rating, in terms of severity level, to the landslide-prone slope areas in view of future engineering studies and designs. PARSIFAL takes into account first-time rock- and earth-slides as well as re-activations of existing landslides performing slope stability analyses of different failure mechanisms. The results consist of mapping earthquake-induced landslide scenarios in terms of exceedance probability of critical threshold values of co-seismic displacements (P[D ≥ Dc|a(t),ay]). PARSIFAL was applied in the framework of level 3 SM studies over the municipality area of Accumoli (Rieti, Italy), strongly struck by the 2016 seismic sequence of Central Apennines. The use of the PARSIFAL was tested for the first time to screen the Susceptibility Zones (ZSFR) from the Attention Zones (ZAFR) in the category of the unstable areas, according to the guidelines by Italian Civil Protection. The results obtained were in a GIS-based mapping representing the possibility for a landslide to be induced by an earthquake (with a return period of 475 years) in three different saturation scenarios (i.e. dry, average, full). Only 41% of the landslide-prone areas in the Municipality of Accumoli are existing events, while the remaining 59% is characterized by first-time earth- or rock-slides. In dry conditions, unstable conditions or P[D ≥ Dc|a(t),ay] > 0 were for 54% of existing landslides, 17% of first-time rock-slides and 1% of first-time earth-slides. In full saturation conditions, the findings are much more severe since unstable conditions or P[D ≥ Dc|a(t),ay] > 0 were found for 58% of the existing landslides and for more than 80% of first-time rock- and earth-slides. Moreover, comparison of the total area of the ZAFR versus ZSFR, resulted in PARSIFAL screening reducing of 22% of the mapped ZAFR.

Highlights

  • The reconstruction of landslide scenarios is a milestone for environmental planning in terms of both hazard mapping and strategic and engineering solutions to be adopted in urbanised areas

  • Thematic maps were obtained through GIS by synthetically reporting the slope stability conditions under dynamic action as well as the probability of exceedance of the critical displacement referred to scenarios of different saturation conditions

  • The methodology aimed at deducting the Z­ SFR map starting from the scenario maps initially obtained; they were taken into account all the results obtained in the three considered scenarios reconstructed by PARSIFAL, as the saturation conditions range from zero to the admissible maximum, the final susceptibility was attributed through a weighting of the probabilities of exceedance resulting from all the reconstructed scenarios

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Summary

Introduction

The reconstruction of landslide scenarios is a milestone for environmental planning in terms of both hazard mapping and strategic and engineering solutions to be adopted in urbanised areas. The combined nature of the hazard related to earthquake-induced landslides implies that such processes should be analyzed taking into account both the proneness to failure (landslide susceptibility), and the probability of occurrence of the triggering event (seismic hazard). The predisposing conditions to slope failures vary according to the environmental constraints, among which the water saturation of covers and deposits or the presence of pore water pressures related to groundwater flow, more commonly originated by impulsive events such as heavy rainfall. It is necessary to resort to the reconstruction of scenario maps which have the dual purpose of: (1) providing a spatial distribution of effects to a certain probability of occurrence; and (2) make it possible to take into account their variability as a function of the predisposing environmental conditions, including soil saturation

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