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The vast majority of landslide susceptibility studies assumes the slopeinstability process to be time-invariant under the definition that "the pastand present are keys to the future". This assumption may generally be valid.However, the trigger, be it a rainfall or an earthquake event, clearly variesover time. And yet, the temporal component of the trigger is rarely included inlandslide susceptibility studies and only confined to hazard assessment. Inthis work, we investigate a population of landslides triggered in response tothe 2017 Jiuzhaigou earthquake ($M_w = 6.5$) including the associated groundmotion in the analyses, these being carried out at the Slope Unit (SU) level.We do this by implementing a Bayesian version of a Generalized Additive Modeland assuming that the slope instability across the SUs in the study areabehaves according to a Bernoulli probability distribution. This procedure wouldgenerally produce a susceptibility map reflecting the spatial pattern of thespecific trigger and therefore of limited use for land use planning. However,we implement this first analytical step to reliably estimate the ground motioneffect, and its distribution, on unstable SUs. We then assume the effect of theground motion to be time-invariant, enabling statistical simulations for anyground motion scenario that occurred in the area from 1933 to 2017. As aresult, we obtain the full spectrum of potential susceptibility patterns overthe last century and compress this information into a susceptibility model/maprepresentative of all the possible ground motion patterns since 1933. Thisbackward statistical simulations can also be further exploited in the oppositedirection where, by accounting for scenario-based ground motion, one can alsouse it in a forward direction to estimate future unstable slopes.

From scenario-based seismic hazard to scenario-based landslide hazard: rewinding to the past via statistical simulations