Proceedings of the 12th International INQUA meeting on paleoseismology, active tectonic and archaeoseismology

We infer the distribution in time for interevent times (IETs) of the whole region from 10 6 simulated earthquake time histories of individual faults. These latter are obtained by randomly choosing a scenario for each fault and randomly selecting a time from each paleoearthquake age interval of that scenario (see Cinti et al., 2021 for description). The temporal trend of the median value (MIET) shows a change point at about 6000 BCE. Since this time to nowadays there is a decrease of the values (Figure 3). Then, the history of IETs appears divided in two periods in which the median recurrence time (computed as the median of MIET time histories) is close to 120 and 480 years, for the more and the less recent periods, respectively. Given the substantially higher degree of completeness of the data after 6000 BCE to nowadays, we statistically analysed only the dataset in this time window as can be considered the most robust for detecting rupture patterns in time. Results for earthquake forecast assessment We investigated the rupture recurrence on individual faults by estimating mean IETs on 10 6 simulated fault rupture scenarios. The average recurrence varies fromseveral hundreds to fewthousands of years. We choose to employ two temporal models as representative of the whole class of renewal models and of different possible time- dependent behaviors: a reference Poisson process, predicting a memoryless occurrence of fault ruptures, and a Brownian Passage Time model (Ellsworth et al., 1999), capable of representing a wide variety of time-dependent behaviors, according to parameters values. Specifically, we compute the probabilities of occurrence for the next event, both for individual faults and at regional scale, and we show the effects of time-dependent and time-independent occurrence hypothesis on earthquake forecast assessment. It is worth to note that the probabilities presented here are not intended to represent absolute estimates; they strongly depend on choices about the occurrence model and data treatment, but help us to understand the sensitivity of regional and fault hazard assessment to all sources of uncertainty. This may drive future research and set novel trends in this field. Fig. 3: Temporal behavior of median IETs derived from the 16 faults data (Lombardi et al., submitted). The vertical red line marks the change point at ~6000 BCE. The dotted red horizontal lines mark the median interevent times in the two time periods identified by change point.