No abstract

In recent years, new approaches for developing earthquake rupture forecasts (ERFs) have been proposed to be used as an input for probabilistic seismic hazard assessment (PSHA). Zone- based approaches with seismicity rates derived from earthquake catalogs are commonly used in many countries as the standard for national seismic hazard models. In Italy, a single zone- based ERF is currently the basis for the official seismic hazard model. In this contribution, we present eleven new ERFs, including five zone-based, two smoothed seismicity-based, two fault- based, and two geodetic-based, used for a new PSH model in Italy. The ERFs were tested against observed seismicity and were subject to an elicitation procedure by a panel of PSHA experts to verify the scientific robustness and consistency of the forecasts with respect to the observations. Tests and elicitation were finalized to weight the ERFs. The results show a good response to the new inputs to observed seismicity in the last few centuries. The entire approach was a first attempt to build a community-based set of ERFs for an Italian PSHA model. The project involved a large number of seismic hazard practitioners, with their knowledge and experience, and the development of different models to capture and explore a large range of epistemic uncertainties in building ERFs, and represents an important step forward for the new national seismic hazard model.

A version of the restricted trigger model is used to analyse the temporal behaviour of some aftershock sequences. The conditional intensity function of the model is similar to that of the Epidemic Type Aftershock-Sequence (ETAS) model with the restriction that only the aftershocks of magnitude bigger than or equal to some threshold M tr can trigger secondary events. For this reason we have named the model Restricted Epidemic Type Aftershock-Sequence (RETAS) model. Varying the triggering threshold we examine the variants of the RETAS model which range from the Modified Omori Formula (MOF) to the ETAS model, including such models as limit cases. In this way we have a quite large set of models in which to seek the model that fits best an aftershock sequence bringing out the specific features of the seismotectonic region struck by the crisis. We have applied the RETAS model to the analysis of two aftershock sequences: The first is formed by the events which followed the strong earthquake of M=7.8 which occurred in Kresna, SW Bulgaria, in 1904. The second includes three main shocks and a large swarm of minor shocks following the quake of 26 September 1997 in the Umbria-Marche region, central Italy. The MOF provides the best fit to the sequence in Kresna; that leads to the thought that just the stress field changes due to the very strong main shock generate the whole sequence. On the contrary, the complex behaviour of the seismic sequence in Umbria-Marche appears when we make the threshold magnitude vary. Setting the cut-off magnitude M 0 =2.9 the best fit is provided by the ETAS model, while if we raise the threshold magnitude M 0 =3.6 and set M tr =5.0, the RETAS model turns out to be the best model. In fact, observing the time distribution of this reduced data set, it appears more evident that especially the strong secondary events are followed by a cluster of aftershocks.

In the study of earthquakes, several aspects of the underlying physical process, such as the time non-stationarity of the process, are not yet well understood, because we lack clear indications about its evolution in time. Taking as our point of departure the theory that the seismic process evolves in phases with different activity patterns, we have attempted to identify these phases through the variations in the interevent time probability distribution within the framework of the multiple-changepoint problem. In a nonparametric Bayesian setting, the distribution under examination has been considered a random realization from a mixture of Dirichlet processes, the parameter of which is proportional to a generalized gamma distribution. In this way we could avoid making precise assumptions about the functional form of the distribution. The number and location in time of the phases are unknown and are estimated at the same time as the interevent time distributions. We have analysed the sequence of main shocks that occurred in Irpinia, a particularly active area in southern Italy: the method consistently identi®es changepoints at times when strong stress releases were recorded. The estimation problem can be solved by stochastic simulation methods based on Markov chains, the implementation of which is improved, in this case, by the good analytical properties of the Dirichlet process.