GNGTS 2014 - Atti del 33° Convegno Nazionale

102 GNGTS 2014 S essione 2.1 Third, the various interpretations of probability so far proposed cannot easily be applied to earthquake prediction (e.g., Freedman and Stark, 2003; Marzocchi and Zechar, 2011). The classical interpretation, developed to analyze gambling, is poorly linked to the phenomenology of seismic events. The objective (or propensity) interpretation is also inadequate, since it properly applies to events that can be repeatable, like the outcomes of a controlled laboratory experiment. This is not the case for large earthquakes, which represent unique episodes in the evolution of the earth system, and irreversibly perturb the system itself. At least, the verification of the prediction would imply very long periods of observation, amounting to many consecutive prediction intervals. The subjective (or Bayesian) interpretation, representing the degree of belief of the forecaster, implies the substantial impossibility of validate the prediction by usual statistical tests (e.g., ��������� ��� ������� ������ Marzocchi and Zechar, 2011). In summary, the many uncertainties involved in probabilistic models make these tools inherently unreliable, as admitted by Marzocchi and Zechar (2011): “�� �������� ���� ����� ���� In practice this means that any forecast model that worked satisfactorily in a given period may fail in future experiments.” It is also worth recalling the sharp remarks by Freedman and Stark (2003): “������ ����� Making sense of earthquake forecasts is difficult, in part because standard interpretations of probability are inadequate… The problem in earthquake forecasts is that the models (unlike the models for coin-tossing) have not been tested against relevant data. Indeed, the models cannot be tested on a human time scale, so there is little reason to believe the probability estimates. … although some parts of the earthquake models are constrained by the laws of physics, many steps involve extrapolating rules of thumb far beyond the data they summarize; other steps rely on expert judgment separate from any data; still other steps rely on ad hoc decisions made as much for convenience as for scientific relevance.” Conclusions. ��������� ���������� ���������� �� ������������� ���������� �������� ������ Long-term earthquake prediction by probabilistic approaches presents severe shortcomings. The interpretation of their basic outcome (i.e. probability values) is still debated. The assumption that future shocks can be predicted by stochastic models of past seismicity is crucially weakened by the shortness of known seismic history. The implementation of probabilistic algorithms often neglects basic aspects of seismogenic processes, such as fault interactions and stress perturbation processes. The practical use of the probability maps is made difficult by the usually very low estimated probability values. Finally, recent attempts performed for the Italian region have not forecast the most important earthquakes occurred during the 2009-2014 prevision interval. Taking into account the above problems, we suggest that the identification of the zones most prone to the next destructive shocks should be pursued by alternative approaches. In this regard, a number of papers has been devoted to the elaboration of a deterministic methodology for the Italian region (Mantovani et al. , 2009, 2010, 2012, 2014; Viti et al. , 2011, 2012, 2013). This methodology relies on the assumption that past and future seismic activity are closely related to the development of tectonic processes, mostly controlled by the interaction between the Adriatic plate and the surrounding orogenic belts (i.e., Hellenides, Dinarides, Alps, Apennines and Calabrian Arc). In particular, the spatio-temporal distribution of the past strong events can significantly influence the location of the next earthquakes. Thus, the recognition of regularity patterns of seismicity in the central Mediterranean, in terms of migration of seismic activity and interrelation between seismic sources, may provide valuable information about the location of the future destructive shocks in Italy. Furthermore, a detailed knowledge of the post-early Pleistocene tectonic setting of the Apennines has allowed us to propose reliable explanations for the interaction among the main seismic zones of the Italian region. Then, the physical plausibility of the presumed interactions has been tested by numerical experiments based on the long-term and long-range post-seismic stress perturbation processes. The results of the above mentioned researches provide a sound basis for the identification of which sectors of the Italian region may first be affected by strong earthquakes, as described in detail by Mantovani et al. (2014).