GNGTS 2021 - Atti del 39° Convegno Nazionale

169 GNGTS 2021 S essione 2.1 APPLICATION OF EEPAS SEISMIC FORECASTING MODEL TO ITALY E. Biondini 1 , D. Rhoades 2 , P. Gasperini 1 1 Dipartimento di Fisica e Astronomia, Università di Bologna, Bologna, Italy 2 GNS Science, Lower Hutt, New Zealand The EEPAS (“Every Earthquake a Precursor According to Scale”) model is a space-time point process model for earthquakes forecasting based on the observation that the seismicity increases prior to major earthquakes. Each earthquake contributes a transient increase to the expected rate of occurrence in its vicinity following empirical predictive scaling relationships associated with the precursory scale increase phenomenon (Ψ) on which EEPAS model is based. The model uses only seismic data (from earthquake catalogs), with no explicit use of tectonic or geologic information. EEPAS model has already been applied and tested in some seismic regions of the world such as New Zealand, California, and Japan (Rhoades and Evison, 2004, 2005). In this work we applied and evaluated the retrospective forecast performance of the EEPAS model for Italy using an “alarm-based” approach. We applied the EEPAS model to Italy using data from the HORUS - HOmogenized instRUmental Seismic catalog (http://horus.bo.ingv.it) from 1960 to 2020 (Lolli et al. 2020), also adding the earthquakes of the CPTI15 catalog (Rovida et al, 2020) from 1920 to 1959. We then evaluated the forecasting performances using Molchan diagrams (Molchan 1990,1991) and Area Skill Score statistics (Zechan & Jordan 2008, 2010) and compared them with the performance obtained by an already published forecasting model based on the occurrence of foreshock before a mainshock (Gasperini et al. 2021). References Gasperini, P., E. Biondini, B. Lolli, A. Petruccelli, and G. Vannucci. 2021. “Retrospective Short-Term Forecasting Experiment in Italy Based on the Occurrence of Strong (Fore) Shocks.” Geophysical Journal International 1192–1206. Lolli, Barbara, Daniele Randazzo, Gianfranco Vannucci, and Paolo Gasperini. 2020. “The Homogenized Instrumental Seismic Catalog (HORUS) of Italy from 1960 to Present.” Seismological Research Letters 91(6):3208–22. Molchan, G. M. 1990. “Strategies in Strong Earthquake Prediction.” Physics of the Earth and Planetary Interiors 61(1):84–98. Molchan, George M. 1991. “Structure of Optimal Strategies in Earthquake Prediction.” Tectonophysics 193(4):267–76. Rhoades, David A. and Frank F. Evison. 2004. “Long-Range Earthquake Forecasting with Every Earthquake a Precursor According to Scale.” Pure and Applied Geophysics 161(1):47–72. Rhoades, David A. and Frank F. Evison. 2005. “Test of the EEPAS Forecasting Model on the Japan Earthquake Catalogue.” Pure and Applied Geophysics 162(6–7):1271–90. Rovida, Andrea, Mario Locati, Romano Camassi, and Barbara Lolli. 2020. The Italian Earthquake Catalogue CPTI15 . Springer Netherlands. Woessner, Jochen, Annemarie Christophersen, J. Douglas Zechar, and Damiano Monelli. 2010. “Building Self-Consistent, Short-Term Earthquake Probability (STEP) Models: Improved Strategies and Calibration Procedures.” Annals of Geophysics 53(3):141–54. Zechar, J. Douglas and Thomas H. Jordan. 2008. “Testing Alarm-Based Earthquake Predictions.” Geophysical Journal International 172(2):715–24. Zechar, J. Douglas and Thomas H. Jordan. 2010. “The Area Skill Score Statistic for Evaluating Earthquake Predictability Experiments.” Pure and Applied Geophysics 167(8–9):893–906. Corresponding authors: emanuele.biondini2@unibo.it; d.rhoades@gns.cri.nz; paolo.gasperini@unibo.it