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Ensemble Smoothed Seismicity Models for the New Italian Probabilistic Seismic Hazard Map

Aybige Akinci, Morgan P. Moschetti, and Matteo Taroni

Penerbit : Seismological Research Letters
Tahun : 2018

We develop a long-term (a few decades or longer) earthquake rate forecast for Italy based on smoothed seismicity for incorporation in the 2017–2018 Italian Probabilistic Seismic Hazard Maps (IPSHM). Because the earthquake rate models from previous IPSHM were computed using source zones that were drawn around seismicity and tectonic provinces, the present model will be the first introduction of the smoothed seismicity method into the IPSHM. Smoothed seismicity models are constructed from both historical CPTI15 (Catalogo Parametrico dei Terremoti Italiani, 1000–2014) and instrumental (1981–2016) earthquake catalogs and use both fixed and adaptive smoothing methods. We compute spatial likelihood values comparing the spatial distribution of observed earthquakes with a suite of trial earthquake rate models to optimize smoothing parameters and catalogs. Then we produce an ensemble model using two different smoothing models (adaptive and fixed) and two earthquake catalogs (historical and instrumental), which are weighted equally through a logictree approach to improve the forecast capability. We also compare our optimized smoothed seismicity models with the best two models of the Italian Collaboratory for the Study of Earthquake Predictability (CSEP) experiment and retrospectively test them with the CSEP methodology. We observed that the ensemble model performs slightly better than the optimized fixed and the adaptive smoothing seismicity models obtained in this study and the best time-independent model of the CSEP Italian experiment. The preferred ensemble model forecasts an annual rate of 1.47 M ≥ 5:0 earthquakes, with higher rates mainly concentrating along the Apennines chain, eastern Alps, Calabria, and northeast Sicily. Finally, six ensemble models are created from the different smoothing methods using different weights through a logic-tree approach to estimate the uncertainty associated with the model

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    doi: 10.1785/0220180040
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  • Lokasi Terbit
    USA
  • Jumlah Hal
    11
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  • Versi Digital
    TIDAK
  • Versi Fisik
    TIDAK
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