Articles | Volume 21, issue 8
https://doi.org/10.5194/nhess-21-2299-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-2299-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Integrating macroseismic intensity distributions with a probabilistic approach: an application in Italy
Andrea Antonucci
CORRESPONDING AUTHOR
Istituto Nazionale di Geofisica e Vulcanologia, Milan, 20133, Italy
Department of Earth Sciences, University of Pisa, Pisa, 56126, Italy
Andrea Rovida
Istituto Nazionale di Geofisica e Vulcanologia, Milan, 20133, Italy
Vera D'Amico
Istituto Nazionale di Geofisica e Vulcanologia, Pisa, 56125, Italy
Dario Albarello
Department of Physics, Earth and Environmental Sciences, University of Siena, Siena, 53100, Italy
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We used 100 years of seismicity in Italy to predict the hypothetical tectonic style of future earthquakes, with the purpose of using this information in a new seismic hazard model. To squeeze all possible information out of the available data, we created a chain of criteria to be applied in the input and output selection processes. The result is a list of cases from very clear ones, e.g., extensional tectonics in the central Apennines, to completely random tectonics for future seismic events.
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Short summary
We present a probabilistic approach for integrating incomplete intensity distributions by means of the Bayesian combination of estimates provided by intensity prediction equations (IPEs) and data documented at nearby localities, accounting for the relevant uncertainties. The performance of the proposed methodology is tested at 28 Italian localities with long and rich seismic histories and for the strong 1980 and 2009 earthquakes in Italy. An application of this approach is also illustrated.
We present a probabilistic approach for integrating incomplete intensity distributions by means...
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