Forecasting Italian seismicity through a spatio-temporal physical model: importance of considering time-dependency and reliability of the forecast

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Chung-Han Chan
Mathilde B. Sørensen
Dietrich Stromeyer
Gottfried Grünthal
Oliver Heidbach
Amir Hakimhashemi
Flaminia Catalli

Abstract

We apply here a forecasting model to the Italian region for the spatio-temporal distribution of seismicity based on a smoothing Kernel function, Coulomb stress variations, and a rate-and-state friction law. We tested the feasibility of this approach, and analyzed the importance of introducing time-dependency in forecasting future events. The change in seismicity rate as a function of time was estimated by calculating the Coulomb stress change imparted by large earthquakes. We applied our approach to the region of Italy, and used all of the cataloged earthquakes that occurred up to 2006 to generate the reference seismicity rate. For calculation of the time-dependent seismicity rate changes, we estimated the rate-and-state stress transfer imparted by all of the ML≥4.0 earthquakes that occurred during 2007 and 2008. To validate the results, we first compared the reference seismicity rate with the distribution of ML≥1.8 earthquakes since 2007, using both a non-declustered and a declustered catalog. A positive correlation was found, and all of the forecast earthquakes had locations within 82% and 87% of the study area with the highest seismicity rate, respectively. Furthermore, 95% of the forecast earthquakes had locations within 27% and 47% of the study area with the highest seismicity rate, respectively. For the time-dependent seismicity rate changes, the number of events with locations in the regions with a seismicity rate increase was 11% more than in the regions with a seismicity rate decrease.

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How to Cite
Chan, C.-H., Sørensen, M. B., Stromeyer, D., Grünthal, G., Heidbach, O., Hakimhashemi, A. and Catalli, F. (2010) “Forecasting Italian seismicity through a spatio-temporal physical model: importance of considering time-dependency and reliability of the forecast”, Annals of Geophysics, 53(3), pp. 129–140. doi: 10.4401/ag-4761.
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