Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/3066
AuthorsIervolino, I.* 
Convertito, V.* 
Giorgio, M.* 
Manfredi, G.* 
Zollo, A.* 
TitleThe Crywolf Issue in Earthquake Early Warning Applications for the Campania Region
Issue Date2007
URIhttp://hdl.handle.net/2122/3066
KeywordsEarthquake Early
Campania Region
Subject Classification04. Solid Earth::04.06. Seismology::04.06.03. Earthquake source and dynamics 
04. Solid Earth::04.06. Seismology::04.06.04. Ground motion 
04. Solid Earth::04.06. Seismology::04.06.11. Seismic risk 
AbstractEarthquake early warning systems (EEWS), based on real-time prediction of ground motion or structural response measures, may play a role in re- ducing vulnerability and/or exposure of buildings and lifelines. Indeed, seismologists have recently developed efficient methods for real-time es- timation of an event’s magnitude and location based on limited informa- tion of the P-waves. Therefore, when an event occurs, estimates of magni- tude and source-to-site distance are available, and the prediction of the structural demand at the site may be performed by Probabilistic Seismic Hazard Analysis (PSHA) and then by Probabilistic Seismic Demand Analysis (PSDA) depending upon EEWS measures. Such an approach contains a higher level of information with respect to traditional seismic risk analysis and may be used for real-time risk management. However, this kind of prediction is performed in very uncertain conditions which may affect the effectiveness of the system and therefore have to be taken into due account. In the present study the performance of the EWWS under development in the Campania region (southern Italy) is assessed by simu- lation. The earthquake localization is formulated in a Voronoi cells ap- proach, while a Bayesian method is used for magnitude estimation. Simu- lation has an empirical basis but requires no recorded signals. Our results, in terms of hazard analysis and false/missed alarm probabilities, lead us to conclude that the PSHA depending upon the EEWS significantly improves seismic risk prediction at the site and is close to what could be produced if magnitude and distance were deterministically known.
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