Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/4826
AuthorsMurru, M.* 
Console, R.* 
Falcone, G.* 
TitleReal time earthquake forecasting in Italy
Issue Date20-Sep-2008
DOI10.1016/j.tecto.2008.09.010
URIhttp://hdl.handle.net/2122/4826
KeywordsEarthquake forecasting, Real time forecasting, Epidemic model, Hypothesis testing, Error diagrams
Subject Classification04. Solid Earth::04.06. Seismology::04.06.02. Earthquake interactions and probability 
AbstractWe have applied an earthquake clustering epidemic model to real time data at the Italian Earthquake Data Center operated by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for short-term forecasting of moderate and large earthquakes in Italy. In this epidemic-type model every earthquake is regarded, at the same time, as being triggered by previous events and triggering following earthquakes. The model uses earthquake data only, with no explicit use of tectonic, geologic, or geodetic information. The forecasts are displayed as time-dependent maps showing both the expected rate density of Ml ≥ 4.0 earthquakes and the probability of ground shaking exceeding Modified Mercalli Intensity VI (PGA ≥ 0.01 g) in an area of 100 × 100 km2 around the zone of maximum expected rate density in the following 24 h. For testing purposes, the overall probability of occurrence of an Ml ≥ 4.5 earthquake in the same area of 100 × 100 km2 is also estimated. The whole procedure is tested in real time, for internal use only, at the INGV Earthquake Data Center. Forecast verification procedures have been carried out in forward-retrospective way on the 2006–2007 INGV data set, making use of statistical tools as the Relative Operating Characteristics (ROC) diagrams. These procedures show that the clustering epidemic model performs up to several hundred times better than a simple random forecasting hypothesis. The seismic hazard modeling approach so developed, after a suitable period of testing and refinement, is expected to provide a useful contribution to real time earthquake hazard assessment, even with a possible practical application for decision making and public information.
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