AGU Fall Meeting, San Francisco CA, USA, 10-14 December, 2007
Iannaccone Giovanni, Zollo Aldo, Bobbio Antonella, Cantore Luciana, Convertito Vincenzo, Elia Luca, Festa Gaetano, Lancieri Maria, Martino Claudio, Romeo Annalisa, Satriano Claudio, Vassallo Maurizio
A new seismic network (ISNet, Irpinia Seismic Network) is now operating in the Southern Italy. It is conceived as the core infrastructure for an Earthquake Early Warning System (EEWS) under development in Southern Italy. It is primarily aimed at providing an alert for moderate to large earthquakes (M$>$4) to selected target sites in Campania Region and it also provides data for rapid computation of regional ground-shaking maps. ISNet is deployed over an area of about $100\times 70 km^2$ covering the Apenninic active seismic zone where most of large earthquakes occurred during the last centuries, including the $M_s=6.9$, 1980 Irpinia earthquake. ISNet is composed of 29 seismic stations equipped with three components accelerometers and elocimeters aggregated in six smaller sub-nets. The sub-net stations are connected with a real-time communications to a central data-collector site (LCC, Local Control Center). The different LCCs are linked among them and to a Network Control Center (NCC) located in the city of Naples 100 km away from the network center, with different type of transmission systems chosen according their transmission mode robustness and reliability. The network is designed to provide estimates of the location and size of a potential destructive earthquake within few seconds from the earthquake detection, through an evolutionary and fully probabilistic approach. For the real time location we developed a methodology which extends and generalizes the one Horiuchi et al. (2005) by a) starting the location procedure after only one station has triggered, b) using the Equal Differential Time (EDT) approach to incorporate the triggered arrivals and the not-yet-triggered stations, c) estimating the hypocenter probabilistically as a pdf instead of as a point, and d) applying a full, non-linearized, global-search for each update of the location estimate. Following an evolutionary approach, the method evaluates, at each time step, the EDT equations considering not only each pair of triggered stations, but also those pairs where only one station has triggered. The size of earthquake is also evaluated by a real time, evolutionary algorithm based on a magnitude predictive model and a Bayesian formulation. It is aimed at valuating the conditional probability density function of magnitude as a function of ground motion quantities measured on the early part of the acquired signals. The predictive models are empirical relationships which correlate the final event magnitude with the P-displacement amplitudes measured on first 2-4 seconds of record after the first-P arrival. The methods previously described for rapidly estimating the event’s location and magnitude, are used to perform a real-time seismic hazard analysis allowing to compute the probabilistic distribution, or hazard curve, of ground motion intensity measures (IM) i.e. the peak ground acceleration (PGA) or the spectral acceleration (Sa), at selected sites of the Campania Region. We show the performances of the earthquake early warning system through applications to simulated large events and recorded low magnitude earthquakes.