A New Network-Based Approach for the Earthquake Early Warning
Abstract
Here we propose a new method which allows for issuing an early warning based upon the real-time mapping of the Potential Damage Zone (PDZ), e.g. the epicentral area where the peak ground velocity is expected to exceed the damaging or strong shaking levels with no assumption about the earthquake rupture extent and spatial variability of ground motion. The system includes the techniques for a refined estimation of the main source parameters (earthquake location and magnitude) and for an accurate prediction of the expected ground shaking level. The system processes the 3-component, real-time ground acceleration and velocity data streams at each station. For stations providing high quality data, the characteristic P-wave period (τc) and the P-wave displacement, velocity and acceleration amplitudes (Pd, Pv and Pa) are jointly measured on a progressively expanded P-wave time window. The evolutionary estimate of these parameters at stations around the source allow to predict the geometry and extent of PDZ, but also of the lower shaking intensity regions at larger epicentral distances. This is done by correlating the measured P-wave amplitude with the Peak Ground Velocity (PGV) and Instrumental Intensity (IMM) and by interpolating the measured and predicted P-wave amplitude at a dense spatial grid, including the nodes of the accelerometer/velocimeter array deployed in the earthquake source area. Depending of the network density and spatial source coverage, this method naturally accounts for effects related to the earthquake rupture extent (e.g. source directivity) and spatial variability of strong ground motion related to crustal wave propagation and site amplification. We have tested this system by a retrospective analysis of three earthquakes: 2016 Italy 6.5 Mw, 2008 Iwate-Miyagi 6.9 Mw and 2011 Tohoku 9.0 Mw. Source parameters characterization are stable and reliable, also the intensity map shows extended source effects consistent with kinematic fracture models of evets.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.S44C..08A
- Keywords:
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- 7299 General or miscellaneous;
- SEISMOLOGY