Earthquake early warning (EEW) systems aim to provide advance warning of impending ground shaking, and the technique used for real-time prediction of shaking is a crucial element of EEW systems. Many EEW systems are designed to predict the strength of seismic ground motions (peak ground acceleration, peak ground velocity, or seismic intensity) based on rapidly estimated source parameters (the source-based method), such as hypocentral location, origin time, magnitude, and extent of fault rupture. Recently, however, the wavefield-based (or ground-motion-based) method has been developed to predict future ground motions based directly on the current wavefield, i.e., ground motions monitored in real-time at neighboring sites, skipping the process of estimation of the source parameters. The wavefield-based method works well even for large earthquakes with long duration and huge rupture extents, highly energetic earthquakes that deviate from standard empirical relations, and multiple simultaneous earthquakes, for which the conventional source-based method sometimes performs inadequately. The wavefield-based method also enables prediction of the ongoing seismic waveform itself using the physics of wave propagation, thus providing information on the duration, in addition to the strength of strong ground motion for various frequency bands. In this paper, I review recent developments of the wavefield-based method, from simple applications using relatively sparse observation networks to sophisticated data assimilation techniques exploiting dense networks.
Real-time Prediction of Earthquake Ground Motion Using Seismic Records Observed in Deep Boreholes
