Physics-based earthquake early warning using distributed acoustic sensing

We present a physics-based point source earthquake early warning system using distributed acoustic sensing (DAS) data. All core modules of the system are based on physical principles of wave propagation, and models that describe the earthquake source and far-field ground motion. The detection-location algorithm is based on time-domain delay-and-sum beamforming, and the magnitude estimation and ground motion prediction are performed using analytical equations based on the Brune omega squared model. We demonstrate the performance of the system in terms of magnitude estimation and ground motion prediction, and in terms of real-time computational feasibility using local $$3.1 \le \textrm{M} \le 3.6$$ earthquakes. This DAS early warning system allows for fast deployment, circumventing some calibration phases that require gathering local DAS earthquake data before the system becomes operational.