Generic Source Parameter Determination for Earthquake Early Warning: Theory, Observations and Implications for the Mw 7.1 Ridgecrest Earthquake

A generic approach for real-time magnitude and stress drop is introduced that is based on the omega-squared model (Brune, 1970) and results from Lior and Ziv (2018). This approach leads to approximate expressions for earthquake magnitude and stress drop as functions of epicentral distance and ground motion root-mean-squares (rms). Because the rms of the ground motion (acceleration, velocity and displacement) may be calculated directly from the seismogram in the time domain, the use of this approach for automated real-time processing is rather straightforward. Once the seismic moment and stress drop are known, they may be plugged in the ground motion prediction equations (GMPE) of Lior and Ziv (2018) to map the predicted peak shaking.

This method is generic in the sense that it is readily implementable in any tectonic environment, without having to go through a calibration phase. The potential of these results for automated early warning applications is demonstrated using a large dataset of about 6000 seismograms recorded by strong-motion and broadband velocity sensors from different tectonic environments. Optimal real-time performance is achieved by integrating magnitude and stress drop estimates into an evolutionary algorithm. The result of such an evolutionary calculation for the Mw 7.1 Ridgecrest earthquake indicates close agreement with the true magnitude.