Rapid Estimation of Seismic Intensities Using a New Algorithm That Incorporates Array Technologies and Ground-Motion Prediction Equations (GMPEs)

Abstract

Rapid seismic intensity maps for damaging earthquakes enable the swift implementation of earthquake disaster mitigation action, issuance of accurate tsunami warnings, and prevention of associated secondary disasters. However, many countries lack dense local seismic observation networks, making it infeasible to obtain accurate seismic intensity maps of earthquakes within a few hours, particularly for earthquakes that have considerable source extents. In this study, we developed a new algorithm for rapidly obtaining seismic intensity maps of damaging earthquakes. With our model, source energy radiation is acquired using backprojection, and then the locations and relative amplitudes of the fault geometry and subevents are determined. Peak ground accelerations and peak ground velocities (PGVs) are subsequently calculated based on ground-motion prediction equations and the distribution of the estimated subevents. PGVs are then further site-corrected using the VS30 database (Wald and Allen, 2007; Heath et al., 2020). The algorithm was applied to the 2008 Mw 7.9 Wenchuan and 2010 Mw 6.9 Yushu earthquakes, and the resulting seismic intensity maps were highly similar to those generated by field surveys. The algorithm is simple and straightforward to use, and local real-time instrument observations are not required. Calculations can be performed automatically, and reliable seismic intensity maps can be issued within 30 min following damaging earthquakes. The model’s application may assist greatly with rescue and recovery efforts, and enable tsunami hazards to be evaluated immediately following earthquakes, particularly in regions lacking dense observation networks.

Rapid estimation of seismic intensities by analyzing early aftershock sequences using the robust locally weighted regression program (LOWESS)

“…We gathered data on the estimated source rupture of the back-projection algorithm for the Wenchuan earthquake (Chen et al, 2022a). Using the same technique, a set of results reflecting the surface rupture of the 2016 Kaikura M w 7.8 earthquake was calculated using waveform data from the high-sensitivity seismograph network in Japan.…”

“…The combination of back-projection results and P-wave amplitudes could be used to quickly estimate the source length and magnitude of large earthquakes (Wang et al, 2017). Using the back-projection technique and ground motion prediction equation (GMPE), Chen et al (2022a) developed a new algorithm for quickly obtaining the intensity maps of destructive earthquakes. The algorithm was validated during the emergency response phase of the 2021 Maduo M w 7.3 and 2021 Yangbi M w 6.1 earthquakes in China and was confirmed to be suitable for intensity assessment in regions with sparse observation networks (Chen et al, 2022b).…”

Bayesian maximum entropy interpolation analysis for rapid assessment of seismic intensity using station and ground motion prediction equations

“…Many early warning stations have also been deployed in Chinese Taiwan, and the seismic intensity rapid reporting system is mainly composed of a rapid reporting system (RSS) and an early warning system (EWS) (Kinoshita, 1998); this approach is older and more comprehensive than that employed in mainland China. At present, some scholars have developed rapid seismic intensity assessment methods based on real-time seismology (source rupture process) (Smith and Mooney, 2021), and these studies have explored rapid 10.3389/feart.2024.1394937 seismic intensity assessment methods and achieved fruitful results (Chen et al, 2022a;Chen et al, 2022b;Peng et al 2023), which have been well applied in practical earthquake emergency response cases (Chen et al, 2022c). In addition to these methods, other seismic intensity assessment methods based on network surveys (Did You Feel It?)…”

“…Many scholars have established the relationship between the duration of strong ground motion acceleration, velocity, and displacement, as well as the MMI (Trifunac and Brady, 1975;Atkinson and Sonley, 2000;Worden et al, 2012). For the soft data, the formula released by Si in 1999 is used as the GMPE (Si and Midorikawa, 1999); it has been verified in many earthquake cases, and the results have been proven to be reliable and applicable (Chen et al, 2022b;Zhao et al, 2022;Kang et al, 2023;An et al, 2023;Peng et al, 2023;Chen et al, 2023;Zhou et al, 2024;Jia et al, 2024). The ground motion value mainly used in this article is the PGV.…”

“…The ground motion value mainly used in this article is the PGV. In order to achieve faster seismic intensity assessment, we performed linear field correction on PGV (PGA is usually non-linear field correction) (Chen et al, 2022b). Both GMPE and instrument records were calculated using PGV as the input value.…”