Real-Time Characterization of Finite Rupture and Its Implication for Earthquake Early Warning: Application of FinDer to Existing and Planned Stations in Southwest China

Abstract

Earthquake early warning (EEW) not only improves resilience against the risk of earthquake disasters, but also provides new insights into seismological processes. The Finite-Fault Rupture Detector (FinDer) is an efficient algorithm to retrieve line-source models of an ongoing earthquake from seismic real-time data. In this study, we test the performance of FinDer in the Sichuan-Yunnan region (98.5oE–106.0oE, 22.0oN–34.0oN) of China for two datasets: the first consists of seismic broadband and strong-motion records of 58 earthquakes with 5.0 ≤ MS ≤ 8.0; the second comprises additional waveform simulations at sites where new stations will be deployed in the near future. We utilize observed waveforms to optimize the simulation approach to generate ground-motion time series. For both datasets the resulting FinDer line-source models agree well with the reported epicenters, focal mechanisms, and finite-source models, while they are computed faster compared to what traditional methods can achieve. Based on these outputs, we determine a theoretical relation that can predict for which magnitudes and station densities FinDer is expected to trigger, assuming that at least three neighboring stations must have recorded accelerations of 4.6 cm/s2 or more. We find that FinDer likely triggers and sends out a report, if the average distance between the epicenter and the three closest stations, Depi, is equal or smaller than log10 (Ma + b) + c, where a = 1.91, b = 5.93, and c = 2.34 for M = MW ≥ 4.8, and c = 2.49 for M = MS ≥ 5.0, respectively. If the data used in this study had been available in real-time, 40–70% of sites experiencing seismic intensities of V-VIII (on both Chinese and MMI scales) and 20% experiencing IX-X could have been issued a warning 5–10 s before the S-wave arrives. Our offline tests provide a useful reference for the planned installation of FinDer in the nationwide EEW system of Chinese mainland.

Real-Time Seismic Intensity Measurements Prediction for Earthquake Early Warning: A Systematic Literature Review

“…Compared with the PSA, FinDer takes into account the fault distance from the target point and is more precise for the prediction of IMs. In a retrospective study whereby the FinDer algorithm was used for the Wenchuan earthquake, the alarm was triggered 12 s after the earthquake, and the final estimated rupture length and strike were consistent with the actual findings [78]. In the improved version of the FinDer algorithm, the applicability of FinDer is extended to the entire EM range using a list of PGA thresholds, which compensates for the previous generation FinDer algorithm, which was only applicable to large earthquakes [20].…”

Retrospective Study of FinDer Algorithm During the 2019, Ridgecrest Earthquake Sequence

“…This roughly corresponds to a region with radius of over 20 km assuming an approximate propagation speed of 3.75 km/s in Southern California (Mori et al, 1996;Wurman et al 2007). With regard to FinDer, the dimension of late-alert-zone actually depends on the network geometry thus the relevant algorithm trigger threshold predefined as the amplitude exceedance level surpassed by the minimal number of stations (Li et al 2021). But warning times would hardly change for decreased station spacing beyond certain limits due to the processing and algorithms delays also contributing to the data latency (Kuyuk et al 2013;Behr et al 2015).…”

“…The inerstation distance is defined as the average distance between the epicenter to the three closest stations (Li et al, 2021). The degree of sparseness is calculated according to the arithmetic sum of angular sectors with every 15° azimuthal range having zero stations in this article (Convertito et al 2012).…”