Near‐Real‐Time Estimates on Earthquake Rupture Directivity Using Near‐Field Ground Motion Data From a Dense Low‐Cost Seismic Network

Abstract

Rupture directivity of earthquakes could amplify ground shaking and cause serious earthquake hazards. Its timely information is therefore of great importance for early shaking alerts and emergency responses. To this end, we test the feasibility of using near‐field (<25 km) ground motion data from a dense low‐cost seismic network in Taiwan to constrain directivity information and provide warning for far‐field areas. The method is simple and robust, based on the real‐time shaking map interpolation and directional attenuation regression analysis. Applications to 16 moderate‐ to large‐magnitude earthquakes in Taiwan and California show that the directivity can be stably obtained within 17 s and agrees well with previous studies when available. An indicator of the strength of directivity amplification is also defined and reveals a prevalence of strong directivity effect for ML ≥ 6.0 earthquakes in Taiwan. Such near‐real‐time directivity information can therefore be useful in earthquake early warning systems for providing more accurate ground shaking alerts.

Evidence for Fluid Migration During the 2016 Meinong, Taiwan, Aftershock Sequence

“…The 5 February 2016 Meinong earthquake ( Mw 6.4) and its aftershock sequence, which occurred in a fold‐and‐thrust belt of southern Taiwan, was well documented due to the high density of seismic stations in Taiwan (Figure 1; Lee et al, 2016; Kanamori et al, 2017). Despite being relatively deep (~15 km) and small, the Meinong earthquake caused strong ground motions, extensive damage and 117 fatalities in the city of Tainan (Jan et al, 2018; Kanamori et al, 2017). Its rupture was also complex and triggered seismic and aseismic faulting at multiple depths (Huang et al, 2016; Lin et al, 2018).…”

Line‐Source Model Based Rapid Inversion for Deriving Large Earthquake Rupture Characteristics Using High‐Rate GNSS Observations

“…For the shaking map generation part, we propose a new algorithm for the generation of shaking maps using a sparse GNSS network, instead of directly interpolating based on a dense seismic network. For the directional attenuation regression analysis, we directly adopt the algorithm described by Jan et al (2018). The shaking map generation algorithm based on a sparse GNSS network is described in detail.…”

“…Jan et al. (2018) presented a near‐real‐time method for estimating earthquake rupture directivity, but this method can not determine fault rupture length for large earthquakes. A Finite‐Fault Rupture Detector (FinDer) algorithm was proposed to swiftly determine line‐source models of large earthquakes within a few to several tens of seconds using a dense seismic network (Böse et al., 2012, 2015, 2018).…”

A Review on the Development of Earthquake Warning System Using Low-Cost Sensors in Taiwan

“…The rupture direction using shakemaps from this network during the 2018 Hualien earthquake correlated well with aftershock distribution and surface ruptures [18], which again emphasizes the ability of this instrumentation in estimating rupture direction. Using real-time shakemap interpolation and attenuation regression, Jan et al ( 2018) [45] tested the feasibility of using rupture direction from the near-source P-Alert instruments for delivering a warning to the far areas. They used 16 moderate-to-large earthquakes to infer that directivity can be obtained precisely within 17 s of the occurrence of an earthquake, which in turn is very helpful for EEW.…”