Ground motion models for shallow crustal and deep earthquakes in Hawaii and analyses of the 2018 M 6.9 Kalapana sequence

EARTHQUAKE SPECTRA(2022)

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摘要
The damaging 4 May 2018 M 6.9 Kalapana earthquake and its aftershocks have provided the largest suite of strong motion records ever produced for an earthquake sequence in Hawaii exceeding the number of records obtained in the deep 2006 M 6.7 Kiholo Bay earthquake. These records provided the best opportunity to understand the processes of strong ground shaking in Hawaii from shallow crustal (< 20 km) earthquakes. There were four foreshocks and more than 100 aftershocks of M 4.0 and greater recorded by the seismic stations. The mainshock produced only a modest horizontal peak ground acceleration (PGA) of 0.24 g at an epicentral distance of 21.5 km. In this study, we evaluated the 2018 strong motion data as well as previously recorded shallow crustal earthquakes on the Big Island. There are still insufficient strong motion data to develop an empirical ground motion model (GMM) and so we developed a GMM using the stochastic numerical modeling approach similar to what we had done for deep Hawaiian (>20 km) earthquakes. To provide inputs into the stochastic model, we performed an inversion to estimate kappa, stress drops, Ro, and Q(f) using the shallow crustal earthquake database. The GMM is valid from M 4.0 to 8.0 and at Joyner-Boore (R-JB) distances up to 400 km. Models were developed for eight V(S)30 (time-averaged shear-wave velocity in the top 30 m) values corresponding to the National Earthquake Hazards Reduction Program (NEHRP) site bins: A (1500 m/s), B (1080 m/s), B/C (760 m/s), C (530 m/s), C/D (365 m/s), D (260 m/s), D/E (185 m/s), and E (150 m/s). The GMM is for PGA, peak horizontal ground velocity (PGV), and 5%-damped pseudo-spectral acceleration (SA) at 26 periods from 0.01 to 10 s. In addition, we updated our GMM for deep earthquakes (>20 km) to include the same NEHRP site bins using the same approach for the crustal earthquake GMM.
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关键词
Ground motion models, seismic hazard, stress drops, stochastic point-source model
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