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South Korea was considered a stable continental region (SCR) until the recent seismic events, specifically the 5.5- and 5.4- magnitude earthquakes in Gyeongju and Pohang, respectively, highlighting the need for reliable ground-motion models (GMMs), which are key to seismic hazard assessment analysis. Although it is appropriate to employ GMMs that are tailored to regional characteristics, irrespective of whether they are developed based on a stochastic method or actual data, a model that is similar to the tailored GMM can also be used. Recently, several earthquakes with magnitudes greater than 5 have occurred in South Korea, enabling us to assess whether the GMMs previously developed in Korea or those applied for South Korea's disaster management system are suitable for use throughout the country. Therefore, this study conducted an evaluation to assess the suitability of GMMs tailored to domestic characteristics. GMMs developed for various regions including active crustal regions, SCRs, and South Korea, were employed. Amplification functions were applied to several GMMs developed for hard rock sites. A total of 48 GMMs, considering site effects, were compared using the Korean earthquake ground motion data. The suitability of GMMs for Korea was assessed through statistical techniques such as log-likelihood method, multivariate logarithmic score, Euclidean distance-based ranking, Euclidean metric distance, deviance information criterion, and cumulative-distribution-based area metric method. Ensemble GMMs were also developed based on the rank results and analyzed using statistical methods. Un-normalized weight was used to calculate the outcomes of the above mentioned six ranking methods, and weighted GMMs were judged to be optimal for South Korea. [ABSTRACT FROM AUTHOR]

Two moderate earthquakes (the 2016 Gyeongju and 2017 Pohang earthquakes with local magnitudes of 5.8 and 5.4, respectively) in Korea caused severe damage to buildings and grounds, raising attention to local seismic hazard assessments. However, ground motion amplifications owing to site effects have not been studied yet for Korea. In 2020, the Haenam swarm produced 74 earthquakes with local magnitudes ranging from 0.87 to 3.08, providing great opportunities to investigate single-path ground motion amplifications. We develop a local ground motion model for predicting within-rock motions using the records from nine borehole stations, and evaluate empirical amplification ratios at four surface stations based on a non-reference approach. We check that the peak periods from the horizontal-to-vertical spectral ratios agree well with those from the empirical amplification ratios. Based on the shear wave velocity profiles obtained from downhole tests and multichannel analyses of surface waves, we perform one-dimensional site response analyses for the four surface stations. The amplification ratios estimated from the site response analyses are comparable with those from the empirical approach for the periods shorter than 0.07 s, but not for the periods longer than 0.07 s, raising the necessity of detailed studies on dynamic properties of soils and rocks in Korea. [ABSTRACT FROM AUTHOR]

Previously, time-domain algorithms were proposed to extract long-period waveforms, which do not consider frequency content of near-fault ground motions effectively. In this study, we developed an algorithm extracting high-energy long-period locations of near-fault ground motions in the time-frequency domain combining the Adaptive Chirp Mode Pursuit (ACMP) and Asymmetric Gaussian Chirplet Model (AGCM). The ACMP is an adaptive time-frequency filter, decomposes ground motions into long-period and short-period components, extracts nonlinear components one by one, and updates the bandwidth of each component to reach to the actual value. The AGCM is used to extract a velocity pulse from the long-period component. Because of the high flexibility of AGCM's chirplet atoms, the AGCM can simulate asymmetric, irregular, and multi-cycle waveforms with one atom and time-varying frequency content of waveforms. The results of the proposed algorithm showed superior performance in the detection and extraction of pulse-like waveforms, compared to the previous methods. By analyzing 1398 ground motions, we propose a linear equation for the prediction of pulse-period as a function of moment magnitude for soil and rock sites, and for all pulse-like data. The results showed that the proposed prediction equations have greater slop than the previous ones. Moreover, it was shown that for a greater moment magnitude, the energy ratio and pulse-period are distributed in a wider range, the skewness of the distribution becomes less, near-fault records have a longer pulse-period, and the velocity pulse contributes more to the total energy of the record. Investigation of the Fourier spectrum of ground motions showed that the period corresponding to the peak amplitude can be considered as the initial estimate of a pulse-period, especially for intense velocity pulses. • Adaptive Chirp Mode Pursuit (ACMP) and Asymmetric Gaussian Chirplet Model (AGCM) are combined to extract velocity pulses. • Proposed method surpasses previous models in detecting high-energy long-period waveforms and extracting multi-cycle pulses. • This study developed a prediction equation for the pulse period. • Relation of pulse features with seismological parameters (magnitude and distance) is discussed. • The period corresponding to the peak of Fourier spectrum can be considered as an initial estimate of the pulse period. [ABSTRACT FROM AUTHOR]