Quancai Xie

The significant amplification of ground-motion records associated with Moho-reflected S waves (SmS) has been well documented in previous studies. The deployment of the Chinese earthquake early warning system has provided denser station coverage, enabling deeper investigation into SmS behavior, particularly the interaction between local site effects and successive SmS arrivals. During the 2023 Ms 4.7 earthquake in Pulandian, Liaoning, peak ground acceleration was notably enhanced at stations located approximately 80 km from the epicenter. The reflected SmS exhibited an average peak amplitude 1.86 times that of the direct S wave. Notably, northeastern stations exhibited amplification, with SmS amplitudes reaching up to approximately eight times that of the S wave. Further analysis suggests that resonance between the SmS dominant frequency and the fundamental site frequency contributed to additional ground-motion amplification. These results imply that current ground-motion prediction equations may underestimate the structural damage potential associated with SmS waves in the far field. However, incorporating such effects into prediction equations is not straightforward, as it requires more detailed constraints on crustal velocity structure, source depth, and 3D path effects.

The seismic design response spectrum is a vital parameter for determining the potential seismic load of the engineering structure. Differential evolution algorithm (DE) with a novel hybrid mutation operator is utilized to calibrate the spectral parameters in order to enhance iteration efficiency. This study calibrates the seismic design response spectrum for China based on the Chinese seismic intensity scale and compares the results with the Code for Seismic Design of Buildings (CSDB2010).The calibration spectra are based on strong ground motion records with destructive power exceeding the Chinese seismic intensity 7 and above. The characteristics of the calibration spectral parameters are analyzed and subsequently compared with the design spectra of the Code for Seismic Design of Buildings (CSDB2010). It is found that: Increasing the number of iterations can enhance the fitting goodness of DE between the calibration spectrum and the record response spectrum. The average site characteristic period ( T _g ) for rock and hard soil site conditions (Class I and II) is greater than the T _g specified in CSDB2010. The average T _g for intensity 10 + is greater than the average T _g for intensity 7, 8, and 9. T _g increases with the seismic intensity. The average spectra platform value ( β _max ) from this study gradually approaches the β _max in CSDB2010 as the intensity increases. The average attenuation index ( γ ) at different intensities of this study is greater than γ in CSDB2010.

Seismic phase picking is a critical geophysical process for earthquake monitoring and early warning. The exponential growth of continuous waveform data from modern seismic networks renders traditional manual analysis increasingly time-consuming and labor-intensive. Here, we introduce EQAnomalyNet, an unsupervised Transformer-based autoencoder that learns to reconstruct continuous seismic waveforms, thereby detecting phase arrivals by identifying reconstruction anomalies without labeled data. Technically, we introduce an intrapane/ inter-pane partitioning strategy informed by seismological understanding of wave propagation to separate background noise from potential windows containing phases, reflecting the fact that seismic events are sparse in time. Our approach shows that the self-attention weight distribution of sequences containing seismic phase arrivals can effectively capture the complex correlations inherent in the “development-peak” process of seismic waves. Experiments on the public STEAD dataset and K-NET strong-motion records indicate that EQAnomalyNet achieves phase-picking accuracy competitive with supervised methods while supporting rapid inference. These results demonstrate that unsupervised learning, through architectures designed with seismological insights, can effectively identify seismic phase arrivals and fulfill practical requirements such as swift event location and early warning.

Ground motion recording with peak ground acceleration (PGA) exceeding 1.43 g was observed at the Yamamoto (MYGH10) station during the M_W 7.1 Fukushima earthquake off the east coast of Honshu, Japan, in February 2021. In this study, we investigated the site amplification effect and nonlinear site response at the MYGH10 site using the horizontal‐to‐vertical spectral ratio (HVSR) and surface‐to‐borehole spectral ratio (SBSR), respectively. The site transfer function of station MYGH10 was presented using HVSR_s (HVSR on the ground surface) and SBSR at different frequency bands. The dominant contributing frequency band of the PGA was determined by increasing the high cutoff frequency of the bandpass filter when filtering the acceleration recording, which was used to interpret the anomaly of the PGA by combining it with the site characteristics. We found an obvious site effect below the downhole sensor through the HVSR_b (HVSR on the downhole bedrock) and determined the influence of the frequency band of the downhole site on ground motion. In addition, substantial discrepancies in the frequency and amplitude between the spectral ratio curves for the Fukushima mainshock records and the weak historical motions were identified. The calculated values of the degree of nonlinearity suggested that a strong nonlinear site response occurred at station MYGH10. Finally, the recovery of the site after strong shaking was evaluated by using the average spectral ratio curves of several aftershock records.