Parameters estimation of stochastic finite fault ground motion simulation method and its application in North China

The stochastic finite-fault method based on dynamic corner frequency has been widely applied to simulate high-frequency ground motion of near-fault field. The model input parameters include source term, path term and site condition, many of which exhibit strong regional properties and are particularly sensitive to the site. Based on strong-motion stations drilling data and recordings within North China, some region-specific key parameters including local site amplification and high-frequency decay factor kappa are examined and analyzed. The local amplification function over versus frequency for class II and III site are computed using the quarter-wavelength approximation. The kappa in North China Plain and Mountain regions are calculated by employing the spectral decay method, respectively. In addition, the calibration of stress drop is achieved by adopting the trial-and-error method, which can be also applicable to the determination of other uncertain model parameters. After input parameters are determined and model bias is evaluated, we applied the region-specific parameters in North China to simulate and analyze time history, peak ground acceleration, Fourier amplitude spectrum, acceleration response spectrum, ShakeMap of PGA for the Dezhou earthquake. Overall, the simulated results coincide well with observed recordings. The validation of region-specific parameters demonstrates that they could be applied to the synthetic high-frequency ground motions in North China.

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Journal
PLoS ONE
Published
2025-12-03
DOI
https://doi.org/10.1371/journal.pone.0337602
Citations
1
Primary Topic
Seismic Performance and Analysis
Type
article
Field-Weighted Citation Impact
0.95
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Parameters estimation of stochastic finite fault ground motion simulation method and its application in North China

Xiaohui Jia, Aiwen Liu, Xiaoshan Wang, Zihan Feng
1 citations
PLoS ONE
Seismic Performance and Analysis
0.95
article

Parameters estimation of stochastic finite fault ground motion simulation method and its application in North China

Xiaohui Jia, Aiwen Liu, Xiaoshan Wang, Zihan Feng
article en
1 citations

Abstract

The stochastic finite-fault method based on dynamic corner frequency has been widely applied to simulate high-frequency ground motion of near-fault field. The model input parameters include source term, path term and site condition, many of which exhibit strong regional properties and are particularly sensitive to the site. Based on strong-motion stations drilling data and recordings within North China, some region-specific key parameters including local site amplification and high-frequency decay factor kappa are examined and analyzed. The local amplification function over versus frequency for class II and III site are computed using the quarter-wavelength approximation. The kappa in North China Plain and Mountain regions are calculated by employing the spectral decay method, respectively. In addition, the calibration of stress drop is achieved by adopting the trial-and-error method, which can be also applicable to the determination of other uncertain model parameters. After input parameters are determined and model bias is evaluated, we applied the region-specific parameters in North China to simulate and analyze time history, peak ground acceleration, Fourier amplitude spectrum, acceleration response spectrum, ShakeMap of PGA for the Dezhou earthquake. Overall, the simulated results coincide well with observed recordings. The validation of region-specific parameters demonstrates that they could be applied to the synthetic high-frequency ground motions in North China.

PLoS ONEVol. 20(12)
Heilongjiang Earthquake Agency (CN), Hebei Science and Technology Department (CN), China Earthquake Administration (CN), Hebei GEO University (CN)
Openalex Percentile: Top 19%
Seismic Performance and Analysis
0.95
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Parameters estimation of stochastic finite fault ground motion simulation method and its application in North China — Xiaohui Jia, Aiwen Liu, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS