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<p>Utilizing strong-motion data recorded by seismic stations to study the correlation characteristics between ground motion parameters can provide fundamental references for ground motion parameter selection and seismic risk assessment, which has important theoretical and practical significance. This study selected near-field acceleration records from several moderate-to-strong earthquakes in western China since 2008, focused on 27 ground motion parameters including peak ground acceleration (PGA), peak ground velocity (PGV), spectral acceleration (Sa(T), T = 0.1–5.0&#xa0;s, 21 period points), Arias intensity (AriasIM), spectrum intensity (SI), cumulative absolute velocity (CAV), and 5–95% significant duration (t<sub>D5−95</sub>), and used the Pearson Correlation Coefficient (PCC) method to compute the correlation coefficients between each pair of the parameters. A correlation coefficient matrix was obtained, and the correlation characteristics among the parameters were analyzed in detail. Finally, continuous correlation function models for PGA, PGV, AriasIM, SI, CAV, t<sub>D5−95</sub> with Sa(T) were fitted, and compared with previous research results. The findings indicated that among the six parameters PGA/PGV/AriasIM/SI/CAV/t<sub>D5−95</sub>, AriasIM and CAV exhibited the strongest correlation, while t<sub>D5−95</sub> showed weak correlation with the other parameters; the correlation coefficients of Sa(T) at different periods were related to the period interval, with smaller intervals corresponding to higher correlation coefficient values; the correlation between PGA/PGV/AriasIM/SI/CAV/t<sub>D5−95</sub> and Sa(T) varied with different periods, and t<sub>D5−95</sub> demonstrated extremely weak correlation with Sa(T) across the entire period range. Additionally, the correlation function models derived in this study showed similar trends to previous research results but exhibited certain detailed deviations, indicating that the correlation of ground motion parameters possessed distinct regional characteristics.</p>

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Correlation of ground motion parameters based on strong-motion records and GMPE residuals in western China

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Xiufeng Tian,
  • Nana Chang,
  • Minglang Che,
  • Xuan Zhang

摘要

Utilizing strong-motion data recorded by seismic stations to study the correlation characteristics between ground motion parameters can provide fundamental references for ground motion parameter selection and seismic risk assessment, which has important theoretical and practical significance. This study selected near-field acceleration records from several moderate-to-strong earthquakes in western China since 2008, focused on 27 ground motion parameters including peak ground acceleration (PGA), peak ground velocity (PGV), spectral acceleration (Sa(T), T = 0.1–5.0 s, 21 period points), Arias intensity (AriasIM), spectrum intensity (SI), cumulative absolute velocity (CAV), and 5–95% significant duration (tD5−95), and used the Pearson Correlation Coefficient (PCC) method to compute the correlation coefficients between each pair of the parameters. A correlation coefficient matrix was obtained, and the correlation characteristics among the parameters were analyzed in detail. Finally, continuous correlation function models for PGA, PGV, AriasIM, SI, CAV, tD5−95 with Sa(T) were fitted, and compared with previous research results. The findings indicated that among the six parameters PGA/PGV/AriasIM/SI/CAV/tD5−95, AriasIM and CAV exhibited the strongest correlation, while tD5−95 showed weak correlation with the other parameters; the correlation coefficients of Sa(T) at different periods were related to the period interval, with smaller intervals corresponding to higher correlation coefficient values; the correlation between PGA/PGV/AriasIM/SI/CAV/tD5−95 and Sa(T) varied with different periods, and tD5−95 demonstrated extremely weak correlation with Sa(T) across the entire period range. Additionally, the correlation function models derived in this study showed similar trends to previous research results but exhibited certain detailed deviations, indicating that the correlation of ground motion parameters possessed distinct regional characteristics.