Abstract
A new non-ergodic ground-motion model (GMM) for effective amplitude spectral (EAS) values for California is presented in this study. EAS, which is defined in Goulet et al. (Effective amplitude spectrum (eas) as a metric for ground motion modeling using fourier amplitudes, 2018), is a smoothed rotation-independent Fourier amplitude spectrum of the two horizontal components of an acceleration time history. The main motivation for developing a non-ergodic EAS GMM, rather than a spectral acceleration GMM, is that the scaling of EAS does not depend on spectral shape, and therefore, the more frequent small magnitude events can be used in the estimation of the non-ergodic terms. The model is developed using the California subset of the NGAWest2 dataset (Ancheta in PEER NGA-West2 database. Tech. rep., PEER, Berkeley, CA, 2013). The Bayless and Abrahamson (Bull Seismol Soc Am 109(5): 2088-2105, https://doi.org/10.1785/0120190077, 2019b) (BA18) ergodic EAS GMM was used as backbone to constrain the average source, path, and site scaling. The non-ergodic GMM is formulated as a Bayesian hierarchical model: the non-ergodic source and site terms are modeled as spatially varying coefficients following the approach of Landwehr et al. (Bull Seismol Soc Am 106(6):2574-2583. https://doi.org/10.1785/0120160118, 2016), and the non-ergodic path effects are captured by the cell-specific anelastic attenuation attenuation following the approach of Dawood and Rodriguez-Marek (Bull Seismol Soc Am 103(2B):1360-1372, https://doi.org/10.1785/0120120125, 2013). Close to stations and past events, the mean values of the non-ergodic terms deviate from zero to capture the systematic effects and their epistemic uncertainty is small. In areas with sparse data, the epistemic uncertainty of the non-ergodic terms is large, as the systematic effects cannot be determined. The non-ergodic total aleatory standard deviation is approximately 30 to \(40\%\) smaller than the total aleatory standard deviation of BA18. This reduction in the aleatory variability has a significant impact on hazard calculations at large return periods. The epistemic uncertainty of the ground motion predictions is small in areas close to stations and past events.
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The are python scripts for the non-ergodic regressions are provided at: https://github.com/glavrentiadis/NonErgodicGMM_public
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Acknowledgements
This work was partially supported by the PG&E Geosciences Department Long-Term Seismic Program. The authors also thankful to the three anonymous reviewers for constructive comments that helped to improve the final article.
Funding
This work was partially funded by the Pacific Earthquake Engineering Research Center (PEER) Transportation Systems Research Program and by the PG&E Geosciences Department Long-Term Seismic Program.
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Lavrentiadis, G., Abrahamson, N.A. & Kuehn, N.M. A non-ergodic effective amplitude ground-motion model for California. Bull Earthquake Eng 21, 5233–5264 (2023). https://doi.org/10.1007/s10518-021-01206-w
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DOI: https://doi.org/10.1007/s10518-021-01206-w