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Abstract
The Sichuan–Yunnan area is one of the most seismically active regions in China. As ground-motion models form a key component of seismic hazard analysis, it is important to select (or develop) appropriate models for this area. The increasing number of digital ground-motion records of earthquakes in this area has allowed the development of local ground motion prediction equations (GMPEs). This study compares and, later, recommends appropriate GMPEs for the Sichuan–Yunnan area. We first evaluate the inherent quality of local GMPEs, with respect to their underlying datasets, the variables used and their functional forms, to determine a set of candidate GMPEs. Then we investigate how well the predictions from the GMPEs match observations computed from strong-motion records of recent earthquakes in this area. The fit between predictions and observations varies significantly amongst the GMPEs. The results suggest that some recent local GMPEs would lead to biased ground-motion estimates due to limitations of their underlying datasets and functional forms. Based on both evaluations of inherent quality and compatibility with observations, only one local GMPE is recommended. A comparison of the predictions from three widely-used non-local GMPEs indicates that ground motions in the Sichuan–Yunnan area appear more variable than those in other regions but that predictions from these non-local GMPEs are generally unbiased. We recommend use of a mixture of robust local and non-local GMPEs within seismic hazard analyses to capture the epistemic uncertainty in ground-motion prediction for this area.
Original language | English |
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Pages (from-to) | 2303-2328 |
Number of pages | 26 |
Journal | Bulletin of Earthquake Engineering |
Volume | 22 |
Issue number | 5 |
Early online date | 1 Feb 2024 |
DOIs | |
Publication status | Published - 31 Mar 2024 |
Funding
This work was undertaken during Jingwei Liu’s visit at the Department of Civil and Environmental Engineering, University of Strathclyde, which was funded by the China Scholarship Council (No. 202004190043).
Keywords
- ground-motion models (GMMs)
- predictions and observations
- ground-motion records
- residual analysis
- epistemic uncertainty
- seismic hazard assessment
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Jingwei Liu
Douglas, J. (Host)
1 Oct 2022 → 30 Sept 2023Activity: Hosting a visitor types › Hosting an academic visitor