Articles | Volume 23, issue 7
https://doi.org/10.5194/nhess-23-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-23-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference
Lukas Bodenmann
CORRESPONDING AUTHOR
Department of Civil,
Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland
Jack W. Baker
Department of Civil and
Environmental Engineering, Stanford
University, Stanford, CA, USA
Božidar Stojadinović
Department of Civil,
Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland
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Cited
19 citations as recorded by crossref.
- Clustering-based analysis to address nonstationary spatial ground motion correlations using physics-based simulated data M. Zolfaghari & M. Forghani
- Spatial correlation assessment of multiple earthquake intensity measures using physics-based simulated ground motions M. Zolfaghari & M. Forghani
- An efficient ground motion model coupling spatial correlations for large-scale field simulation W. Fang et al.
- Risk-informed representative earthquake scenarios for Valparaíso and Viña del Mar, Chile H. Rosero-Velásquez et al.
- Correlation models for next‐generation amplitude and cumulative intensity measures using artificial neural networks S. Aristeidou et al.
- Quantifying the impacts of Canadian wildfires on regional air pollution networks T. McCracken et al.
- Prediction of ground motion intensity measures using support vector machine in analysing spatial correlation P. Wen et al.
- Near-Fault Amplification and Ground-Motion Variability During the 2019 Ridgecrest, California, Sequence E. Cochran et al.
- Spatial variability of site effects and its correlation with site response in Japan C. Lorenzo-Velazquez & A. Cabas
- Engineering attributes of ground motions from February 2023 Türkiye earthquake sequence T. Buckreis et al.
- Double Convolution Methodology for Developing Input Ground Motions for Site Response and Nonlinear Dynamic Analyses R. Pretell et al.
- February 6, 2023 Türkiye Earthquakes: Ground Motions T. E Buckreis et al.
- Accounting for ground‐motion uncertainty in empirical seismic fragility modeling L. Bodenmann et al.
- A review of ground motion correlation modelling for regional seismic risk analysis V. Monteiro & G. O’Reilly
- Spatial Variation Analysis for Ground Motions Based on Regional Site Conditions and Separation Distance P. Wen & X. Bi
- Revision of empirical NGA-West2 horizontal ground-motion models using fixed-effects and mixed-effects regression and Bayesian inference K. Campbell et al.
- Near-fault ground motions and regional shaking damage assessment of the 2024 Noto Peninsula Earthquake in Japan K. Goda et al.
- Regional Site Response Model via Uncertainty Projected Mapping: Application to Kanto Region, Japan A. Chakraborty & S. Kotha
- Seismic performance of four adjacent buildings affected by severe liquefaction in İskenderun during the 2023 M7.8 Pazarcık earthquake M. Doan et al.
19 citations as recorded by crossref.
- Clustering-based analysis to address nonstationary spatial ground motion correlations using physics-based simulated data M. Zolfaghari & M. Forghani
- Spatial correlation assessment of multiple earthquake intensity measures using physics-based simulated ground motions M. Zolfaghari & M. Forghani
- An efficient ground motion model coupling spatial correlations for large-scale field simulation W. Fang et al.
- Risk-informed representative earthquake scenarios for Valparaíso and Viña del Mar, Chile H. Rosero-Velásquez et al.
- Correlation models for next‐generation amplitude and cumulative intensity measures using artificial neural networks S. Aristeidou et al.
- Quantifying the impacts of Canadian wildfires on regional air pollution networks T. McCracken et al.
- Prediction of ground motion intensity measures using support vector machine in analysing spatial correlation P. Wen et al.
- Near-Fault Amplification and Ground-Motion Variability During the 2019 Ridgecrest, California, Sequence E. Cochran et al.
- Spatial variability of site effects and its correlation with site response in Japan C. Lorenzo-Velazquez & A. Cabas
- Engineering attributes of ground motions from February 2023 Türkiye earthquake sequence T. Buckreis et al.
- Double Convolution Methodology for Developing Input Ground Motions for Site Response and Nonlinear Dynamic Analyses R. Pretell et al.
- February 6, 2023 Türkiye Earthquakes: Ground Motions T. E Buckreis et al.
- Accounting for ground‐motion uncertainty in empirical seismic fragility modeling L. Bodenmann et al.
- A review of ground motion correlation modelling for regional seismic risk analysis V. Monteiro & G. O’Reilly
- Spatial Variation Analysis for Ground Motions Based on Regional Site Conditions and Separation Distance P. Wen & X. Bi
- Revision of empirical NGA-West2 horizontal ground-motion models using fixed-effects and mixed-effects regression and Bayesian inference K. Campbell et al.
- Near-fault ground motions and regional shaking damage assessment of the 2024 Noto Peninsula Earthquake in Japan K. Goda et al.
- Regional Site Response Model via Uncertainty Projected Mapping: Application to Kanto Region, Japan A. Chakraborty & S. Kotha
- Seismic performance of four adjacent buildings affected by severe liquefaction in İskenderun during the 2023 M7.8 Pazarcık earthquake M. Doan et al.
Saved (final revised paper)
Latest update: 30 Apr 2026
Short summary
Understanding spatial patterns in earthquake-induced ground motions is key for assessing the seismic risk of distributed infrastructure systems. To study such patterns, we propose a novel model that accounts for spatial proximity, as well as site and path effects, and estimate its parameters from past earthquake data by explicitly quantifying the inherent uncertainties.
Understanding spatial patterns in earthquake-induced ground motions is key for assessing the...
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