Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 23, issue 7
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.
https://doi.org/10.5194/nhess-23-2387-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 7
Research article
 | 
05 Jul 2023
Research article |  | 05 Jul 2023

Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference

Lukas Bodenmann, Jack W. Baker, and Božidar Stojadinović

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Cited articles

Abrahamson, N. A. and Youngs, R. R.: A stable algorithm for regression analyses using the random effects model, B. Seismol. Soc. Am., 82, 505–510, https://doi.org/10.1785/BSSA0820010505, 1992. a
Ancheta, T. D., Darragh, R. B., Stewart, J. P., Seyhan, E., Silva, W. J., Chiou, B. S.-J., Wooddell, K. E., Graves, R. W., Kottke, A. R., Boore, D. M., Kishida, T., and Donahue, J. L.: NGA-West2 Database, Earthq. Spectra, 30, 989–1005, https://doi.org/10.1193/070913EQS197M, 2014. a, b, c
Baker, J. W. and Chen, Y.: Spatial correlation estimation, GitHub [code], https://github.com/bakerjw/spatialCorrelationEstimation/ (last access: 25 April 2022), 2020. a
Baker, J., Bradley, B., and Stafford, P.: Seismic Hazard and Risk Analysis, Cambridge University Press, 582 pp., https://doi.org/10.1017/9781108425056, 2021. a
Baker, J. W. and Chen, Y.: Ground motion spatial correlation fitting methods and estimation uncertainty, Earthq. Eng. Struct. D., 49, 1662–1681, https://doi.org/10.1002/eqe.3322, 2020. a, b, c
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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.
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