Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference
<p>Ground-motion correlation models play a crucial role in regional seismic risk modeling of spatially distributed built infrastructure. Such models predict the correlation between ground-motion amplitudes at pairs of sites, typically as a function of their spatial proximity. Data from physics...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-07-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/23/2387/2023/nhess-23-2387-2023.pdf |
| _version_ | 1797787264738131968 |
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| author | L. Bodenmann J. W. Baker B. Stojadinović |
| author_facet | L. Bodenmann J. W. Baker B. Stojadinović |
| author_sort | L. Bodenmann |
| collection | DOAJ |
| description | <p>Ground-motion correlation models play a crucial role in regional seismic risk modeling of spatially distributed built infrastructure. Such models predict the correlation between ground-motion amplitudes at pairs of sites, typically as a function of their spatial proximity. Data from physics-based simulators and event-to-event variability in empirically derived model parameters suggest that spatial correlation is additionally affected by path and site effects. Yet, identifying these effects has been difficult due to scarce data and a lack of modeling and assessment approaches to consider more complex correlation predictions. To address this gap, we propose a novel correlation model that accounts for path and site effects via a modified functional form. To quantify the estimation uncertainty, we perform Bayesian inference for model parameter estimation. The derived model outperforms traditional isotropic models in terms of the predictive accuracy for training and testing data sets. We show that the previously found event-to-event variability in model parameters may be explained by the lack of accounting for path and site effects. Finally, we examine implications of the newly proposed model for regional seismic risk simulations.</p> |
| first_indexed | 2024-03-13T01:20:24Z |
| format | Article |
| id | doaj.art-7f37c3aa253e4296888f41a409c0dcda |
| institution | Directory Open Access Journal |
| issn | 1561-8633 1684-9981 |
| language | English |
| last_indexed | 2024-03-13T01:20:24Z |
| publishDate | 2023-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj.art-7f37c3aa253e4296888f41a409c0dcda2023-07-05T04:12:16ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812023-07-01232387240210.5194/nhess-23-2387-2023Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inferenceL. Bodenmann0J. W. Baker1B. Stojadinović2Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, SwitzerlandDepartment of Civil and Environmental Engineering, Stanford University, Stanford, CA, USADepartment of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland<p>Ground-motion correlation models play a crucial role in regional seismic risk modeling of spatially distributed built infrastructure. Such models predict the correlation between ground-motion amplitudes at pairs of sites, typically as a function of their spatial proximity. Data from physics-based simulators and event-to-event variability in empirically derived model parameters suggest that spatial correlation is additionally affected by path and site effects. Yet, identifying these effects has been difficult due to scarce data and a lack of modeling and assessment approaches to consider more complex correlation predictions. To address this gap, we propose a novel correlation model that accounts for path and site effects via a modified functional form. To quantify the estimation uncertainty, we perform Bayesian inference for model parameter estimation. The derived model outperforms traditional isotropic models in terms of the predictive accuracy for training and testing data sets. We show that the previously found event-to-event variability in model parameters may be explained by the lack of accounting for path and site effects. Finally, we examine implications of the newly proposed model for regional seismic risk simulations.</p>https://nhess.copernicus.org/articles/23/2387/2023/nhess-23-2387-2023.pdf |
| spellingShingle | L. Bodenmann J. W. Baker B. Stojadinović Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference Natural Hazards and Earth System Sciences |
| title | Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference |
| title_full | Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference |
| title_fullStr | Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference |
| title_full_unstemmed | Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference |
| title_short | Accounting for path and site effects in spatial ground-motion correlation models using Bayesian inference |
| title_sort | accounting for path and site effects in spatial ground motion correlation models using bayesian inference |
| url | https://nhess.copernicus.org/articles/23/2387/2023/nhess-23-2387-2023.pdf |
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