Capturing Geographically-Varying Uncertainty in Earthquake Ground Motion Models or What We Think We Know May Change

Part of the Geotechnical, Geological and Earthquake Engineering book series (GGEE, volume 46)


Our knowledge of earthquake ground motions of engineering significance varies geographically. The prediction of earthquake shaking in parts of the globe with high seismicity and a long history of observations from dense strong-motion networks, such as coastal California, much of Japan and central Italy, should be associated with lower uncertainty than ground-motion models for use in much of the rest of the world, where moderate and large earthquakes occur infrequently and monitoring networks are sparse or only recently installed. This variation in uncertainty, however, is not often captured in the models currently used for seismic hazard assessments, particularly for national or continental-scale studies.

In this theme lecture, firstly I review recent proposals for developing ground-motion logic trees and then I develop and test a new approach for application in Europe. The proposed procedure is based on the backbone approach with scale factors that are derived to account for potential differences between regions. Weights are proposed for each of the logic-tree branches to model large epistemic uncertainty in the absence of local data. When local data are available these weights are updated so that the epistemic uncertainty captured by the logic tree reduces. I argue that this approach is more defensible than a logic tree populated by previously published ground-motion models. It should lead to more stable and robust seismic hazard assessments that capture our doubt over future earthquake shaking.



I thank the conference organizers for inviting me to deliver a Theme Lecture. I thank the developers of the ESM strong-motion flat-file 2017 for providing these data. Finally, I thank Dino Bindi, Hilmar Bungum, Fabrice Cotton, Laurentiu Danciu, Ben Edwards and Graeme Weatherill for their comments on a previous version of this study. In an effort not to increase the length of this article, I have chosen not to follow some of their suggestions, despite agreeing with them.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringUniversity of StrathclydeGlasgowUK

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