• Media type: E-Article
  • Title: A regionally-adaptable “scaled backbone” ground motion logic tree for shallow seismicity in Europe: application to the 2020 European seismic hazard model
  • Contributor: Weatherill, Graeme [Author]; Kotha, Sreeram Reddy [Author]; Cotton, Fabrice [Author]; GFZ German Research Centre for Geosciences, Potsdam, Germany [Author]; Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, IFSTTAR, ISTerre, Grenoble, France [Author]
  • imprint: Springer Netherlands, 2020-07-07
  • Language: English
  • DOI: https://doi.org/10.1007/s10518-020-00899-9
  • Keywords: Regionalisation ; Epistemic uncertainty ; Ground motion models ; Probabilistic seismic hazard assessment
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  • Description: The selection of ground motion models, and the representation of their epistemic uncertainty in the form of a logic tree, is one of the fundamental components of probabilistic seismic hazard and risk analysis. A new ground motion model (GMM) logic tree has been developed for the 2020 European seismic hazard model, which develops upon recently compiled ground motion data sets in Europe. In contrast to previous European seismic hazard models, the new ground model logic tree is built around the scaled backbone concept. Epistemic uncertainties are represented as calibrations to a reference model and aim to characterise the potential distributions of median ground motions resulting from variability in source scaling and attenuation. These scaled backbone logic trees are developed and presented for shallow crustal seismic sources in Europe. Using the new European strong motion flatfile, and capitalising on recent perspectives in ground motion modelling in the scientific literature, a general and transferable procedure is presented for the construction of a backbone model and the regionalisation of epistemic uncertainty. This innovative approach forms a general framework for revising and updating the GMM logic tree at national and European scale as new strong motion data emerge in the future. ; Horizon 2020 http://dx.doi.org/10.13039/501100007601
  • Access State: Open Access
  • Rights information: Attribution (CC BY)