Methods for assessing the epistemic uncertainty captured in ground-motion models

Abstract A key task when developing a ground-motion model (GMM) is to demonstrate that it captures an appropriate level of epistemic uncertainty. This true whether multiple ground motion prediction equations (GMPEs) are used or backbone approach followed. The GMM developed for seismic hazard assessment the site UK new-build nuclear power plant as example discuss complementary approaches assess Firstly, trellis plots showing various percentiles examined relevant magnitudes, distances and structural periods search evidence “pinching”, where narrow excessively. Secondly, Sammon’s maps, including GMPEs were excluded from logic tree, check spread magnitudes in single plot. Thirdly, contour standard deviation logarithms predicted motions each branch tree (σ µ ) compared with drawn other studies. Fourthly, uncertainties implied by derived using Campbell (2003)’s hybrid stochastic empirical method those proposed multi-GMPE GMM. Finally, percentile curves resulting implementing different return any bands lower uncertainty space result space. These five enabled systematic captured