Partially non-ergodic region specific GMPE for Europe and Middle-East

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• 作者：Sreeram Reddy Kotha ; Dino Bindi ; Fabrice Cotton
• 关键词：Ground motion prediction equations ; Europe and the Middle ; East ; RESORCE ; Regional variations ; Non ; ergodicity ; Nonlinear mixed effects regression
• 刊名：Bulletin of Earthquake Engineering
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：14
• 期：4
• 页码：1245-1263
• 全文大小：1,537 KB
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• 作者单位：Sreeram Reddy Kotha (1)
  Dino Bindi (1)
  Fabrice Cotton (1)
  
  1. GFZ German Research Centre for Geosciences, Telegrafenberg, 14473, Potsdam, Germany
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geotechnical Engineering
  Civil Engineering
  Geophysics and Geodesy
  Hydrogeology
  Structural Geology
  
• 出版者：Springer Netherlands
• ISSN：1573-1456

文摘

The ergodic assumption considers the time sampling of ground shaking generated in a given region by successive earthquakes as equivalent to a spatial sampling of observed ground motion across different regions. In such cases the estimated aleatory variability in source, propagation, and site seismic processes in ground motion prediction equations (GMPEs) is usually larger than with a non-ergodic approach. With the recently published datasets such as RESORCE for Europe and Middle-East regions, and exploiting algorithms like the non-linear mixed effects regression it became possible to introduce statistically well-constrained regional adjustments to a GMPE, thus ‘partially’ mitigating the impact of the assumption on regional ergodicity. In this study, we quantify the regional differences in the apparent attenuation of high frequency ground motion with distance and in linear site amplification with V_s30, between Italy, Turkey, and rest of the Europe-Middle-East region. With respect to a GMPE without regional adjustments, we obtain up to 10 % reduction in the aleatory variability σ, primarily contributed by a 20 % reduction in the between-station variability. The reduced aleatory variability is translated into an epistemic uncertainty, i.e. a standard error on the regional adjustments which can be accounted for in the hazard assessment through logic-tree branches properly weighted. Furthermore, the between-event variability is reduced by up to 30 % by disregarding in regression the events with empirically estimated moment magnitude. Therefore, we conclude that a further refinement of the aleatory variability could be achieved by choosing a combination of proxies for the site response, and through the homogenization of the magnitude scales across regions.