Enriching the RESORCE database by synthetic waveforms to weight Ground-Motion Prediction Equations for seismic hazard assessment

Corentin Gouache and Paul Cupillard and Pierre Tinard. ( 2020 )
in: 2020 RING Meeting, ASGA

Abstract

Peak Ground Acceleration and Velocity (PGA and PGV) are commonly used to describe the seismic hazard. Given an earthquake and a studied site at the surface, they can be estimated by empirical Ground-Motion Prediction Equations (GMPE). GMPE provide simple analytical solutions to assess the seismic hazard and can be easily deployed to get a fast estimation of PGA or PGV in Probabilistic Seismic Hazard Assessment studies. In order to mitigate the GMPE simplicity compared to the complex physical processes involved in seismic wave propagation, seismic hazard analysis attempt to weight a set of selected GMPE. However, the weights are often based on past-experiences from users in similar contexts and set independently from two important parameters: earthquake magnitude and source-site distance. In this paper, we propose to use the recent European acceleration database, called RESORCE (https://resorce-portal.eu/), and Spectral Element Method (SEM) simulations of seismic wave propagation to calibrate a set of ve selected GMPE applicable on French mainland. RESORCE data are classied through magnitude and distance distribution. They are used to weight the ve GMPE except for magnitude - distance couples considered as poorly represented in the RESORCE database. For those magnitude - distance couples, synthetic data are generated thanks to SEM simulations, which enriches the database and helps in constraining the weights for the ve GMPE. The obtained weights display a categorical behaviour: for each magnitude - distance couple, only one GMPE controls the estimated PGA or PGV, the ve others being insignicant. Moreover, only two GMPE among the ve studied seem to be involved in the whole range of magnitude and distance covered by the RESORCE data.

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    BibTeX Reference

    @INPROCEEDINGS{GOUACHE_RM2020,
        author = { Gouache, Corentin and Cupillard, Paul and Tinard, Pierre },
         title = { Enriching the RESORCE database by synthetic waveforms to weight Ground-Motion Prediction Equations for seismic hazard assessment },
     booktitle = { 2020 RING Meeting },
          year = { 2020 },
     publisher = { ASGA },
      abstract = { Peak Ground Acceleration and Velocity (PGA and PGV) are commonly used to describe the seismic hazard. Given an earthquake and a studied site at the surface, they can be estimated by empirical Ground-Motion Prediction Equations (GMPE). GMPE provide simple analytical solutions to assess the seismic hazard and can be easily deployed to get a fast estimation of PGA or PGV in Probabilistic Seismic Hazard Assessment studies. In order to mitigate the GMPE simplicity compared to the complex physical processes involved in seismic wave propagation, seismic hazard analysis attempt to weight a set of selected GMPE. However, the weights are often based on past-experiences from users in similar contexts and set independently from two important parameters: earthquake magnitude and source-site distance. In this paper, we propose to use the recent European acceleration database, called RESORCE (https://resorce-portal.eu/), and Spectral Element Method (SEM) simulations of seismic wave propagation to calibrate a set of ve selected GMPE applicable on French mainland. RESORCE data are classied through magnitude and distance distribution. They are used to weight the ve GMPE except for magnitude - distance couples considered as poorly represented in the RESORCE database. For those magnitude - distance couples, synthetic data are generated thanks to SEM simulations, which enriches the database and helps in constraining the weights for the ve GMPE. The obtained weights display a categorical behaviour: for each magnitude - distance couple, only one GMPE controls the estimated PGA or PGV, the ve others being insignicant. Moreover, only two GMPE among the ve studied seem to be involved in the whole range of magnitude and distance covered by the RESORCE data. }
    }