A Bayesian update of Kotha et al. (2020) ground-motion model using Résif dataset

Abstract

Recent updates of pan-European seismic hazard and risk maps adopted the partially non-ergodic Kotha et al. ( 2020) ground-motion model. This model was regressed from the Engineering Strong Motion dataset, containing ground-motion data of 𝑀 𝑊 ≥ 3 events mostly from Italy, Turkey, Greece, and in smaller fractions from rest of the active shallow crustal tectonic regions of Europe. Through mixed-effects regressions, the non-ergodic model partially resolved the spatial variability of attenuation characteristics across most of seismically active Europe, but not in France due to the then lack of a regional dataset. With the availability of a manually processed dataset from Résif network, and a computationally viable Bayesian inferencing algorithm, this study extends the non-ergodic applicability of the model to 𝑀 𝑊 < 3 earthquakes, attenuating regions, tectonic localities, and sites located in France. In process, a few important decisions had to be made concerning the updating methodology, and the interpretation of spatial variability of attenuationspecifically, that of the tectonic localities producing earthquakes. The methodology and results are discussed, emphasising the need to revise the current ground-motion regionalisation approach, and to tailor the updating procedure to be application specific. This study anticipates and supports a shift from frequentist to Bayesian approach of ground-motion modelling, in order to maintain continuity of knowledge regressed from various ground-motion datasets.