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 𝑀𝑊 ≥ 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 𝑀𝑊 < 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 attenuation – specifically, 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.