Faults have been increasingly included in seismic hazard assessment (SHA), but the level of knowledge about seismogenic faults is not homogeneous, even in neighbouring countries, and several approaches have been developed to tranfer earthquake-fault geology into fault-models suitable for probabilistic SHA.
The session aims at linking field geologists, fault modelers, earthquake-rupture simulators, data modelers and seismic hazard practitioners. The objective is threefold (i) achieve a common understanding of the uncertainties that affect PSHA, (ii) focus on data acquisition and research strategies towards the collection of data in the field that is relevant for SHA calculations and (iii) promote the development of existing PSHA codes to better reflect the present day understanding of physical and geological complexities.
We solicit contributions that:
• Compare and analyze fault data and fault models around the world; we encourage participants to present the data retrieved from the field in their region of study and aimed at characterizing fault behavior, and we encourage them to describe how this fault data has been translated into a fault model for probabilistic and deterministic SHA.
• Compare PSHA-fault practitioners’ experiences; we are interested in how a fault-based model for PSHA has been implemented and complemented by different disciplines (e.g. paleo-archeo-historical-instrumental seismology; geodesy; etc.), and in how faults uncertainties have been accounted for (e.g. fault characterization in the field, implementation in SHA codes and resulting variability in expected ground-motion).
• Propose strategies to integrate in future PSHA physics-based ground-motion simulations which can capture phenomena such as ground-motion variability, directivity effects, scattering, and attenuation that control the high frequency part of strong ground-motions.
• Develop testing approaches to ensure that the wealth of data available today is used following state-of-the-art methods, rigorous uncertainty handling, and appropriate input model parametrization.