Proceedings of the 12th International INQUA meeting on paleoseismology, active tectonic and archaeoseismology

Fault displacement hazard analysis requires to collect detailed geologic information within a certain distance to the site of interest (e.g., IAEA, 2022). But the degree of knowledge that can be collected varies from site to site and may evolve with time. Thanks to the different logistic and fault displacement models for DRs developed here, a PFDHA decision process can be implemented considering the level of geologic knowledge available. The idea is that, to manage the epistemic uncertainties, the level of geologic background of the area under investigation should guide the applicant in choosing the most appropriate regressions, or combination of regressions, to be applied. To illustrate this PFDHA decision process, consider a site located at a certain distance from a well-located PF trace (Fig. 2). In this example, attention is focused on the application of the new regressions here developed, ignoring the probability of surface rupturing and the annual rate of occurrence of the earthquakes. Three different situations can be considered: C ase 1: a pre-existing fault (potential rupture of Rank 1.5) cannot be excluded under the site or at a close distance to the site because it has not been studied. In this case the probability of its reactivation as DR should be considered. The regressions for probability of occurrence and displacement exceedance to be used are then: i) the occurrence Rank 2 DRs associated with PF rupturing (Rank 1); ii) Rank 2 associated with Rank 1.5; and Rank 1.5 associated with Rank 1. In this case, the hazard is dominated by DR Rank 1.5. The total hazard is given as a sum of combinations. The same applies when a pre-existing fault is proved to exist beneath the site (i.e., it has been studied and located). C ase 2: following detailed investigations, a preexisting fault (Rank 1.5) is identified at a distance from the site and excluded under the site. Then, only the occurrence of Rank 2 associated with Rank 1 and Rank 2 associated with Rank 1.5 need to be considered. C ase 3: following detailed investigations, a preexisting fault can be excluded at the site and at a relevant distance from the site, then only the occurrence of Rank 2 associated with Rank 1 needs to be considered. Implementing knowledge-based choice of regression models should encourage end-users to perform detailed investigations and to adapt the PFDHA approach to the level of knowledge. R E F E R E N C E S International Atomic Energy Agency (2022) Site Evaluation for Nuclear Installations. IAEA Specific Safety Guide No. SSG-9 (Rev. 1). Vienna Nurminen, F., Baize, S., Boncio, P., Blumetti, A. M., Cinti, F. R., Civico, R. & Guerrieri, L. 2022. SURE 2.0 – New release of the worldwide database of surface ruptures for fault displacement hazard analyses. Scientific Data, 9:729, DOI : 10.1038/s41597-022-01835-z. Nurminen F, Boncio P, Visini F, Pace B, Valentini A, Baize S and Scotti O (2020) Probability of Occurrence and Displacement Regression of Distributed Surface Rupturing for Reverse Earthquakes. Front. Earth Sci. 8:581605, doi: 10.3389/ feart.2020.581605. Sarmiento, A., Lavrentiadis, G., Bozorgnia, Y., Chen, R., Chiou, B.S.J., Dawson T.E., Kottke A., Kuehn N., Kuo C.-H., Madugo C., Milliner C.W.D., Moss, R., Thomas, K., Thompson S., Wang, Y., Younesi, K., & Zandieh, A. (2023) Comparison of FDHI Fault Displacement 859 Models. Report GIRS 2022- 10. UCLA engineering, California, USA. DOI : 860 10.34948/N3W88V