Likelihood of Primary Surface Faulting: Updating of Empirical Regressions

M Pizza, MF Ferrario, F Thomas… - Bulletin of the …, 2023 - pubs.geoscienceworld.org
Bulletin of the Seismological Society of America, 2023pubs.geoscienceworld.org
Surface faulting is a common phenomenon for crustal earthquakes and is an important
source of localized hazard to buildings and infrastructure. Nevertheless, not all earthquakes
of a given magnitude generate surface faulting. To correctly assess the hazard posed by
surface fault displacement, it is critical to use reliable regressions of the likelihood of surface
faulting. Such regressions are derived from empirical data and the ones currently used in
engineering practice are based on datasets acquired several years ago. The aim of this …
Abstract
Surface faulting is a common phenomenon for crustal earthquakes and is an important source of localized hazard to buildings and infrastructure. Nevertheless, not all earthquakes of a given magnitude generate surface faulting. To correctly assess the hazard posed by surface fault displacement, it is critical to use reliable regressions of the likelihood of surface faulting. Such regressions are derived from empirical data and the ones currently used in engineering practice are based on datasets acquired several years ago. The aim of this work is to update the regressions characterizing the likelihood of primary surface faulting (i.e., P(Slip|m)). We systematically analyze earthquakes that occurred in 1992–2018, with hypocentral depths lower than 20 km and epicenter onshore. We obtain information on the occurrence or non‐occurrence of primary surface faulting for 363 earthquakes (87 with primary surface faulting and 276 without). We derive empirical regressions of P(Slip|m) from the entire dataset as well as for normal, strike‐slip, and reverse earthquakes, and discuss the potential sources of aleatory and epistemic uncertainty. A sensitivity analysis shows that the P(Slip|m) term has a significant impact on the hazard curve expressed as the annual frequency of exceeding a given displacement value. We argue that the regressions presented in this work can be incorporated in models for probabilistic fault displacement hazard assessment, ultimately providing a better evaluation of the hazard.
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