Uses of epistemic uncertainties in the USGS National Seismic Hazard Models

Abstract

The need for US Geological Survey (USGS) National Seismic Hazard Models (NSHMs) to report estimates of epistemic uncertainties in the hazard (e.g. fractile hazard curves) in all forthcoming releases is increasing. With fractile hazard curves as potential new outputs from the USGS 2023 NSHM, a simultaneous need is to help end-users better understand these epistemic uncertainties and clarify their potential uses. In this article, we address the latter need by (1) characterizing epistemic uncertainties in two updates of the USGS NSHM (2014 for California and 2021 for Hawaii), (2) illustrating a variety of downstream applications of fractile hazard curves in both hazard and risk contexts, and (3) discussing implications from the various types of uncertainties. We found that the epistemic uncertainty in hazard is generally larger for Hawaii than for California, the epistemic uncertainty in hazard can be reasonably approximated with a lognormal distribution for most of the cases considered, and the correlation between epistemic uncertainty in hazard at two different intensity measure levels generally varies with both location and type of intensity measure. Furthermore, we developed models for readily generating approximate fractile hazard curves in California and Hawaii. Finally, given the complexities involved in the hazard modeling process, we developed an open-source interactive tool to enable a broad range of users to independently examine and potentially start using such epistemic uncertainties for their respective applications.