JpGU-AGU Joint Meeting 2017

講演情報

[EE] 口頭発表

セッション記号 S (固体地球科学) » S-SS 地震学

[S-SS09] [EE] Rethinking PSHA

2017年5月24日(水) 13:45 〜 15:15 A07 (東京ベイ幕張ホール)

コンビーナ:Matt Gerstenberger(GNS Science)、はお 憲生(防災科学技術研究所 防災システムセンター)、Ma Kuo-Fong(Institute of Geophysics, National Central University, Taiwan, ROC)、Schorlemmer Danijel(GFZ German Research Centre for Geosciences)、座長:Gerstenberger Matthew(GNS Science, New Zealand)、座長:Schorlemmer Danijel(GFZ German Research Centre for Geosciences)、座長:Hao Ken(National Research Institute for Earth Science and Disaster Resilience, Japan)、座長:Ma Kuo-Fong(Institute of Geophysics, National Central University, Taiwan, ROC)

15:00 〜 15:15

[SSS09-06] Is modern PSHA too precise?

*Matt Gerstenberger1David Rhoades1 (1.GNS Science)

キーワード:seismic hazard, PSHA, uncertainty

For the last 20 years, the New Zealand National Seismic Hazard Model (NSHM) has been constructed using standard probabilistic seismic hazard assessment techniques. In this algorithmic approach the model is constructed by first combining models developed from earthquake catalogue data and active fault data; these models are assumed to be Poissonian in nature. The combined source model is then coupled with ground-motion prediction equations (GMPEs) to estimate the potential shaking at desired locations. In recent years, there has been considerable progress and improvement in understanding of the uncertainties inherent to GMPEs. In our current work, we are exploring some of the fundamental assumptions of the NSHM and investigating how uncertainties in the earthquake source and ground motion modelling propagate through to the end uses of the model. In New Zealand, a major end-use is the development of the national building design standards. Some uncertainties are not quantified in the present model. These include uncertainties resulting from a paucity of earthquake occurrence data and from different methods that can be used to model the seismic sources. Additionally, seismic sources are generally assumed to be a stationary Poisson process and earthquake clustering is ignored. Here we will explore the impact of including these uncertainties in the NSHM on downstream risk-based applications of the model. Including these uncertainties will likely lead to more robust estimates of risk for use by industry and in the development of design standards.