Calculation of National Seismic Hazard Models with Large Logic Trees: Application to the NZ NSHM 2022

Author:

DiCaprio Christopher J.1ORCID,Chamberlain Chris B.1ORCID,Bora Sanjay S.1ORCID,Bradley Brendon A.2ORCID,Gerstenberger Matthew C.1ORCID,Hulsey Anne M.3ORCID,Iturrieta Pablo45ORCID,Pagani Marco67ORCID,Simionato Michele6

Affiliation:

1. 1GNS Science, Lower Hutt, New Zealand

2. 2University of Canterbury, Christchurch, New Zealand

3. 3University of Auckland, Auckland, New Zealand

4. 4GFZ German Research Centre for Geosciences, Potsdam, Germany

5. 5Institute of Geosciences, University of Potsdam, Potsdam, Germany

6. 6GEM Foundation, Pavia, Italy

7. 7Institute of Catastrophe Risk Management, Nanyang Technological University, Singapore

Abstract

Abstract National-scale seismic hazard models with large logic trees can be difficult to calculate using traditional seismic hazard software. To calculate the complete 2022 revision of the New Zealand National Seismic Hazard Model—Te Tauira Matapae Pūmate Rū i Aotearoa, including epistemic uncertainty, we have developed a method in which the calculation is broken into two separate stages. This method takes advantage of logic tree structures that comprise multiple, independent logic trees from which complete realizations are formed by combination. In the first stage, we precalculate the independent realizations of the logic trees. In the second stage, we assemble the full ensemble of logic tree realizations by combining components from the first stage. Once all realizations of the full logic tree have been calculated, we can compute aggregate statistics for the model. This method benefits both from the reduction in the amount of computation necessary and its parallelism. In addition to facilitating the computation of a large seismic hazard model, the method described can also be used for sensitivity testing of model components and to speed up experimentation with logic tree structure and weights.

Publisher

Seismological Society of America (SSA)

Subject

Geophysics

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