The Seismicity Rate Model for the 2022 Aotearoa New Zealand National Seismic Hazard Model

Matthew C. Gerstenberger, Russ J. Van Dissen, Chris Rollins, Christopher DiCaprio, Kiran K S. Thingbaijim, Sanjay S. Bora, Chris Chamberlain, Annemarie Christophersen, Genevieve L. Coffey, Susan Ellis, Pablo C. Iturrieta, Kaj M. Johnson, Nicola J. Litchfield, Andy Nicol, Kevin R. Milner, Sepi J. Rastin, David A. Rhoades, Hannu Seebeck, Bruce E. Shaw, Mark Stirling, Laura M. Wallace, Trevor I. Allen, Brendon A. Bradley, Danielle Charlton, Kate Clark, Jeff Fraser, John Griffin, Ian Hamling, Andrew Howell, Emma Hudson-Doyle, Anne Hulsey, V. Oakley Jurgens, Anna E. Kaiser, Rachel Kirkman, Robert M. Langridge, Jeremy L. Maurer, Mark S. Rattenbury, John Ristau, Danijel Schorlemmer, John Townend, Pilar Villamor, & Charles A. Williams

Published January 2, 2024, SCEC Contribution #13421

A seismicity rate model (SRM) has been developed as part of the 2022 Aotearoa New Zealand National Seismic Hazard Model revision. The SRM consists of many component models, each of which falls into one of two classes: (1) inversion fault model (IFM); or (2) distributed seismicity model (DSM). Here we provide an overview of the SRM and a brief description of each of the component models. The upper plate IFM forecasts the occurrence rate for hundreds of thousands of potential ruptures derived from the New Zealand Community Fault Model version 1.0 and utilizing either geologic- or geodetic- based fault-slip rates. These ruptures are typically less than a couple of hundred kilometers long, but can exceed 1500 km and extend along most of the length of the country (albeit with very low probabilities of exceedance [PoE]). We have also applied the IFM method to the two subduction zones of New Zealand and forecast earthquake magnitudes of up to ∼ Mw 9.4, again with very low PoE. The DSM combines a hybrid model developed using multiple datasets with a non-Poisson uniform rate zone model for lower seismicity regions of New Zealand. Forecasts for 100 yr are derived that account for overdispersion of the rate variability when compared with Poisson. Finally, the epistemic uncertainty has been mod- eled via the range of models and parameters implemented in an SRM logic tree. Results are presented, which indicate the sensitivity of hazard results to the logic tree branches and that were used to reduce the overall complexity of the logic tree.

Citation
Gerstenberger, M. C., Van Dissen, R. J., Rollins, C., DiCaprio, C., Thingbaijim, K. S., Bora, S. S., Chamberlain, C., Christophersen, A., Coffey, G. L., Ellis, S., Iturrieta, P. C., Johnson, K. M., Litchfield, N. J., Nicol, A., Milner, K. R., Rastin, S. J., Rhoades, D. A., Seebeck, H., Shaw, B. E., Stirling, M., Wallace, L. M., Allen, T. I., Bradley, B. A., Charlton, D., Clark, K., Fraser, J., Griffin, J., Hamling, I., Howell, A., Hudson-Doyle, E., Hulsey, A., Jurgens, V., Kaiser, A. E., Kirkman, R., Langridge, R. M., Maurer, J. L., Rattenbury, M. S., Ristau, J., Schorlemmer, D., Townend, J., Villamor, P., & Williams, C. A. (2024). The Seismicity Rate Model for the 2022 Aotearoa New Zealand National Seismic Hazard Model. Bulletin of the Seismological Society of America, 114(1), 182-216. doi: 10.1785/0120230165.