JpGU-AGU Joint Meeting 2017

Presentation information

[EE] Oral

S (Solid Earth Sciences) » S-SS Seismology

[S-SS05] [EE] earthquake statistics, physics-based earthquake forecasting, and earthquake model testing

Wed. May 24, 2017 3:30 PM - 5:00 PM A05 (Tokyo Bay Makuhari Hall)

convener:Danijel Schorlemmer(GFZ German Research Centre for Geosciences), Naoshi Hirata(Earthquake Research Institute, the University of Tokyo), Matt Gerstenberger(GNS Science), Hiroshi Tsuruoka(Earthquake Research Institute, Tokyo Univ.), Jiancang Zhuang(Institute of Statistical Mathematics), Chairperson:Hiroshi Tsuruoka(Earthquake Research Institute, Tokyo Univ.)

4:30 PM - 4:45 PM

[SSS05-11] Earthquake forecast modelling for the Mw 7.8 Kaikoura Earthquake and triggered Slow Slip Events

*Matt Gerstenberger1, David Rhoades1, Annemarie Christophersen1, David Harte1, Bill Fry1, Sara McBride1, Stephen Bannister1 (1.GNS Science)

Keywords:New Zealand, earthquake forecasting, slow slip event

The November 14th, 2016, Mw 7.8 Kaikoura, New Zealand earthquake affected a large part of central New Zealand. The event ruptured around 12 independent faults and caused significant damage and shaking in many areas. This has meant that recovery effort has also been distributed over a very large area and has required a new approach to the dissemination of information about the potential for future shaking. We have provided forecasting information that targets a broad range of end-users who have become increasingly sophisticated in their use of the forecast information. Our information has ranged from aftershock probability tables through to detailed and specific engineering information. Additionally, the main shock triggered three slow slip events (SSE) on the Hikurangi subduction zone that were unique in character in our approximately 20 years of observations; these SSE provided a difficult challenge to the on going forecasting efforts and required a new approach to incorporate the effect of the SSE.
As is typical in such aftershock sequences, data quality issues have provided a challenge to the forecast modelling. The models we have applied are based on our past work and have used a hybrid of the STEP, ETAS and EEPAS models to produce the forecasts. An important change has been the use of the negative binomial distribution, constrained by ETAS simulations (Harte, 2013), to describe the uncertainty in the STEP rates. These uncertainties were also used to produce stochastic events sets for use in hazard calculations for engineering decisions (e.g., forecast design spectra as compared to the design standard or probabilities of landslide). To date the aftershock productivity has been low when compared to average New Zealand aftershock behavior.