The Forecasting Skill of Physics‐Based Seismicity Models during the 2010–2012 Canterbury, New Zealand, Earthquake Sequence

Camilla Cattania, Maximilian Werner, Warner Marzocchi, S. Hainzl, David A. Rhoades, Matthew C. Gerstenberger, Maria Liukis, William Savran, Annemarie Christophersen, Agnes Helmstetter, Abigail Jimenez, Sandy Steacy, Thomas H. Jordan

Research output: Contribution to journalArticle (Academic Journal)peer-review

60 Citations (Scopus)
327 Downloads (Pure)

Abstract

The static Coulomb stress hypothesis is a widely known physical mechanism for earthquake triggering, and thus a prime candidate for physics-based Operational Earthquake Forecasting (OEF). However, the forecast skill of Coulomb-based seismicity models remains controversial, especially in comparison to empirical statistical models. A previous evaluation by the Collaboratory for the Study of Earthquake Predictability (CSEP) concluded that a suite of Coulomb-based seismicity models were less informative than empirical models during the aftershock sequence of the 1992 $M_w7.3$ Landers, California, earthquake. Recently, a new generation of Coulomb-based and Coulomb/statistical hybrid models were developed that account better for uncertainties and secondary stress sources. Here, we report on the performance of this new suite of models in comparison to empirical Epidemic Type Aftershock Sequences (ETAS) models during the 2010-2012 Canterbury, New Zealand, earthquake sequence. Comprising the 2010 $M 7.1$ Darfield earthquake and three subsequent $M \geq 5.9$ shocks (including the February 2011 Christchurch earthquake), this sequence provides a wealth of data (394 $M \geq 3.95$ shocks). We assessed models over multiple forecast horizons (1-day, 1-month and 1-year, updated after $M \geq 5.9$ shocks). The results demonstrate substantial improvements in the Coulomb-based models. Purely physics-based models have a performance comparable to the ETAS model, and the two Coulomb/statistical hybrids perform better or as well as the corresponding statistical model. On the other hand, an ETAS model with anisotropic (fault-based) aftershock zones is just as informative. These results provide encouraging evidence for the predictive power of Coulomb-based models. To assist with model development, we identify discrepancies between forecasts and observations.
Original languageEnglish
Pages (from-to)1238-1250
Number of pages13
JournalSeismological Research Letters
Volume89
Issue number4
Early online date13 Jun 2018
DOIs
Publication statusPublished - Jul 2018

Keywords

  • earthquake
  • seismic hazard
  • earthquake forecasting and testing
  • natural hazards
  • probabilistic forecasting
  • reproducibility
  • model validation

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