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 language | English |
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Pages (from-to) | 1238-1250 |
Number of pages | 13 |
Journal | Seismological Research Letters |
Volume | 89 |
Issue number | 4 |
Early online date | 13 Jun 2018 |
DOIs | |
Publication status | Published - Jul 2018 |
Keywords
- earthquake
- seismic hazard
- earthquake forecasting and testing
- natural hazards
- probabilistic forecasting
- reproducibility
- model validation
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Dr Max Werner
- School of Earth Sciences - Associate Professor of Geophysics and Natural Hazards
- Geophysics
- Cabot Institute for the Environment
Person: Academic , Member