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

Camilla Cattania, Maximilian J. Werner

Penerbit : Seismological Research Letters
Tahun : 2018

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 compared with 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 Mw 7.3 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 compared with empirical epidemic-type aftershock sequence (ETAS) models during the 2010–2012 Canterbury, New Zealand, earthquake sequence. Comprising the 2010 M 7.1 Darfield earthquake and three subsequent M ≥ 5:9 shocks (including the February 2011 Christchurch earthquake), this sequence provides a wealth of data (394 M ≥ 3:95 shocks). We assessed models over multiple forecast horizons (1 day, 1 month, and 1 yr, updated after M ≥ 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 similar to 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

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