Department of Earth Sciences, University of Western Ontario, London, ON, N6A 5B7, Canada.
Department of Physics and Astronomy, University of Western Ontario, London, ON, N6A 3K7, Canada.
Nat Commun. 2019 Sep 6;10(1):4051. doi: 10.1038/s41467-019-11958-4.
The majority of earthquakes occur unexpectedly and can trigger subsequent sequences of events that can culminate in more powerful earthquakes. This self-exciting nature of seismicity generates complex clustering of earthquakes in space and time. Therefore, the problem of constraining the magnitude of the largest expected earthquake during a future time interval is of critical importance in mitigating earthquake hazard. We address this problem by developing a methodology to compute the probabilities for such extreme earthquakes to be above certain magnitudes. We combine the Bayesian methods with the extreme value theory and assume that the occurrence of earthquakes can be described by the Epidemic Type Aftershock Sequence process. We analyze in detail the application of this methodology to the 2016 Kumamoto, Japan, earthquake sequence. We are able to estimate retrospectively the probabilities of having large subsequent earthquakes during several stages of the evolution of this sequence.
大多数地震都是出乎意料地发生的，并可能引发随后的一系列事件，最终导致更强烈的地震。地震活动性的这种自我激发性质导致了地震在空间和时间上的复杂集群。因此，在未来时间间隔内约束最大预期地震震级的问题对于减轻地震灾害至关重要。我们通过开发一种方法来计算此类极端地震超过一定震级的概率来解决这个问题。我们将贝叶斯方法与极值理论相结合，并假设地震的发生可以用流行病型余震序列过程来描述。我们详细分析了该方法在 2016 年日本熊本地震序列中的应用。我们能够回溯地估计在该序列演化的几个阶段发生后续大地震的概率。
