论文标题

从破坏性海啸的轶事叙述中对历史地震事件的方法论重建:1852年伟大的班达巨大巨型巨型地震和海啸的案例研究

Methodological reconstruction of historical seismic events from anecdotal accounts of destructive tsunamis: a case study for the great 1852 Banda arc mega-thrust earthquake and tsunami

论文作者

Ringer, Hayden, Whitehead, Jared P., Krometis, Justin, Harris, Ronald A., Glatt-Holtz, Nathan, Giddens, Spencer, Ashcraft, Claire, Carver, Garret, Robertson, Adam, Harward, McKay, Fullwood, Joshua, Lightheart, Kameron, Hilton, Ryan, Avery, Ashley, Kesler, Cody, Morrise, Martha, Klein, Michael Hunter

论文摘要

我们证明了贝叶斯统计反演框架的功效,可以从海啸观察的历史记录中重建大型前prumentaumentation地震的可能特征。我们的框架是设计和实施的,以估计海震事件的位置和幅度,从海啸的轶事账户(包括海岸波浪到达时间,高度和淹没长度)上的各种空间分离的观测位置。作为初始测试案例,我们使用我们的框架重建了印度尼西亚东部的1852年地震和海啸。依赖于这些观察结果是通过俯冲推力事件产生的,后验分布表明,可观察到的物体是大规模的大型狂潮事件的结果,其大小接近8.8兆瓦,并且在东北东部Banda Arc中可能破裂。如有记录的地震事件所示,预测的地下位置的分布与该地区最大的主要地震间隙重叠。这些结果为印度尼西亚人口增长和城市化的沿海社区中的危险风险评估提供了地质和地震环境。此外,此处证明的方法强调了采用贝叶斯方法来增强对世界其他俯冲带的地震历史的理解的潜力。

We demonstrate the efficacy of a Bayesian statistical inversion framework for reconstructing the likely characteristics of large pre-instrumentation earthquakes from historical records of tsunami observations. Our framework is designed and implemented for the estimation of the location and magnitude of seismic events from anecdotal accounts of tsunamis including shoreline wave arrival times, heights, and inundation lengths over a variety of spatially separated observation locations. As an initial test case we use our framework to reconstruct the great 1852 earthquake and tsunami of eastern Indonesia. Relying on the assumption that these observations were produced by a subducting thrust event, the posterior distribution indicates that the observables were the result of a massive mega-thrust event with magnitude near 8.8 Mw and a likely rupture zone in the north-eastern Banda arc. The distribution of predicted epicentral locations overlaps with the largest major seismic gap in the region as indicated by instrumentally recorded seismic events. These results provide a geologic and seismic context for hazard risk assessment in coastal communities experiencing growing population and urbanization in Indonesia. In addition, the methodology demonstrated here highlights the potential for applying a Bayesian approach to enhance understanding of the seismic history of other subduction zones around the world.

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