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从震动历史模拟看地震危险图的性能

Insights into earthquake hazard map performance from shaking history simulations.

机构信息

Royal Observatory of Belgium, B-1180, Brussels, Belgium.

Department of Earth and Planetary Sciences, Northwestern University, Evanston, IL, 60208, USA.

出版信息

Sci Rep. 2018 Jan 30;8(1):1855. doi: 10.1038/s41598-018-20214-6.

Abstract

Why recent large earthquakes caused shaking stronger than shown on earthquake hazard maps for common return periods is under debate. Explanations include: (1) Current probabilistic seismic hazard analysis (PSHA) is deficient. (2) PSHA is fine but some map parameters are wrong. (3) Low-probability events consistent with a map sometimes occur. This issue has two parts. Verification involves how well maps implement PSHA ("have we built the map right?"). Validation asks how well maps forecast shaking ("have we built the right map?"). We explore how well a map can ideally perform by simulating an area's shaking history and comparing "observed" shaking to that predicted by a map generated for the same parameters. The simulations yield shaking distributions whose mean is consistent with the map, but individual shaking histories show large scatter. Infrequent large earthquakes cause shaking much stronger than mapped, as observed. Hence, PSHA seems internally consistent and can be regarded as verified. Validation is harder because an earthquake history can yield shaking higher or lower than the hazard map without being inconsistent. As reality gives only one history, it is hard to assess whether misfit between a map and actual shaking reflects chance or a map biased by inappropriate parameters.

摘要

为何最近的大地震产生的震动比常见重现期的地震危险性图所示的要强,这一点存在争议。解释包括:(1) 当前的概率地震危险性分析(PSHA)存在缺陷。(2) PSHA 没问题,但某些地图参数有误。(3) 与地图一致的低概率事件有时会发生。这个问题有两个部分。验证涉及地图如何很好地实施 PSHA(“我们是否正确地构建了地图?”)。验证则询问地图对震动的预测效果如何(“我们是否构建了正确的地图?”)。我们通过模拟一个地区的震动历史并将“观察到的”震动与为相同参数生成的地图进行预测的震动进行比较,来探索地图的理想性能。模拟产生的震动分布的平均值与地图一致,但个别震动历史显示出很大的离散性。罕见的大地震会产生比地图上显示的更强的震动,正如观察到的那样。因此,PSHA 似乎具有内在一致性,可以被视为已验证。验证更难,因为地震历史产生的震动可能高于或低于危险地图,而不会出现不一致的情况。由于现实中只有一个历史记录,因此很难评估地图与实际震动之间的不匹配是偶然的还是由于参数不合适而导致的地图偏差。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0063/5789888/4c9df8276359/41598_2018_20214_Fig1_HTML.jpg

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本文引用的文献

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2
Shake-up time for Japanese seismology.
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