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首页> 外文期刊>Journal of geophysical research. Solid earth: JGR >Modeling the Sources of the 2018 Palu, Indonesia, Tsunami Using Videos From Social Media
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Modeling the Sources of the 2018 Palu, Indonesia, Tsunami Using Videos From Social Media

机译:模拟2018 Palu,印度尼西亚,海啸的来源使用社交媒体的视频

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摘要

The 2018 Palu tsunami contributed significantly to the devastation caused by the associated M-W 7.5 earthquake. This began a debate about how the moderate size earthquake triggered such a large tsunami within Palu Bay, with runups of more than 10 m. The possibility of a large component of vertical coseismic deformation and submarine landslides have been considered as potential explanations. However, scarce instrumental data have made it difficult to resolve the potential contributions from either type of source. We use tsunami waveforms derived from social media videos in Palu Bay to model the possible sources of the tsunami. We invert InSAR data with different fault geometries and use the resulting seafloor displacements to simulate tsunamis. The coseismic sources alone cannot match both the video-derived time histories and surveyed runups. Then we conduct a tsunami source inversion using the video-derived time histories and a tide gauge record as inputs. We specify hypothetical landslide locations and solve for initial tsunami elevation. Our results, validated with surveyed runups, show that a limited number of landslides in southern Palu Bay are sufficient to explain the tsunami data. The Palu tsunami highlights the difficulty in accurately capturing with tide gauges the amplitude and timing of short period waves that can have large impacts at the coast. The proximity of landslides to locations of high fault slip also suggests that tsunami hazard assessment in strike-slip environments should include triggered landslides, especially for locations where the coastline morphology is strongly linked to fault geometry.
机译:2018 PALU海啸对由相关的M-W 7.5地震造成的毁灭作出了重大贡献。这开始辩论,关于中等大小地震如何在帕卢湾内引发如此大的海啸,超过10米的润滑。垂直电影变形和潜艇滑坡的大量组分的可能性被认为是潜在的解释。但是,稀缺的乐器数据使得难以解决从任何类型的源的潜在贡献。我们使用Palu Bay中派生自社交媒体视频的海啸波形来模拟海啸的可能源。我们将insar数据与不同的故障几何形状反转,并使用得到的海底位移来模拟海啸。单独的电源源不能匹配视频衍生的时间历史和调查的运行。然后,我们使用视频派生的时间历史和潮汐仪表记录作为输入进行海啸源反转。我们指定假设的滑坡位置,并解决初始海啸高程。我们的结果,验证了被调查的润肺座,表明南部普鲁湾的有限数量的山体滑坡足以解释海啸数据。 Palu海啸突出了潮汐准确捕获的难度,仪表测量在海岸上可能具有大冲击的短时期波浪的幅度和时序。滑坡接近高故障滑坡的位置也表明,防滑环境中的海啸危险评估应包括触发的山体滑坡,特别是对于海岸线形态与故障几何形状强烈相关的位置。

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    Univ Calif San Diego Scripps Inst Oceanog Cecil H &

    Ida M Green Inst Geophys &

    Planetary Ph La Jolla CA 92093 USA;

    Univ Calif San Diego Scripps Inst Oceanog Cecil H &

    Ida M Green Inst Geophys &

    Planetary Ph La Jolla CA 92093 USA;

    Pontificia Univ Catolica Valparaiso Escuela Cieneias Mar Valparaiso Chile;

    Univ Calif San Diego Scripps Inst Oceanog Cecil H &

    Ida M Green Inst Geophys &

    Planetary Ph La Jolla CA 92093 USA;

    Natl Univ Singapore Dept Civil &

    Environm Engn Singapore Singapore;

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  • 正文语种 eng
  • 中图分类 地球物理学;
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