Probabilistic Landslide-Generated Tsunamis in the Indus Canyon, NW Indian Ocean, Using Statistical Emulation

Probabilistic Landslide-Generated Tsunamis in the Indus Canyon, NW Indian Ocean, Using Statistical Emulation
复制标题

使用统计模拟研究印度洋西北部印度河峡谷发生山体滑坡概率引发的海啸

DOI:
10.1007/s00024-019-02187-3
复制
发表时间:
2019
影响因子:
2
通讯作者:
Salmanidou D
Salmanidou D
中科院分区:
地球科学3区
文献类型:
--
作者:
Salmanidou D

文献摘要

参考文献

被引文献

相似文献

据报道,印度洋西北部的印度河峡谷过去曾多次发生海底重大事故。这项研究是第一次调查与该地区这种大规模破坏相关的潜在海啸危险。我们使用了统计仿真,即代理模型,有效地量化了与峡谷斜坡上的滑坡引发的海啸相关的不确定性。我们模拟了60个坍塌情景,厚度100-300米,宽度6-10.5公里,行程500-2000米,淹没深度250-450米,然后用这些情景训练模拟器,预测50万个试验情景,以便对近场海啸风险进行概率研究。由于峡谷壁窄而深,邻近区域有浅大陆架(水深m),海啸的传播具有独特的模式,即沿NE-西南方向拉伸的椭圆。结果表明,最有可能发生的海啸波幅约为0.2m~1.0m,速度约为2.5m~13m/S,可能对船舶和海上设施造成潜在冲击。我们证明,基于仿真器的方法是概率风险分析的重要工具,因为它可以在几秒钟内生成数千个海啸情景,而我们在这里使用的分散海啸解算器的一次运行需要数天的计算。
The Indus Canyon in the northwestern Indian Ocean has been reported to be the site of numerous submarine mass failures in the past. This study is the first to investigate potential tsunami hazards associated with such mass failures in this region. We employed statistical emulation, i.e. surrogate modelling, to efficiently quantify uncertainties associated with slump-generated tsunamis at the slopes of the canyon. We simulated 60 slump scenarios with thickness of 100–300 m, width of 6–10.5 km, travel distances of 500–2000 m and submergence depth of 250–450 m. These scenarios were then used to train the emulator and predict 500,000 trial scenarios in order to study probabilistically the tsunami hazard over the near field. Due to narrow–deep canyon walls and the shallow continental shelf in the adjacent regions (m water depth), the tsunami propagation has a unique pattern as an ellipse stretched in the NE–SW direction. The results show that the most likely tsunami amplitudes and velocities are approximately 0.2–1.0 m and 2.5–13 m/s, respectively, which can potentially impact vessels and maritime facilities. We demonstrate that the emulator-based approach is an important tool for probabilistic hazard analysis since it can generate thousands of tsunami scenarios in few seconds, compared to days of computations on High Performance Computing facilities for a single run of the dispersive tsunami solver that we use here.
DOI: 10.1016/j.ocemod.2014.09.001
发表时间: 2014-11
期刊: Ocean Modelling
影响因子: 3.2
作者:
I. Sraj;K. Mandli;O. Knio;C. Dawson;I. Hoteit
通讯作者: I. Sraj;K. Mandli;O. Knio;C. Dawson;I. Hoteit
1945 年 11 月 27 日莫克兰 8.1 级地震海啸的地震-滑坡联合震源模型
DOI: 10.1785/0120160196
发表时间: 2017
影响因子: 3
作者:
M. Heidarzadeh;K. Satake
通讯作者: K. Satake
DOI: 10.1063/1.5009552
发表时间: 2018-02
期刊: Physics of Fluids
影响因子: 4.6
作者:
D. Salmanidou;A. Georgiopoulou;S. Guillas;F. Dias
通讯作者: D. Salmanidou;A. Georgiopoulou;S. Guillas;F. Dias
根据验潮仪记录得出的 1998 年 7 月 17 日巴布亚新几内亚海啸的震源特性
DOI: --
发表时间: 2015
期刊:
影响因子: --
作者:
M. Heidarzadeh;K. Satake
通讯作者: K. Satake
DOI: 10.1137/140989613
发表时间: 2016-01-01
影响因子: 2
作者:
Beck, Joakim;Guillas, Serge
通讯作者: Guillas, Serge