气候变化领域集成服务门户(CCPortal): Applying a Deep Learning Algorithm to Tsunami Inundation Database of Megathrust Earthquakes

CCPortal

DOI	10.1029/2020JB019690
	Applying a Deep Learning Algorithm to Tsunami Inundation Database of Megathrust Earthquakes
	Mulia I.E.; Gusman A.R.; Satake K.
发表日期	2020
ISSN	21699313
卷号	125 期号:9
英文摘要	We explore recent developments in computer science on deep learning to estimate high-resolution tsunami inundation from a quick low-resolution computation result. Deep network architecture is capable of storing large information acquired via a training/learning process by pairing low- and high-resolution deterministic simulation results from precalculated hypothetical scenarios. In a real case, with a real-time source estimate and linear simulation computed on a relatively low-grid resolution, optimized network parameters can be used to rapidly and accurately transform low-resolution simulation outputs to higher-resolution grids. We generate 532 source scenarios of interplate earthquakes (Mw 8–9) along the Japan Trench subduction zone to simulate tsunamis and utilize a precalculated library for deep learning. To test the proposed method, we consider a realistic source model inferred from static ground displacements and offshore tsunami data presumably available in real-time and compare forecasted inundation heights against observations in Rikuzentakata and Otsuchi cities associated with the 2011 Tohoku-oki tsunami. Our results show that the proposed method exhibits comparable accuracy to the conventional physics-based simulation but achieves approximately 90% reduction of real-time computational efforts. Thus, it has good potential as a future tsunami forecasting algorithm. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	deep learning; forecasting; tsunami inundation
语种	英语
来源期刊	Journal of Geophysical Research: Solid Earth
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/187634
作者单位	Earthquake Research Institute, The University of Tokyo, Tokyo, Japan; GNS Science, Lower Hutt, New Zealand
推荐引用方式 GB/T 7714	Mulia I.E.,Gusman A.R.,Satake K.. Applying a Deep Learning Algorithm to Tsunami Inundation Database of Megathrust Earthquakes[J],2020,125(9).
APA	Mulia I.E.,Gusman A.R.,&Satake K..(2020).Applying a Deep Learning Algorithm to Tsunami Inundation Database of Megathrust Earthquakes.Journal of Geophysical Research: Solid Earth,125(9).
MLA	Mulia I.E.,et al."Applying a Deep Learning Algorithm to Tsunami Inundation Database of Megathrust Earthquakes".Journal of Geophysical Research: Solid Earth 125.9(2020).