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ID 118752
Author
Takahashi, Narumi National Research Institute for Earth Science and Disaster Resilience
Imai, Kentaro Japan Agency for Marine-Earth Science and Technology
Ishibashi, Masanobu Wakayama Prefecture
Sueki, Kentaro Japan Agency for Marine-Earth Science and Technology
Obayashi, Ryoko Japan Agency for Marine-Earth Science and Technology
Tanabe, Tatsuo NTT data CCS corporation
Tamazawa, Fumiyasu NTT data CCS corporation
Kaneda, Yoshiyuki Kagawa University
Keywords
tsunami
real-time prediction
DONET
Content Type
Journal Article
Description
We constructed a real-time tsunami prediction system using the Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET). This system predicts the arrival time of a tsunami, the maximum tsunami height, and the inundation area around coastal target points by extracting the proper fault models from 1,506 models based on the principle of tsunami amplification. Since DONET2, installed in the Nankai earthquake rupture zone, was constructed in 2016, it has been used in addition to DONET1 installed in the Tonankai earthquake rupture zone; we revised the system using both DONET1 and DONET2 to improve the accuracy of tsunami prediction. We introduced a few methods to improve the prediction accuracy. One is the selection of proper fault models from the entire set of models considering the estimated direction of the hypocenter using seismic and tsunami data. Another is the dynamic selection of the proper DONET observatories: only DONET observatories located between the prediction point and tsunami source are used for prediction. Last is preparation for the linked occurrence of double tsunamis with a time-lag. We describe the real-time tsunami prediction system using DONET and its implementation for the Shikoku area.
Journal Title
Journal of Disaster Research
ISSN
18812473
18838030
Publisher
Fuji Technology Press
Volume
12
Issue
4
Start Page
766
End Page
774
Published Date
2017-08-01
Rights
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nd/4.0/).
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DOI (Published Version)
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language
eng
TextVersion
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departments
Science and Technology