Item type |
文献 / Documents(1) |
公開日 |
2023-11-24 |
アクセス権 |
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アクセス権 |
open access |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
出版社版DOI |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.20965/jdr.2017.p0766 |
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言語 |
ja |
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関連名称 |
10.20965/jdr.2017.p0766 |
出版タイプ |
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出版タイプ |
VoR |
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出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
タイトル |
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タイトル |
Real-Time Tsunami Prediction System Using DONET |
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言語 |
en |
著者 |
タカハシ, ナルミ
イマイ, ケンタロウ
イシバシ, マサノブ
スエキ, ケンタロウ
オオバヤシ, リョウコ
タナベ, タツオ
タマザワ, フミヤス
馬場, 俊孝
カネダ, ヨシユキ
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抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
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. |
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言語 |
en |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
tsunami |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
real-time prediction |
キーワード |
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言語 |
en |
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主題Scheme |
Other |
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主題 |
DONET |
書誌情報 |
en : Journal of Disaster Research
巻 12,
号 4,
p. 766-774,
発行日 2017-08-01
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収録物ID |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
18812473 |
収録物ID |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
18838030 |
出版者 |
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出版者 |
Fuji Technology Press |
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言語 |
en |
権利情報 |
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言語 |
en |
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権利情報 |
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/). |
EID |
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識別子 |
340642 |
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識別子タイプ |
URI |
言語 |
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言語 |
eng |