2023 Fiscal Year Final Research Report
Investigation of site amplification at Ocean Bottom stations in the Japan Trench area for earthquake early warning
| Project/Area Number |
20K05055
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 25030:Disaster prevention engineering-related
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| Research Institution | National Research Institute for Earth Science and Disaster Prevention |
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Principal Investigator |
DHAKAL Yadab 国立研究開発法人防災科学技術研究所, 地震津波火山ネットワークセンター, 主任専門研究員 (60708890)
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| Co-Investigator(Kenkyū-buntansha) |
山中 浩明 東京工業大学, 環境・社会理工学院, 教授 (00212291)
若井 淳 国立研究開発法人防災科学技術研究所, マルチハザードリスク評価研究部門, 特別研究員 (20869151)
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| Project Period (FY) |
2020-04-01 – 2024-03-31
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| Keywords | S-net / Site amplification / Japan Trench / Earthquake early warning / S waves / Quality factors / Ocean bottom seismograph |
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| Outline of Final Research Achievements |
We examined the ground-motion data from about 2,000 earthquakes recorded by all the 150 stations of S-net for magnitudes between about 4 and 7.5 that occurred in and around the Japan Trench area after the start of the network. One of the primary objectives was to obtain the site amplifications at the S-net observation sites due to the sedimentary layers lying over the hard base layer. The objective was achieved by careful selection of high-quality data and performing separation of source, path, and site factors of S waves in frequency domain. The obtained site amplification factors were clearly frequency dependent and also the values were moderately regionally distributed such as the values near the Trench in the landward and the ocean sides were different. The estimated magnitudes based on the source factors were very similar to the catalog values. These results were published in peer-reviewed journal and were recognized in academic community.
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| Free Research Field |
構造工学および地震工学関連
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| Academic Significance and Societal Importance of the Research Achievements |
The amplification factors estimated in this study will help to construct the underground model of the seafloor area, while these results can be incorporated to develop algorithms to estimate ground motion intensity at target sites on land for earthquake early warning.
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