Time-independent forecast model for large crustal earthquakes in southwest Japan using GNSS data

• 資料種別: 記事
• タイトル: Time-independent forecast model for large crustal earthquakes in southwest Japan using GNSS data
• 著者・編者: Takuya Nishimura
• 出版事項: 日本 : Springer Nature
• 出版年月日等: 2022-04-22
• 出版年（W3CDTF）: 2022-04-22
• タイトル（掲載誌）: EPS : Earth, Planets and Space
• 巻号年月日等（掲載誌）: 74(58)
• 掲載巻: 74(58)
• ISSN（掲載誌）: 1880-5981
• ISSN-L（掲載誌）: 1343-8832
• 本文の言語コード: eng
• DOI: 10.1186/s40623-022-01622-5; https://doi.org/10.1186/s40623-022-01622-5
• 国立国会図書館永続的識別子: info:ndljp/pid/12287126; https://dl.ndl.go.jp/pid/12287126
• コレクション（共通）: 障害者向け資料
• コレクション（障害者向け資料：レベル1）: テキストデータ
• コレクション（個別）: 国立国会図書館デジタルコレクション > 電子書籍・電子雑誌 > その他; https://dl.ndl.go.jp/collections/B00035
• 収集根拠: オンライン資料収集制度
• 受理日（W3CDTF）: 2022-05-18T20:14:28+09:00
• 保存日（W3CDTF）: 2022-04-27
• 記録形式（IMT）: application/pdf
• オンライン閲覧公開範囲: 国立国会図書館内限定公開
• デジタル化資料送信: 図書館・個人送信対象外
• 遠隔複写可否（NDL）: 可
• 掲載誌（URI）: https://earth-planets-space.springeropen.com/articles
• 掲載誌（国立国会図書館永続的識別子）: info:ndljp/pid/12287068; https://dl.ndl.go.jp/pid/12287068
• 連携機関・データベース: 国立国会図書館 : 国立国会図書館デジタルコレクション; https://dl.ndl.go.jp

• 要約等: In this study, we developed a regional likelihood model for crustal earthquakes using geodetic strain-rate data from southwest Japan. First, the smoothed strain-rate distributions were estimated from continuous Global Navigation Satellite System (GNSS) measurements. Second, we removed the elastic strain rate attributed to interplate coupling on the subducting plate boundary, including the observed strain rate, under the assumption that it is not attributed to permanent loading on crustal faults. We then converted the geodetic strain rates to seismic moment rates and calculated the 30-year probability for M ≥ 6 earthquakes in 0.2 × 0.2° cells, using a truncated Gutenberg–Richter law and time-independent Poisson process. Likelihood models developed using different conversion equations, seismogenic thicknesses, and rigidities were validated using the epicenters and moment distribution of historical earthquakes. The average seismic moment rate of crustal earthquakes recorded during 1586–2020 was only 13–20% of the seismic moment rate converted from the geodetic data, which suggests that the observed geodetic strain rate includes considerable inelastic strain. Therefore, we introduced an empirical coefficient to calibrate the moment rate converted from geodetic data with the moment rate of the earthquakes. Several statistical scores and the Molchan diagram showed all models could predict real earthquakes better than the reference model, in which earthquakes occur uniformly in space. Models using principal horizontal strain rates exhibited better predictive skill than those using the maximum horizontal shear strain rate. There were no significant differences in predictive skill between uniform and variable distributions for seismogenic thickness and rigidity. The preferred models suggested high 30-year probability in the Niigata–Kobe Tectonic Zone and central Kyushu, exceeding 1% in more than half of the analyzed region. The model predictive skill was also verified by a prospective test using earthquakes recorded during 2010–2020. This study suggests that the proposed forecast model based on geodetic data can improve the regional likelihood model for crustal earthquakes in Japan in combination with other forecast models based on active faults and seismicity.
• DOI: 10.1186/s40623-022-01622-5; https://doi.org/10.1186/s40623-022-01622-5; 10.21203/rs.3.rs-1120373/v1; https://doi.org/10.21203/rs.3.rs-1120373/v1
• オンライン閲覧公開範囲: インターネット公開
• 著作権情報: © The Author(s) 2022.; This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
• 関連情報（URI）: http://hdl.handle.net/2433/274586; http://id.ndl.go.jp/digimeta/12287126; https://dl.ndl.go.jp/pid/12287126; https://link.springer.com/content/pdf/10.1186/s40623-022-01622-5.pdf; https://link.springer.com/article/10.1186/s40623-022-01622-5/fulltext.html
• 参照: Geodetic data inversion to estimate a strain-rate field by introducing sparse modeling; https://cir.nii.ac.jp/crid/1050866882758946304; Evaluation of earthquake potential using a kinematic crustal block motion model in Java, Indonesia, based on GNSS observation; https://cir.nii.ac.jp/crid/1360865816799207168; Chief Research Achievements of the Earthquake Long-Term Forecast Panel During 2019–2023; https://cir.nii.ac.jp/crid/1390303697454388480
• 連携機関・データベース: 国立情報学研究所 : CiNii Research; https://cir.nii.ac.jp/
• 提供元機関・データベース: 学術機関リポジトリデータベース; https://irdb.nii.ac.jp; 雑誌記事索引データベース; https://ndlsearch.ndl.go.jp; Crossref; https://www.crossref.org
• 書誌ID（NDLBibID）: 12287126; http://id.ndl.go.jp/bib/12287126