Development of Bayesian space-time models in stochastic forecast methods for recurrent earthquakes

2016 Fiscal Year Final Research Report

• Project/Area Number: 26870193
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Solid earth and planetary physics; Statistical science
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Nomura Shunichi 東京工業大学, 情報理工学院, 助教 (70719640)
• Research Collaborator: UCHIDA Naoki 東北大学, 理学研究科, 准教授 (80374908) ; OGATA Yosihiko 情報・システム研究機構, 統計数理研究所, 名誉教授 (70000213) ; MATSU'URA Mitsuhiro 情報・システム研究機構, 統計数理研究所, 外来研究員 (00114645)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 繰り返し地震 / 地震予測 / 更新過程 / ベイズ予測 / ガウス過程事前分布 / 時空間モデル / プレートテクトニクス / 東日本大震災

Outline of Final Research Achievements

There are many active faults in inland Japan that have risks of future catastrophic earthquakes. Since inland active faults in Japan have very long cycles of activity, forecasting is difficult because of the scarcity and unreliability of historical data. For stability of predictive performance, we established Bayesian prediction methods to deal with the uncertainty of data and parameters caused by these problems.
Small repeating earthquakes are also useful for monitoring interplate slip because their recurrence times reflect the quasi-static slip rate on plate interfaces. Here, we developed a space-time model extended from a renewal process to estimate the spatio-temporal distribution of slip rate on plate boundaries.

Free Research Field

統計地震学