第26回統計地震学セミナー

日時(Date)

2012年5月29日（火）/ 29 May 2012 (Tuesday)

時間(Time)

16:00-

場所
(Location)

統計数理研究所 D312A号室 /
Room D312A @ Institute of Statistical Mathematics

講演題目
(Title)

Short-term earthquake forecasting through a smoothing Kernel and the rate-and-state friction law: Application to Taiwan and the Kanto region, Japan

講演者
(Speaker)

Chung-Han Chan
(Department of Geosciences, National Taiwan University)

概要
(Abstract)

An earthquake forecasting approach was employed for estimating the spatio-temporal distribution of seismicity density in Taiwan and the Kanto region, Japan. To evaluate long-term seismicity rate, a smoothing Kernel function based on the distribution of past earthquakes was proposed. With the use of the rate-and-state friction model, short-term rate evolution according to the fault-interaction stress disturbance was forecasted. To test feasibility of this model, it was applied using a catalog for the area surrounding Taiwan. It leads to good agreement between the model forecast and actual observations to prove its forecasting accuracy. To check its stability, we estimated the deviation of the models according to different parameters used in the approach. We conclude that deviations within each parameter had an insignificant impact on forecasting stability. For the application to the Kanto region, we proposed a 3D forecasting model due to its complex tectonic setting.
The seismicity patterns at various depths are illustrated and the seismicity rate in the crust and along the subduction zones can be distinguished. The high seismicity rate offshore in the east at the depth of 20-50 km can be associated with stress increase imparted by the 2011 Tohoku sequence. This phenomenon can be forecasted according to the rate-and-state friction model. The proposed approach, with verified applicability for seismicity forecasts, could be useful for seismic hazard mitigation. The application could provide a warning before the occurrence of consequent earthquakes and would be valuable for consequent studies, e.g., probabilistic seismic hazard assessment.