Development of real-time tsunami prediction system using ocean-floor network system and its future plan

The damage and loss of life caused by tsunamis can be reduced by timely warnings, which predict the arrival time and maximum height of tsunamis, to support evacuations and other mitigating actions. We have developed the real-time tsunami prediction system, based on data from the Dense Oceanfloor Network system for Earthquakes and Tsunamis (DONET), that has been implemented in some local governments along the Nankai Trough coast of Japan. The system visualizes predicted travel times, the heights, the inundation area and the calculated tsunami waveform for each target position in real-time among 1506 fault models along the Nankai Trough area changing the location, magnitude, dip and depth. We validate the application for other areas like the Inland Sea to expand the area for the installation (Takahashi et al., 2018), and continue the consideration to add options of visualization. Normally, it displays the maximum inundation area indicating the maximum predicted tsunami height at each target point. The inundation area, however, may depend on the frequency of tsunami coming to the predicted target point in addition to the tsunami height. Therefore, we added options to show the maximum traces of the upper limit of inundation areas using the worst five fault models. In addition, we consider to extend it to tsunami damages prediction. Recently, Kosono et al (2017) developed a method how to calculate debris of generation and the floating after tsunami inundation and to evaluate locations of the concentration. We validate the motions of debris using many fault models changing the magnitude and locations using above method, and will add the function of the evaluation of debris on the current real-time tsunami prediction system. It is significant to predict the debris distribution for improvement of the disaster mitigation. Because the debris tends to concentrate on low inundation area, which the residents consider safe there, and because the debris has risks bringing tsunami fires. In this presentation, we introduce the any options for the real-time tsunami prediction system and its future plan.