Real-time tsunami prediction system using oceanfloor network system

Around Japan, some oceanfloor network systems were installed, which are dense oceanfloor network system for earthquakes and tsunamis (DONET), seafloor observation network for earthquakes and tsunamis along the Japan trench (S-net), and so on. These systems have seismometers and pressure sensor, respectively, and are indispensable for early detection of earthquakes and tsunamis around huge events with a magnitude of over eight around the subduction zone. We have developed a real-time tsunami prediction system using above oceanfloor network systems and it was already installed on some local governments and private company of the infrastructure. The prediction items are tsunami arrival time, maximum tsunami height and inundation area. The principal of the tsunami prediction system is based on the tsunami amplification. We set total 1,506 models changing a magnitude, depth, and dip along the Nankai trough area from the off the Boso Peninsula to Hyuganada of the off Kyushu, and calculated tsunami waveforms of the DONET observatories and target points of the tsunami prediction near the coast line. Our system has a tsunami database including these calculated waveforms and inundation areas for each target point, and the system extracts the worse cases from the database corresponding to input pressure data observed by DONET. The calculated tsunami waveforms of extracted models are also shown with above predicted information. The accuracy of the tsunami prediction depends on the correlation between the maximum height of the target point and the pressure value observed by DONET. And the correlation is influenced by seafloor topography and shape of the coastal line. When diffracted tsunami waves only propagate to the target point, the predicted tsunami height is relatively small. In cases with the same directions of the bay mouse and the tsunami prediction, the tsunami amplification becomes large. Therefore, it is important to select fault models from the database. We use triggering orders of the seismometers and the pressure data for the selection of models based on the source direction and keep accuracy of the prediction. Considering the simple principle for the prediction, tsunami propagation is one of important elements affecting the accuracy of the prediction. In cases with some complicated propagation routes, the tsunamis traveling different routes are stacked and possible large tsunami is locally generated. Through social implementation of the prediction system, we confirm the effectiveness around the rias coast around the Kii Peninsula, small islands area around the Shima Peninsula, and possible area expected some complicated propagation routes around the inland sea. However, oceanfloor network systems do not cover all seismogenic zones around Japan. For such areas, tentative real-time system using a buoy is effective like the DART system installed in worldwide. Around Japan with very strong current like the Kuroshio, the buoy observation system for tsunami and crustal displacement adopting slack mooring has been developed. The real-time tsunami prediction can be applied for the buoy system. With mobility of the buoy system, the deployment point for the buoy system can be selected as needed for the disaster prevention. We investigated that the tsunami height calculated using above models at a point far from a target point. The tsunami height at the estimated buoy location has strongly correlation for that of the target point.