3:45 PM - 4:00 PM
[SCG53-02] Real-time tsunami prediction using oceanfloor network systems and its utilization
★Invited Papers
Keywords:Tsunami prediction, real-time, ocean-floor network system
Since 2011 off Tohoku earthquake and tsunami, re-evaluation of hazard risks by huge earthquakes and tsunamis. Japanese Cabinet Office (2012) proposed eleven cases models with a magnitude nine. These models brought us critical awareness for disaster prevention. In particular, predicted tsunami becomes higher than previous estimation and the inundation area becomes broader.
We started development of a real-time tsunami prediction system using dense ocean-floor network system for earthquakes and tsunamis (DONET) in 2012 (Takahashi et al., 2017; Takahashi and Imai, 2022). The principal is based on positive correlation between pressure data observed by seafloor stations and estimated tsunami height of the coastal areas. The system estimates tsunami arrival time, tsunami height, inundation area and its depth distribution in real-time, and it was already installed on some local governments and an infrastructure company in Japan. To improve the accuracy, we took some measures of extraction of fault models in database. Using traveltime difference of the first arrivals on seismic data and order of tsunami triggering, we succeeded to narrow down fault models for improvement of the positive correction. In addition, other information can be also used, which are estimation of rough area brought by electromagnetic studies and some information from Japan Meteorological Agency. In 2018, we expanded the prediction system for Chiba prefecture using Seafloor network system along the Japan trench for earthquakes and tsunamis (S-net). And we added the feature to be able to visualize the tsunami prediction on mobile system, which is smart phone and tablet. The real-time imaging of the inundation lead to evaluation of tsunami debris, which are the volume, accumulation places, volumes of drift in the sea. Making measure for these issues lead to fast reconstruction and decreasing damages.
It is important to be able to use the prediction system from normal to familiar this system. Some municipalities and local government utilize it as a tool of evacuation drill. In an area, which it takes a few hours until tsunami arrival, there are much issues of the prevention during the grace period. We will also introduce some examples how to use the prediction system in normal.
We started development of a real-time tsunami prediction system using dense ocean-floor network system for earthquakes and tsunamis (DONET) in 2012 (Takahashi et al., 2017; Takahashi and Imai, 2022). The principal is based on positive correlation between pressure data observed by seafloor stations and estimated tsunami height of the coastal areas. The system estimates tsunami arrival time, tsunami height, inundation area and its depth distribution in real-time, and it was already installed on some local governments and an infrastructure company in Japan. To improve the accuracy, we took some measures of extraction of fault models in database. Using traveltime difference of the first arrivals on seismic data and order of tsunami triggering, we succeeded to narrow down fault models for improvement of the positive correction. In addition, other information can be also used, which are estimation of rough area brought by electromagnetic studies and some information from Japan Meteorological Agency. In 2018, we expanded the prediction system for Chiba prefecture using Seafloor network system along the Japan trench for earthquakes and tsunamis (S-net). And we added the feature to be able to visualize the tsunami prediction on mobile system, which is smart phone and tablet. The real-time imaging of the inundation lead to evaluation of tsunami debris, which are the volume, accumulation places, volumes of drift in the sea. Making measure for these issues lead to fast reconstruction and decreasing damages.
It is important to be able to use the prediction system from normal to familiar this system. Some municipalities and local government utilize it as a tool of evacuation drill. In an area, which it takes a few hours until tsunami arrival, there are much issues of the prevention during the grace period. We will also introduce some examples how to use the prediction system in normal.