[HDS11-05] Tsunami modeling by marine landslides and reduction of disasters
★Invited Papers
Keywords:Landslide and Tsunami simulation, Tsunami forecast
The marine landslides due to large earthquakes caused much larger tsunamis than that expected from the magnitudes of the earthquakes. One example is the large tsunami along Aleutian Inlands due to the 1946 Aleutian earthquake (Ms7.2). The maximum tsunami height was about 40 m. The marine landslide is believed to be the main cause for this large tsunami near the source area. The other example is the 1929 Great Banks tsunami due to the earthquake of Ms7.2. The earthquake itself was caused by the marine landslide which cut the ocean bottom cables. Therefore, the large tsunami was completely generated by the marine landslide. We try to model the tsunami by our numerical simulation of marine landslide and tsunami to find volume of the landslide.
The marine landslides due to the volcanic eruptions also caused large tsunamis. One example is the landslide during the 1741 eruption of Oshima-Oshima volcano in Hokkaido, Japan, which generated a large tsunami. We numerically simulated the lanslide and tsunami generated by the 1741 Oshima-Oshima eruption using an improved two-layer model to explain the depositional area od the landslide, the tsunami heights writen in historical records, and the distributions of tsunami deposits (Ioki et al., 2019). Areas of erosion and deposition by the 1741 landslide were estimated from the bathimetric data on the northern slope of Oshima-Oshima volcano. From the bahymetry difference before and after the landslide, the volume of collapsed material was estimted at 2.2 km3. Based on those data, the landslide and tsunami were numerically simulated by solving equations of an improved two-layer model that incorporates Manning's formula in the bottom friction terms of the lower layer. An apparent friction angle of 2.5 and a Manning's roughness coefficient of 0.15 were selectied to explain the area of deposition estimated from the bathymetry analysis and distributions of tsunami deposits. The thickness distribution of the computed landslide mass fits relatively well with the depositional area. Computed tsunami heights match those from historical records along the coast. Coomputed tsunami inundation areas cover most of the distributins of tsunami deposits identified along the coasts. The other recent exapmle is the 2018 Anal Krakatau volcano eruption which caused a landslide generated a large tsunami. The generation of the tsunami has been studied well (Grilli et al., 2019).
No tsunami forecast method for those tsunamis generated by marine landslides exists. The method is need to be developed for tsunami disaster mitigation. Becuase a dense cabled obsrvation network, called the seafloor observation network for earthquakes and tsunami along the Japan Trench (S-net), was installed in Japan recently, those ocean bottom pressure data should be used to forecast tsunami heights along the coast for marine landslide tsunamis. We developed a tsunami numerical simulation method by assimilating those ocean bottom pressure data as a tsunami forecast method (Tanioka and Gusman, 2018). The method was tested for tsunami generated by earthquakes, but it should be used for landslide tsunamis, too.
References
Grilli, S.T., Tappin, D.R., Carey, S. et al. Modelling of the tsunami from the December 22, 2018 lateral collapse of Anak Krakatau volcano in the Sunda Straits, Indonesia. Sci Rep 9, 11946 (2019). https://doi.org/10.1038/s41598-019-48327-6
Ioki, K., Y. Tanioka, H. Yanagisawa, G. Kawakami, (2019) Numerical simulation of the landslide and tsunami due to the 1741 Oshima-Oshima eruption in Hokkaido, Japan, J. Geophys. Res., doi:10.1029/2018JB016166
Tanioka, Y. and A.R. Gusman, (2018) Near-field tsunami inundation forecast method assimilating ocean bottom pressure data: A synthetic test for the 2011 Tohoku-oki tsunami, Phys. Earth Planet. Int., 283, 82-91, https://doi.org/10.1016/j.pepi.2018.08.006
The marine landslides due to the volcanic eruptions also caused large tsunamis. One example is the landslide during the 1741 eruption of Oshima-Oshima volcano in Hokkaido, Japan, which generated a large tsunami. We numerically simulated the lanslide and tsunami generated by the 1741 Oshima-Oshima eruption using an improved two-layer model to explain the depositional area od the landslide, the tsunami heights writen in historical records, and the distributions of tsunami deposits (Ioki et al., 2019). Areas of erosion and deposition by the 1741 landslide were estimated from the bathimetric data on the northern slope of Oshima-Oshima volcano. From the bahymetry difference before and after the landslide, the volume of collapsed material was estimted at 2.2 km3. Based on those data, the landslide and tsunami were numerically simulated by solving equations of an improved two-layer model that incorporates Manning's formula in the bottom friction terms of the lower layer. An apparent friction angle of 2.5 and a Manning's roughness coefficient of 0.15 were selectied to explain the area of deposition estimated from the bathymetry analysis and distributions of tsunami deposits. The thickness distribution of the computed landslide mass fits relatively well with the depositional area. Computed tsunami heights match those from historical records along the coast. Coomputed tsunami inundation areas cover most of the distributins of tsunami deposits identified along the coasts. The other recent exapmle is the 2018 Anal Krakatau volcano eruption which caused a landslide generated a large tsunami. The generation of the tsunami has been studied well (Grilli et al., 2019).
No tsunami forecast method for those tsunamis generated by marine landslides exists. The method is need to be developed for tsunami disaster mitigation. Becuase a dense cabled obsrvation network, called the seafloor observation network for earthquakes and tsunami along the Japan Trench (S-net), was installed in Japan recently, those ocean bottom pressure data should be used to forecast tsunami heights along the coast for marine landslide tsunamis. We developed a tsunami numerical simulation method by assimilating those ocean bottom pressure data as a tsunami forecast method (Tanioka and Gusman, 2018). The method was tested for tsunami generated by earthquakes, but it should be used for landslide tsunamis, too.
References
Grilli, S.T., Tappin, D.R., Carey, S. et al. Modelling of the tsunami from the December 22, 2018 lateral collapse of Anak Krakatau volcano in the Sunda Straits, Indonesia. Sci Rep 9, 11946 (2019). https://doi.org/10.1038/s41598-019-48327-6
Ioki, K., Y. Tanioka, H. Yanagisawa, G. Kawakami, (2019) Numerical simulation of the landslide and tsunami due to the 1741 Oshima-Oshima eruption in Hokkaido, Japan, J. Geophys. Res., doi:10.1029/2018JB016166
Tanioka, Y. and A.R. Gusman, (2018) Near-field tsunami inundation forecast method assimilating ocean bottom pressure data: A synthetic test for the 2011 Tohoku-oki tsunami, Phys. Earth Planet. Int., 283, 82-91, https://doi.org/10.1016/j.pepi.2018.08.006