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[S17-08] Tsunami forecast method for future Nankai earthquakes using a hybrid method of data assimilation with preliminary estimated fault model
The dense pressure station networks (S-net, DONET, and N-net) were installed along the Pacific side of Japan to detect early tsunamis to predict tsunamis along the coast. Because real-time pressure data at dense sensors are available, the tsunami data assimilation method was developed by Maeda et al. (2015). However, the pressure data in the source area cannot be used for the assimilation because an initial ocean surface deformation cannot be observed by the pressure sensors. Tanioka and Gusman (2018) and Tanioka (2020) developed the method by using the time derivative pressure data to estimate the initial ocean surface deformation. However, the pressure data near the source include large strong motion, large acoustic waves, and unusual steps due to the response of the strong motion (Kubota et al. 2021), it is unrealistic to use the method developed by Tanioka (2020). If we used the pressure data observed at outside of the source region for the data assimilation, it takes too long to get a tsunami propagation field which is accurate enough for tsunami early warning, Recently, Atobe and Tanioka (2024) developed a hybrid method of tsunami data assimilation with a rapid estimated fault model. They showed that the hybrid method reduced the data assimilation time to get an appropriate tsunami propagation field and concluded that the hybrid method is useful to increase the accuracy of tsunami forecast. However, they tested their method for the 1896 Sanriku earthquake case in which the rupture interface is relatively far from the coast. This results that a lead time to forecast tsunami heights along the coast makes long, so that the data assimilation time is long enough. In this paper, we test the effectiveness of the hybrid method of tsunami data assimilation with a rapid estimated fault model for the great Nankai Trough earthquake case. The fault model of the 1707 great Hoei earthquake estimated by Furumura et al. (2011) was used as a reference model in this study. The 270m grided bathymetry was used in the tsunami simulation and the tsunami data assimilation. The stations of DONET and N-net are used in data assimilation. However, stations of DONET and N-net in the main uplifted area were eliminated. A large rectangular fault model is assumed to be estimated as a rapid preliminary fault model. The tsunami waveforms at Tosashimizu, Kochi, Shirahama, Kumano, and Owase were used to evaluate the effectiveness of the hybrid method of tsunami data assimilation with a rapid fault model. By using 10 minutes data assimilation without a preliminary fault model, the waveforms along the coast were not modeled well but the amplitude were well enough to be modeled. By using the hybrid method with 10 minutes data assimilation, the waveforms along the coast were better explained. This indicates that the hybrid method is useful to forecast the tsunami along the coast.
References
Atobe, Y. and Tanioka, Y. (2024), Tsunami Forecast Method Using Tsunami Data Assimilation with Real-time Source Estimation, JpGU 2024, Abstract HDS11-P07
Furumura, T., Imai, K., & Maeda, T. (2011). A revised tsunami source model for the 1707 Hoei earthquake and simulation of tsunami inundation of Ryujin Lake, Kyushu, Japan. Journal of Geophysical Research: Solid Earth, 116(2), 1–17.
Kubota, T., Kubo, H., Yoshida, K., Chikasada, N. Y., Suzuki, W., Nakamura, T., & Tsushima, H. (2021). Improving the constraint on the Mw7.1 2016 off-Fukushima shallow normal-faulting earthquake with the high azimuthal coverage tsunami data from the S-net wide and dense network: Implication for the stress regime in the Tohoku overriding plate. Journal of Geophysical Research: Solid Earth, 126, e2021JB022223.
Maeda, T., Obara, K., Shinohara, M., Kanazawa, T., & Uehira, K. (2015). Successive estimation of a tsunami wavefield without earthquake source data: A data assimilation approach toward real-time tsunami forecasting. Geophysical Research Letters, 42(19), 7923–7932.
Tanioka, Y. (2020). Improvement of near-field tsunami forecasting method using ocean-bottom pressure sensor network (S-net). Earth, Planets and Space, 72(1), 1–10.
Tanioka, Y., & Gusman, A. R. (2018). Near-field tsunami inundation forecast method assimilating ocean bottom pressure data: A synthetic test for the 2011 Tohoku-oki tsunami. Physics of the Earth and Planetary Interiors, 283: 82–91.
References
Atobe, Y. and Tanioka, Y. (2024), Tsunami Forecast Method Using Tsunami Data Assimilation with Real-time Source Estimation, JpGU 2024, Abstract HDS11-P07
Furumura, T., Imai, K., & Maeda, T. (2011). A revised tsunami source model for the 1707 Hoei earthquake and simulation of tsunami inundation of Ryujin Lake, Kyushu, Japan. Journal of Geophysical Research: Solid Earth, 116(2), 1–17.
Kubota, T., Kubo, H., Yoshida, K., Chikasada, N. Y., Suzuki, W., Nakamura, T., & Tsushima, H. (2021). Improving the constraint on the Mw7.1 2016 off-Fukushima shallow normal-faulting earthquake with the high azimuthal coverage tsunami data from the S-net wide and dense network: Implication for the stress regime in the Tohoku overriding plate. Journal of Geophysical Research: Solid Earth, 126, e2021JB022223.
Maeda, T., Obara, K., Shinohara, M., Kanazawa, T., & Uehira, K. (2015). Successive estimation of a tsunami wavefield without earthquake source data: A data assimilation approach toward real-time tsunami forecasting. Geophysical Research Letters, 42(19), 7923–7932.
Tanioka, Y. (2020). Improvement of near-field tsunami forecasting method using ocean-bottom pressure sensor network (S-net). Earth, Planets and Space, 72(1), 1–10.
Tanioka, Y., & Gusman, A. R. (2018). Near-field tsunami inundation forecast method assimilating ocean bottom pressure data: A synthetic test for the 2011 Tohoku-oki tsunami. Physics of the Earth and Planetary Interiors, 283: 82–91.