JpGU-AGU Joint Meeting 2017

Presentation information

[JJ] Oral

H (Human Geosciences) » H-DS Disaster geosciences

[H-DS16] [JJ] Tsunami and Tsunami Forecast

Wed. May 24, 2017 9:00 AM - 10:30 AM Convention Hall A (International Conference Hall 2F)

convener:Yuichi Namegaya(Institute of Earthquake and Volcano Geology, Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology), Naotaka YAMAMOTO(National Research Institute for Earth Science and Disaster Resilience), Chairperson:Kenji Hirata(National Research Institue for Earth Science and Diaster Prevention), Chairperson:Akio Katsumata(Meteorological Research Institute, Japan Meteorological Agency)

9:15 AM - 9:30 AM

[HDS16-02] Offshore tsunami observation array suitable for coastal tsunami prediction using multiple linear regression with L1 regularization

*Junichi Taniguchi1, Takashi Yoshikawa2, Shin Murata2, Yasuhiko Murata2, Takane Hori3, Masato Okada2, Toshitaka Baba1 (1.Tokushima University, 2.Tokyo University, 3.JAMSTEC)

Keywords:tsunami prediction, offshore observation, L1 regularization term

In recent years, tsunami prediction methods using the offshore tsunami data are investigated while high-density offshore tsunami observation networks have been deployed around Japan. We proposed methods to predict the coastal tsunami height by regression from offshore tsunami heights in the previous studies (Baba et al., 2014; Igarashi et al. 2016). These aimed to utilize the tsunami data observed by previously installed offshore gauges to improve the accuracy of tsunami prediction at the coast as possible. On the other hand, considering a development of a similar system including construction of a new offshore observation network in other area, we have to answer a question where we should install observation points to make the prediction accuracy the best. Therefore, in this study, the importance of each offshore observation point was evaluated by introducing L1 regularization term (LASSO) in the regression analysis. This study was carried out by the following procedure. We assumed 2622 rectangular fault models in total in the Nankai trough subduction zone. Uniform sliding was assigned for 1506 models. The remaining 1116 models have heterogeneity of slip distribution by assuming a large slip patch on the fault plane. The tsunamis caused by the 2622 fault models were repeatedly calculated by solving the nonlinear long wave theory. We performed a multiple linear regression analysis with L1 regularization term to the maximum tsunami heights at a point in the Asakawa bay, Tokushima, and these recorded at the 57 offshore points of GPS wave meters and the DONET water pressure gauges. The analysis showed that it is possible to predict the coastal tsunami height with the accuracy of RMS residual less than 1 m by using only 12 offshore points which are located in the Kii Channel between the Cape Shiono and the Cape Muroto.