Aditya Riadi Gusman

Earthquake Research Institute, the University of Tokyo

1. INTRODUCTION

Great earthquakes in the subduction zones generated large tsunamis that devastated coastal areas. Huge tsunamis such as the 2004 Indian Ocean or the 2011 Tohoku tsunamis caused fatal damages in areas more than 1 km away from the coastlines. Unfortunately, existing tsunami early warning systems in the world do not have the capability to forecast tsunami inundation in the near field.

We developed a methodology for Near-field Tsunami Inundation Forecasting (NearTIF) that can produce high-resolution tsunami inundation forecast maps in around 3 minutes after the source of the tsunami has been determined (Gusman et al., 2014). This algorithm requires database of pre-computed tsunami waveforms and tsunami inundations.

The algorithm has been tested in a retrospective forecast of the 2011 Tohoku tsunami along the Sanriku Coast, Japan. Tsunami inundation maps were forecasted with earthquake source model that was estimated from the W phase of seismic data. We found that the resulting tsunami inundations were similar to the observed tsunami run-up heights.

We carried out tsunami evacuation drill in Kushiro city Hokkaido that used results from our algorithm to evaluate the effectiveness of tsunami inundation forecast maps.

2. NEAR-FIELD TSUNAMI INUNDATION FORECASTING (NearTIF)

Tsunami inundations from different scenarios can be similar to each other as long as the tsunami waveforms at near-shore points are also similar. Tsunami waveforms at near-shore point deeper than 50 m from low-resolution and high-resolution simulations are similar. Base on these assumptions, we developed a methodology for high-resolution tsunami inundation forecasting. This method required pre-computed tsunami waveforms and tsunami inundation database.

When an earthquake happens, tsunami waveforms at near-shore points can be simulated on low-resolution grid by solving the linear shallow water equations. This kind of simulation does not take long time and can be done using regular computer. A scenario in the database than produced tsunami waveform that is similar to the simulated one can be found by RMS analysis. Finally the corresponding tsunami inundation map from that best-fit scenario is selected as tsunami inundation forecast map. This process takes only approximately 3 minutes on a regular computer.

3. FAULT MODEL FOR THE 2011 TOHOKU TSUNAMI

W phase is a long period phase (200 to 1,000 s) that arrives before S phase, and can be used for rapid and robust determination of great earthquake’s source parameters with sufficient accuracy for tsunami early warning purposes (Kanamori and Rivera, 2008). About 5 minutes after the 2011 Tohoku earthquake Japanese F-net stations recorded seismic data that is enough to accurately estimate the seismic moment by W phase inversion. The estimated scalar moment for the 2011 Tohoku earthquake from the 5 min W phase data is 3.69 × 10^{22} Nm (Mw 9.0). The moment tensor solution was used to make a fault model for the 2011 Tohoku earthquake. The length (L) and width of the fault model using scaling relation of Hanks and Bakun (2002) and simple relation of L = 2 × W are 246 km and 123 km, respectively (Gusman and Tanioka, 2013).

4. RETROSPECTIVE TSUNAMI INUNDATION FORECAST MAPS FOR THE 2011 TOHOKU TSUNAMI

The fault model based on the 5-min W phase solution was used as an input for NearTIF to produce tsunami inundation maps in 15 locations along the Sanriku Coast. The retrospective tsunami inundation forecast from this fault model can explain the observed limit of tsunami inundation and inland tsunami heights very well in all locations (Gusman et al., 2014). For example, tsunami inundation maps for Rikuzentakata, Japan produced by the NearTIF algorithm is shown in Fig. 1. The forecasted limit of inundation and inland tsunami heights are very similar with the observations (Fig. 1).

Fig. 1 Tsunami inundation forecast in Rikuzentakata produced by the NearTIF algorithm from the fault model of 5-min W phase solution. Green bars represent the measured tsunami heights, magenta dots represent the forecasted tsunami heights, blue lines represent the actual limit of inundation, and black dots are the measured positions. K value indicates the relative size of the observed and simulated tsunami heights, and κ (kappa) value indicates the precision of the simulated tsunami heights (Gusman et al., 2014).

The tsunami inundation map produced by the NearTIF algorithm is comparable with that from numerical forward modeling. However, the numerical forward modeling required approximately 2 hours of CPU time to produce tsunami inundation map for a single location (Rikuzentakata). The required time is much longer if we simulate more locations. Based on performance test of NearTIF vs. numerical forward modeling in our previous study, the NearTIF algorithm is 800 times faster than numerical forward modeling to produce tsunami inundation maps in 15 locations (Gusman et al., 2014).

5. TSUNAMI EVACUATION DRILL IN KUSHIRO CITY, HOKKAIDO

From historical and pre-historical tsunamigenic earthquake studies (Hatori, 1984; Hirata et al., 2003; Satake et al., 2005; Tanioka et al., 2007; Ioki, 2013), Kushiro city has been identified as a tsunami prone area. Kushiro city office has provided to the public a tsunami hazard map that can increase the effectiveness of evacuation plans for the community.

We evaluated the effectiveness of the NearTIF algorithm in the real world by carrying out a tsunami evacuation drill in Kushiro city, Hokkaido, Japan, involving the residents. The drill started by an announcement of tsunami warning to evacuate the residents to the nearest evacuation building. About 10 minutes after the announcement, the participants used tablet computers to see the tsunami inundation forecast map that was uploaded to the Internet. It was easy for the participants to see their current location on the tsunami inundation forecast map because the tablet computer was equipped with GPS device. The participants found that the use of the tsunami inundation forecast map produced by NearTIF was effective to make a better decision with high confidence during the tsunami evacuation drill.

6. CONCLUSIONS

Tsunami inundation forecast on high-resolution topography can help to make a decision for evacuation during a tsunami event. Tsunami inundation can be simulated accurately by solving the nonlinear shallow water wave equations. However, high-resolution tsunami simulation is numerically expensive. To resolve this challenge, we developed a methodology for Near-field Tsunami Inundation Forecasting (NearTIF) that is equipped with a database of pre-computed tsunami waveforms and pre-computed tsunami inundation. The tsunami inundation forecasted by the NearTIF algorithm is similar to the result from numerical forward simulation and thus are a fast alternative to the slower numerical simulation.

W phase data can give a reliable earthquake magnitude estimate (Kanamori, 2008; Duputel et al., 2011; Gusman and Tanioka, 2013; Benavente and Cummins, 2013). Reliable centroid moment tensor solutions of the 2011 Tohoku earthquake can be estimated using 5 min of W phase data recorded at Japanese F-net stations (Gusman and Tanioka 2013; Gusman et al., 2014).

We evaluated the effectiveness of the NearTIF algorithm in the real world by carrying out a tsunami evacuation in Kushiro city, Hokkaido, Japan. The participants found that the use of the tsunami inundation forecast map was effective to make a better decision with high confidence during the tsunami evacuation process.

The NearTIF algorithm is recommended to be use as part of the reconstruction policy by local authorities to improve the evacuation efficiency particularly in tsunami prone areas. We recommend the use of the NearTIF method in developing future tsunami forecasting systems with a capability of providing tsunami inundation forecast maps for locations near the tsunami source area.

REFERENCES

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