Toward the integration of seismic analysis and tsunami model for rapid inundation forecasting system

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 × 1022 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 (W) 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).

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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Numerical experiment and a case study of sediment transport simulation of the 2004 Indian Ocean tsunami in Lhok Nga, Banda Aceh, Indonesia

Aditya Riadi Gusman, Yuichiro Tanioka, Tomoyuki Takahashi

Earth Planets Space, 64, 817–827, 2012, doi:10.5047/eps.2011.10.009

Abstract

We use a two-dimensional tsunami sediment transport model to study the source of the 2004 earthquake. To test the model behavior, numerical experiment on sediment deposition and erosion is performed using various hypothetical parameters of tsunami wavelength, topographic slope, and sediment supply. The numerical experiment results show that erosion and deposition are strongly influenced by the tsunami wavelength and the topographic slope. The model is used to compute the spatial distribution of tsunami deposit thickness produced by the 2004 Indian Ocean over an actual elevation datasets in the coastal area of Lhok Nga, Banda Aceh, Indonesia. The model produced simulated tsunami deposits that have similar thicknesses with the measured data along a surveyed transect. Then we estimate a simple fault model for the southern portion of the 2004 earthquake using tsunami sediment transport simulations. The simulated tsunami run-up from the fault model is very close to the measured run-up. This result indicates that a source process of a large earthquake that generates a large tsunami has a potential to be estimated using sediment deposit distribution data.

Tsunami Hazard Mitigation at Palabuhanratu, Indonesia

Yuichiro Tanioka, Hamzah Latief, Haris Sunendar, Aditya Riadi Gusman, Shunichi Koshimura

Journal of Disaster Research 7 (1), 19-25

Abstract

Several large earthquakes have recently occurred along the Sumatra-Java subduction zone, the 2004 great Sumatra-Andaman earthquake, the 2005 great Nias earthquake, the 2006 West Java tsunami earth- quake, the 2007 great Bengkulu earthquake, and the 2010 Mentawai tsunami earthquakes. Serious tsunami disasters were caused by the great underthrust earthquakes which ruptured the plate interface near the trench such as the 2004 Sumatra-Andaman, 2006 West Java, 2010 Mentawai earthquakes. At Palabuhanratu, maximum tsunami height distribution and inundation areas were computed from expected fault models located near the Java trench. The results shows that the most populated areas of Palabuhanratu would be severely damaged by the expected tsunami caused by the fault model of Mw 8.5. After discussing tsunami disaster mitigation measures with the local government, the result of tsunami inundation area in this study were used to decide tsunami evacuation areas and evacuation routes. The local government also installed tsunami evacuation sign boards near the coast.

Sedimentary Deposits from the 17 July 2006 Western Java Tsunami, Indonesia: Use of Grain Size Analyses to Assess Tsunami Flow Depth, Speed, and Traction Carpet Characteristics

Andrew Moore, James Goff, Brian G. McAdoo, Hermann M. Fritz, Aditya Gusman, Nikos Kalligeris, Kenia Kalsum, Arif Susanto, Debora Suteja, Costas E. Synolakis

Pure and Applied Geophysics, November 2011, Volume 168, Issue 11, pp 1951-1961, DOI: 10.1007/s00024-011-0280-8
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Abstract

The 2006 western Java tsunami deposited a discontinuous sheet of sand up to 20 cm thick, flooded coastal southern Java to a depth of at least 8 m and inundated up to 1 km inland. In most places the primarily heavy mineral sand sheet is normally graded, and in some it contains complex internal stratigraphy. Structures within the sand sheet probably record the passage of up to two individual waves, a point noted in eyewitness accounts. We studied the 2006 tsunami deposits in detail along a flow parallel transect about 750 m long, 15 km east of Cilacap. The tsunami deposit first becomes discernable from the underlying sediment 70 m from the shoreline. From 75 to 300 m inland the deposit has been laid down in rice paddies, and maintains a thickness of 10–20 cm. Landward of 300 m the deposit thins dramatically, reaching 1 mm by 450 m inland. From 450 m to the edge of deposition (around 700 m inland) the deposit remains <1 mm thick. Deposition generally attended inundation—along the transect, the tsunami deposited sand to within about 40 m of the inundation limit. The thicker part of the deposit contains primarily sand indistinguishable from that found on the beach 3 weeks after the event, but after about 450 m (and roughly coinciding with the decrease in thickness) the tsunami sediment shifts to become more like the underlying paddy soil than the beach sand. Grain sizes within the deposit tend to fine upward and landward, although overall upward fining takes place in two discrete pulses, with an initial section of inverse grading followed by a section of normal grading. The two inversely graded sections are also density graded, with denser grains at the base, and less dense grains at the top. The two normally graded sections show no trends in density. The inversely graded sections show high density sediment to the base and become less dense upward and represents traction carpet flows at the base of the tsunami. These are suggestive of high shear rates in the flow. Because of the grain sorting in the traction carpet, the landward-fining trends usually seen in tsunami deposits are masked, although lateral changes of mean sediment grain size along the transect do show overall landward fining, with more variation as the deposit tapers off. The deposit is also thicker in the more seaward portions than would be produced by tsunamis lacking traction carpets.