Citation: Malodali, J. S., B. Shibazaki, Y. Fujii (2023), Tsunami propagation and inundation simulations inFiji based on scenario earthquakes, Synopsis of IISEE-GRIPS Master’s Thesis.

TSUNAMI PROPAGATION AND INUNDATIONSIMULATIONS IN FIJI BASED ON SCENARIO
EARTHQUAKESJoji MALODALI1
MEE22713

Supervisors: Bunichiro SHIBAZAKI2*, Yushiro FUJII2**

ABSTRACTIn this study, tsunami simulations are conducted by assuming an M8.5 earthquake generated along theTonga Trench, including horizontal deformation effect, and using a depth of five kilometers aligned tothe buried faults. We performed numerical tsunami simulations using the Tohoku University's
Numerical Analysis Model for Investigation (TUNAMI) code for the linear or non-linear wave
equations in a spherical coordinate system. We tested two bathymetry data of GEBCO and ETOPO for
single grid computations. We used the GEBCO for bathymetry data and the SRTM data for thetopography for the tsunami inundation simulations. We adopted the nesting grid system with four layers
including the finer grid merging the GEBCO and SRTM data on the tsunami inundation area. We
selected two study areas to focus on the inundation: Suva and Ono-i-Lau. We placed four output points
along the Suva coastlines in FDB foreshore, Walu bay, Lami, and Draunibota. The computational resultin the Suva study area shows that the maximum inundation height recorded was at Walu Bay, with aheight of 3.06 meters, and the earliest wave recorded was at FDB foreshore, with a time of 103.8 minutes.
For the second study area in Ono-i-Lau, the four output points are Nukuni, South Nukuni, North
Matokana, and Doi. The results show that the maximum inundation height recorded was at South Nukuni,with a height of 1.61 meters, and the earliest wave recorded was also at South Nukuni, with a time of62.5 minutes.
Keywords: Tonga Trench, Horizontal deformation effect, Buried faults, Tsunami inundation, Tsunami
simulations.
1. INTRODUCTION
Fiji, a small island nation in the South Pacific, is vulnerable to natural disasters, including earthquakes
and tsunamis. In 1953, a devastating tsunami hit Fiji caused by a submarine landslide allowing
significant damage to infrastructure and loss of life (Rahiman et al., 2007).
Understanding the potential impact of tsunamis on Fijis' coastal communities is critical fordisaster preparedness and risk reduction. One of the key aspects of this understanding is modelingtsunami inundation, which involves simulating how tsunamis would spread across coastal areas andpredicting the extent of flooding and damage that could result.
According to Murata et al. (2018), even with present technologies and knowledge, we stillcannot predict the occurrence of earthquakes in advance. Hence it is also impossible to predict thetsunami occurrence. Therefore, providing knowledge and information on tsunami hazard is very
important for people living in prone areas to save lives from tsunamis.

1Technical Officer, Mineral Resources Department, Fiji Islands.
International Institute of Seismology and Earthquake Engineering, Building Research Institute.
* Chief examiner, ** Examiner
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This study aims to model tsunami inundation along the Fiji coastline by merging
bathymetry and topography data. This study's results will help authorities inform about coastal hazard
assessments and support disaster risk reduction efforts in Fiji.
2. DATAThis study uses the General Bathymetric Chart of the Oceans (GEBCO) as bathymetry data (GEBCO
Compilation Group, 2023). We used the current GEBCO_2023 version with the 15 arc-sec interval grid.
We also utilized the ETOPO data as bathymetry data. The ETOPO data are available on and downloaded
from the (https://www.ncei.noaa.gov/maps/grid-extract/) website. The version used is the ETOPO 2022with a 15 arc-sec grid interval.
We used the Shuttle Radar Topography Mission (SRTM) for the topography data in this study.
It is a one arc-second or about 30 meters (98 feet) sampling that reveals the full resolutions of the original
measurements.
Thesedataareavailable
onanddownloadedfromthe( https://search.earthdata.nasa.gov/search ) website. This SRTM data is then merged with GEBCO data
to attain a finer grid to simulate inundation for a selected region within a study area.
This study selected nine output points inhigh tsunami risk areas identified by Rawaikala (2011).
Among the nine output points, we set two study areas.
First is Suva the capital city, located in one of Fiji's mainislands. The second study area is Ono-i-Lau, an island thatis part of the Lau group and one nearest to the Tonga
trench. Figure 1 illustrates the different output points andtheir locations. It identifies Suva with a star indicatingthat it is an actual tide gauge station. The rest shows
assumed tide gauge stations.

Figure 1. Close-up map of the locations ofthe nine selected output points in thestudy region.

3. METHODOLOGY

We calculated the tsunami propagation, travel time, wave height, and inundation through the tsunami
simulations. The Tohoku University’s Numerical Analysis Model for Investigation (TUNAMI) code(Yanagisawa, 2022-2023) was employed in the tsunami wave propagation simulation in the single gridsof 1 arc-min using GEBCO and ETOPO in linear and non-linear. For tsunami inundation, we applied
the nesting grids of 1 arc-min, 20 arc-sec, 20/3 arc-esc using GEBCO and SRTM in non-linear.
After conducting a few tests on the results of Rawaikala (2011), we selected the 8.5
magnitude earthquake (source model "B2") along Tonga trench. This earthquake source model is located186.4˚ east and -21.0˚ south. Added to this study is applying the mentioned effects on the horizontal andburied faults. Figure 2 illustrates the fault deformations with three different depths and horizontal impact.
(c)(b)(a)mmm

Figure 2. Comparison of fault deformation simulations of the three depths of (a) 0 km, (b) 5 km;
and (c) 10 km. The red color depicts the uplift, while the blue color denotes the subsidence area.

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Figure 3. Transect of the vertical deformation by the threefaults with different depths of 0, 5, and 10 km.

Cross-section view ofvertical deformation can be crucial
in estimating fault displacements.
Figure 3 illustrates the cross-section
view of the vertical deformation of
the three faults with different depths
corresponding to those in Figure 2.
The red line indicates the 0 km fault
depth. The blue line denotes the 5km fault depth. Lastly, the black line
indicates the 10 km fault depth. InFigure 3, the 5 km depth wasrecorded as the highest comparing
the other two models.

4. RESULTS AND DISCUSSION
Tsunami heights vary due to various reasons. Bathymetry and topography are contributing factors.
Figure 4 shows the waveforms calculated through a non-linear computation between GEBCO andETOPO with 5 km depth and the horizontal deformation effect obtained from the tsunami simulation atthe nine output points placed along the Fiji coastlines. The result contributed to the selection of whichbathymetry data to be used for tsunami inundation simulations in this study.

Figure 4. Comparison of the non-linear computations between
GEBCO (blue waveforms) and ETOPO (orange waveforms)
at the nine output points.
For the tsunami inundation modeling, the tsunami run-up and inundated area are the crucial
elements or outputs contributing to the tsunami hazard assessment and disaster mitigation planning. We
measured the inundation height from the mean sea level (MSL) to the tsunami inundation limit(Yanagisawa, 2022-2023). The tsunami inundation modeling focused on Suva, which is the capital ofFiji and located in Viti Levu, and Ono-i-Lau, which is an island in the Lau region, closest to the Tonga
region. Figure 5 illustrate the nesting grid system with four regions. Region 4 provided finer details of
the determined inundated areas in the two study areas by merging the bathymetry and topography data.

3R1

R1
R3

R2
R4R2R4R3Figure 5. Nesting grids for the Suva (left) and Ono-i-Lau (right)
study area with an indication of the four regions.
Suva is the capital city of Fiji and amajor commercial center for other Pacific islands.
Figure 6 shows the merged topography andbathymetry data around the Suva peninsula, andshows the four assumed output points, namely FDB
foreshore, Walubay, Lami, and Draunibota, fromwhich the tsunami inundation waves were recorded.
Figure 7 shows the tsunami waveforms at the four
output points in the Suva coastline. Also, Figure 8
shows the areas affected by the tsunami waves.

Figure 6. Merged topography andbathymetry grid data with the four
assumed output points around Suva
harbor. This region is denoted as R4
in Figure 5.

Figure 7. Tsunami simulation waveforms
recorded at the four output points along
the Suva coastline.

mFigure 8. Inundated areas around Suva
with the maximum inundation height.

4For output point FDB foreshore, the first tsunami arrival time is 103.8 min, with aninundation depth of 0.66 m and an inundation height of 0.98 m. For the output point in Walu Bay, thefirst tsunami arrival time is 108.6 min, with an inundation depth of 2.38 m and the 3.06 m inundation
height. In Lami, the first tsunami arrival time is 107.6 min, with an inundation depth of 2.05 m and the2.44 m inundation height. Lastly, for the output point in Draunibota, the first tsunami arrival time is 108
min, with an inundation depth of 2.23 m and the 2.44 m inundation height. The maximum inundation
height of 3.06 m was recorded at Walu Bay, and the earliest wave was recorded at the FDB foreshore,with a time of 103.8 min.
Ono-i-Lau is an island located 400 km
from Suva and 350 km from Tongatapu Island.
According to Clark (2009), it has three mainislands and several islets with a total land area of
7.9 km2 within an 80 km² reef system. Figure 9shows the merged topography and bathymetry
data around Ono-i-Lau Island and the four
assumed output points, of Nukuni, South Nukuni,
North Matokana, and Doi, where the tsunami
inundation were simulated. Figure 10 shows thetsunami waveforms at the four output points in theOno-i-Lau coastline. Also, Figure 11 shows theareas affected by the tsunami waves.

Figure 9. Merged topography andbathymetry grid data with the four
assumed output points around Onoi-Lau Island. This region is denoted
as R4 in Figure 5.

Figure 10. Tsunami simulation
waveforms recorded at the four output
points along the Ono-i-Lau coastline.

Figure 11. Inundated areas aroundOno-i-Lau with the maximum
inundation height.

mFor the output point in Nukuni, the first tsunami arrival time is 64 min, with 0.55 m
inundation depth and 0.81 m inundation height. For the output point in South Nukuni, the first tsunami
arrival time is 62.5 min, with 1.20 m inundation depth and 1.61 m inundation height. In North Matokana,
the first tsunami arrival time is 68.4 min, with 1.49 m inundation depth and 1.60 m inundation height.
Lastly, for the output point in Doi, the first tsunami arrival time is 70.7 min, with 0.66 m inundation
depth and 1.01 m inundation height. The maximum inundation height of 1.61 m recorded at SouthNukuni, along with the earliest wave with a time of 62.5 min.

55. CONCLUSIONSIn this study, we conducted tsunami propagation and inundation simulations along the Tonga trenchwith a source model earthquake of 8.5 magnitude. Along with the fault parameters, the horizontal
deformation effect and buried faults of 5 km depth are also applied to examine and investigate the impactof tsunami simulations on Fiji coastlines. Also, we conducted single grid computations with thebathymetry data between GEBCO and ETOPO to compare results and to see the differences. We adopted
the TUNAMI code to simulate the tsunami propagation and inundation together with the nested gridsystem, where for the fourth layer we merged GEBCO and SRTM data to get finer detailing ofinundation simulations in Suva and Ono-i-Lau. Around Suva and Ono-i-Lau, we placed four output
points to assess important parameters such as tsunami arrival times and tsunami inundation heights. For
Suva, the output points were FDB foreshore, Walu bay, Lami, and Draunibota. While in Ono-i-Lau,they were Nukuni, South Nukuni, North Matokana and Doi.
Tsunami simulation results showed that assuming fault parameters and the effects. The
computational result in the Suva study area showed that the maximum inundation height recorded wasat Walu Bay, with a height of 3.06 meters, and the earliest wave recorded was at FDB foreshore, with atime of 103.8 minutes. As for the second study area in Ono-i-Lau, the results showed that the maximum
inundation height recorded was at South Nukuni, with a height of 1.61 meters, and the earliest wave
recorded was also at South Nukuni, with a time of 62.5 minutes.
The tsunami simulation results generally indicate that tsunami travel times for Suva andOno-i-Lau are about an hour and a half, respectively. At the same time, the inundation height is morethan 1.5 meters for both. Given these simulation results, the residents in these high-risk areas will know
their vulnerability and give them time to move regarding future disasters like tsunamis.

ACKNOWLEDGEMENTS
This research was conducted during the individual study period of the training course “Seismology,Earthquake Engineering and Tsunami Disaster Mitigation” by the Building Research Institute, JICA,and GRIPS. I would like to express my sincere gratitude to my supervisor Dr. Bunichiro Shibazaki for
his valuable support and experience which helped me to complete my research successfully, and to Dr.
Yushiro Fujii for his guidance and constructive comments during my individual study.

REFERENCES
Clark, G. (2009). Early ceramic sites in southern Lau, Fiji. Archaeology in New Zealand, 62, 81-89.
GEBCO Compilation Group (2023). GEBCO 2023 Grid (doi:10.5285/f98b053b-0cbc-6c23-e0536c86abc0af7b)
Murata, S., Imamura, F., Katoh, K., Kawata, Y., Takahashi, S., & Takayama, T. (2018). Tsunami: tosurvive from tsunami. World Scientific.
Rahiman, T. I., Pettinga, J. R., & Watts, P. (2007). The source mechanism and numerical modelling ofthe 1953 Suva tsunami, Fiji. Marine Geology, 237(1-2), 55-70.
Rawaikala, U. R. (2011). TSUNAMI SIMULATION AND HAZARD ASSESSMENT ALONG THE
COASTS OF FIJI. Bulletin of the International Institute of Seismology and Earthquake Engineering,45, 103-108.
Yanagisawa, H. (2022-2023). Lecture note on Numerical simulation of Tsunami inundation and itsapplication.

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