Citation: Manu, M.S., T. YOKOI, T. AZUHATA (2022), Fragility evaluation of building structures basedon damage survey results of tsunami disaster from Hunga Tonga – Hunga Ha’apai volcano eruption on 15
January 2022, Synopsis of IISEE-GRIPS Master’s Thesis.

FRAGILITY EVALUATION OF BUILDINGSTRUCTURES BASED ON DAMAGE SURVEYRESULTS OF TSUNAMI DISASTER FROM HUNGATONGA – HUNGA HA'APAI VOLCANO ERUPTION
ON 15 JANUARY 2022.
Mele Siale Manu1
MEE21715

Supervisors: Toshiaki YOKOI2, Tatsuya AZUHATA3
ABSTRACTOn 15 January 2022, Tonga was hit by a tsunami caused by the eruption of the HUNGA TONGA –HUNGA HA'APAI (HT-HH) volcano. This study aims to detect the vulnerable structural systems fromthis disaster, using fragility curves for future disaster mitigation planning. I gathered data on theinundation depth and structural damages through the government ministries' post-disaster field surveys
and completed the required dataset on an independent field survey. This study focused on Hihifo andNuku'alofa on Tongatapu island. The method used to determine fragility functions was the Grid Searchmethod. Structural damages have two classifications: destroyed and survived. Fragility curves forstructural damages were developed for all building types of Hihifo and Nuku'alofa, timber buildings ofHihifo and Nuku'alofa, and Reinforced Concrete (RC) buildings with masonry infill of Hihifo. The
result showed that the Hihifo area has a stronger structural system than Nuku'alofa. The fragility curvesof Hihifo and Nuku'alofa were compared with those developed in other countries. It showed that thetimber buildings and RC structures with masonry infill of Hihifo are stronger than in other countries.
However, American Samoa's RC structures are more resilient than Hihifo at higher inundation depths.
Therefore, the timber buildings of Nuku'alofa need to be assessed in detail. The RC with masonry infill
buildings of Hihifo must follow the building code so that all RC buildings will be equally resilient to atsunami. Lastly, areas exposed to tsunami disasters should have RC structures instead of timber.
Keywords: Fragility function, tsunami, Hunga Tonga-Hunga Ha'apai, structural damages
1. INTRODUCTION
Tonga is vulnerable to tsunami disasters due to its geographical location and geological formation. It is
in a subduction region where the level of seismicity is high, with 22 active volcanoes. Seismic andvolcanic activities are two of the three leading causes of a tsunami. The last tsunami to hit Tonga wasin 2009, caused by a tsunamigenic earthquake known as the Samoa 2009 earthquake and tsunami. The
tsunami swept the island of Niuatoputapu, leaving people homeless. On 15 January 2022, at 5:15 pm
local time, the HTHH eruption explosion reached its maximum strength, equivalent to around ten
megatons of TNT (National Emergency Management Office, 2022). The grounds and buildings wereshaking, which was also felt and heard in other South Pacific islands (World Bank & GFDRR, 2022).
It was followed by a tsunami warning, which immediately triggered a mass evacuation of thecommunities of Tonga. Nevertheless, tsunami waves with a height of up to 15 meters swept away theislands of Mango and Fonoi and other coastal communities, leading to the misplacing of the people.
The tsunami affected nearby Pacific countries and distant shores such as Japan, California, Mexico and
1Ministry of Lands and Natural Resources, Tonga.
Japan International Cooperation Agency.
3
Department of Structural Engineering, Building Research Institute.
2

1Peru (Ramírez-Herrera et al., 2022). Such damages caused by the tsunami in Tonga lead to the main
objective of this study: to detect the vulnerable structural systems using fragility curves for futuredisaster mitigation planning. Fragility curves were introduced as one of the main tools for assessing
damage and loss from natural disasters. For example, it is defined as the probability of reaching or
exceeding a specific damage state under inundation depth and other parameters for a tsunami. The
curves can be used as a decision-making tool for pre- and post-disasters.
2. METHODOLOGY
2.1. Research target areas
Two main areas were chosen from the main island, Tongatapu, as the study areas. First is the Hihifo
area, which covers the three affected villages: 'Ahau, Kanokupolu and Ha'atafu. HT-HH is about 53 km
away from the north of Hihifo. The affected areas were mainly resorts and residential areas. There arealso church buildings, church halls,
city halls, and primary schools withinthese residential areas. The Hihifo
area has higher elevations on thewestern side, where the tsunami
wave came from (Figure 1).
The second study areais the Nuku'alofa area which includes
Kolomotu'a, Fasi, and Tukutonga.
These are also residential areas withsimilar buildings to Hihifo. However,
the affected area of Kolomotu'a
village has some motels andrestaurants on the waterfront, whichwere not affected by the tsunami.
Figure 1. A map showing the inundation area of Tongatapu
The affected areas of Nuku'alofa areisland (light pink shade), the study areas (black oval),almost flat throughout, with a bit
contour lines showing elevations (grey lines), and thelower
toward the northern side,
direction of incoming tsunami waves (red arrows).
where the wave came from (Figure 1).
However, Nuku'alofa has a rock revetment shoreline protection which may intervene in the wave's
energy. HT-HH is about 68 km away from the north-northwest of Nuku'alofa.
2.2. Data
The inundation data for the two study areas were from a field survey conducted by the Ministry ofLands and Natural Resources (MLNR). The Hihifo area had an inundation depth of up to 8.5 meters,
while Nuku'alofa had an inundation depth of up to 1.6 meters. The inundation depth was measured fromthe local ground level.
On the other hand, the Ministry of Infrastructure (MOI) and disaster-related ministries
conducted an initial damage assessment, which collected damaged data used in this study. The data did
not have the location and the damaged building type, except for a few that MLNR collected. Therefore,
I went out to the field and completed data collection independently. I used the QField application tocollect data on the field and then analyzed it with the QGIS. The spatial distribution of damagedbuildings in the Hihifo area showed that the survived buildings were away from the shoreline of its
northern side (Figure 2A). In contrast, the damaged buildings were distributed along the shoreline in
the Nuku'alofa area (Figure 2B).
The structures considered by the MOI as destroyed or washouts and severely damagedbuildings were classified in this study as destroyed buildings. The destroyed buildings are defined inthis study as structural damages that are not repairable. Structures with moderate and minor damage
and buildings that were not damaged were classified as survived. Survived buildings were then defined2

in this study
as damaged
houses thatwererepairable
and houses
that were
not affected
at all. There
were
85
destroyed
Figure 2. Spatial distribution of damaged buildings in (A) Hihifo and (B) Nuku'alofabuildings
areas. It shows the destroyed buildings (white dots) and survived buildings (greywith 112 indots).
the Hihifo
area and 27 destroyed buildings with 237 survived buildings in the Nuku'alofa area.
2.3. Analysis procedure
There are two approaches used in trying to attain the fragility curves for the study area. The first method
is a linear regression analysis that follows the equation used by Koshimura et al. (2009b), as shown in
Eq. (1).

ln 𝑥 − 𝜆𝑃𝐷 (𝑥) = Φ [
],
𝜉

(1)

where 𝑥 represents the inundation depth, while 𝜆 and 𝜉 represent the mean and standard deviation (SD)of ln 𝑥 respectively, and Φ is the cumulative log-normal distribution function. However, this procedure
was not used because the inundation depth ranges with damage probabilities of 0 or 1 were notconsidered in determining the fragility function. Therefore, I think the data is not well represented.
The second method used for calculating the fragility function is the Gird Search methodsuggested by Dr Yokoi. Whereby the simulated damage probability for every value of the inundation
depth (x) was calculated using the log-normal cumulative distribution function, and the hyperparameters
mean (ln x) and SD (ln x). Then the misfit function was estimated using Eq. (2) for all available x, where
ODP is the observed damage probability, and the CSDP is the calculated simulated damage probability.
This procedure was repeated for all pairs of the hyperparameters within the given search ranges.

𝑀𝑖𝑠𝑓𝑖𝑡 𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛 = (𝑂𝐷𝑃 − 𝐶𝑆𝐷𝑃)2
Table 1: Hyperparameters for fragility curves of each area and building types

Area

Mean (ln x)

SD (ln x)

Hihifo – all building types

1.08

0.405

Hihifo – timber structures

0.78

0.21

Hihifo – RC with masonry

1.18

0.40

Nuku'alofa – all building types

0.83

0.38

Nuku’alofa – timber structures

0.67

0.32

infill structures

mean (ln x) and the SD (ln x) that gives this minimum.

3(2)
The search ranges
were modified until I
found a minimum of
the misfit. Also, thesearch ranges wereshrunkuntil
Iobtained the mean(ln x) and SD (ln x)
valueswith
sufficient resolution,
as summarised inTable 1. The best fit,
the fragility curve,
for each study area
was given by the3. RESULTS AND DISCUSSION
The data was categorized into ranges of inundation depth with an interval of 0.5 meters (Figure 3). The
midpoints of the inundation depth ranges are used in drawing the histograms. After around 3.75 metersof inundation depth, all building types in the Hihifo area were destroyed. However, in the Nuku'alofa
area, the inundation depth did not reach any point where such destruction would occur.

Figure 3. Histograms of the number of survived (green) and destroyed (red)buildings in each inundation depth range in the tsunami inundated area of
Hihifo (left) and Nuku'alofa (right).

Figure 4. Fragility curves (orange curves) and the observed damage
probability (blue dots) for (a) all types of buildings for Hihifo, (b) all typesof buildings for Nuku'alofa, (c) timber buildings for Hihifo, (d) timberbuildings for Nuku'alofa, (e) RC structures with masonry infill in Hihifo.
In comparing the fragility curves obtained, the buildings of the Hihifo area (Figure 4a) arestronger than those of the Nuku'alofa area (Figure 4b). Though both the fragility curves start rising after
one meter, indicating damages start to occur when inundation depth is above one meter, the fragility
curve for Hihifo's all types of buildings rises gently after one meter. In contrast, the fragility curve for
Nuku'alofa's all types of buildings rises steeply after one meter. It means that the same degree of4

Damage probability

Damage probability

Damage probability

destruction occurred in Nuku'alofa at a higher inundation depth also occurred in Hihifo at a lower
inundation
depth,
indicating
theHihifo - all
1.2
vulnerability of structures in Nuku'alofa.
building
1
types
Comparing these fragility curves with the
0.8
Nuku'alofa existing fragility curves of Banda Aceh,all building
0.6
Indonesia and Dichato, Chile (Figure 5),
types
0.4
the structures of my study areas are more
Dichato0.2
resilient than Dichato's. At the same time,0
Hihifo's buildings are similar to Banda
Banda Aceh
0
5
10
-0.2
Aceh's, while Nuku'alofa's buildings are
Inundation depth (m)more vulnerable than Banda Aceh's.
Moreover, comparing the
Figure 5. Comparison of tsunami fragility curves forfragility curves for timber buildings, the different types of buildings. It shows Hihifo's (orange)
fragility of timber buildings in Hihifo and Nuku'alofa's (green) all types of buildings; wood,(Figure 4c) began after 1.5 meters oftimber, and RC buildings in Banda Aceh, Indonesia
inundation depth, while Nuku'alofa (blue); wood, masonry, and mixed buildings in(Figure 4d) began after one meter. Dichato, Chile (red) (Mas et al., 2012).
Nuku'alofa's fragility curve is a bit steeper
than Hihifo's (Figure 6), indicating that the Nuku'alofa area has more destroyed timber buildings thanthose in Hihifo at the same inundation depth. For example, the timber buildings of Hihifo will be 60%
destroyed at 2.3 meters, while 60% of
1.2
Nuku'alofa's timber buildings will be
Nuku'alofa 1
destroyed at 2.1 meters. Hence a slighttimberdifference was observed in the curves.
0.8
buildings
The starting inundation depth of
0.6
Okushiri
destruction shows that the timber
0.4
buildings of Hihifo are somehow strong
0.2
enough to withstand tsunami to some
Hihifo extent because, in other countries such as0
timber0
5
10Japan, the timber structures are-0.2
buildings
completely
destroyedwhentheInundation depth (m)inundation
depth
ishigherthan
twoFigure 6. Comparison of tsunami fragility curves formeters (Koshimura et al., 2009a). Timber
timber buildings of Hihifo (blue) and Nuku'alofabuildings in Tonga, both Hihifo and(orange) with wood buildings in Okushiri, Japan (green)
Nuku'alofa, are designed to withstand the(Mas et al., 2012).
impacts of tropical cyclones, andtherefore, they are resilient to tsunamis to some extent. Therefore, the timber buildings in my study
areas are stronger than those on
Hihifo - RC
1.2
Okushiri Island, Japan (Figure
with masonry
6).
1
infill buildings
Furthermore,aPhang Nga
0.8close look at the building typesof Hihifo shows that the RC
0.6
Phuketstructures with masonry infill
0.4
are stronger than the timber
structures. The pattern of theAmerican0.2
fragility curves shows thisSamoa
0
(Figure 7). The fragility curve
Hihifo - timber
0
5
10of the RC with masonry infill
buildings-0.2
structures rises gently after 1.5
Inundation depth (m)meters, while the timber
Figure 7. Comparison of tsunami fragility curves developed forstructures' fragility curve rises RC with masonry infill structures (orange) and timber buildings
steeply. However, comparing (blue) of Hihifo with those of RC buildings in Phang Nga (grey)
the fragility curves of RC with and Phuket (red), Indonesia and American Samoa (green) (Mas etmasonry infill structures ofal., 2012).

5

Hihifo with that of RC structures of Phang Ga and Phuket, Thailand, the RC structures of Hihifo arestronger (Figure 7). On the other hand, the fragility function of RC buildings in American Samoa isstronger than that of the Hihifo area when looking at higher inundation depth (Figure 7). Nevertheless,at inundation depths lower than three meters, the Hihifo RC structures are stronger than American
Samoa's. It can also be observed in the fragility curve for RC structures with masonry infill of Hihifo(Figure 4e) that the damage probability varies, unlike Hihifo's timber structures (Figure 4c) where thedamage probability is uniform.
4. CONCLUSIONS
From comparing the fragility curves of all building types of Hihifo and Nuku'alofa, the structural systemof the Nuku'alofa area needs to be surveyed and analyzed for disaster mitigation purposes. Since no RC
with masonry infill structure was destroyed in Nuku'alofa, we concluded that the timber buildings are
too vulnerable as they start to be destroyed when the inundation depth is higher than one meter.
Therefore, the timber structural system of Nuku'alofa needs to be assessed in detail to address thevulnerability of structures to tsunami hazards.
However, the observed damage probability of timber structures shows a uniform pattern
while the RC structures show variation in the damage probability. We concluded that this variation isdue to some RC structures with masonry infill not following the building code while the others do.
Therefore, there is a need for all RC buildings to follow the building code and for the existing ones tobe retrofitted so that all RC buildings will have the similar strength to endure tsunamis.
Since RC structures with masonry infill of Hihifo are stronger than timber buildings, werecommended that areas exposed to tsunamis build RC with masonry infill structures instead of timber
structures. RC buildings are more resilient to tsunamis than timber buildings. However, we can liaise
with American Samoa on what makes the differences in fragility function of RC structures at higher
inundation depth to modify the RC structures of Hihifo and Tonga to be more resilient to 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 express my sincere gratitude to my supervisors Dr. Tatsuya Azuhata and Dr. Toshiaki
Yokoi for their valuable support and experience, which helped me complete my research successfully.
I acknowledge the staff of MLNR and MOI for allowing me to use their data. Special thanks to myhusband and children for assisting me during my data collection period. Thanks also to the residents of
my study areas for helping me to complete my dataset. You are highly appreciated.
REFERENCES
Koshimura, S., Namegaya, Y., & Yanagisawa, H. (2009a). Tsunami Fragility-A New Measure to
Identify Tsunami Damage, Journal of Disaster Research, 4(6), 479 – 488.
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Indonesia.
CoastalEngineering
Journal,51(3),
243–273,https://doi.org/10.1142/S0578563409002004.
Mas, E., Koshimura, S., Suppasri, A., Matsuoka, M., Matsuyama, M., Yoshii, T., ... & Imamura, F.
(2012). Developing Tsunami fragility curves using remote sensing and survey data of the 2010
Chilean Tsunami in Dichato. Natural Hazards and Earth System Sciences, 12(8), 2689-2697.
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Ha'apai volcanic eruption and Tonga tsunami (HTHH disaster) January 2022.
Ramírez-Herrera, M. T., Coca, O., & Vargas-Espinosa, V. (2022). Tsunami effects on the Coast of
Mexico by the Hunga Tonga-Hunga Ha'apai volcano eruption, Tonga. Pure and applied geophysics,
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