Journal of Asian Earth Sciences 36 (2009) 93–97

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Journal of Asian Earth Sciences

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Tsunami hazard from the subduction Megathrust of the South China Sea:Part II. Hydrodynamic modeling and possible impact on Singapore

Zhenhua Huang a,*, Tso-Ren Wu b, Soon Keat Tan a, Kusnowidjaja Megawati a, Felicia Shaw c, Xiaozhen Liu c,Tso-Chien Pan a,c

a School of Civil and Environmental Engineering, Nanyang Technological University, Block N1, 50 Nanyang Avenue, 639798, Singaporeb Graduate Institute of Hydrological and Oceanic Sciences, National Central University, Taichung, Taiwan, Republic of Chinac Protective Technology Research Center, School of Civil and Environmental Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore

a r t i c l e i n f o a b s t r a c t

Article history:Received 8 May 2008Received in revised form 1 August 2008Accepted 21 August 2008

Keywords:Tsunami wavesSouth China SeaTsunami warning system

1367-9120/$ - see front matter � 2008 Elsevier Ltd. Adoi:10.1016/j.jseaes.2008.08.007

* Corresponding author.E-mail address: zhhuang@ntu.edu.sg (Z. Huang).

USGS has identified certain section of the Manila (Luzon) trench as a high-risk earthquake zone. This zoneis where the Eurasian plate is actively subducting eastward underneath the Luzon volcanic arc on thePhilippine Sea plate. An earthquake of magnitude 9.0 could be generated based on the worst case scenariorupture of Manila Trench. In this paper, the possible impact of this worst case scenario rupture on Singa-pore is investigated using a numerical model. It is found that (1) it takes about 12 h for the tsunami wavesgenerated at Manila Trench to arrive at Singapore coastal waters; (2) the wave period of the tsunamiwave, i.e., time interval between two peaks, is about 5 h; (3) the maximum water level rise in Singaporewater is about 0.8 m; and (4) the maximum velocity associated with the tsunami waves is about 0.5 m/s,which is not likely to have significant impact on the port operations in Singapore.

� 2008 Elsevier Ltd. All rights reserved.

1. Introduction

Coastal areas and shorelines are exposed to potentially damag-ing effects from severe environmental conditions associated withlong waves, such as tsunamis and storm surges, which may leadto wave run-up and landward inundation. After the devastating In-dian Ocean tsunami in 2004 (see Titov et al. (2005), Choi et al.(2005), Narayan et al. (2005), for example), tsunami forecast andmitigation have been implemented by many coastal nations inand around the Indian and Pacific Oceans. Economic and long-termsocial impacts of tsunamis, as shown in the 2004 Asian tsunami,have been devastating (see Yalciner et al. (2005)). The goal of Oper-ational Tsunami Prediction and Assessment System (OTPAS) in Sin-gapore is to build Singapore’s capabilities in earthquake andtsunami modeling and forecasting by integrating cutting-edge sci-entific knowledge, software, equipment, monitoring stations, infra-structure and telecommunications in an automatic/semi-automatic warning system for Singapore. Recently USGS has iden-tified the Manila (Luzon) trench as a high-risk earthquake zone,where the Eurasian plate is actively subducting eastward under-neath the Luzon volcanic arc on the Philippine Sea plate. This sub-duction zone can also rupture and generate large tsunamis in thefuture that will have significant impacts on the countries in theSouth China Sea region. The rupture characterization of ManilaTrench and the resulting tsunami waves in South China Sea are re-

ll rights reserved.

ported in Megawati et al. (2009). In this paper, we will focus on thenumerical modeling of tsunami waves and the possible impact toSingapore.

The tsunami-induced devastation at any particular location is afunction of the velocity, acceleration, and the elevation of water levelas tsunami waves interact with natural and man-made coastal struc-tures. The economic costs of strengthening local infrastructures andevacuating coastal areas are very high. More importantly, severe tsu-namis and storm surges can cause significant losses in human lives.Singapore also has in its southern coastline, an estuarine reservoir –the Marina Bay, which is isolated from the sea by a tidal barrage withgates. Large waves overtopping the tidal barrage/gate could also setup other shock waves which could propagate deeper inland. The im-pact of the return waves could be equally devastating. Furthermore,the current associated with the tsunami waves could cause collisionof ships mooring in the harbor. In this study, we will focus on the pos-sible impact of the tsunami waves generated by the worst case sce-nario rupture at Manila Trench (see Megawati et al. (2009)), whichcould trigger an earthquake of magnitude 9.0. A clear understandingof the behavior of tsunami waves in Singapore coastal water is crit-ical in developing appropriate warning system and evacuation strat-egies for Singapore.

Although field measurements of run-up of several recenttsunamis exist, they are insufficient because of the nature of after-the-event field surveys. Very little information about temporal vari-ations can be obtained (except tide gauge data) and the data are oftenextremely spatially sparse. Furthermore, the source of tsunami gen-eration cannot be accurately specified, since any information in deep

94 Z. Huang et al. / Journal of Asian Earth Sciences 36 (2009) 93–97

water is difficult to obtain. Physical experimentation is valuable butit is costly and slow, and requires high-resolution, real-time captureof multidimensional data. It is also ephemeral, in that there is onlyone brief opportunity to capture suitable data for a particular run.Numerical experiments offer an attractive alternative. An excellentrecent review on tsunami simulation can be found in Gisler (2008).One recent experimental study of non-breaking tsunami waverun-up on a plan beach is reported in Gedik et al. (2005). One break-ing criterion for solitary waves on slopes was given by Grilli et al.(1997). A good discussion on breaking tsunami run-up was providedby Heller et al. (2005) and Li and Raichlen (2003). In this paper, weshall use a numerical model to investigate the characteristics ofthe tsunami waves in Singapore coastal water.

The outline of this paper is as follows: Section 2 briefly intro-duces the numerical model for studying tsunami waves in Singa-pore coastal water; Section 3 discusses the compilation of thegeometrical data for the study; Section 4 presents and discussesthe main results, and finally Section 5 summaries the main conclu-sions from this study.

2. Numerical model

Recently, as a result of a strong effort by the tsunami commu-nity, several two- and three-dimensional numerical models havebeen developed to study the generation and propagation of tsu-nami waves, and to quantify the interactions of tsunamis withshorelines. Example models include MOST described by Titovet al. (1997) and Tang et al. (2006), AnuGA described by Nielsenet al. (2005), COMCOT (Cornell Multi-grid Coupled Tsunami Model)described by COMCOT User Manual (2007) and Wang and Liu(2006), Tsunami-N2 developed at the Tohoku University, Japan.

The numerical model adopted in this study is COMCOT, whichhas been widely used to investigate tsunami events, such as the1992 Flores Islands (Indonesia) tsunami (Liu et al., 1994; Liuet al., 1995), the 2003 Algeria Tsunami (Wang and Liu, 2005) andmore recently the 2004 Indian Ocean tsunami (Wang and Liu,2006). With the flexible nested grids setup, we are able to performsimulations from near-coast regions to far-field regions. In thisstudy, the wave breaking is not considered, thus the energy dissi-pation comes solely from the bottom friction.

COMCOT adopts the leap-frog time-differencing scheme tosolve the following nonlinear shallow water equations on stag-gered grids

ogotþ oP

oxþ oQ

oy¼ 0 ð2:1Þ

oPotþ o

oxP2

H

!þ o

oyPQH

� �� fQ þ gH

ogoxþ sxH ¼ 0 ð2:2Þ

oQotþ o

oxPQH

� �þ o

oyQ 2

H

!þ fP þ gH

ogoyþ syH ¼ 0 ð2:3Þ

Table 1Grid information (corresponding to Fig. 1)

Grid 0 Grid A

Grid cells (lon. � lat.) 1075 � 1275 520 � 360Lat. Scope (Deg) 97.0106–139.9706 102.6406–1Lon. Scope (Deg) �9.9743 to 40.9857 0.1757–7.35Grid size (min.) 2.4 1.2Parent grid (None) Grid 0Grid ratio (None) 2Time step (in sec) 2 1Coordinates Spherical SphericalGoverning equation Linear SWE Linear SWEManning coefficient 0 0

where P and Q are fluxes in x and y directions, respectively. Theinstantaneous water depth is H = h + g, with g being the surface dis-placement and h being the still water depth. In Eqs. (2.2),(2.3), g isthe gravitational acceleration, and f is the Coriolis parameterdescribing the effects of earth rotation on wave propagation. For gi-ven Manning’s coefficient n, the bottom shear stresses, sx and sy,can be modeled by

sx ¼gn2

H10=3 PffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP2 þ Q 2

q; ð2:4Þ

sy ¼gn2

H10=3 QffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiP2 þ Q 2

qð2:5Þ

On open boundaries, radiation boundary conditions are used toeliminate the reflection from artificial boundaries.

In this paper we are interested in the numerical simulation ofthe tsunami waves excited by a hypothetical worst case scenarioearthquake and the impact to the coastal area of Singapore. Thesimulation area covers the domain from Java, Indonesia, to Japan.In order to calculate the tsunami propagation from Manila Trenchto Singapore coastal water, four nested grids are adopted. The gridresolution varies from 2.5 to 0.06 min from Grid 0 to Grid C. Thenumber of grid cells varies from 1075 � 1275 for Grid 0 to516 � 356 for Grid C. The total number of grid cells is 1,924,346.In Grids 0, A and B where water depth is of O (1000 m) and thewave height is of O (1–10 m), the nonlinear terms and the frictionterms in Eqs. (2.2) and (2.3) can be ignored safely based on the fol-lowing simple order of magnitude estimate

oPot

�o

oxP2

H

!� 1;

oPot

�o

oyPQH

� �� 1 ð2:6Þ

oQot

�o

oxPQH

� �� 1;

oQot

�o

oyQ 2

H

!� 1 ð2:7Þ

oPot

�sxH� 1;

oQot

�syH� 1 ð2:8Þ

In this study, linear shallow wave equations are solved in sphericalcoordinates on Grid 0, Grid A, and Grid B, while the nonlinear shal-low water equations are solved in Cartesian coordinates on Grid C.The detailed grid information can be found in Table 1. Nonlinearmodel is taken into account on Grid C with the bottom friction op-tion being turned on. The Manning’s relative roughness coefficientused in Grid C is 0.013 (Table 1) (See Fig. 1).

The rupture model for the worse case scenario has been dis-cussed in Megawati et al. (2009), where the earthquake faultparameter values used in the present simulation are listed in Table1. The earthquake magnitude for this worst case scenario isMw = 9.0. The initial surface profile for this worst case scenario isshown in Fig. 2. We used Okada (1985)’s model to calculate the ini-tial free surface near the source. The maximum free surface eleva-tion can be more than 15 m for the worst case scenario rupture atManila Trench. This paper will focus on the tsunami waves in Sin-

Grid B Grid C

515 � 355 516 � 35613.0206 103.4526–105.5086 103.6031–104.118157 0.9877–2.4037 1.1382–1.4932

0.24 0.06Grid A Grid B5 40.2 0.05Spherical CartesianLinear SWE Nonlinear SWE0 0.013

Fig. 1. Region of interests and grids used in simulations. Top figure – Grid 0 andGrid A; bottom figure – Grid B and Grid C.

Fig. 2. Initial surface elevation.

Z. Huang et al. / Journal of Asian Earth Sciences 36 (2009) 93–97 95

gapore coastal waters, including the arrival time, period betweentwo peaks, maximum wave height distribution, and the velocitydistribution in Singapore water.

3. Bathymetrical and topographical data

Bathymetrical data for the region outside of Singapore was de-rived from a public archive, ETOPO2, which is freely available fromNational Geophysical Data Center (NGDC), National Oceanic Atmo-spheric Administration (NOAA). ETOPO2 data has visible artifactsdue to imperfect data integration. It is necessary to smooth thebottom bathymetrical data by removing rectangular artifacts sothat they would not cause anomalous wave reflections. The bathy-metrical data in Singapore water was complied from local surveydata. Fig. 3 shows the bottom bathymetry in Singapore water aftersmoothing.

For further investigation, 3 virtual gauges are deployed in thestudy area. Gauge 1 is located near Marina Bay and Sentosa resort;Gauge 2 is located close to Johor Strait; and Gauge 3 is located closeto Changi Airport, as shown in Fig. 3.

4. Results and discussion

Fig. 4 shows the time history of water levels recorded at threevirtual wave gages shown in Fig. 3. The time zero denotes the in-stant when the rupture at Manila Trench occurs. It can be seen thatit takes about 12 h for the tsunami waves to arrive at Singapore

after traveling over a distance of 8000 km. This gives Singapore en-ough time to issue a warning and prepare evacuation if necessary.The maximum water level rise for the worst case scenario studiedhere is about 0.8 m at Marina Bay, about 0.7 m at both Johor Straitand Changi Airport. The period between two adjacent tsunamiwave peaks is about 5 h, which is much longer than the period oftypical tsunami waves. In a sense this is also good news for Singa-pore as it allows affected areas to have enough time to prepare forthe subsequent attacks. Note that before the first peak arrives thecoastal water does not retreat first. It takes about 1.5 h for thewater level to reach the first peak. The tsunami wave impact canlast more than 2 days, which could have adverse impact on Singa-pore. It should be mentioned that the effects of tides and theroughness related to coastal structures are not considered in oursimulation. The local water level rise and the tsunami-inducedinundation are sensitively dependent on the detailed local bathym-etry and topography, which are not available now.

The map of maximum water level rise is shown in Fig. 5, whichreveals the information on the tsunami energy distribution andmagnitude. This figure shows that the maximum water level rise40 h after the worst case scenario rupture of Manila Trench. In gen-eral, the water level rise in the area along the Singapore coast var-ies from 0.3 to 0.8 m. Near Jurong Island the maximum water levelrise is about 0.6 m, while the maximum water level rise near Mar-ina Bay could be as large as about 0.8 m. The largest water level risein Johor Strait could go up to 0.7 m, because of the Johor causewaywhich stops the water and causes the water to pile up in front ofthe dam. Most coastal structures along the Singapore coast are

Fig. 3. Local bathymetry and topography used in the simulation (Grid C).

Fig. 4. Free-surface elevation.The horizontal axis is the time in second.

Fig. 5. Maximum free-surface elevation (40 h after the rupture at Manila Trench).

Fig. 6. Velocity distribution in Singapore coastal water.

96 Z. Huang et al. / Journal of Asian Earth Sciences 36 (2009) 93–97

designed to resist a water level rise of 1.5 m, thus major floodingdue to the tsunami waves is not expected in Singapore.

In addition to the damage caused by the large wave amplitude,which could cause flooding and destruction of coastal structures,the current induced by the tsunami waves could also cause dam-ages to certain extent. The current associated with tsunami waves

could cause ships to break away from their moorings, resulting incollision among ships, and damage to quay cranes and docks. Thosedamages could cause the port operations to be suspended andships in the harbors to move out to the open seas. To assess thepossible impact of the current associated with the worst case sce-nario tsunami waves, we examine the velocity distribution in Sin-gapore water.

The depth-averaged mean velocity components, u and t, can becalculated by the two flux components, P and Q

u ¼ PH; v ¼ Q

Hð4:1Þ

where H is the instantaneous water depth. The vertical structure ofthe current system can not be resolved in the present model.

Fig. 6 shows the velocity distribution in Singapore coastal water13.9 h after the rupture of Manila Trench. It can be seen that themaximum velocity associated with the tsunami waves is about0.5 m/s, which occurs in Johor Strait and in some shallower partsof Singapore waters. In waters near Marina Bay and Jurong Island,the maximum velocity is between 0.2 and 0.25 m/s. Since the typ-ical tidal current in Singapore water is about 1 m/s, it is expectedthat the current velocity associated with the tsunami waves islikely to have only minimum impact on the port operations in Sin-gapore. The possible impact of the tsunami currents on shipsmooring in the coastal waters where the velocity is about 0.5 m/s, however, needs further studies.

The period between the first two peaks in Singapore water isabout 5 h, which is longer than what we would expect for typicaltsunami waves. To investigate this interesting phenomenon, fourvirtual wave gauges (S01–S04) are deployed along the path ofwave propagation from Manila trench to Singapore. The locationsof these virtual wave gages are shown in Fig. 7. S01 and S02 arein the region of Grid 0, while S03 is in the region of Grid A. GageS04 is in the region of Grid B.

Fig. 8 shows the time-history of the surface elevation for eachvirtual gauge shown in Fig. 7. Wave components of period less than1 h can be observed in the region close to the rapture zone. Fromthe initial surface elevation, it can be estimated that the initial tsu-nami would have a period of O(30) min. As waves propagate awayfrom Manila Trench, tsunami waves of period less than 1 h travelover the vast reaches of relatively deep ocean. Starting from thegauge S03, tsunami waves enter the shallow water area, and shortwaves start merging to form a series of waves of longer period. Thewave period changes from less than 1 h at the gauge S01 to about5 h at the gauge S04. Currently there is no definite explanation tothe long wave-period in shallower water found in this study. When

Fig. 7. Locations of virtual gauges deployed in South China Sea.

Fig. 8. Wave records along the path of tsunami wave propagation from the sourceto Singapore.

Z. Huang et al. / Journal of Asian Earth Sciences 36 (2009) 93–97 97

waves enter the shallower water, nonlinear wave-wave interac-tions become important. Two possible hypotheses are given here.It is well-known that the nonlinear wave-wave interactions amongthe wave components in an irregular sea may generate the so-called frequency down-shift phenomena (see Hara and Mei(1991)), for which wave energy transfers from short waves to longwaves. It is possible that the long wave-period found in our simu-lations is related to this frequency down-shift phenomenon. An-other possibility is related to the wave interactions with thevariation in bottom bathymetry. It has been long realized thatwhen the bottom has a periodic variation the resonant interactionsbetween surface waves and the periodic bottom (Bragg resonance)will result in a strong reflection for certain wave components (seeMei et al. (1988)). It is also possible that the Bragg resonance mayhave contributed to filtering out the short period waves.

5. Conclusions

In this study, the worse case scenario (earthquake magnitudeMw = 9.0 at Manila Trench) is studied numerically. It takes about12 h for the first peak of the tsunami waves to travel a distanceof 8000 km from Manila Trench to Singapore. This indicates thatSingapore has plenty of time to be prepared for the tsunami gener-ated by the rupture of Manila Trench. The maximum water level

rise recorded by the virtual wave gauges is 0.8 m in Singaporewater for the worst case scenario reported herein. The wave period(the time interval between two wave peaks) is about 5 h, and ittakes about 1.5–2 h for the water level to reach the first peak.The maximum water particle velocity is 0.5 m/s in Singaporewater. It may be concluded that major damage related to the tsu-nami event due to the rupture of Manila Trench is unlikely.

Acknowledgement

The authors are grateful to Professor Philip L.-F. Liu of CornellUniversity, USA, for providing the latest version of COMCOT soft-ware package and suggestions on monitoring the wave period evo-lution along the path of wave propagation. Two anonymousreviewers are acknowledged for their constructive comments,which have greatly improved the quality of this paper. This workis funded by the National Environmental Agency of Singapore.The opinions described in this paper do not necessarily reflectthe standing of the funding agency.

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