Tsunami-induced coastal change: scenario studies for Painan, West Sumatra, Indonesia
© The Society of Geomagnetism and Earth, Planetary and Space Sciences (SGEPSS); The Seismological Society of Japan; The Volcanological Society of Japan; The Geodetic Society of Japan; The Japanese Society for Planetary Sciences; TERRAPUB. 2012
Received: 31 October 2010
Accepted: 2 August 2011
Published: 24 October 2012
There exists a high probability of a great earthquake rupture along the subduction megathrust under the Mentawai Islands of West Sumatra in the near future. Six rupture models were used to assess the tsunami inundation and the accompanying sediment movement in Painan, West Sumatra, Indonesia. According to a worst scenario, the potential tsunami might hit the coast of Painan about 26 minutes after the rupture and the entire city could be inundated with a maximum inundation depth of about 7 m. Severe erosion may also occur in the near-shore region. Two scenarios, one scenario with a positive leading wave and the other with a negative leading wave, were selected to simulate the tsunami-induced morphological changes. A positive leading wave would cause severe erosion in the shoreline area and a large sandbar in the offshore area adjacent to the shoreline; a small amount of sediment could be deposited in the city area; a negative leading wave could cause moderate erosion in the further offshore area due to the strong retreating wave front, an offshore sandbar could form in the bay area, while no noticeable large area of sand deposit could be found in the city area. The difference in the erosion and deposition patterns between these two scenarios provides very helpful information in the investigation of historical tsunamis through tsunami deposits.
Key wordsCoastal erosion tsunami inundation shoreline changes sediment transport West Sumatra megath-rust
The Sunda megathrust is located at a convergent plate boundary where it forms the interface between the overriding Eurasian plate and the subducting Indo-Australian plate. Several large sections of the megathrust have ruptured sequentially in the past decade, causing a series of earthquakes along the western coast of Sumatra: the largest of these failures is the giant Aceh-Andaman earthquake of Mw 9.15 in 2004 caused by a 1600-km long rupture along the magathrust (Sieh, 2007); the great Nias earthquake of March 28, 2005 ruptured another segment south to the Aceh earthquake segment. These rapid failures have raised great concern about the unbroken Mentawai segment(Aydan, 2008; McCloskey et al., 2005; Nalbant et al., 2005; Natawidjaja et al., 2006; Natawidjaja and Triyoso, 2007; Sieh, 2007). According to the studies of McCloskey et al. (2005) and Nalbant et al. (2005), the rupture of adjoining 1600- and 300-km sections of the Sunda megathrust in December 2004 and March 2005 has increased the stresses on the megathrust immediately to the south, under the Batu and Mentawai islands. The increased stresses have significantly boosted the possibility of earthquake and tsunami hazard in West Sumatra. Historically, two great earthquakes of 1797 and 1833 have happened in this 700-kilometer-long unbroken Mentawai segment (Natawidjaja et al., 2006). Geodetic and paleogeodetic measurements have revealed that the slip deficit accumulated in this area has already exceeded the slip occurred during the 1797 earthquake and is slowly reaching the slip occurred during the 1833 earthquake (Chlieh et al., 2008). This information indicates that the unbroken Mentawai segment may already be advanced in the seismic supercycle, which has a period about 200 years according to palaeoseismologic studies (Zachariasen et al., 1999; McCloskey et al., 2005; Sieh et al., 2008). The imminent hazard in this area is vindicated by the megathrust rupture of September 2007. However, only a small amount of the accumulated potential slip has been relieved by the 2007 earthquake and its aftershocks (Aydan, 2008; Konca et al., 2008); larger earthquakes approaching the size of 2004 Aceh-Andaman earthquake might be possible in the near future (Sieh et al., 2008; Natawidjaja et al., 2009).
As the Mentawai section of the Sunda megathrust is very close to the coast of West Sumatra, potential ruptures and subsequently triggered tsunamis may pose a significant threat to the people and property in the nearby cities. Several rupture models for the unbroken Mentawai segment have been proposed (Tobita, 2007; Aydan, 2008; Chlieh et al., 2008; Natawidjaja et al., 2009) and used by some researchers (Borrero et al., 2006; McCloskey et al., 2008; Taubenbock et al., 2009; Muhari et al., 2010) in an attempt to assess the tsunami threat to the major cities along thecoast of western Sumatra, including Padang, Bengkulu and Painan. Tsunami arrival time, tsunami height and inundation map were presented for these proposed scenarios. The results of these studies indicate that the maximum tsunami height along the coast of Padang and Painan could reach 5– 10 m (Borrero et al., 2006; McCloskey et al., 2008; Muhari et al., 2010). We noticed that the tsunami-induced sediment transport was not considered in all these studies. However, tsunami waves with the height of 5–10 m will be inevitably accompanied by very high flow velocities when they penetrate inland (Imamura et al., 2001; Matsutomi et al., 2006; Goto et al., 2007), which will undoubtedly produce high bed shear stresses and sediment movements over large areas, resulting in beach erosion, scouring around coastal structures, and widespread deposition in inland areas (Gelfenbaum and Jaffe, 2003; Srinivasalu et al., 2007; Pari et al., 2008; Meilianda et al., 2010; Paris et al., 2010). Relative to other tsunami behaviors, sediment transport is one of the poorest understood characteristics as it is almost impossible to conduct detailed real-time measurements during tsunami events.
Understanding tsunami-induced sediment movement is also extremely important for tsunami geologists who have made significant effort to estimate the tsunami heights, flow depths and velocities by establishing qualitative relationships between tsunami deposits and tsunami hydrodynamic characteristics (Jaffe and Gelfenbuam, 2007; Moore et al., 2007; Morton et al., 2008; Spiske et al., 2010). The information derived by inverse modeling from paleo-tsunami deposits, can further help us understand tsunami sources and attendant tectonic character of a particular region in some detail (Bourgeois, 2009; Martin et al., 2008; Nelson et al., 2006). However, the inverse modeling faces great challenges since sediment movement is highly depended on tsunami wave form, bathymetry and topography near shoreline and sediment sources. Forward numerical modeling of tsunami-induced sediment transport could provide quantitative information in terms of tsunami height, flow velocity, and tsunami deposit characteristics to help understand the complex patterns of erosion and sedimentation process in both onshore and seaward directions (Goto and Imamura, 2007).
2. Numerical Models
The ability of the model to predict the runup and rundown processes of non-breaking long waves has been tested against 1D (Carrier and Greenspan, 1958) and 2D (Ozkan-Haller and Kirby, 1997) analytical solutions.
The model has also been tested by a series of large-scale experiments in which real beach profiles and real storm conditions were scaled and reproduced in a 233 m long, 7 m deep and 5 m wide wave flume (Deltares, 2010). The sand beaches were exposed to various wave conditions, and the dune erosion and retreat process were measured in the experiments and also simulated using XBeach. It was concluded that the calculated wave heights, flow velocities, sediment concentrations as well as sediment transports rates compared reasonable well with the measurements.
XBeach has also been used to simulate the morphodynamic responses of sandy dunes to an extreme storm at Assateague Island, Maryland, USA (Jimenez et al., 2006). The calculated changes of bed profile were found to be largely consistent with the measured data. The model has been applied to several case studies involving dune erosion and sediment deposition during Hurricanes Ivan and Katrina (Lindemer et al., 2010; McCall et al., 2010). Their numerical results demonstrate reasonable erosion and deposition patterns, indicating that the model is capable of handling practical situations with large wave heights (larger than 5 m) and long durations (20 hrs or more).
Wind waves are not considered in this study, thus shallow water equations are adopted to calculate the flow field without wave radiation stresses. The performance of the model without considering wind waves has been validated against several laboratory experiments on the transports of fine sand on uniform slopes under breaking solitary waves (Kobayashi and Lawrence, 2004; Young et al., 2010). Since XBeach is a 2DH model, the sediment entrainment by turbulent flows and the density stratification in sediment-laden flows (both are related to the vertical flow structure) cannot be simulated.
2.1 Nonlinear shallow water equations
When running COMCOT to simulate the tsunami wave propagation in deep oceans, the shallow water equations are solved in a spherical coordinate system and the effects of Coriolis force are added to Eqs. (2) and (3). See Liu et al. (1995), Wang and Liu (2005) or Wijettunge et al. (2008) for details. The coupling of COMCOT and XBeach for simulating tsunami-induced sediment transport and beach profile changes is described at the end of Subsection 3.2.
2.2 Sediment transport model
Multiple sand layers, which are composed of multiple sediment classes, can be considered by assigning different grain sizes in different areas. These features make it possible for tracking sediment movement and discussing characteristics of tsunami deposits such as landward fining.
3. Model Setup
3.1 Tsunami sources
Fault parameters of earthquake scenarios used in tsunami simulations.
No. of segment
3.2 Offshore boundary condition
Information on the setup of the four grids for COMCOT.
Grid C (Painan)
Number of grids
481 × 421
723 × 723
543 × 543
680 × 680
Latitude scope (degree)
95E to 103E
98E to 102E
100E to 101E
100.4E to 100.65E
Longitude scope (degree)
6S to 1N
4S to 0N
1.8S to 0.8S
1.45S to 1.2S
Grid size (m)
Ratio to parent grid
Time step (sec)
XBeach is used to simulate the sediment transport in thePainan Bay and the city area which are covered by the innermost grid (grid C in Fig. 3). To run XBeach, the incoming wave conditions must be specified on the offshore boundary; to achieve that, we first run COMCOT for each fault rupture model to get the time series of the surface elevation and velocity on this boundary, then interpolate the surface elevation and velocity from COMCOT simulation using the time step and spatial spacing required by XBeach simulations.
Figure 4 shows sample time series of the incident tsunami waves at P1 (shown in Fig. 1) for the six scenarios listed in Table 1. For the scenarios SA, SB, S3 and S4, the leading waves are negative waves; while for the scenarios S1 and S2, the leading waves are positive waves, with maximum wave heights of nearly 5 m and 7 m, respectively.
For all sediment transport simulations, the time series of surface elevation and water velocity at the offshore bound-ary were also linearly interpolated to a smaller time step of 0.1 s. The innermost gird size used in all COMCOT simulations is 41 m in the bay area; the velocity and surface elevation provided by COMCOT are interpolated to a finergrid (5 m) on the offshore boundary for all sediment transport simulations. The condition that sediment can freely pass through the offshore boundary is achieved by requesting that the normal gradient of sediment concentration iszero at the offshore boundary.
3.3 Topography and bathymetry
A relatively high resolution topography data set is needed for inundation and sediment transport simulations. The bathymetric and topographic data near-shore and onshore of Painan are derived from two data sets: (i) the SRTM topography data1 and (ii) the bathymetry and topography provided by USC Tsunami Research Center and GreenInfo Network (we shall call it USC-TRC data in this paper). The first set of data has a spatial resolution of 92 m. The second data has a spatial resolution of about 200 m which combined 1:250,000 digitized nautical charts (1997–2004) with publicly available deep water bathymetry (SRTM30-Plus). Borrero et al. (2006) used the second data set in their study of tsunami inundation modeling for western Sumatra. To prepare our bathymetric and topographic data, we first interpolated the bathymetric data from USC-TRC onto a 92.13 m × 92.13 m grid using a bilinear method without gap filling; then we combined the SRTM topography data with the new 92 m-USC-TRC bathymetric data to produce a uniform bathymetric and topographic data set with a spatial resolution of 92.13 m. The digitized shoreline from nautical charts was adjusted manually for consistency with SRTM-water boundary; data gaps between the bathymetry and topography were interpolated and filled up with nautical charts. Since a finer grid is needed for predicting erosion and deposition maps, we further interpolated the bathymet-ric and topographic data onto a 5 m×5 m grid for sediment transport simulations.
3.4 Size distribution and composition of sand
Accumulative percentages of grain size for sand samples collected from 5 locations.
Based on the surveyed data, a two-layer sand distribution model (Fig. 5) was assumed as the initial setting. The cement road near the shoreline is assumed non-erodible and the area between shoreline and the cement road is assumed erodible: the influences of the wooden houses on the sediment transport are ignored as these wooden houses can be easily smashed and swept by the strong tsunami waves (see Fig. 6 for the typical appearance of these wooden houses and the road). The simulated area is divided into 4 zones along the cross-shore direction. The boundary between zone-1 and zone-2 is chosen such that the local wave length of typical wind waves is about 90% of the deep water wave length and the bottom sand is not likely to be moved by the wind waves. The thickness of the top layer is 0.35 m and the thickness of the bottom layer is 4.65 m. Medium sand (d50 = 0.4 mm) is used in the high wave energy zone for both the top and bottom layers; the width of this zone is 20 m. In the region between the offshore boundary and the high wave energy zone, fine sand (d50 = 0.2 mm) was used for both the top and bottom layers. In the shore-face zone (width = 20 m), fine sand was used for the top layer1The Shuttle Radar Topography Mission (SRTM) data has a horizontal resolution of 3 seconds or approximately 92 meters. The data is available at http://srtm.csi.cgiar.org/.and medium sand was used for the bottom layer. In the region (width = 40 m) between the shore-face and the cement road, medium sand was used for both the top and bottom layers. The city area, seaport and stone platform were all considered to be non-erodible.
4. Results and Discussion
4.1 Inundation maps
The simulated inundation parameters for 6 scenarios in Painan.
Arrival time of first crest(min)
Arrival time of first wave trough(min)
Water surface elevation along shoreline(m)
Maximum inundation distance(m)
After comparing the simulated tsunami wave heights and inundation distances for all scenarios, we found that scenario S2 is the worst case scenario. The inundation map for S2 is shown in Fig. 7, where variations of the inundation depth along two cross-sections are also shown. Scenario S3 represents a typical scenario of negative leading wave. The inundation map for S3 is shown in Fig. 8, where variations of the inundation depth along two cross-sections are also shown. These two scenarios are chosen to further study the hydrodynamics, sediment transport and shoreline changes.
For S2, the first wave front would reach the coast of Painan about 26 minutes after the rupture, with an initial set-down of water surface before the peak. The initial set-down of the surface elevation is because of the subsidencein the coastal area (Fig. 4). Figure 7 shows a map of the maximum flow depth during the first three hours of tsunami wave attack: the entire city would be inundated with a maximum tsunami inundation depth of about 6.8 m in the city area. Within the first three hours, three main peak waves could reach the Painan bay area: the first peak wave might hit the shoreline 37 minutes after the rupture, raise the water surface up to 7 m at the shoreline and penetrate 1884m inland within 14 minutes. The average inundation depth is about 3–4 m in the city area and the maximum inundation depth occurs in the northeast part of the city, where the elevation is relatively low. According to Shuto (1993), when the inundation depth is larger than 2 m, wooden house will be completely washed away. Thus the wooden houses near the high-tide line would be swept away, producing a large amount of floating debris. The average speed of the wave front could be about 2 m/s, and the inundation flow velocities may reach about 5 m/s which are large enough to erode a large amount of sediment near the shoreline. Bearing in mind that we have not considered the city buildings in the simulations; if the effects of buildings were considered, the maximum flow speed within constrained streets may be faster than 5 m/s due to the channelling effects (Borrero, 2005).
4.2 Sediment transport for scenario S2
4.2.1 Erosion and deposition
4.2.2 Scouring around the road and the seaport
It is realized that the scouring induced by tsunamis is different from the present understanding of scour processes in a river or coastal environment around bridge piers (Kato et al., 2000; Nakamura et al., 2008). Tsunami waves are very long waves and tsunami flows are far from steady and uniform. For tsunami flows, scouring occurs often within less than 1 hour. Some experimental and numerical studies have been done to understand the tsunami-induced scours around coastal structures (Kato et al., 2001; Tonkin et al., 2003;Nakamura et al., 2008), and it is revealed that most rapid scour on sand substrate occurred at the tsunami down-rush stage.
4.2.3 Characteristics of tsunami deposits
One way to study the historical tsunami is to examine the characteristics (e.g., grain size distribution) of the tsunami deposits onshore (Shi et al., 1995; Dawson et al., 1996; Gelfenbaum and Jaffe, 2003; Moore et al., 2007; Paris et al., 2007). When analyzing tsunami deposits, it is important to know the origin of the sediments in a core sample and to relate the tsunami deposits to the flooding and retreating process during a tsunami event. Figure 12 shows the change of bed profile and the change of sand fraction in the upper layer along the cross-section E–E in Fig. 11. After the attack of the tsunami, due to the severe erosion in the shore-face, the fine sand in the shore-face could be moved, exposing the bottom sand layer to the water above. A large amount of fine sand and part of medium sand could be deposited in the bay area, however, no significant change in the sand fraction can be observed in the bay area. Some of the sand deposited in several places in the city areas may come from the bay and the shore-face areas, and it is possible to examine the sediment cores in these places to investigate the historical tsunamis from tsunami deposits (Bourgeois, 2009).
4.2.4 Remarks on equilibrium sediment concentration and settling velocity
In addition to the van Rijn’s formula, we have also tested the Bagnold’s formula (1966) and Ackers-White’s formula (1973) for the equilibrium sediment concentration (the detailed comparison is not shown here). The erosion and deposition patterns obtained by these three formulas are generally similar: the erosion depth predicted by van Rijn’s formula is between those predicted by Ackers-White’s formula and Bagnold’s formula. Our simulated erosion and deposition depths are quantitatively reasonable even though the hindered settling effects are not considered. This could also be evaluated through the measured data during the post-tsunami field surveys (Gelfenbaum and Jaffe, 2003; Narayana et al., 2007; Srini-vasalu et al., 2007; Pari et al., 2008). However, the maximum sediment concentration could reach more than 800 kg/m3 in several spots during a short period of time; there is a concern that the high suspended sediment concentration may hinder the settling of sediment grains (van Rijn, 2007). We have evaluated the effect of hindered settling by using the modified setting velocity , where ws,0 is the original settling velocity, is the total mass concentration of suspended sediment in the water column and c d is a reference density (Richardson and Zaki, 1954). We took c d = 1600 kg/m3 in this exercise. For a uniform concentration of 50 kg/m3 during the entire inundation period, the hindered settling velocity would be reduced by less than 15% relative to the original settling velocity. For the scenario S2, the concentration of suspended sand is less than 50 kg/m3 most of the time during inundation period; high concentration region may be found only near the shoreline (see Fig. 10). Our simulation shows that the modified settling velocity does not cause noticeable changes in the deposit thickness or the scour depth; our results are consistent with those of Apotsos et al. (2011), who considered the combined effects of hindered settling and stratification. However, for 3D models, Apotsos et al. (2011) found the significant influence of hindered settling velocity on the deposit thickness if the mixing of sediment into water was not reduced by the density stratification due to the high concentration of suspended sediment.
4.3 Hydrodynamics and sediment transport for scenario S3
The sand source should come from the shore-face which can be easily inferred from the hydrodynamic process and the resulting distribution of sand fraction. The fine sand in the shore-face has been moved to the seaward and mixed with the medium sand from either the high wave energy area or the house base area. Very little deposition could be observed in the city area except a small patch near the limit line of runup. Similar to S2, the deposition is mainly medium sand. The morphological change is moderate compared with scenario S2. But it is hard to conclude that the leading depression wave form would cause slighter sediment movement than the leading positive one since the magnitude of the hydrodynamic parameters for these two scenarios are different (e.g. wave heights, wave lengths). Though some investigations (Kobayashi and Lawrence, 2004; Apotsos et al., 2011) claimed that the leading depression wave would cause little erosion during retreating stage of first wave. Meanwhile, smaller runup and weaker backwash flow would cause less sediment movement. The difference of the erosion and deposition pattern between these two scenarios provides very helpful information in the selection of drilling sites for core samples in investigation of historical and prehistoric tsunami deposits.
Six rupture models with magnitude ranging from Mw = 8.7 to Mw = 8.92 have been considered in this study to assess the tsunami inundation and sediment transport in Painan, West Sumatra, Indonesia. According to the worst scenario, Painan would be hit by the first tsunami wave about 26 minutes after the rupture, and the tsunami could cause a maximum inundation depth of about 6.8 m and a maximum inundation distance about 1884 m, with an average inundation depth of about 3–4 m in the city area. Sediment transport caused by the tsunami waves has also been examined for two representative scenarios: one has a positive leading wave and the other has a negative leading wave. For the case of a positive leading tsunami wave, a large amount of sediment would be suspended near the shoreline during the backwash stage and the suspended sediment would be deposited in the offshore area forming a large sandbar near the shoreline. A considerable amount of sediment would be suspended by the passing wave front and leaving behind a small amount deposition in the city area. The foundation of a shore-parallel road could be severely eroded by the backwash flows. For the case of a negative leading tsunami wave, significant sediment movement would occur during the backwash stage accompanying the negative peak wave; an offshore sandbar could form in the bay area, while no noticeable large area of sand deposit could be found in the city area. The difference of the erosion and deposition patterns between these two scenarios provides useful information for tsunami geologists to further study the paleo-tsunami in this area.
This work has been supported by the Earth Observatory of Singapore (EOS), Nanyang Technological University, Singapore, through the project “Tsunami Hazard Mitigation for West Sumatra”. The authors would like to thank the following colleagues at the Earth Observatory of Singapore: Dr. Kusnowid-jaja Megawati for arranging our survey trips; Dr. Adam D. Switzer and Miss Lee Yingsin for providing the facilities for the grain-size analysis. We also thank the two anonymous reviewers for their constructive comments and suggestions, which have greatly improved the quality of the manuscript. This is EOS contribution No. 17.
- Ackers, P. and W. R. White, Sediment transport: New approach and analysis, J. Hydraul. Div., 99, 2041–2060, 1973.Google Scholar
- Ahrens, J. P., A fall-velocity equation, J. Waterway Port Coast. Ocean Eng., 126, 99–102, 2000.View ArticleGoogle Scholar
- Apotsos, A., G. Gelfenbaum, and B. Jaffe, Process-based modeling of tsunami inundation and sediment transport, J. Geophys. Res., 116, 20, 2011.Google Scholar
- Aydan, O., Seismic and tsunami hazard potentials in Indonesia with a special emphasis on Sumatra Island, Journal of The School of Marine Science and Technology, Tokai University, 6, 19–38, 2008.Google Scholar
- Bagnold, R. A., An approach to the sediment transport problem from general physics, Geological Survey Professional Papers, Washington, USA, 1966.Google Scholar
- Borrero, J. C., Field survey of northern Sumatra and Banda Aceh, Indonesia after the Tsunami and earthquake of 26 December 2004, Seismol. Res. Lett., 76, 312–320, 2005.View ArticleGoogle Scholar
- Borrero, J. C., K. Sieh, M. Chlieh, and C. E. Synolakis, Tsunami inundation modeling for western Sumatra, Proc. Natl. Acad. Sci. USA, 103, 19673–19677, 2006.View ArticleGoogle Scholar
- Bourgeois, J., Geologic effects and records of tsunamis, in The Sea: Tsunamis, edited by E. N. Bernard and A. R. Robinson, Harvard University Press, London, England, 2009.Google Scholar
- Brooks, O., Tsunami Alert: Beating Asia’s Next Big One, 215 pp., Marshall Cavendish Editions, Singapore, 2010.Google Scholar
- Carrier, G. F. and H. P. Greenspan, Water waves of finite amplitude on a sloping beach, J. Fluid Mech., 4, 97–109, 1958.View ArticleGoogle Scholar
- Chien, N. and Z. Wan, Mechanics of Sediment Transport, 913 pp., American Society of Civil Engineers, 1999.Google Scholar
- Chlieh, M., J. P. Avouac, K. Sieh, D. H. Natawidjaja, and J. Galetzka, Heterogeneous coupling of the Sumatran megathrust constrained by geodetic and paleogeodetic measurements, J. Geophys. Res. B: Solid Earth, 113, 2008.Google Scholar
- Dawson, A. G., S. Shi, S. Dawson, T. Takahashi, and N. Shuto, Coastal sedimentation associated with the June 2nd and 3rd, 1994 Tsunami in Rajegwesi, Java, Quat. Sci. Rev., 15, 901–912, 1996.View ArticleGoogle Scholar
- Deltares, XBeach Testbed Report, Delft, The Netherlands, 2010.Google Scholar
- Folk, R. L. and W. C. Ward, Brazos River Bar: A study in the significance of grain size parameters, J. Sediment. Petrol., 27, 3–26, 1957.View ArticleGoogle Scholar
- Galappatti, G. and C. B. Vreugdenhil, A depth-integrated model for suspended sediment transport, J. Hydraul. Res., 23, 359–377, 1985.View ArticleGoogle Scholar
- Gelfenbaum, G. and B. Jaffe, Erosion and sedimentation from the 17 July, 1998 Papua New Guinea tsunami, Pure Appl. Geophys., 160, 1969– 1999, 2003.View ArticleGoogle Scholar
- Gelfenbaum, G., D. Vatvani, B. Jaffe, and F. Dekker, Tsunami inundation and sediment transport in vicinity of coastal mangrove forest, Coast. Sediment., 1–12, 2007.Google Scholar
- Goseberg, N. and T. Schlurmann, Relevant factors on the extent of inundation based on tsunami scenarios for the city of Padang, West Sumatra, in Proceedings of the International Conference on Tsunami Warn-ing(ICTW), Bali, Indonesia, 2008.Google Scholar
- Goto, K. and F. Imamura, Numerical models for sediment transport by tsunamis, Quatern. Res., 46, 463–475, 2007.Google Scholar
- Goto, K., S. A. Chavanich, F. Imamura, P. Kunthasap, T. Matsui, K. Mi-noura, D. Sugawara, and H. Yanagisawa, Distribution, origin and transport process of boulders deposited by the 2004 Indian Ocean tsunami at Pakarang Cape, Thailand, Sediment. Geol., 202, 821–837, 2007.View ArticleGoogle Scholar
- Huang, Z. H., T. R. Wu, S. K. Tan, K. Megawati, F. Shaw, X. Z. Liu, and T. C. Pan, Tsunami hazard from the subduction Megathrust of the South China Sea: Part II. Hydrodynamic modeling and possible impact on Singapore, J. Asian Earth Sci., 36, 93–97, 2009.View ArticleGoogle Scholar
- Huang, Z. H., Q. Qiu, K. Sieh, K. Megawati, D. H. Natawidjaja, and X. Wang, Numerical simulations of tsunami inundation for the city of Painan, Indonesia–Effects of coastal vegetations and man-made structures, in Tsunami Simulation for Impact Assessment, edited by H. L. Koh, P. L.-F. Liu, and S. Y. Teh, 249 pp., Penerbit Universiti Sains Malaysia, Malaysia, 2011.Google Scholar
- Imamura, F., I. Yoshida, and A. Moore, Numerical study of the 1771 Meiwa tsunami at Ishigaki island, Okinawa and the movement of the tsunami stones, in Proceedings of Coastal Engineering, Japan Society of Civil Engineers, 48, 346–350, 2001.Google Scholar
- Jaffe, B. E. and G. Gelfenbuam, A simple model for calculating tsunami flow speed from tsunami deposits, Sediment. Geol., 200, 347–361, 2007.View ArticleGoogle Scholar
- Jimenez, J. A., A. H. Sallenger, and L. Fauver, Sediment transport and barrier island changes during massive overwash events, in Proceedings of the 30th International Conference on Coastal Engineering, ASCE, 2870–2879, San Diego, USA, 2006Google Scholar
- Kato, F., S. Sato, and Y. E. H. Harry, Large-scale experiment on dynamic response of sand bed around a cylinder due to tsunami, in Proceedings of the 27th International Conference on Coastal Engineering, ASCE, 1848–1859, Sydney, Australia, 2000.Google Scholar
- Kato, F., S. Tonkin, H. Yeh, S. Sato, and K.-I. Torii, The grain-size effects on scour around a cylinder due to tsunami run-up, in Proceedings of the International Tsunami Symposium 2001, 905–917, Seattle, Washington, USA, 2001.Google Scholar
- Kobayashi, N. and A. R. Lawrence, Cross-shore sediment transport under breaking solitary waves, J. Geophys. Res. C: Oceans, 109, 2004.Google Scholar
- Komar, P. D., Beach Processes and Sedimentation, 429 pp., Prentice-Hall, Inc., Englewood Cliffs, New Jersey, 1976.Google Scholar
- Konca, A. O., J. P. Avouac, A. Sladen, A. J. Meltzner, K. Sieh, P. Fang, Z. Li, J. Galetzka, J. Genrich, M. Chlieh, D. H. Natawidjaja, Y. Bock, E. J. Fielding, C. Ji, and D. V. Helmberger, Partial rupture of a locked patch of the Sumatra megathrust during the 2007 earthquake sequence, Nature, 456, 631–635, 2008.View ArticleGoogle Scholar
- Lindemer, C. A., N. G. Plant, J. A. Puleo, D. M. Thompson, and T. V. Wamsley, Numerical simulation of a low-lying barrier island’s morphological response to Hurricane Katrina, Coast. Eng., 57, 985–995, 2010.View ArticleGoogle Scholar
- Liu, P. L. F., C. Yong-Sik, M. J. Briggs, U. Kanoglu, and C. E. Synolakis, Runup of solitary waves on a circular island, J. Fluid Mech., 302, 259– 285, 1995.View ArticleGoogle Scholar
- Lukkunaprasit, P. and A. Ruangrassamee, Building damage in Thailand in the 2004 Indian Ocean tsunami and clues for tsunami-resistant design, The IES Journal Part A: Civil & Structural Engineering, 1, 17–30, 2008.Google Scholar
- Maheshwari, B. K., M. L. S. M. EERI, and J. P. Narayan, Geotechnical and Structural Damage in Tamil Nadu, India, from the December 2004 Indian Ocean Tsunami, Earthq. Spectr., 22, 475–493, 2006.View ArticleGoogle Scholar
- Martin, M. E., R. Weiss, J. Bourgeois, T. K. Pinegina, H. Houston, and V. V. Titov, Combining constraints from tsunami modeling and sedimen-tology to untangle the 1969 Ozernoi and 1971 Kamchatskii tsunamis, Geophys. Res. Lett., 35, L01610, 2008.Google Scholar
- Matsutomi, H., T. Sakakiyama, S. Nugroho, and M. Matsuyama, Aspects of inundated flow due to the 2004 Indian Ocean Tsunami, Coast. Eng. J., 48, 167–195, 2006.View ArticleGoogle Scholar
- McCall, R. T., J. S. M. Van Thiel de Vries, N. G. Plant, A. R. Van Dongeren, J. A. Roelvink, D. M. Thompson, and A. J. H. M. Reniers, Two-dimensional time dependent hurricane overwash and erosion modeling at Santa Rosa Island, Coast. Eng., 57, 668–683, 2010.View ArticleGoogle Scholar
- McCloskey, J., S. S. Nalbant, and S. Steacy, Indonesian earthquake: earthquake risk from co-seismic stress, Nature, 434, 291, 2005.View ArticleGoogle Scholar
- McCloskey, J., A. Antonioli, A. Piatanesi, K. Sieh, S. Steacy, S. Nalbant, M. Cocco, C. Giunchi, J. Huang, and P. Dunlop, Tsunami threat in the Indian Ocean from a future megathrust earthquake west of Sumatra, Earth Planet. Sci. Lett., 265, 61–81, 2008.View ArticleGoogle Scholar
- Megawati, K., F. Shaw, K. Sieh, Z. H. Huang, T. R. Wu, Y. Lin, S. K. Tan, and T. C. Pan, Tsunami hazard from the subduction megathrust of the South China Sea: Part I. Source characterization and the resulting tsunami, J. Asian Earth Sci., 36, 13–20, 2009.View ArticleGoogle Scholar
- Meilianda, E., C. M. Dohmen-Janssen, B. H. P. Maathuis, S. J. M. H. Hulscher, and J. P. M. Mulder, Short-term morphological responses and developments of Banda Aceh coast, Sumatra Island, Indonesia after the tsunami on 26 December 2004, Mar. Geol., 275, 96–109, 2010.View ArticleGoogle Scholar
- Moore, A. L., B. G. McAdoo, and A. Ruffman, Landward fining from multiple sources in a sand sheet deposited by the 1929 Grand Banks tsunami, Newfoundland, Sediment. Geol., 200, 336–346, 2007.View ArticleGoogle Scholar
- Morton, R. A., J. R. Goff, and S. L. Nichol, Hydrodynamic implications of textural trends in sand deposits of the 2004 tsunami in Sri Lanka, Sediment. Geol., 207, 56–64, 2008.View ArticleGoogle Scholar
- Muhari, A., F. Imamura, D. H. Natawidjaja, S. Diposaptono, H. Latief, J. Post, and F. A. Ismail, Tsunami mitigation efforts with pTA in west Sumatra province, Indonesia, J. Earthq. Tsunami, 4, 341–368, 2010.View ArticleGoogle Scholar
- Nakamura, T., Y. Kuramitsu, and N. Mizutani, Tsunami scour around a square structure, Coast. Eng. J., 50, 209–246, 2008.View ArticleGoogle Scholar
- Seismology: Earthquake risk on the Sunda trench, Nature, 435, 756– 757, 2005.View ArticleGoogle Scholar
- Narayana, A. C., R. Tatavarti, N. Shinu, and A. Subeer, Tsunami of December 26, 2004 on the southwest coast of India: Post-tsunami geomor-phic and sediment characteristics, Mar. Geol., 242, 155–168, 2007.View ArticleGoogle Scholar
- Natawidjaja, D. H. and W. Triyoso, The Sumatran fault zone-from source to hazard, J. Earthq. Tsunami, 1, 21–47, 2007.View ArticleGoogle Scholar
- Natawidjaja, D. H., K. Sieh, M. Chlieh, J. Galetzka, B. W. Suwargadi, H. Cheng, R. L. Edwards, J.-P. Avouac, and S. N. Ward, Source parameters of the great Sumatran megathrust earthquakes of 1797 and 1833 inferred from coral microatolls, J. Geophys. Res., 111, B06403, 2006.Google Scholar
- Natawidjaja, D., K. Sieh, W. Kongko, A. Muhari, G. S. Prasetya, and I. Meilano, Scenario for future megathrust tsunami event in the Sumatran subduction zone, in Proceedings of the Asian Oceania Geo-sciences Society (AOGS) Meeting, Singapore, 2009.Google Scholar
- Nelson, A. R., H. M. Kelsey, and R. C. Witter, Great earthquakes of variable magnitude at the Cascadia subduction zone, Quatern. Res., 65, 354–365, 2006.View ArticleGoogle Scholar
- Okada, Y., Surface deformation due to shear and tensile faults in a halfspace, Bull. Seismol. Soc. Am., 75, 1135–1154, 1985.Google Scholar
- Ozkan-Haller, H. T. and J. T. Kirby, A Fourier-Chebyshev collocation method for the shallow water equations including shoreline runup, Appl. Ocean Res., 19, 21–34, 1997.View ArticleGoogle Scholar
- Pari, Y., M. V. Ramana Murthy, S. Jaya kumar, B. R. Subramanian, and S. Ramachandran, Morphological changes at Vellar estuary, India-Impact of the December 2004 tsunami, J. Environ. Manag., 89, 45–57, 2008.View ArticleGoogle Scholar
- Paris, R., F. Lavigne, P. Wassmer, and J. Sartohadi, Coastal sedimentation associated with the December 26, 2004 tsunami in Lhok Nga, west Banda Aceh (Sumatra, Indonesia), Mar. Geol., 238, 93–106, 2007.View ArticleGoogle Scholar
- Paris, R., P. Wassmer, J. Sartohadi, F. Lavigne, B. Barthomeuf, E. Desgages, D. Grancher, P. Baumert, F. Vautier, D. Brunstein, and C. Gomez, Tsunamis as geomorphic crises: Lessons from the December 26, 2004 tsunami in Lhok Nga, West Banda Aceh (Sumatra, Indonesia), Geomor-phology, 104, 59Ȅ72, 2009.View ArticleGoogle Scholar
- Paris, R., J. Fournier, E. Poizot, S. Etienne, J. Morin, F. Lavigne, and P. Wassmer, Boulder and fine sediment transport and deposition by the 2004 tsunami in Lhok Nga (western Banda Aceh, Sumatra, Indonesia): A coupled offshore-onshore model, Mar. Geol., 268, 43–54, 2010.View ArticleGoogle Scholar
- Qiu, Q., Z. H. Huang, K. Megawati, K. Sieh, and D. H. Natawidjaja, A scenario study of tsunami-induced inundation for Pariaman, West Sumatra, Indonesia, in Proceedings of 5th Annual International Workshop & Ex-pro on Sumatra Tsunami Disaster & Recovery 2010, Banda Aceh, Indonesia, 2010.Google Scholar
- Richardson, J. F. and W. N. Zaki, Sedimentation and fluidization, Trans. Inst. Chem. Eng., 32, 35–50, 1954.Google Scholar
- Roelvink, D., A. Reniers, A. van Dongeren, J. van Thiel de Vries, R. McCall, and J. Lescinski, Modelling storm impacts on beaches, dunes and barrier islands, Coast. Eng., 56, 1133–1152, 2009.View ArticleGoogle Scholar
- Shi, S., A. G. Dawson, and D. E. Smith, Coastal sedimentation associated with the December 12th, 1992 tsunami in Flores, Indonesia, Pure Appl. Geophys., 144, 525–536, 1995.View ArticleGoogle Scholar
- Shuto, N., Tsunami intensity and Disasters, Adv. Nat. Technol. Haz. Res., 1, 197–216, 1993.View ArticleGoogle Scholar
- Sieh, K., The Sunda magathrust-past, present and future, J. Earthq. Tsunami, 1, 1–19, 2007.View ArticleGoogle Scholar
- Sieh, K., D. H. Natawidjaja, A. J. Meltzner, C. C. Shen, H. Cheng, K. S. Li, B. W. Suwargadi, J. Galetzka, B. Philibosian, and R. L. Edwards, Earthquake supercycles inferred from sea-level changes recorded in the corals of west Sumatra, Science, 322, 1674–1678, 2008.View ArticleGoogle Scholar
- Spiske, M., R. Weiss, H. Bahlburg, J. Roskosch, and H. Amijaya, The TsuSedMod inversion model applied to the deposits of the 2004 Sumatra and 2006 Java tsunami and implications for estimating flow parameters of palaeo-tsunami, Sediment. Geol., 224, 29–37, 2010.View ArticleGoogle Scholar
- Srinivasalu, S., N. Thangadurai, A. D. Switzer, V. Ram Mohan, and T. Ayyamperumal, Erosion and sedimentation in Kalpakkam (N Tamil Nadu, India) from the 26th December 2004 tsunami, Mar. Geol., 240, 65–75, 2007.View ArticleGoogle Scholar
- Takahashi, T., N. Shuto, F. Imamura, and D. Asai, Modeling sediment transport due to tsunamis with exchange rate between bed load layer and suspended load layer,in Proceedings of the 27th International Conference on Coastal Engineering, ASCE, 1508–1519, Sydney, Australia, 2000.Google Scholar
- Taubenbock, H., N. Goseberg, N. Setiadi, G. Lammel, F. Moder, M. Oczipka, H. Klupfel, R. Wahl, T. Schlurmann, G. Strunz, J. Birkmann, K. Nagel, F. Siegert, F. Lehmann, S. Dech, A. Gress, and R. Klein, “Last-Mile” preparation for a potential disaster–Interdisciplinary approach towards tsunami early warning and an evacuation information system for the coastal city of Padang, Indonesia, Nat. Haz. Earth Syst. Sci., 9, 1509–1528, 2009.View ArticleGoogle Scholar
- Tobita, M., Crustal deformation of 2007 Southern Sumatra earthquake observed by SAR interferometry, in Proceedings of DPRI(Disaster Prevention Research Institute) Kyoto Workshop, Kyoto, Japan, 2007.Google Scholar
- Tonkin, S., H. Yeh, F. Kato, and S. Sato, Tsunami scour around a cylinder, J. Fluid Mech., 165–192, 2003.Google Scholar
- van Rijn, L. C., Principles of Sediment Transport in Rivers, Estuaries and Coastal Seas, 715 pp., Aqua Publications, The Netherlands, 1993.Google Scholar
- van Rijn, L. C., Unified view of sediment transport by currents and waves. II: Suspended transport, J. Hydraul. Eng., 133, 668–689, 2007.View ArticleGoogle Scholar
- Wang, X. and P. L. F. Liu, A numerical investigation of Boumerdes-Zemmouri (Algeria) earthquake and Tsunami, Comput. Model. Eng. Sci., 10, 171–183, 2005.Google Scholar
- Wijettunge, J. J., X. Wang, and P. L. F. Liu, India Ocean Tsunami on 26 December 2004: Numerical modeling of inundation in three cities on the south coast of Sri Lanka, J. Earthq. Tsunami, 2(2), 133–155, 2008.View ArticleGoogle Scholar
- Young, Y. L., H. Xiao, and T. Maddux, Hydro- and morpho-dynamic modeling of breaking solitary waves over a fine sand beach. Part I: Experimental study, Mar. Geol., 269, 107–118, 2010.View ArticleGoogle Scholar
- Zachariasen, J., K. Sieh, F. W. Taylor, R. L. Edwards, and W. S. Hantoro, Submergence and uplift associated with the giant 1833 Sumatran subduction earthquake: Evidence from coral microatolls, J. Geophys. Res., 104, 895–919, 1999.View ArticleGoogle Scholar