Modeling tsunami impacts on the. Western Australian coast

Modeling tsunami impacts on the Western Australian coast Scott Martin Leggett Supervisor: Professor Charitha Pattiaratchi School of Environmental Systems Engineering This dissertation is presented for the degree of Bachelor of Applied Ocean Science Engineering of the University of Western Australia October 2006

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3 1 Contents 1 Contents...3 2 Figures...5 3 Tables...10 4 Acknowledgements...11 5 Abstract...12 6 Glossary of terms...13 7 Introduction...14 8 Literature Review...16 8.1 Background to tsunami waves...16 8.2 Background to tsunamigenic earthquakes...16 8.3 Work done in numerical tsunami modeling...18 8.3.1 The MOST model...18 8.3.2 Historic tsunami events modeled using MOST...21 8.3.2.1 Hokkaido-Nansei-Oki event...22 8.3.2.2 Andreanov event...26 8.3.2.3 Chimbote Event...30 8.4 Realtime tsunami simulation with MOST...31 8.5 Tsunami Risk Assessment for Western Australia...32 8.5.1 Current recommendations...34

4 9 Research Motivation and Aim...35 10 Methodology...37 10.1.1 Modeled source location...38 10.1.2 Modeled source parameters...41 10.1.3 Running the MOST model...42 11 Results...44 12 Discussion...74 12.1 Scenario 1...74 12.2 Scenario 2...76 12.3 Scenario 3...77 12.3.1 17 th July 2006 Java tsunami...79 12.4 Scenario 4...79 12.5 Scenario 5...81 12.6 Scenario 6...82 12.7 Scenario 7...83 12.8 Overall...84 13 Conclusions and further work...87 14 References...89

5 2 Figures Figure 7.3.1: Ocean bottom deformation corresponding to earthquake parameters used in testing MOST. Ocean surface deformation is assumed equivalent and instantaneous (Titov and Gonzalez, 1997)...20 Figure 7.3.2: Comparison of the 1993 Okushiri inundation model (crosses), field observations (circles) and stereo photo data (triangles). Top frame shows aerial photograph of section of coastline studied. Middle frame shows inundation, topography and computational nodes. Bottom from shows maximum vertical runup along the same section...24 Figure 7.3.3: Modeled maximum tsunami heights and maximum wave velocities over a cross-section of Aonae Cape (Titov and Synolaksis, 1998)...25 Figure 7.3.4: Comparison between computed (red) and measured (blue) water levels for various offshore locations in the Andreanov tsunami event (Titov and Gonzalez, 1997)...27 Figure 7.5.1: Seismicity Australia, Indonesia and New Zealand 1977 1997 (Canterford et al., 2006)...33 Figure 7.5.1: Recorded earthquakes of magnitude >4.0 shown as small circles. Tsunamigenic events on record shown as larger circles (Tsunami Laboratory, 2005)....39 Figure 7.5.2: The domain over which modeling took place, with significant features marked. Location of tsunami sources within the domain used in numerical modeling indicated by crosses (Tsunami Laboratory, 2005, Robb et al., 2005)...40 Figure 7.5.3: Diagram showing relationship of source parameters to fault...42 Figure 7.5.1: Maximum water heights over the domain for Scenario 1...45 Figure 7.5.2: Maximum water heights over the domain for Scenario 2...46

6 Figure 7.5.3: Maximum water heights over the domain for Scenario 3...47 Figure 7.5.4: Maximum water heights over the domain for Scenario 4...48 Figure 7.5.5: Maximum water heights over the domain for Scenario 5...49 Figure 7.5.6: Maximum water heights over the domain for Scenario 6...50 Figure 7.5.7: Maximum water heights over the domain for Scenario 7...51 Figure 10.8: Water level predicted offshore of Karratha for the duration of Scenario 1...52 Figure 10.9: Water level predicted offshore of Exmouth for the duration of Scenario 1...52 Figure 10.10: Water level predicted offshore of Carnarvon for the duration of Scenario 1...53 Figure 10.11: Water level predicted offshore of Steep Point for the duration of Scenario 1...53 Figure 10.12: Water level predicted offshore of Geraldton for the duration of Scenario 1...54 Figure 10.13: Water level predicted offshore of Perth for the duration of Scenario 1...54 Figure 10.14: Water level predicted offshore of Karratha for the duration of Scenario 2...55 Figure 10.15: Water level predicted offshore of Exmouth for the duration of Scenario 2...55 Figure 10.16: Water level predicted offshore of Carnarvon for the duration of Scenario 2...56

7 Figure 10.17: Water level predicted offshore of Steep Point for the duration of Scenario 2...56 Figure 10.18: Water level predicted offshore of Geraldton for the duration of Scenario 2...57 Figure 10.19: Water level predicted offshore of Perth for the duration of Scenario 2...57 Figure 10.20: Water level predicted offshore of Karratha for the duration of Scenario 3...58 Figure 10.21: Water level predicted offshore of Exmouth for the duration of Scenario 3...58 Figure 10.22: Water level predicted offshore of Carnarvon for the duration of Scenario 3...59 Figure 10.23: Water level predicted offshore of Steep Point for the duration of Scenario 3...59 Figure 10.24: Water level predicted offshore of Geraldton for the duration of Scenario 3...60 Figure 10.25: Water level predicted offshore of Perth for the duration of Scenario 3...60 Figure 10.26: Water level predicted offshore of Karratha for the duration of Scenario 4...61 Figure 10.27: Water level predicted offshore of Exmouth for the duration of Scenario 4...61 Figure 10.28: Water level predicted offshore of Carnarvon for the duration of Scenario 4...62

8 Figure 10.29: Water level predicted offshore of Steep Point for the duration of Scenario 4...62 Figure 10.30: Water level predicted offshore of Geraldton for the duration of Scenario 4...63 Figure 10.31: Water level predicted offshore of Perth for the duration of Scenario 4...63 Figure 10.32: Water level predicted offshore of Karratha for the duration of Scenario 5...64 Figure 10.33: Water level predicted offshore of Exmouth for the duration of Scenario 5...64 Figure 10.34: Water level predicted offshore of Carnarvon for the duration of Scenario 5...65 Figure 10.35: Water level predicted offshore of Steep Point for the duration of Scenario 5...65 Figure 10.36: Water level predicted offshore of Geraldton for the duration of Scenario 5...66 Figure 10.37: Water level predicted offshore of Perth for the duration of Scenario 5...66 Figure 10.38: Water level predicted offshore of Karratha for the duration of Scenario 6...67 Figure 10.39: Water level predicted offshore of Exmouth for the duration of Scenario 6...67 Figure 10.40: Water level predicted offshore of Carnarvon for the duration of Scenario 6...68

9 Figure 10.41: Water level predicted offshore of Steep Point for the duration of Scenario 6...68 Figure 10.42: Water level predicted offshore of Geraldton for the duration of Scenario 6...69 Figure 10.43: Water level predicted offshore of Perth for the duration of Scenario 6...69 Figure 10.44: Water level predicted offshore of Karratha for the duration of Scenario 7...70 Figure 10.45: Water level predicted offshore of Exmouth for the duration of Scenario 7...70 Figure 10.46: Water level predicted offshore of Carnarvon for the duration of Scenario 7...71 Figure 10.47: Water level predicted offshore of Steep Point for the duration of Scenario 7...71 Figure 10.48: Water level predicted offshore of Geraldton for the duration of Scenario 7...72 Figure 10.49: Water level predicted offshore of Perth for the duration of Scenario 7...72 Figure 11.8.1: Scenario water heights after 2.5 hours. Reflective effects of Wallaby Extension and Wallaby Plateau indicated...85

10 3 Tables Table 9.1.1-1: Location of source tsunamigenic earthquakes modeled...38 Table 9.1.2-1: Parameters used for all source earthquakes in the MOST numerical model...41

11 4 Acknowledgements I would like to thank my supervisor, Professor Charitha Pattiaratchi for his help and advice on this project. His help, especially with getting the model up and running and with processing the results, was invaluable. Thanks also to the high performance computing service provided by the Interactive Virtual Environments Centre (IVEC). Without the use of this facility, the numerical modeling which was so crucial to this project would not have been possible.

12 5 Abstract Using a numerical model over a domain from -5 to -35 North and 100 to 117 east, a series of hypothetical tsunami events were simulated. The sources of these events were located along the Java Trench, in an area of known tsunamigenic earthquake activity. These model results were studied in order to determine the areas of the fault which could produce the most damaging tsunamis in relation to Western Australia. The results of the tsunami simulation at the coastline of Western Australia were also studied to determine areas which were particularly susceptible to tsunamis. The study found that the bathymetry of the deep ocean had a very strong effect on the resultant tsunami wave propagation. Areas of relatively shallow water such as seamounts or plateaus strongly refracted and reflected tsunami wave energy. Large plateaus adjacent to the north-west coast of Western Australia strongly refracted tsunami waves towards the coastline at specific locations. The maximum wave heights predicted along the Western Australian coast varied with the location of the source, with the closer tsunami sources producing much larger waves at vulnerable areas. However, the densely populated south-west coastal areas of Western Australia were not significantly affected in any tsunami scenarios tested. Again, this was largely due to the offshore bathymetric features of this area.

13 6 Glossary of terms BoM: Bureau of Meteorology. IVEC: Interactive Virtual Environments Centre MOST: Method Of Splitting Tsunami, a numerical tsunami model. MSL: Mean sea level. NOAA: PTWC: Pacific Tsunami Warning Center Sumatera fault: Also known as the Java trench, this is the earthquake fault to the north of Western Australia, between the Australian and Eurasian tectonic plates. TIME: Center for Tsunami Inundation Mapping Efforts

14 7 Introduction The risks of tsunami inundation for Western Australia have been illustrated clearly by the tsunami of boxing day 2004, in which many countries bordering the Indian ocean suffered heavy damage and many casualties (Lay et al., 2005). This event brought tsunamis to the attention of the world and served as a wake-up call for government organisations, especially in Australia, interested in mitigating the dangers. The unpredictable and intermittent nature of tsunami events means that numerical modeling is an essential tool in understanding the characteristics of tsunami generation and propagation. One group interested in predicting tsunami impact in Australia was the Australian Bureau of Meteorology. Since the 2004 tsunami, the Bureau have begun using numerical modeling to produce scenarios of tsunami events, however this is in extremely preliminary stages and the group has focused mainly on the eastern coast of Australia. There has been very little tsunami modeling work conducted for Western Australia (Greenslade et al., 2006), and this leaves the relative dangers for a large section of the coastline unknown. Current warnings for the region are delivered by the seismic division of Geoscience Australia, and the Pacific Tsunami Warning Center in Hawaii. These rely largely on seismic data, so warnings which are passed on the Bureau cannot be specific with regard to the threat. No modeling of tsunami generation, propagation or inundation is currently utilised in warning systems (Bureau of Meteorology, 2006). As a direct result of the 2004 Tsunami, the Australian Government has allocated 68.9 million dollars to fund the development of a tsunami warning system for Australia (Downer and Ruddock, 2005). This will take the form of a national tsunami warning centre jointly managed by the Bureau of Meteorology and Geoscience Australia. This will form part of the Australian contribution to the international Indian Ocean Tsunami Warning System. Modeling of various possible tsunami scenarios with respect to Western Australia is important in creating an understanding of the wave processes shaping the impact of tsunamis along the coast. This study seeks to improve the

15 understanding of tsunami generation and propagation with respect to Western Australia.

16 8 Literature Review 8.1 Background to tsunami waves Tsunamis are surface gravity waves with an extremely long wavelength and a large period, which are generated in a body of water by disturbances of large scale and short duration. The duration of a tsunami event can be 5-100 min, wavelength 100m-1000km and propagation speed of up to 200m/s, with wave heights in the tens of metres in coastal areas. Tsunami waves of seismic origin usually have the longest wavelength; for example the massive tsunami which struck the Indian Ocean on Boxing Day 2004 had a wavelength of 670km and a height of 12m (Zahibo et al., 2006). Due to the extremely long wavelength of tsunami waves, the propagation model can be treated as simple shallow water propagation, where the square of wave speed (c) is proportional to gravity acceleration constant (g) and water depth (H): c = gh Tsunamis are generated by several mechanisms including seismic, landslides, and external impact such as an asteroid or comet. However by far the most common tsunamigenic mechanism is seismic (Kharif and Pelinovsky, 2005). Modeling research and work has concentrated on this type of tsunami since it is most common, and because the formation / propagation characteristics are quite different to impact tsunamis (Kharif and Pelinovsky, 2005). 8.2 Background to tsunamigenic earthquakes Tsunamigenic earthquakes generally occur along the edges of tectonic plates at known faults. The parameters of an earthquake dictate the tsunami generation parameters and three features in particular are most important. These three features, moment, mechanism, and depth, are in turn described by several important parameters. (Yalçiner et al., 2005)

17 The moment of an earthquake, M0, measures the earthquake strength and is a product of the rigidity of the earth s crust in the region (µ), the length (L) and width (W) of the fault, and the average fault slip (u0). In general, the larger the moment of an earthquake, the large tsunami generated (Yalçiner et al., 2005). The relationship between these components is shown in the equation (Titov et al., 1999): M = µ LWu 0 0 This is related to the commonly reported Moment Magnitude (Mw) of the earthquake as shown: MW = (log ( M ) 9.1) 2 3 10 0 The mechanism refers to the type of faulting occurring in the earthquake and the orientation of the fault. When stress is released along a fault in an earthquake there are some major parameters describing the mechanism. The slip of the fault describes the amount of movement which has taken place. In general the larger the slip, then the larger the magnitude of the earthquake, and therefore, tsunami (Yalçiner et al., 2005). However the slip and magnitude of the earthquake alone cannot determine tsunamigenesis. There are also the factors of the fault type, rupture area and speed, and the physical properties of the earth s crust in the area such as stiffness which determine tsunamigenic impact of the earthquake (Geist, 2006). The depth of the earthquake s epicentre is another important parameter in determining tsunamigenesis. The closer the epicentre is to the surface of the ocean floor, the larger the surface offset is likely to be and therefore the larger the tsunami generated. Also, the orientation of the slip vector is an important consideration. Work done by (Geist, 2006) shows that the obliquity of the slip vector in the dip of the fault can have a dramatic effect on the resulting tsunami and its propagation. A major reason for this is that oblique faulting results in a much different vertical offset of the seafloor than simple thrust faulting. This oblique movement results in

18 secondary tsunamis which move in different directions than otherwise expected from the orientation of the fault. Secondary mass failure may also contribute to the generation of a tsunami; either acting alone or as a result of an initial faulting mechanism. This type of failure often takes the form of landslides both submarine and coastal. A mass failure can greatly increase the magnitude of a tsunami as well significantly alter the characteristics of the resulting wave (Synolakis et al., 2002). A mass failure can also occur some time after the earthquake has taken place. These effects make the accurate prediction of tsunami propagation from seismic readings much more difficult. 8.3 Work done in numerical tsunami modeling Work on tsunami modeling has been done through various academic institutions. Since the creation of the Center for Tsunami Inundation Mapping Efforts (TIME), there has been some collaboration between different teams working on separate models. TIME monitors advances in tsunami modeling techniques and uses two major models in its simulations. (NOAA, 2006a) The TUNAMI-N2 model, originally developed by Professor Fumihiko Imamura in the Disaster Control Research Center in Tohoku University Japan, is a key tool in investigating near-shore propagation and coastal amplification of tsunamis (Yalçiner et al., 2005). It is currently used in the Hawaii branch of TIME (NOAA, 2006b). The tool this review will be concentrating on however, and the one which will be used in the investigation of tsunami risk for Western Australia, is the Method Of Splitting Tsunamis (MOST) model. This is the standard model used by the TIME project. MOST uses a finite difference method in order to divide its computational domain (NOAA, 2006b). 8.3.1 The MOST model This model was developed and initially tested at the Pacific Marine Environmental Laboratory (PMEL). At the completion of this initial phase, the model

19 was transferred to the Defence Advanced Research Projects Agency s (DARPA) Early Detection and Forecast of Tsunami (EDFT) project. In its initial form, the model was able to simulate a tsunamigenic event near the Alaskan coast, and the impact on the Hawaiian islands (Titov and Gonzalez, 1997). Since the late 80 s, the NOAA s Tsunami Research Program at Pacific Marine Environmental Lab has been developing numerical models with high spatial resolution (Mofjeld et al., 2004). The published aims of this programme are to create accurate inundation maps for US coastal communities bordering the pacific ocean, and to provide US tsunami warning Centres with improved tsunami forecasting systems based on real-time reporting through the use of BPG (tsunameters) and on the use of a database of simulations known as SIFT (Short-tem Inundation Forecast for Tsunamis) (Mofjeld et al., 2004). A prototype of this database was made available to Tsunami Warning Centres in February 2004. The MOST model was the first to show scattering effects of submarine features on tsunami propagation. It also showed how ridges could act as waveguides. For example, the 1996 Irian Jaya tsunami was modelled and it was found that the South Honshu Ridge in the Western Pacific directed wave energy towards Japan, matching previously unexplained inundation observations (Mofjeld et al., 2004). The model calculates the three basic stages of a tsunami event separately. The stages are generation, propagation and inundation. This gives the model the capability to simulate an event completely (Titov and Gonzalez, 1997). The generation process simulation is based on elastic deformation theory. It uses an initial deformation of the ocean surface due to a seafloor seismic event. This deformation of the ocean surface evolves to a long gravity wave which then can be input to the propagation model.

20 Figure 8.3.1: Ocean bottom deformation corresponding to earthquake parameters used in testing MOST. Ocean surface deformation is assumed equivalent and instantaneous (Titov and Gonzalez, 1997). The generation model assumes a fault plane model of the earthquake source. This is based on an elastic half-space overlaid with an incompressible liquid layer representing the earth s crust and ocean respectively (Titov and Gonzalez, 1997). Linear models are used to study the generation process of the model because the gravity wave formation due to the initial water disturbance is generally a slow process driven by hydrostatic forces with negligible non-linear effects (Titov, 1997). The propagation algorithm of the model is extremely flexible and can simulate tsunami movement over global scales. Over such large distances, it is important to take into account properties such as the curvature of the earth, Coriolis forces and dispersion (Titov and Gonzalez, 1997). While Coriolis can be accounted for by the use of explicit terms in the governing algorithm, dispersion can be taken into effect by exploiting the numerical dispersion inherent in finite-difference algorithms. This allows the use of nondispersive linear or non-linear equations in the wave propagation model. This numerical dispersion scheme is used in MOST, along with spherical co-ordinates and Coriolis terms. The non-linear shallow water wave equations are solved numerically

21 using a splitting method similar to that outlined in (Titov, 1997). It has been shown, through the use of, and comparison with, historical tsunami data, that the splitting method is highly accurate in modeling both the propagation and the runup of tsunami waves over complex topography when compared with similar models. This is despite the fact that the dynamics of the breaking wave front cannot be resolved (Titov, 1997, Titov and Gonzalez, 1997, Titov and Synolaksis, 1998). The major difficulties in the modeling of inundation are a lack of detailed field measurements used for testing the models, and also lack of fine resolution bathymetry and topography data required as input. The lack of field measurements has been addressed to some extent through large-scale runup experiments conducted by the Coastal Engineering Research Center (CERC) of the US Corps of Engineers, as well as several surveys of tsunami effected areas which yielded detailed field data (Titov, 1997, Titov and Synolaksis, 1998). A lack of high resolution bathymetric and topographic data is harder to overcome, however it has been made available for some areas historically subject to tsunami inundation, such as Okushiri Island, Japan, which was the site of a tsunami in 1993. The MOST model, unlike other models based on the shallow wave approximation, does not use explicit dissipation terms. Though bottom friction undoubtedly has an effect on wave evolution, it has been shown that inundation results are largely insensitive of the roughness coefficient (Titov and Synolaksis, 1998). The neglect of arbitrary friction factors and artificial viscosity values in MOST makes it relatively simple when compared to similar existing models (Kobayashi et al., 1987, Zelt, 1991), and removes the risk of introducing additional numerical error (Titov and Synolakis, 1995). 8.3.2 Historic tsunami events modeled using MOST All modeling conducted using the MOST model, to date, has had a distinct concentration on the Pacific. Little effort has been directed at the Atlantic Ocean and even less at the Indian or Southern oceans. This is reflective of the major funding

22 contributor of the research being the US Department of Defence, as well as the lack of many governmental interests in areas other than the Pacific. MOST modeling has found that accurate realism of the model relies much more on accurate and high-resolution bathymetric and topographical data rather than on numerical grid resolution within the model. Bathymetric grids of 150m resolution have been found to be adequate for reproducing overall runup heights, while a 50m resolution grid is required to reproduce the extreme runup heights and flow velocities observed in the field. While the studies have tended to show the accuracy of the MOST model, there is still a lot of work to be done in order to understand the effects of friction, wave breaking, and wave forces on structures, ground deformation over time and the performance of seafloor displacement models. 8.3.2.1 Hokkaido-Nansei-Oki event An early published use of the MOST model algorithm was in simulating the tsunami produced at Okushiri Island as a result of the Hokkaido-Nansei-Oki earthquake. This earthquake had a moment magnitude of 7.8, and occurred on July 12, 1993. The resultant tsunami had an extreme runup of 30m and velocity of 20m/s inferred from structural damage. (Titov and Synolaksis, 1997) Other models used to reproduce this tsunami event, based on the shallow water wave approximation (SW) have been successful to some extent. These models predicted correctly the first order runup heights along the coast of Hokkaido and to a lesser extent around Okushiri. However, these models were unable to reproduce either the extreme runup values, or the extreme velocities observed around the south end of Okushiri; at best, the predictions were a factor of two from field measurements of the extreme runup heights. These models applied the previously ubiquitous (Imamura et al., 1993, Satake et al., 1993, Yeh et al., 1993, Synolakis et al., 1995, Satake and Tanioka, 1995) method of a 10m depth computational threshold. That is, the model calculations were stopped at the 10m depth and the height of the wave at this point was used to infer the runup heights along the coast. For this event, and using the identical grid resolutions, the models underestimated inundation by a factor of two on average. This method also significantly underestimated the height at

23 the 10m contour compared to the full inundation calculations used by MOST, suggesting that this method may have significant inaccuracies in tsunami modeling (Titov and Synolaksis, 1998). It is clear, in any case, that there is considerable wave evolution between the 10m contour and maximum runup height. The MOST model, on the other hand, successfully predicted runup heights along the entire coastline of Okushiri Island. A small canyon in the south-west area of Okushiri served to amplify the effect of the tsunami, with field observers recording a runup height of 31.7 metres. This was one area where previous models had failed to accurately reproduce effects of small scale local bathymetry, predicting only ~15 metre runup. The MOST model predicted a runup of 29.7 metres, remarkably close to the measured field data, especially considering the resolution of the bathymetry being 50 metres. It is suspected that the inclusion of dissipation factors in the other models meant that bottom friction was taken to be much more significant than in reality. In general, the MOST model predicted runup heights slightly above those measured in field data. It is suspected that the non-inclusion of dissipation factors is responsible for this. (Titov and Synolaksis, 1997)

24 Figure 8.3.2: Comparison of the 1993 Okushiri inundation model (crosses), field observations (circles) and stereo photo data (triangles). Top frame shows aerial photograph of section of coastline studied. Middle frame shows inundation, topography and computational nodes. Bottom from shows maximum vertical runup along the same section. This event was ideal for use with MOST because of the availability of highresolution bathymetric data. The entire computational area was covered by nested grids, with the coarsest resolution being 450m. This covered a large portion of the Sea of Japan. Areas around Okushiri Island and west Hokkaido Island had a resolution of 150m and areas near Aonae and Monai had a 50m resolution grid. Another interesting result to come from this study was the effect of bathymetric resolution on the numerical model. Computations performed using the 150m grid were able to produce the correct distribution of heights along the coast, but failed to predict the extreme runup height. Calculations done using the 450m grid failed, by a significant margin, to correctly predict the distribution of runup heights most predictions seriously underestimated the correct distribution. This suggested to the researchers that the smallest scale features along the coast, and thus high-resolution bathymetry data, was essential in accurate prediction of local

25 inundation patterns. This is important because while wavelength measurements can be interpolated to produce higher resolution data, coarse topographical measurements, when interpolated, retain the same resolution (Titov and Synolaksis, 1997). Tsunami waves overtopping a peninsula or other narrow strip of land, is known as overland flow. It is a more challenging scenario to model when using the shallow water theory, and has been identified as a leading cause of casualties and physical damage associated with tsunami inundation (Synolakis et al., 1995). Though runup measurements may not suggest an extreme event, high flow velocities can cause extensive damage. This usually supercritical flow occurs because while the slope of a shoreline converts the initial kinetic energy of the tsunami into potential energy, the kinetic energy of overland flow is reduced only by dissipation. In the Hokkaido-Nansei-Oki tsunami event, the peninsula at Anoae Cape exhibited such overland flow in the model, and observations taken after the event also suggested low-level, high velocity flow (Titov and Synolaksis, 1998). Figure 8.3.3: Modeled maximum tsunami heights and maximum wave velocities over a cross-section of Aonae Cape (Titov and Synolaksis, 1998). Figure 8.3.3: Modeled maximum tsunami heights and maximum wave velocities over a cross-section of Aonae Cape shows the computed maximum velocities and wave amplitudes for a typical section of the Aonae Cape. It illustrates that while the highest amplitudes occurred on the western side of the peninsula, maximum flow velocities were much higher for the eastern side of the peninsula, and coincided with the lowest amplitudes. This area, however, was the scene of most devastation, suggesting that inundation heights alone are not the best indicator of tsunami danger.

26 A hydraulic shock, or standing bore, was another phenomenon predicted by the MOST model for this tsunami. The bore was formed on the west side of the Anoae peninsula from the rundown of the first wave of the tsunami. This resulted in the retreat of the waterline to the 10m contour, approximately 500m from the shoreline. While it was not reported in any eyewitness accounts (possibly due to the fact that the tsunami occurred at night), numerous accounts of distant water withdrawal for other tsunami events can be found, indirectly supporting the calculated estimates (Titov and Synolaksis, 1998). In addition, field estimates of overland flow for the peninsula of 10-18m/s (Shimamato et al., 1995) are consistent with computed values of 10-19m/s (Titov and Synolaksis, 1997), further illustrating the usefulness of the MOST model, especially in examining inundation. 8.3.2.2 Andreanov event The Andreanov tsunami, which occurred on June 10 1996, provided an early opportunity to test the generation and propagation algorithms of the model. This was the example used in the announcement of the MOST algorithms (Titov and Gonzalez, 1997). Several bottom pressure records (BPRs) from the Andreanov event were compared to the time series generated by the MOST model, demonstrating the model s accuracy and usefulness. The generation and propagation sections of the model were used to simulate the 1996 Andreanov tsunami, with results in good agreement to field measurements taken (Titov and Gonzalez, 1997).

27 Figure 8.3.4: Comparison between computed (red) and measured (blue) water levels for various offshore locations in the Andreanov tsunami event (Titov and Gonzalez, 1997). Through the inversion of seismic data, the initial parameters of the earthquake were estimated and entered into the model. The strike, dip, slip and moment were estimated using this method and the Harvard CMT solution (Nettles,

28 2006) for this event. The distribution of aftershocks gave an estimate of the fault length, and the relationship between the moment, the shear modulus, area of the slip gave the magnitude of the slip. The parameters gained from this rough estimation were input to the elastic earthquake model. This gave an initial deformation which was then assumed to be identical to the ocean surface initial deformation. This was the input for the MOST model. The window of the tsunami model was 50 North-South, and 60 East-West with a bathymetric resolution of 4 minutes (Titov and Gonzalez, 1997). Despite being a relatively small tsunami, with amplitudes in the range of 10mm, the model performed well at matching the measured waveforms. It also successfully predicted measured anomalies such as the interactions between the continental shelf and the Aleutian Trench. Titov and Gonzalez (1997) also discuss the runup model testing using the example of Okushiri Island. In particular they conclude that the MOST model is well suited to creating tsunami hazard and forecasting services. Modeling in this study was carried out at 6.5 times real-time, and Titov and Gonzalez suggest that advances in computer architecture could see speed improvement factors in the range of 10-100 times. This means that if input parameter collection becomes more streamlined, real-time forecasting / prediction could become useful. The study also emphasises the modular nature of tsunami forecasting, matching the modular nature of the MOST model. However, the study also outlines problems with this idea. The acquisition of initial earthquake parameters is all-important for modeling tsunamigenic events and currently there is a lot of estimation involved with this. The simulations themselves can only be assumed reliable after many iterative computations conducted by an experienced tsunami modeller (Titov and Gonzalez, 1997). A later study used the MOST model to simulate the same event, aiming to find the sensitivity of tsunami propagation to various parameters describing the fault. These included length, width, dip, strike and slip angle. With this information, a database of pre-computed scenarios varying the most sensitive parameters could be produced. Since tsunami propagation is a linear process in the deep ocean, this

29 would allow addition of sources multiplied by factors to reproduce complex faulting along known fault lines (Titov et al., 1999). An important choice for this particular study was of stiffness, µ. This parameter varies between 1e+10 and 6e+10, and was chosen as 4.5e+10, an average for this area. By eliminating the variation of parameters to which the tsunami was not particularly sensitive, the database was greatly simplified while still producing useful results (Titov et al., 1999). Numerical analyses conducted in this study revealed that only the first wave in the train carried significant information about the source. Later waves were strongly affected by reflection/refraction. Analytical methods were first used to provide a constraint to numerical parameters and guide the modeling stricture. Small scale features not having a great spatial extent nor extending very far into the water column were shown to be negligible in tsunami attenuation. Larger scale features such as the Emperor Seamount chain / Hawaiian ridge did have the effect of wave channelling or guiding. Thus the propagation section of the model did not require greatly detailed bathymetry (Titov et al., 1999), unlike inundation. Large fields of seamounts did provide some attenuation of the tsunami, but since these are resolved in the large scale bathymetry, it is taken into account by the model. Thus the primary attenuation method of tsunamis in the deep ocean was through spreading refraction from a finite source (Titov et al., 1999). Since the vast majority of historical tsunamigenic earthquakes in the AASZ were both shallow and aligned with the fault, varied parameters were limited to length, width, dip, slip and location. Location proved to be the parameter tsunamigenesis was most sensitive to. Variations in the location (along the existing fault) of the generating earthquake affected arrival time and amplitude as well as the period and shape of the wave train. Period and shape of the leading wave was effected far less. With a constant magnitude, the tsunami proved to be very insensitive to initial fault dimensions. Variations in rake within the common range also had very

30 limited impact on the tsunami characteristics. However lowering the dip from 20 to 10 increased the leading wave amplitude by 30%. The outcome of these results was that tsunami waves are characterised primarily by the source earthquake s magnitude and location. The linear nature of the propagation equations used in the model also lends itself to using combinations of closely spaced models to simulate multiple-fault sources. (Titov et al., 1999) suggest that such a database could be used by an experienced modeller to adjust factors of each earthquake model in order to find a solution which matched real-time data and thus produce forecasts which are adjusted as data becomes available. The study goes on to suggest that the next step is to produce site specific inundations forecasts as a function of offshore tsunami characteristics. This would lead to an inundation scenario database for specific areas which could be used in conjunction with forecasts of propagation (Titov et al., 1999). 8.3.2.3 Chimbote Event The earthquake off the coast of Peru, on the February 21, 1996, was a good example of a highly tsunamigenic event, despite the magnitude of the earthquake being relatively small. An earthquake of this type can be more damaging to coastal communities, many of whom may not even be aware that a seismic event has occurred (BOURGEOIS et al., 1999). Bathymetry and topography data for this area was relatively poor, and consisted of four on-land profiles, as well as a 9 km grid of bathymetry data. These were merged and interpolated down to a 600m resolution in the near-shore area using data from nautical charts. This level of resolution was too poor for accurate inundation calculations, and so the method of 10m depth threshold computations was used instead (Titov and Synolaksis, 1997), except in areas with high resolution 1-D transact information available. The Harvard CMT solution (Nettles, 2006) was used extensively when working on this model, providing the fault parameters such as strike, dip and rake. Dimensions of the fault were determined by looking at the distribution of aftershocks also listed in the Harvard CMT solutions. Accurate reproduction of the tsunami itself required several trials with slight adjustments to the various parameters. This helps

31 to illustrate the inherent problems with rapid and accurate modeling of tsunamis. The use of the CMT solution in this example, though criticised to some extent, produced results not noticeably different to that calculated using an inverted seismic source (BOURGEOIS et al., 1999). The advantage of this is that CMT solutions are available almost in real-time, giving a distinct advantage to tsunami forecasting. Several areas of the coastline had a local maximum of inundation which wasn t reproduced in any of the models. One of these areas was at the deepest point of a small cove, while another was near the city of Trujillo, Peru. These served to illustrate the need for higher resolution bathymetry in order to produce accurate calculations of runup. Bourgeois (1999) noted that runup discrepancies noted near Trujillo could equally be a result of multiple source faults, and it would require another study using higher resolution local bathymetry to resolve this. The one of the four areas of higher bathymetric resolution was at an area of sandbar. This allowed the modeling of the overtopping, which matched the Okushiri overtopping model (Titov and Synolaksis, 1997). 8.4 Real-time tsunami simulation with MOST The Holy Grail of tsunami forecasting would be the ability to perform greater than real-time tsunami simulation, assimilating real-time data into the model as the information became available (Titov et al., 1999). However this is difficult for various reasons including: Insufficient real-time data. Lack of accuracy in data and in model. For example fault parameters, especially preliminary ones, are estimated using empirical formulas which attempt to relate magnitude to size and slip amount. Though it is quite simple to monitor areas at risk for seismic disturbances, it is very difficult to predict the type of faulting which has led to the disturbances. In fact, even many months after the event, further investigations continue to adjust the precise nature of the fault model in a seismic event. Another problem is with the modeling itself. MOST still requires a considerable amount of quality control, judgement, and iterative, exploratory

32 computations to be conducted on a scenario before it is considered to be a reliable simulation. Titov and Gonzales (1997) recommend the creation of a database of precomputed and carefully analysed scenarios which can be referred to in order to construct a robust tsunami forecasting and hazard assessment capability. In fact, such a database has already been created for the Pacific Ocean region, and is planned for the Indian Ocean (Canterford et al., 2006). 8.5 Tsunami Risk Assessment for Western Australia For Australia in general, the historical threat of tsunamis comes from distant sources (Canterford et al., 2006). While it is true that Australia s intraplate location leads to a low siesmicity compared to interplate locations, it remains one of the most active intraplate locations in the world, especially in Western and Central Australia. This is due largely to the northward shift of the Indo-Australasian tectonic plate and its resultant compression (Brown and Gibson, 2004). In fact, while earthquakes with a magnitude greater than Mw 6.0 do occur, they are relatively infrequent and seem to be mostly non-tsunamigenic. Underwater slippage of sediments off the continental shelf is a concern in some areas (Canterford et al., 2006), and this effect is suspected to have contributed to the tsunamigenic properties of some recent earthquakes such as the 1998 Papua New Guinea tsunami event in the Indian Ocean (Synolakis et al., 2002).

33 Figure 8.5.1: Seismicity Australia, Indonesia and New Zealand 1977 1997 (Canterford et al., 2006) The current Australian Tsunami Alert System (ATAS) relies on co-operation between the Bureau of Meteorology (BoM), Geosciences Australia (GA) and Emergency Management Australia (EMA). In the event of an earthquake, GA notifies the National Meteorological and Oceanographic operations Centre (NMOC) of the BoM with the details of the event. Together, the organisations try to predict the likelihood of a tsunami and its probable characteristics. As well as its own sea level data, the NMOC currently relies heavily on warnings and other information from the Pacific Tsunami Warning Centre (PTWC) in Hawaii and the Japan Meteorological Agency (JMA) about possible tsunamis in the Indian ocean (Canterford et al., 2006). These warnings are then disseminated through current meteorological warning system infrastructure by the BoM. In response to the 2004 Sumatra tsunami, the Australian government recognised the need for a tsunami warning system similar to that deployed in the Pacific. This system is to be known as the Australian Tsunami Warning System (ATWS). In the mean time, the ATAS will be gradually upgraded and eventually integrated with the ATWS.

34 8.5.1 Current recommendations Previously published studies of tsunami events have produced recommendations which can be generally applied. These recommendations form the basis for a real-time tsunami forecasting capability (Titov et al., 2004). Modeling of a range of tsunami scenarios and maintaining a database of such scenarios is an important part of ensuring preparedness for tsunami events, as is remote sensing (Titov et al., 2004). Both this technology and a network of water level meters need to be applied together in order to provide effective warnings to coastal communities in the event of a tsunami. Deep ocean tsunami wave gauges, or tsunameters, are especially important as they provide several advantages over the traditionally used coastal water level meters. One important advantage of deep ocean tsunameters is the response time to a tsunami event. Since tsunami waves travel much more quickly in deep water than in shallow coastal areas, these tsunameters allow rapid tsunami observation. A strategically placed network of such gauges would allow early detection of tsunamis threatening a relatively large area of coastline compared to coastal water level meters. Harbour response, or seiching, can contaminate recorded tsunami frequencies. This is especially true of water level meters located outside harbour and along the coast (Synolakis, 2003). Because tsunameters are located in deep water far from the coast, they are unaffected by these local effects and are able to more accurately record the full spectrum of the tsunami wave (Titov et al., 2004). The strong linearity of the tsunami wave in the deep ocean, along with well understood and accurate models of wave propagation allow the use of tsunameter data to relatively accurately predict tsunami size and direction. The accuracy of this prediction is certainly much greater than that relying on relatively complex coastal wave data (Titov et al., 2004).

35 9 Research Motivation and Aim The danger of tsunami inundation to coastal communities, outlined in the introduction, represents a clear threat to Western Australia. Concern about this threat provided most of the motivation for this study. However simple curiosity about the nature of tsunamis in the Indian Ocean was also a strong motivation. As well as being a terrible natural disaster, tsunamis are a fascinating, powerful, and rarely documented force of nature. By their nature, tsunamigenic earthquakes are impossible to accurately predict. Historically, there is relatively little information available about tsunami events and inundation in relation to Australia, especially the WA coast. A dearth of field data related to tsunamis in the Western Australian context meant that in order to investigate tsunami impacts on the WA coast, it was required to carry out modeling of tsunami events. My research involves the use of a well-tested numerical model (MOST) to perform the following investigations: Predict areas of high risk in relation to Western Australia along the section of the Sumatran fault closest to Australia. By selecting a large area of the Sumatran/Australian subduction zone in which to model source earthquakes, I aim to be able to predict the areas of the fault which produce tsunamigenic earthquakes having the most significant impact on Western Australia. The position of the earthquake and orientation of the fault, as discussed in the literature review, has a major effect on the resultant areas affected by a tsunami. Source location and orientation were chosen on the basis of being close to WA, having fault orientation which directed energy towards WA, and being in line with historic tsunamigenic earthquakes. Predict areas of high risk along WA coast.

36 As previous modeling studies as well as previous tsunami events have shown, the coastal areas of maximum inundation in a tsunami event are difficult to predict. Patterns of inundation are not intuitive and are strongly related to the bathymetry of the offshore zone adjacent to the coastline. Even post event modeling has difficulty in reproducing the observed runup patterns in some cases. For this reason, it is important to investigate whether there are areas of the Western Australian coastline which are subject to a concentration of tsunami energy. Investigate bathymetric / topographic features responsible for observed and future tsunami propagation patterns. Previous modeling, especially in the Pacific and areas around Japan, has shown that offshore bathymetric features can have a strong effect on the distribution of tsunami energy (Mofjeld et al., 2004, Titov and Synolaksis, 1997). Various effects have been observed, such as waves scattering, wave guidance and refraction, as well as focusing of tsunami energy. This can cause specific areas of coastline to be either relatively protected from or relatively susceptible to tsunami impact in a majority of scenarios. By modeling a series of different tsunami events along the fault area, it should be possible to determine these areas along the coast of Western Australia. This will allow the identification of susceptible areas along the Western Australian Coast.

37 10 Methodology As mentioned previously, the lack of field data for tsunamis is a major constraint on studies in the area. Accurate collection of field data is important in confirming the accuracy of models. Western Australia has extremely sparse population over much of its coast. This, combined with a historically low incidence of tsunami inundation in populated areas has meant that in the past there has been little interest in conducting surveys of tsunami inundation along the Western Australian coast. This attitude has been changed in light of the Sumatran tsunami event of 2004. For example, Geoscience Australia conducted a survey of inundation at Steep Point following the reports of tsunami impact in the area following the Javanese earthquake of 17 July 2006 (Prendergast, 2006). This work is yet to be published. Due to the lack of repeatable field measurement inherent in tsunami study, the major research area of this study was in numerical modeling. It was important to initially decide on the boundaries of the area used for modeling. Since we were mostly interested in measuring impacts on the Western Australian coast, the area had to include both the length of the source fault along which we wanted to test, and the area of the Western Australian coast we were examining. One major constraint on modeling was the memory of the computer which the model was run on. Modeling was conducted using the IVEC facility specifically the Carlin computer. Limitations on memory meant that the scenarios had to be run in pairs. It also meant that the entire Indian Ocean and Western Australian coast could not be used in the model. Instead, spatial extent of the model was limited to the area 100 to 117 E, and -5 to -35 N. This enclosed both a large extent of the fault and the south-west of Western Australia, as well as a large area of ocean between the two and west of Australia, important for investigating the projected impacts of bathymetry on tsunami propagation. The bathymetric data used in this study was sourced from the General Bathymetric Chart of the Oceans (GEBCO). This data has a one minute resolution and was suitable for use as input to the MOST model in the propagation phase

38 (British Oceanographic Data Centre, 2006, International Hydrographic Organisation et al., 2006). 10.1.1 Modeled source location Seven hypothetical source earthquakes were chosen along the Sumatran fault, to the south of the active deformation zone of the Sunda trench. The precise locations were every two degrees between 103 and 115 E inclusive. The latitude of the sources was chosen to be equivalent to the position just north of the deformation zone at the Sumatran fault, to an accuracy of one degree. This area is historically the most earthquake prone, as well as being most likely to produce tsunamigenic earthquakes. The precise locations used are tabulated below in Table 10.1.1-1, as well as shown in the plot in Figure 8.5.2. Figure 8.5.1 also shows historical earthquakes in the area as well as tsunamigenic events within the modeled domain. 1 2 3 4 5 6 7 Latitude ( ) -6-7 -8-9 -9-10 -11 Longitude ( ) 103 105 107 109 111 113 115 Table 10.1.1-1: Location of source tsunamigenic earthquakes modeled.

39 N Figure 8.5.1: Recorded earthquakes of magnitude >4.0 shown as small circles. Tsunamigenic events on record shown as larger circles (Tsunami Laboratory, 2005).

40 Christmas Island Exmouth Plateau Wallaby Extension Cuvier Abyssal Plain Karratha Exmouth Wallaby Plateau Carnarvon Steep Point Geraldton Perth N Figure 8.5.2: The domain over which modeling took place, with significant features marked. Location of tsunami sources within the domain used in numerical modeling indicated by crosses (Tsunami Laboratory, 2005, Robb et al., 2005).

41 10.1.2 Modeled source parameters The MOST model accepts several source parameters describing the orientation, magnitude and type of fault occurring. These parameters include the length and width of the source, the dip, rake, strike and slip amount, as well as the depth of the fault. The parameters used were kept constant between sources modelled, and were chosen based on typical values for that section of fault, using data from the USGS historical tsunami database (USGS Earthquake Hazards Program, 2006) and Harvard CMT Catalog (Nettles, 2006) as a basis. The parameters used are tabulated below in Table 10.1.1-1. Length (km) 100 Width (km) 50 Dip ( ) 25 Rake ( ) 90 Strike ( ) 299 Slip amount (m) 10 Depth (km) 10 Resultant Moment Magnitude 8.2 Table 10.1.2-1: Parameters used for all source earthquakes in the MOST numerical model. As shown in Figure 8.5.3, the parameters above completely describe the simple faulting mechanism. The length and width describe the horizontal area of the fault, and are an estimate of the extent of the fault. The depth of the fault describes the distance to the top of the fault area from the top of the earths crust. The slip amount describes the average amount of movement between the opposing sides of the fault.

42 Ocean floor North Fault Line δ ΦS Slip Direction Strike Direction λ δ: Dip ( ) ΦS: Strike Azimuth ( ) λ: Rake ( ) Figure 8.5.3: Diagram showing relationship of source parameters to fault. 10.1.3 Running the MOST model The MOST model was run using the facilities of the Interactive Virtual Environments Centre s (IVEC) Carlin server. Each scenario was run as a separate process, with two scenarios being run simultaneously. Constraints on memory allocation for the model programme limited the number of simultaneous scenarios which could be run. Each scenario took several hours to complete. Each scenario was run to simulate a period of 300 minutes, or 5 hours. This meant that each wave had propagated completely through the domain by the end of the model. This allowed the construction of a series of snapshots of water heights, as well as a plot of maximum heights throughout the event for each scenario. This showed clearly where tsunami energy was being directed against the Western Australian coast and throughout the rest of the domain. These plots are listed in the Results section. Various locations just offshore of population centres were analysed for wave heights predicted over the course of the event. This gives a fairly good indication of potential tsunami inundation. For reasons discussed in the Literature Review, the inundation component of the MOST model could not be used in this study, due to the lack of detailed topographic information for large sections of the Western

43 Australian coastline. These plots of water heights over the course of the event are also listed in the Results section.

11 Results The results of the numerical modeling are presented in two sections. The first section consists of a plot of maximum wave heights over the domain of the model for each of the seven scenarios. The second section shows plots of water heights for locations just offshore of population centres on the Western Australian coast. These locations are Karratha, Exmouth, Carnarvon, Steep Point, Geraldton and Perth.

Figure 8.5.1: Maximum water heights over the domain for Scenario 1. 45

46 Figure 8.5.2: Maximum water heights over the domain for Scenario 2.

Figure 8.5.3: Maximum water heights over the domain for Scenario 3. 47

48 Figure 8.5.4: Maximum water heights over the domain for Scenario 4.

Figure 8.5.5: Maximum water heights over the domain for Scenario 5. 49

50 Figure 8.5.6: Maximum water heights over the domain for Scenario 6.

Figure 8.5.7: Maximum water heights over the domain for Scenario 7. 51

52 Figure 11.8: Water level predicted offshore of Karratha for the duration of Scenario 1 Figure 11.9: Water level predicted offshore of Exmouth for the duration of Scenario 1

53 Figure 11.10: Water level predicted offshore of Carnarvon for the duration of Scenario 1 Figure 11.11: Water level predicted offshore of Steep Point for the duration of Scenario 1

54 Figure 11.12: Water level predicted offshore of Geraldton for the duration of Scenario 1 Figure 11.13: Water level predicted offshore of Perth for the duration of Scenario 1

55 Figure 11.14: Water level predicted offshore of Karratha for the duration of Scenario 2. Figure 11.15: Water level predicted offshore of Exmouth for the duration of Scenario 2.

56 Figure 11.16: Water level predicted offshore of Carnarvon for the duration of Scenario 2. Figure 11.17: Water level predicted offshore of Steep Point for the duration of Scenario 2.

57 Figure 11.18: Water level predicted offshore of Geraldton for the duration of Scenario 2. Figure 11.19: Water level predicted offshore of Perth for the duration of Scenario 2.

58 Figure 11.20: Water level predicted offshore of Karratha for the duration of Scenario 3. Figure 11.21: Water level predicted offshore of Exmouth for the duration of Scenario 3.

59 Figure 11.22: Water level predicted offshore of Carnarvon for the duration of Scenario 3. Figure 11.23: Water level predicted offshore of Steep Point for the duration of Scenario 3.

60 Figure 11.24: Water level predicted offshore of Geraldton for the duration of Scenario 3. Figure 11.25: Water level predicted offshore of Perth for the duration of Scenario 3.

61 Figure 11.26: Water level predicted offshore of Karratha for the duration of Scenario 4. Figure 11.27: Water level predicted offshore of Exmouth for the duration of Scenario 4.

62 Figure 11.28: Water level predicted offshore of Carnarvon for the duration of Scenario 4. Figure 11.29: Water level predicted offshore of Steep Point for the duration of Scenario 4.

63 Figure 11.30: Water level predicted offshore of Geraldton for the duration of Scenario 4. Figure 11.31: Water level predicted offshore of Perth for the duration of Scenario 4.

64 Figure 11.32: Water level predicted offshore of Karratha for the duration of Scenario 5. Figure 11.33: Water level predicted offshore of Exmouth for the duration of Scenario 5.

65 Figure 11.34: Water level predicted offshore of Carnarvon for the duration of Scenario 5. Figure 11.35: Water level predicted offshore of Steep Point for the duration of Scenario 5.

66 Figure 11.36: Water level predicted offshore of Geraldton for the duration of Scenario 5. Figure 11.37: Water level predicted offshore of Perth for the duration of Scenario 5.

67 Figure 11.38: Water level predicted offshore of Karratha for the duration of Scenario 6. Figure 11.39: Water level predicted offshore of Exmouth for the duration of Scenario 6.

68 Figure 11.40: Water level predicted offshore of Carnarvon for the duration of Scenario 6. Figure 11.41: Water level predicted offshore of Steep Point for the duration of Scenario 6.

69 Figure 11.42: Water level predicted offshore of Geraldton for the duration of Scenario 6. Figure 11.43: Water level predicted offshore of Perth for the duration of Scenario 6.

70 Figure 11.44: Water level predicted offshore of Karratha for the duration of Scenario 7. Figure 11.45: Water level predicted offshore of Exmouth for the duration of Scenario 7.

71 Figure 11.46: Water level predicted offshore of Carnarvon for the duration of Scenario 7. Figure 11.47: Water level predicted offshore of Steep Point for the duration of Scenario 7.

72 Figure 11.48: Water level predicted offshore of Geraldton for the duration of Scenario 7. Figure 11.49: Water level predicted offshore of Perth for the duration of Scenario 7.

74 12 Discussion The maximum wave height plots over the entire domain are extremely informative in describing the offshore characteristics of the tsunami propagation. There are four specific effects of bathymetric features on tsunami waves which have been described to some extent previously for the Pacific Ocean, but to a much lesser extent for the Indian Ocean, especially not in relation to Western Australia. These effects are: Wave scattering / reflection Structures producing wave shadow Wave refraction Shallow wave guides Each particular scenario will be discussed, describing the most important features, and then the characteristics shown overall will be discussed. Finally, the implications for the coastline of Western Australia will be considered. 12.1 Scenario 1 Model location: 103 E, -6 N. The first scenario modelled was the greatest distance from the Western Australian coast. This source earthquake in this scenario was located just south of the island of Sumatera. In this location, the scattering and shadowing effects of offshore bathymetry is readily apparent. The location of Christmas Island and its surrounding areas of shallow bathymetry directly between the source of the tsunami and population centres on the Western Australian Coast, as well as lack of bathymetric features to direct energy towards the coast, means that there is relatively little tsunami impact on the Western Australian coast. However, there is significant refraction and concentration, of what tsunami energy reaches the coast, by offshore bathymetry. The southern edge of the Exmouth Plateau causes significant refraction of tsunami energy, which is concentrated towards the area of coast around Exmouth. This refractive effect also affects the water levels predicted offshore of Karratha, as the refracted waves arrive less than 15

75 minutes after the direct tsunami wave, with a height almost a large. Exmouth, however, experiences an initial tsunami wave followed by a significantly larger refracted wave. In the plot of wave heights for Carnarvon a similar pattern is observed. The initial tsunami wave height is matched 15 minutes later by a second wave. This is then followed almost 50 minutes later by a third, even larger, wave. By studying the animation of the tsunami event, the source of the second wave is recognised to be the complex bathymetry to the west of Christmas Island. Being directly in the path of the tsunami, even the reduced reflection caused by this feature is significant at the Western Australian Coast. The third wave recorded much later is a result of scattering and reflection of tsunami energy by the Wallaby Extension. This is the relatively shallow area of ocean to the west of the Wallaby Plateau scatters and reflects a significant amount of tsunami energy. Since it is also close to the direct path of the tsunami, it scatters enough energy to be responsible for the maximum wave height offshore of Carnarvon. In this scenario, offshore of Steep Point records relatively small maximum water levels of less than 10 cm above MSL. The angle of incidence of the tsunami wave leads to a focusing of energy further north, more towards Carnarvon. For this reason, while the basic pattern of wave heights is similar between Steep Point and Carnarvon, the effects at Steep Point are on a much smaller scale. The Wallaby Plateau causes significant refraction as well as focusing of energy through the bridge of shallow water between the large shallow offshore plateau, and the coastline. Despite the relatively small amount of tsunami energy which reached the coast at Western Australia, there was significant wave heights predicted for areas affected by the bathymetry. Thus, for these areas, water level meters which detect tsunamis by water level changes may not show a significant tsunami passing while some areas of the coast are still devastated. Geraldton and Perth exhibit a similar pattern of wave heights to each other, and for largely similar reasons. The initial tsunami impact is followed by a peak attributable to the reflection from the Wallaby Extension. The difference between

76 these locations and those further north is the spike in wave heights almost 5 hours after the tsunami event. By further examination of the animation of the event, this can be attributed to reflection from the large plateau to the west of cape Leeuwin. 12.2 Scenario 2 Model location: 105 E, -7 N. The second scenario modelled was interesting because of the greater heights recorded along the coast than scenario 1, despite the apparent shadowing of the tsunami energy by Christmas Island. The energy here was scattered by features around Christmas Island, especially the shallow areas to the southwest. Since the majority of the initial tsunami energy was not directed towards the Western Australian coast, this meant that the scattering effects actually directed more energy towards the coast than would have occurred otherwise. This is visible in the increased maximum heights offshore of Perth. The same refractive and focusing effects of the Exmouth Plateau and The Wallaby Plateau seen in scenario 1 are visible. The heights are increased in the area of the coast affected by the Wallaby Plateau, as in the metropolitan area. An interesting effect is that the coastline south of Karratha experiences lower maximum water heights than in the previous scenario. The reason for this is the scattering effect of the bathymetry southwest of Christmas Island. Much of the energy is deflected, though not to a great enough extent to reach the Exmouth Plateau. The tsunami energy is deflected more to the south than to the west. The pattern of wave heights for Karratha and Exmouth show a similar pattern of three maximum wave heights. After the initial tsunami impact, the second wave is a result of scattering near the tsunami source. The third wave, just over 30 minutes later at Exmouth and almost an hour later at Karratha, is again a result of the scattering effect of the Wallaby Extension. While the water level offshore of Carnarvon shows the impact of the initial wave followed by the reflection of the Wallaby Extension, the water levels at Steep Point exhibits two smaller waves followed by a single, very large wave. This clearly shows the effect of the refraction and focusing around the Wallaby Plateau. In the

77 position offshore of Steep Point, there is a distinct series of three waves which have a period of approximately 10 minutes. The first two waves which reached the position here are smaller, with a maximum excursion from MSL of less than 10 centimetres. This represents the wave travelling directly from the earthquake source, and the wave reflected from the island of Java. The third wave peak is preceded by a trough of almost 30 centimetres below MSL, and then reaches a height of almost 50 centimetres above MSL. This represents the concentration of wave energy by the Wallaby plateau, which is refracted from its original direction towards the coast at Steep Point. The extent of the concentration of wave energy is significant because it is collected from over the area of the plateau. The angle of incidence of the tsunami wave to the plateau is responsible for the difference between this scenario and the previous one. Here, the energy is refracted almost directly towards Steep Point, while in scenario 1, it was directed further north. The water depth at this position is 106 metres and so a deviation from MSL of almost 40 centimetres is significant. Though it is not possible to accurately predict inundation heights above MSL at the coast without more detailed bathymetric information, a wave of this size is certainly large enough to cause damage to coastal structures and property. Again, Geraldton and Perth are relatively unaffected, with deviation from MSL of less than 10 cm offshore. 12.3 Scenario 3 Model location: 107 E, -8 N In the third scenario, there are similar scattering effects near the source to that seen in scenario 2, though to a much greater extent. The majority of the tsunami energy is directed towards Christmas Island, perpendicular to the Sumatran fault. This leads to a much greater scattering effect than that which was observed in the previous two scenarios. The reflective scattering effect of the shallow areas to the southeast of Christmas Island is also significant.

78 The tsunami energy is directed towards the Wallaby Plateau, which strongly refracts the wave towards the coast. The reflective effect of the Wallaby Extension is lessened in this case because it is shielded by the bathymetry surrounding Christmas Island. The Exmouth Plateau refracts and focuses tsunami energy around the southern edge of the Exmouth plateau, towards the coastline between Karratha and Carnarvon. In this scenario there is a strong reflection, from the island of Java, of the tsunami heading north from the source. This causes a secondary wave of similar amplitude to the initial tsunami wave at the Western Australian coast. The complexity of tsunami waves is also illustrated in the comparison between the water heights for the duration of the event at Exmouth and at Steep Point. Exmouth experiences a series of waves of similar amplitude over a period of about 100 minutes. Steep Point, on the other hand, experiences a series of small amplitude waves, followed by one having an amplitude four times that of the other waves. Once again, the water height data from Steep Point indicates that there is a strong refractive effect occurring in the offshore area of Wallaby Plateau. Though less pronounced than in scenario 2, the maximum heights of the series of waves remains at about the magnitude of 10 cm, before the third wave in the train reaches a maximum of almost 40 cm above MSL. This tsunami energy refracted towards the coast by the Wallaby Plateau is represented in both the Carnarvon and the Steep Point wave profiles. In the Carnarvon profile, the refracted wave arrives at almost the same time as the source wave reflected by Java; hence the small spike in water height immediately before the large refracted wave. At Steep point, due to the greater distance the refracted wave has to travel over shallow bathymetry, it arrives slightly after the two direct tsunami waves. The effect of the initial scattering of tsunami energy near the source is exhibited in the smaller maximum wave height recorded here compared to the previous scenario. Once again, the areas offshore of Geraldton and Perth are largely unaffected by the tsunami, recording a maximum excursion from MSL of less than 6 cm.

79 12.3.1 17 th July 2006 Java tsunami On the 17 th July 2006, a tsunami devastated the southern coastline of the island of Java, killing over 500 people (USGS Earthquake Hazards Program, 2006). The location of the earthquake source of this tsunami was extremely close to the source modeled in Scenario 3. A relatively large tsunami was reported at Steep Point. According to surveys carried out by Geoscience Australia, the tsunami inundation reached a vertical height of roughly 10 metres above MSL, making this tsunami event the largest recorded in Australia (Prendergast, 2006). Anecdotal evidence collected from eyewitnesses by the Geoscience Australia survey team suggested that there was a series of waves similar to that predicted in Scenario 3. Witnesses reported a series of three waves with the second wave being much larger than the others (Prendergast, 2006). This matches quite well with the water levels predicted for Steep Point in Scenario 3. Because the initial tsunami wave was small compared to the others and the water level rose over the course of about 15 minutes, it may not have been as noticeable as the following three significant sharp rises in water level. This tsunami is one of the first to be surveyed in Western Australia. 12.4 Scenario 4 Model location: 109 E, -9 N The dispersal of energy both offshore and along the coastline of Western Australia is significantly different in Scenario 4 compared to any of the previous scenarios. The most obvious aspect of this is the direction of the initial tsunami energy. Since the source of the tsunami along the Sumatran fault is several hundred kilometres east of Christmas island, the scattering effects of this obstacle and the bathymetry surrounding it are minimised. This means that the majority of the tsunami energy is directed in a perpendicular direction to the fault. This direction runs almost parallel to the coast and straight out into the Indian Ocean, with very little dispersal effects. For this reason, though the source of the tsunami is very much closer to the Western Australian coastline than in Scenario 3, there is not a massive increase in wave heights along the coast. The bathymetry around the source causes

80 the tsunami energy heading south to be split into two main branches, one of which is directed almost parallel to the Western Australian coast. The refractive effects of the Exmouth plateau and the Wallaby plateau still dominate the patterns of wave heights along the coast. Offshore of Karratha experiences a very different pattern of waves compared to the previous scenarios. The initial tsunami wave is followed by two much larger waves, and then one which is slightly smaller. Inspection of a series of stages of the model again allows the derivation of the wave s source. The first of the larger waves is result of reflection from the island of Java, back towards Australia. It is larger because the reflection angle directs the energy towards the Exmouth Plateau. The second wave is a result of the scattering caused by the bathymetry in the direct path of the initial wave. It is larger again due to the reflection of the energy in the main path of the tsunami towards the wave guide of the Exmouth Plateau, which focuses tsunami energy. The third wave is a result of the very strong refractive properties of the southern edge of the Exmouth Plateau. The path of the wave here is so strongly refracted that it is directed back up towards Karratha, running almost parallel to the coastline. Part of this wavefront is visible in the plot of wave heights for Exmouth, where the initial tsunami wave, already increased in magnitude by the refractive effects of the Exmouth Plateau, is followed by a second larger wave. The wave heights offshore of Carnarvon are difficult to attribute to the effects of reflection and refraction by the plateaus in this scenario. The large secondary wave is possibly a result of small scale refraction or reflection from the northern area, however the scale of the model makes this difficult to determine. The area at Steep Point remains a focus of wave energy, recording a large maximum wave height compared with the surrounding coast. However, the wave train over the course of the event at this point is quite different to the previous scenarios. While the previous scenario had two small waves, followed by a much larger refracted wave, scenario 4 has a single small wave followed by two larger waves. The two secondary waves can be attributed to reflection of first the initial

81 tsunami wave and then the reflection from Java by the Wallaby Plateau which then focuses this energy towards Steep Point. Again, the deviation from MSL in the area of Geraldton and Perth is less than 8 cm. The maximum water level for Geraldton is higher than in the previous scenario due to reflection from Wallaby Plateau. 12.5 Scenario 5 Model location: 111 E, -9 N Scenario 5 clearly illustrates the scattering and wave guiding effects of bathymetry. The source is extremely close to an area of relatively shallow water (200m deep) south of Java. The shallow ridge running parallel to the fault in this area serves to guide the wave north-east, back towards Sumatera. What little energy is directed south is split into three main components. The direction of the main path of tsunami energy is perpendicular to the fault as might be expected. A small shallow area southwest of the source causes wave energy to be refracted towards it, thus drawing energy in a southwest direction to an area south of Christmas Island. However a significant amount of energy is refracted by the bathymetry southwest of the source and is concentrated and guided by a bridge of shallow water between java and Western Australia. This joins onto the northern part of the Exmouth Plateau, and then propagates towards the coast, again in the area between Karratha and Carnarvon. However due to much of the wave energy being dissipated by the initial scattering effects near the source, the maximum wave heights predicted along the coast in this scenario are less than in the previous two scenarios. This is despite the fact that these two scenarios were significantly further west (2 longitude at this latitude = 220 km horizontal distance, and similarly 4 = 440 km). Offshore of Karratha experiences a series of tsunami waves at a period of around 20 minutes. The relatively large number of similarly sized waves for Karratha and Exmouth in this scenario reflects the strong scattering of the tsunami at its source. Another effect of the strong scattering is the relatively small excursion of the water level from MSL, despite the proximity of the source.

82 The Carnarvon plot of wave heights once again shows the effect of the refraction around the Wallaby Plateau, which is represented by the second, much larger wave in the train. The maximum water level for Steep Point is only Water levels offshore Geraldton and Perth again show a very small response to the tsunami. In fact, the response is considerably smaller than that for previous scenarios, even though the source of the tsunami is closer. The strong scattering of the tsunami energy at the source, as well as the guiding effect of the two plateaus serve to shield the southwest of Western Australia from much of the tsunami energy. 12.6 Scenario 6 Model location: 113 E, -10 N. Scenario 6 has entirely different characteristics to any of the previous scenarios. The source of the tsunami in this scenario is at a position where two ridges of shallow bathymetry branch towards the south-west and south-east. The bathymetry directly perpendicular to the fault in this location is deep and flat an abyssal plain. This effectively splits the tsunami energy in half, with one portion headed towards the deep ocean to the southwest, and the other along the bridge of shallow water towards the Exmouth plateau offshore of northwest Western Australia. This bridge acts as an extremely strong wave-guide, which is clearly illustrated by the path of maximum wave heights all the way along it. This energy is concentrated along the wave guide and is directed along the coastline inshore of the Exmouth plateau once again the area between Karratha and Carnarvon, and offshore of Exmouth. The guidance of a significant fraction of the tsunami energy towards this area of coast combined with the physically closer location of the source means that the wave heights recorded here are much greater than in any of the previous scenarios. In fact, the area offshore of Exmouth recorded the highest excursion above MSL with this scenario. The wave guide from the tsunami source to the top of the Exmouth Plateau provides a direct path for the tsunami energy to the area offshore of Exmouth. However a significant proportion of the tsunami energy travels perpendicular to the fault and travels through deep ocean to the southern

83 edge of the Exmouth Plateau. Here the effect of energy refracted around the Exmouth Plateau is visible, in the plot of maximum wave heights. The large initial wave in the area offshore of Exmouth is a result of this refracted wave and the wave travelling directly from the tsunami source crossing and reinforcing at this location. Carnarvon and Steep Point again experience initial peaks in wave height followed by a higher peak provided by the refracted wave energy of the Wallaby Plateau. Perth and Geraldton are again shielded from the majority of the tsunami energy by the guiding effects of the two plateaus, and the scattering effects of bathymetry at the tsunami s source. 12.7 Scenario 7 Model location: 115 E, -11 N. This scenario, as well as being physically closest to Western Australia, has very little scattering effects close to the source. The majority of the energy released is directed perpendicularly to the fault, parallel to the north-western edge of the Exmouth Plateau. As in previous scenarios, the shallow area concentrates the wave energy as it is refracted towards the coast. While most of the tsunami energy is directed away from the Western Australian coast, a significant portion of the energy of the tsunami is guided by the Exmouth plateau and directed once again to the coastline between Karratha and Carnarvon, offshore of Exmouth. The strong refractive effect of the Exmouth plateau is visible on the southern edge in this scenario. Wave energy is strongly refracted towards the coast, which results in the maximum water level in this area of almost 30 cm. Some of the energy also propagates across the edge of the Exmouth plateau and hits the Wallaby plateau which once again directs energy towards Steep Point. This effect is responsible for the maximum wave height at this location. The wave energy is again concentrated in the Steep Point area in comparison to the immediately adjacent coastline. However the tsunami impact here is insignificant compared to that inshore of the Exmouth Plateau.

84 Geraldton and Perth, largely shielded from the tsunami waves by the northwestern coastline of Western Australia record relatively insignificant wave heights less than 2.5 cm in height. 12.8 Overall Overall effects of the bathymetric features offshore of Western Australia on tsunami wave train can be summarised into general effects for all the scenarios discussed above. Two of the most important bathymetric features are directly offshore of the Western Australian Coastline. These are the Exmouth Plateau, to the west of Karratha, and the Wallaby Plateau, including the Wallaby Extension, to the west of Carnarvon. These two relatively shallow areas of offshore bathymetry have a strong effect on the pattern of maximum wave heights along the Western Australian Coastline in a tsunami event. In every scenario the Wallaby Plateau, and the bridge of shallow water between the plateau and the shallow coastal zone, significantly refracted wave energy towards the coast, especially the area around Steep Point. This effect, while visible in every scenario, more significantly affected the pattern of maximum wave heights along the coast in some. The strength of the effect relates strongly to the angle of incidence of the tsunami energy and thus the location of the tsunami. The Wallaby Plateau, and its extension, also reflects tsunami energy. This effect is responsible for the delayed maximum wave height along the coast and can be clearly seen in Figure 12.8.1.

85 Wallaby Plateau Wallaby Extension Figure 12.8.1: Scenario water heights after 2.5 hours. Reflective effects of Wallaby Extension and Wallaby Plateau indicated. The southwest of Western Australia, including Geraldton and the major population centres around Perth, are not affected to the same extent as the areas to the north which have been previously discussed. The reasons for this, as has been shown in the modeling, are twofold. Firstly, Perth is simply at a much greater distance from the source fault. The dissipation of energy over this distance is much greater than that for Karratha, Carnarvon or Steep Point. Secondly, and perhaps more importantly, is the bathymetry offshore of Perth. As can be seen in the maps of bathymetry shown in Figure 8.5.2, the continental shelf is at one of its narrowest points near Perth. There is no significant offshore structure similar to the Exmouth and Wallaby Plateaus to the Northwest, and for this reason the tsunami energy from the Sumatran fault is not refracted in the same way as it is in coastal areas to the north. Much of the wave energy travelling directly from the source fault is uninterrupted and continues travelling parallel to the coast and towards the southern ocean.