Ocean Dynamics

, Volume 60, Issue 5, pp 1115–1138 | Cite as

Towards spatially distributed quantitative assessment of tsunami inundation models

  • John Davis JakemanEmail author
  • Ole M. Nielsen
  • Kristy Van Putten
  • Richard Mleczko
  • David Burbidge
  • Nick Horspool


This paper presents a framework and data for spatially distributed assessment of tsunami inundation models. Our associated validation test is based upon the 2004 Indian Ocean tsunami, which affords a uniquely large amount of observational data for events of this kind. Specifically, we use eyewitness accounts to assess onshore flow depths and speeds as well as a detailed inundation survey of Patong City, Thailand to compare modelled and observed inundation. Model predictions matched well the detailed inundation survey as well as altimetry data from the JASON satellite, eyewitness accounts of wave front arrival times and onshore flow speeds. Important buildings and other structures were incorporated into the underlying elevation model and are shown to have a large influence on inundation extent.


Tsunami Inundation Modelling Spatially distributed Verification Validation 



This project was undertaken at Geoscience Australia and the Department of Mathematics, The Australian National University. The authors would like to thank Niran Chaimanee from the CCOP for providing the post 2004 tsunami survey data, building footprints, satellite image and the elevation data for Patong City; Prapasri Asawakun from the Suranaree University of Technology and Parida Kuneepong for supporting this work; Drew Whitehouse from the Australian National University for preparing the animation of the simulated impact; Rick von Feldt for locating the Novotel from the video footage and for commenting on the model from and eyewitness point of view and Alex Apotsos for his extensive and extremely constructive comments and suggestions. This paper is published with the permission of the Chief Executive Officer, Geoscience Australia.


  1. Ammon C, Ji C, Thio H, Robinson D, Ni S, Hjorleifsdottir V, Lay HTL, Das S, Helmberger D, Ichinose G, Polet J, Wald D (2005) Rupture process of the 2004 Sumatra–Andaman earthquake. Science 308:1133–1139CrossRefGoogle Scholar
  2. Baldock TE, Morrison N, Shimamoto T, Barnes MP, Gray D, Nielsen O (2007) Application and testing of the ANUGA tsunami model for overtopping and coastal sediment transport. In: Coasts and ports.
  3. Bates P, Anderson M (2001) Model validation: perspectives in hydrological science. In: Chap. Validation of hydraulic models. Wiley, New York, pp 325–356Google Scholar
  4. Bilham R, Engdahl R, Feldl N, Satyabala S (2005) Partial and complete rupture of the Indo–Andaman plate boundary. Seismol Res Lett 76:299–311CrossRefGoogle Scholar
  5. Burbidge D, Cummins P, Mleczko R, Thio H (2008) A probabilistic tsunami hazard assessment for Western Australia. Pure Appl Geophys 165:2059–2088. doi: 10.1007/s00024-008-0421-x CrossRefGoogle Scholar
  6. Chlieh M, Avouac JP, Hjorleifsdottir V, Song THA, Ji C, Sieh K, Sladen A, Herbert H, Prawirodirdjo L, Bock Y, Galetzka J (2007) Coseismic slip and afterslip of the great MW 9.15 Sumatra–Andaman earthquake of 2004. Bull Seismol Soc Am 97(1A):S152–S173. doi: 10.1785/0120050631 CrossRefGoogle Scholar
  7. Chlieh M, Avouac JP, Hjorleifsdottir V, Song THA, Ji C, Sieh K, Sladen A, Herbert H, Prawirodirdjo L, Bock Y, Galetzka J (2007) Electronic supplement to Coseismic slip and afterslip of the great MW 9.15 Sumatra–Andaman earthquake of 2004. Bull Seismol Soc Am.
  8. Dao M, Tkalich P (2007) Tsunami propagation modelling–a sensitivity study. Nat Hazards Earth Syst Sci 7:741–754CrossRefGoogle Scholar
  9. Gahalaut VK, Nagarajan B, Catherine JK, Subhash K, Sinha MS (2006) Constraints on 2004 Sumatra–Andaman earthquake rupture from GPS measurements in Andaman–Nicobar islands. Earth Planet Sci Lett 242(3–4):365–374. doi: 10.1016/j.epsl.2005.11.051 CrossRefGoogle Scholar
  10. George D, LeVeque R (2006) Finite volume methods and adaptive refinement for global tsunami propagation and inundation. Sci Tsunami Hazards 24(5):319–328Google Scholar
  11. Gica E, Teng M, Liu PF, Titov V, Zhou H (2007) Sensitivity analysis of source parameters for earthquake-generated distant tsunamis. J Waterw Port Coast Ocean Eng 133(6): 429–441CrossRefGoogle Scholar
  12. Gower J (2005) Jason 1 detects the 26 December 2004 tsunami. EOS 86(4):37–38CrossRefGoogle Scholar
  13. Grilli S, Ioualalen M, Asavanant J, Shi F, Kirby J, Watts P (2006) Source constraints and model simulation of the December 26, 2004 Indian Ocean tsunami. J Waterw Port Coast Ocean Eng 133:414–428CrossRefGoogle Scholar
  14. Grilli S, Ioualalen M, Asavanant J, Shi F, Kirby J, Watts P (2007) Source constraints and model simulation of the December 26, 2004 Indian Ocean tsunami. J Waterw Port Coast Ocean Engineering 133(6):414–428. doi: 10.1061/(ASCE)0733-950X(2007)133:6(414). CrossRefGoogle Scholar
  15. Imamura F (2009) Tsunami modeling: calculating inundation and hazard maps. In: Bernard E, Robinson A (eds) The sea: tsunamis, vol 15. Harvard University Press, Cambridge, pp 321–332Google Scholar
  16. Ioualalen M, Asavanant J, Kaewbanjak N, Grilli ST, Kirby JT, Watts P (2007) Modeling the 26 December 2004 Indian Ocean tsunami: case study of impact in Thailand. J Geophys Res 112:C07024. doi: 10.1029/2006JC003850 CrossRefGoogle Scholar
  17. Arnold KAM, Carlin A (eds) (2003) Building safer cities: the future of disaster risk. In: Disaster risk management series. The World Bank, Washington, DCGoogle Scholar
  18. Kurganov A, Noelle S, Petrova G (2001) Semidiscrete central-upwind schemes for hyperbolic conservation laws and Hamilton–Jacobi equations. SIAM J Sci Comput 23(3): 707–740CrossRefGoogle Scholar
  19. Linsley R, Franzini J (1979) Water resource engineering. McGraw-Hill, New YorkGoogle Scholar
  20. Liu Y, Shi Y, Yuen D, Sevre E, Yuan X, Xing H (2009) Comparison of linear and nonlinear shallow wave water equations applied to tsunami waves over the China Sea. Acta Geotech 4(2):129–137. doi: 10.1007/s11440-008-0073-0 CrossRefGoogle Scholar
  21. Lukkunaprasit P, Ruangrassamee A, Thanasisathit N (2009) Tsunami loading on buildings with openings. Sci Tsunami Hazards 28(5):303–310Google Scholar
  22. Marks K, Smith W (2006) An evaluation of publicly available global bathymetry grids. Mar Geophys Res 27:19–34CrossRefGoogle Scholar
  23. Meltzner AJ, Sieh K, Abrams M, Agnew DC, Hudnut KW, Avouac JP, Natawidjaja DH (2006) Uplift and subsidence associated with the great Aceh–Andaman earthquake of 2004. J Geophys Res 111:B02407. doi: 10.1029/2005JB003891 CrossRefGoogle Scholar
  24. Myers E, Baptista A (2001) Analysis of factors influencing simulations of the 1993 Hokkaido Nansei-Oki and 1964 Alaska tsunamis. Nat Hazards 23(1):1–28CrossRefGoogle Scholar
  25. Nielsen O, Roberts S, Gray D, McPherson A, Hitchman A (2005) Hydrodynamic modelling of coastal inundation. In: Zerger A, Argent R (eds) MODSIM 2005 international congress on modelling and simulation. Modelling and Simulation Society of Australia and New Zealand, Christchurch, pp 518–523.
  26. Papadopoulos GA, Caputo R, McAdoo B, Pavlides S, Fokaefs AKV, Orfanogiannaki K, Valkaniotis S (2006) The large tsunami of 26 December 2004: field observations and eyewitnesses accounts from Sri Lanka, Maldives Is, and Thailand. Earth Planets Space 58:233–241Google Scholar
  27. Ramsden J (1996) Tsunamis forces on a vertical wall caused by long waves, bores, and surge on a dry bed. J Waterw Port Ocean Coast Eng 122(3):134-141CrossRefGoogle Scholar
  28. Roberts S, Nielsen O, Jakeman JD (2006) Simulation of tsunami and flash flood. In: International conference on high performance scientific computing: modeling, simulation and optimization of complex processes. Hanoi, VietnamGoogle Scholar
  29. Roberts S, Zoppou C (2000) Robust and efficent solution of the 2D shallow water wave equation with domains containing dry beds. The ANZIAM Journal 42(E):C1260–C1282Google Scholar
  30. Romano M, Liong SY, Vu M, Zemskyy V, Doan C, Dao M, Tkalich P (2009) Artificial neural network for tsunami forecasting. J Asian Earth Sci 36(1):29–37. doi: 10.1016/j.jseaes.2008.11.003. CrossRefGoogle Scholar
  31. Satake K (1995) Linear and nonlinear computations of the 1992 Nicaragua earthquake tsunami. Pure Appl Geophys 144(3):455–470CrossRefGoogle Scholar
  32. Shuto N (1991) Numerical simulation of tsunamis—its present and near future. Nat Hazards 4:171–191CrossRefGoogle Scholar
  33. Stein S, Okal E (2007) Ultralong period seismic study of the December 2004 Indian Ocean earthquake and implications for regional tectonics and the subduction process. Bull Seismol Soc Am 97(1A):S279–S295CrossRefGoogle Scholar
  34. Subarya C, Chlieh M, Prawirodirdjo L, Avouac JP, Bock Y, Sieh K, Meltzner A, Natawidjaja D, McCaffrey R (2006) Plate-boundary deformation associated with the great Sumatra–Andaman earthquake. Nature 440(2):46–51. doi: 10.1038/nature04522 CrossRefGoogle Scholar
  35. Synolakis C, Bernard E, Titov V, Kanoglu U, Gonalez F (2008) Validation and verification of tsunami numerical models. Pure Appl Geophys 165:2197–2228. doi: 10.1007/s00024-004-0427-y CrossRefGoogle Scholar
  36. Synolakis C, Okal E, Bernard E (2005) The megatsunami of December 26 2004. Bridge 35:26–35Google Scholar
  37. Szczucinski W, Chaimanee N, Niedzielski P, Rachlewicz G, Saisuttichai D, Tepsuwan T, Lorenc S, Siepak J (2006) Environmental and geological impacts of the 26 December 2004 tsunami in coastal zone of Thailand—overview of short and long-term effects. Pol J Environ Stud 15(5):793–810Google Scholar
  38. Taubenböck H, Goseberg N, Setiadi N, Lämmel G, Moder F, Oczipka M, Klupfel H, Wahl R, Schlurmann T, Strunz G, Birkmann J, Nagel K, Siegert F, Lehmann F, Dech S, Gress A, Klein R (2009) “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 Hazards Earth Syst Sci 9:1509–1528CrossRefGoogle Scholar
  39. Thio H, Somerville P, Inchinose G (2008) Probabilistic analysis of tsunami hazards in Southeast Asia. J Earthq Tsunami 1:119–137CrossRefGoogle Scholar
  40. Titov V, Gonzalez F (1997) Implementation and testing of the method of splitting tsunami (MOST) model. NOAA Technical MemorandumGoogle Scholar
  41. Usha T, Murthy M, Reddy N, Murty T (2009) Vulnerability assessment of car Nicobar to tsunami hazard using numerical model. Sci Tsunami Hazards 28(1):15–34Google Scholar
  42. Wang R, Martin FL, Roth F (2003) Computation of deformation induced by earthquakes in a multi-layered crust—FORTRAN programs EDGRN/EDCMP. Comput Geosci 29:195–207CrossRefGoogle Scholar
  43. Watts P, Ioualalen M, Grilli S, Shi F, Kirby J (2005) Numerical simulation of the December 26, 2004 Indian Ocean tsunami using a higher-order Boussinesq model. In: Ocean waves measurement and analysis 5th international symposiumGoogle Scholar
  44. Weiss R, Wunnemann K, Bahlburg H (2006) Numerical modelling of generation, propagation and runup of tsunamis caused by ocean impacts: model strategy and technical solutions. Geohpys J Int 167:77–88. doi: 10.1111/j.1365-246X.2006.02889.x CrossRefGoogle Scholar
  45. Wessel P, Smith W (1998) New, improved version of generic mapping tools released. EOS Trans AGU 79:579CrossRefGoogle Scholar
  46. Zhang Y, Baptista A (2008) An efficient and robust tsunami model on unstructured grids. Part I: inundation benchmarks. Pure Appl Geophys 165(11):2229–2248. doi: 10.1007/s00024-008-0424-7. CrossRefGoogle Scholar
  47. Zoppou C, Roberts S (1999) Catastrophic collapse of water supply reservoirs in urban areas. J Hydraul Eng 125(7):686–695CrossRefGoogle Scholar
  48. Zoppou C, Roberts S (2000) Numerical solution of the two-dimensional unsteady dam break. Appl Math Model 24:457–475CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • John Davis Jakeman
    • 1
    Email author
  • Ole M. Nielsen
    • 2
  • Kristy Van Putten
    • 2
  • Richard Mleczko
    • 2
  • David Burbidge
    • 2
  • Nick Horspool
    • 2
  1. 1.The Australian National UniversityCanberraAustralia
  2. 2.Geoscience AustraliaCanberraAustralia

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