Evaluation of Australian Tsunami Warning Thresholds Using Inundation Modelling

  • Diana J. M. GreensladeEmail author
  • Burak Uslu
  • Stewart C. R. Allen
  • Claire L. Kain
  • Kaya M. Wilson
  • Hannah E. Power


Tsunami warnings issued by the Joint Australian Tsunami Warning Centre (JATWC) are derived from a database (T2) consisting of more than two thousand pre-computed tsunami scenarios. Following any potentially tsunamigenic earthquake, warnings are issued for individual coastal zones with three different levels of threat: Land Threat, Marine Threat or No Threat. The decision is based on the 95th percentile (P95) of the maximum wave amplitudes (over time) of the relevant T2 scenario within each coastal zone. Threshold values for P95 have previously been derived through analysis of observed impacts for recent events. Given that historical records are available for only a short time period and no observations exist for which a Land Threat would have been issued for Australia, it has been difficult to determine the appropriate threshold for a Land Threat. Several recent tsunami hazard assessment studies have used inundation models nested within T2 scenarios. These modelling results are used to evaluate the threshold values for JATWC tsunami warnings and provide guidance on a possible further warning tier—Major Land Threat. The optimal Land Threat threshold for P95 is found to be 48.5 cm, however, it is not recommended that any changes are made from the existing operational threshold of 55 cm. The optimal threshold for P95 a Major Land Threat is found to be 150.5 cm.


Tsunami tsunami warning inundation modelling 



The authors would like to thank the NSW Office of Environment and Heritage (OEH), the NSW State Emergency Service (NSW SES), and Cardno for providing the inundation modelling results used in this study. This work was partly funded by the Natural Disaster Mitigation Program through NSW SES. This work was also funded through an award from the NSW Government under the State Emergency Management Projects 2014–15 program to HEP. KMW is supported by a University of Newcastle Faculty of Science Strategic Scholarship (50:50). The authors would like to thank Robert Greenwood and Eric Schulz for useful comments on the text.


  1. Allen, S. C. R., & Greenslade, D. J. M. (2010). Model-based tsunami warnings derived from observed impacts. Natural Hazards and Earth System Science,10(12), 2631–2642.CrossRefGoogle Scholar
  2. Allen, S. C. R., & Greenslade, D. J. M. (2016). A pilot tsunami inundation forecast system for Australia. Pure and Applied Geophysics,173(12), 3955–3971. CrossRefGoogle Scholar
  3. Greenslade, D. J. M., & Allen, S. C. R. (2019) On the optimal amplitude thresholds for tsunami warning, Bureau Research Report no. 039. Australia: Bur. Met.Google Scholar
  4. Greenslade, D. J. M., Allen, S. C. R., & Simanjuntak, M. A. (2010). An evaluation of tsunami forecasts from the T2 scenario database. Pure and Applied Geophysics,168(6–7), 1137–1151. Scholar
  5. Greenslade, D. J. M., Simanjuntak, M. A., & Allen, S. C. R. (2009). An enhanced tsunami scenario database: T2. BMRC Research Report no. 014. Australia: Bur. Met.Google Scholar
  6. Kain, C. L., Mazengarb, C., Rigby, E. H., Cohen, W., Simard, G., & Lewarn, B. (2018). Technical report on tsunami inundation modelling in South East Tasmania, Tasmanian Geological Survey Record UR2018_02.Google Scholar
  7. Nielsen, O., Roberts, S., Gray, D., McPherson, A., & Hitchman, A. (2005). Hydrodynamic modelling of coastal inundation. MODSIM 2005 International Congress on Modelling and Simulation Modelling and Simulation Society of Australia and New Zealand. pp. 519–523.Google Scholar
  8. NSW State Emergency Service and Office of Environment and Heritage (2012). Final Draft NSW Tsunami Inundation Modelling and Risk Assessment, Cardno Technical report LJ2874/Rep2703Google Scholar
  9. Okada, Y. (1985). Surface deformation due to shear and tensile faults in a half-space. Bulletin of the Seismological Society of America,75, 1135–1154.Google Scholar
  10. Simanjuntak, M. A., Greenslade, D. J. M., & Allen, S. C. R. (2011). Extensions to the T2 tsunami scenario database, CAWCR Research Letters, Issue 7. Australia: Bur. Met.Google Scholar
  11. Somerville, P., Hanslow, D. J., & Gissing, A. (2009). NSW Tsunami Risk–An Overview of the NSW Risk Assessment Scoping Study. In Joint NSW and Victorian Flood Management Conference, Albury-Wodonga, February 2009.Google Scholar
  12. Stelling, G.S. (1984). On the construction of computational methods for shallow water flow problems. Tech. Rep. Rijkswaterstaat No. 35, Rijkswaterstaat. The Netherlands: The Hague.Google Scholar
  13. Stelling, G. S., & Duinmeijer, S. (2003). A staggered conservative scheme for every Froude number in rapidly varied shallow water flows. International Journal Numerical Methods In Fluids CrossRefGoogle Scholar
  14. Synolakis, C. E., Bernard, E. N., Titov, V. V., Kanoğlu, U., & Gonzalez, F. I. (2008). Validation and verification of tsunami numerical models. Pure Applied Geophysics,165(11–12), 2197–2228.CrossRefGoogle Scholar
  15. Titov, V., Kanoglu, U., & Synolakis, C. (2016). Development of MOST for Real-Time Tsunami Forecasting. Journal of Waterway Port Coastal and Ocean Engineering,. Scholar
  16. Titov, V. V., & Synolakis, C. E. (1998). Numerical modeling of tidal wave runup. Journal of Waterway Port Coastal and Ocean Engineering. 124(4), 157–171.CrossRefGoogle Scholar
  17. Uslu, B., & Greenslade, D. J. M. (2013). Validation of tsunami warning thresholds using inundation modelling, CAWCR Technical Report No. 062. Australia: Bur. Met.Google Scholar
  18. Wei, Y., Bernard, E. N., Tang, L., Weiss, R., Titov, V. V., Moore, C., et al. (2008). Real-time experimental forecast of the Peruvian tsunami of August 2007 for U.S. coastlines. Geophysical Research Letters,35, 1–7. Scholar
  19. Wilson, K. M., Allen, S. C. R., & Power, H. E. (2018). The tsunami threat to Sydney Harbour, Australia: Modelling potential and historic events. Scientific Reports,8(1), 15045.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Bureau of MeteorologyMelbourneAustralia
  2. 2.OMC InternationalMelbourneAustralia
  3. 3.Department of State GrowthHobartAustralia
  4. 4.University of NewcastleNewcastleAustralia

Personalised recommendations