The exposure of Sydney (Australia) to earthquake-generated tsunamis, storms and sea level rise: a probabilistic multi-hazard approach

Approximately 85% of Australia's population live along the coastal fringe, an area with high exposure to extreme inundations such as tsunamis. However, to date, no Probabilistic Tsunami Hazard Assessments (PTHA) that include inundation have been published for Australia. This limits the development of appropriate risk reduction measures by decision and policy makers. We describe our PTHA undertaken for the Sydney metropolitan area. Using the NOAA NCTR model MOST (Method for Splitting Tsunamis), we simulate 36 earthquake-generated tsunamis with annual probabilities of 1:100, 1:1,000 and 1:10,000, occurring under present and future predicted sea level conditions. For each tsunami scenario we generate a high-resolution inundation map of the maximum water level and flow velocity, and we calculate the exposure of buildings and critical infrastructure. Results indicate that exposure to earthquake-generated tsunamis is relatively low for present events, but increases significantly with higher sea level conditions. The probabilistic approach allowed us to undertake a comparison with an existing storm surge hazard assessment. Interestingly, the exposure to all the simulated tsunamis is significantly lower than that for the 1:100 storm surge scenarios, under the same initial sea level conditions. The results have significant implications for multi-risk and emergency management in Sydney.

[1]  V. Titov,et al.  Direct energy estimation of the 2011 Japan tsunami using deep‐ocean pressure measurements , 2012 .

[2]  J. Goff,et al.  A synthesis and review of the geological evidence for palaeotsunamis along the coast of southeast Australia: The evidence, issues and potential ways forward , 2012 .

[3]  N. Booij,et al.  A third-generation wave model for coastal regions-1 , 1999 .

[4]  N. C. Nadal,et al.  Building Damage due to Riverine and Coastal Floods , 2010 .

[5]  F. Dall'Osso,et al.  A revised (PTVA) model for assessing the vulnerability of buildings to tsunami damage , 2009 .

[6]  Takashi Furumura,et al.  Three-dimensional simulation of tsunami generation and propagation: Application to intraplate events , 2009 .

[7]  Masson-Delmotte,et al.  The Physical Science Basis , 2007 .

[8]  F. Imamura,et al.  Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami , 2012, Natural Hazards.

[9]  Michael C. Spillane,et al.  Real‐time experimental forecast of the Peruvian tsunami of August 2007 for U.S. coastlines , 2008 .

[10]  J. Laronne,et al.  Applying Geomorphology to Environmental Management , 2002 .

[11]  Vasily Titov,et al.  Implementation and testing of the Method of Splitting Tsunami (MOST) model , 1997 .

[12]  B. Jones,et al.  Large-scale washover sedimentation in a freshwater lagoon from the southeast Australian coast: sea-level change, tsunami or exceptionally large storm? , 2008 .

[13]  Dale Dominey-Howes,et al.  Geological and historical records of tsunami in Australia , 2007 .

[14]  N. Booij,et al.  A third‐generation wave model for coastal regions: 2. Verification , 1999 .

[15]  Keping Chen,et al.  High‐resolution estimates of Australia's coastal population , 2006 .

[16]  V. Titov,et al.  Development, testing, and applications of site‐specific tsunami inundation models for real‐time forecasting , 2009 .

[17]  S. O’Farrell,et al.  Projected changes in climatological forcing for coastal erosion in NSW , 2007 .

[18]  Costas E. Synolakis,et al.  NOAA Technical Memorandum OAR PMEL-135 STANDARDS, CRITERIA, AND PROCEDURES FOR NOAA EVALUATION OF TSUNAMI NUMERICAL MODELS , 2007 .

[19]  H. L. Miller,et al.  Climate Change 2007: The Physical Science Basis , 2007 .

[20]  Vasily Titov,et al.  Modeling of the 2011 Japan Tsunami: Lessons for Near-Field Forecast , 2013, Pure and Applied Geophysics.

[21]  C. E. Synolakis,et al.  Validation and Verification of Tsunami Numerical Models , 2008 .

[22]  D. Blayney,et al.  Challenges and solutions. , 2007, Journal of oncology practice.

[23]  V. R. Schneider,et al.  GUIDE FOR SELECTING MANNING'S ROUGHNESS COEFFICIENTS FOR NATURAL CHANNELS AND FLOOD PLAINS , 1989 .

[24]  F. Dall'Osso,et al.  Assessing the vulnerability of buildings to tsunami in Sydney , 2009 .

[25]  Vasily V. Titov,et al.  Real-Time Tsunami Forecasting: Challenges and Solutions , 2003 .

[26]  Charitha Pattiaratchi,et al.  A New Tool for Inundation Modeling: Community Modeling Interface for Tsunamis (ComMIT) , 2011 .

[27]  D. Airey,et al.  Submarine Landslides on the Upper Southeast Australian Passive Continental Margin – Preliminary Findings , 2012 .

[28]  Vincent R. Gray.  Climate Change 2007: The Physical Science Basis Summary for Policymakers , 2007 .

[29]  David Burbidge,et al.  A Probabilistic Tsunami Hazard Assessment for Western Australia , 2008 .

[30]  K. McInnes,et al.  A numerical modelling study of coastal flooding , 2002 .

[31]  Hermann M. Fritz,et al.  The 2011 Japan tsunami current velocity measurements from survivor videos at Kesennuma Bay using LiDAR , 2012 .

[32]  B. Jones,et al.  On the Possible Origins of an Unusual (Mid to Late Holocene) Coastal Deposit, Old Punt Bay, South-East Australia , 2011 .