Modelling answers tsunami questions  issue 83 Sept 2006 Modelling answers tsunami questions New research will help emergency planners Ole Nielsen, Jane Sexton, Duncan Gray and Nick Bartzis Te Indian Ocean tsunami on 26 December 2004 demonstrated the potentially catastrophic consequences of natural hazards. In addition to humanitarian assistance, the Australian Government’s response included the establishment of the AustralianTsunami Warning System (ATWS) and greater priority for research into hazard and risk modelling of tsunami impacts. Determining tsunami risk Geoscience Australia aims to defne the economic and social threat posed to urban communities by natural hazards such as tsunamis. Predictions of the likely impacts of tsunamis can be made through the integration of earthquake and tsunami hazard research, community exposure and socioeconomic vulnerabilities. By modelling the likely impacts on urban communities as accurately as possible and building these estimates into land use planning and emergency management, we can better prepare communities to respond to tsunamis when they occur. One critical component in understanding tsunami risk is being examined by the Risk Assessment Methods Project (RAMP) at Geoscience Australia which has been developing a hydrodynamic inundation modelling tool developed specifcally to estimate the consequences of possible tsunami impacts on Australian communities. Modelling methodology Tsunami hazard models have been available for some time. Tey generally work by virtually converting the energy released by a subduction earthquake into a vertical displacement of the ocean surface. Te resulting wave is then propagated across a sometimes vast stretch of ocean using a relatively coarse linear model based on bathymetries with a typical resolution of two arc minutes. Te maximal wave height at a fxed contour line near the coastline (say, 50 metres) is then reported as the hazard to communities ashore. Models such as Method of SplittingTsunamis (MOST) (Titov & Gonzalez 1997) and the URS Corporation’s ProbabilisticTsunami Hazard Analysis (Somerville et al 2005) follow this paradigm. Te severity of a hydrological disaster is critically dependent on complex bathymetric and topographic efects near the area of interest. For example, during the 1993 Okushiri Island tsunami, a very large run‑up was observed at one specifc location, whereas surrounding areas received much less inundation (Matsuyama et al 1999). Estimating the impact of a tsunami on a particular community therefore requires modelling of the nonlinear process by which waves are refected and otherwise shaped by the local bathymetries and topographies. Tese complex efects generally require elevation data of much higher resolution than is used by the linear models, which typically use data resolutions in the order of hundreds of metres (sufcient to model long‑wavelength tsunamis in open water). Te data resolution used by nonlinear inundation models, by contrast, is typically in the tens of metres. Te ANUGA model (Nielsen et al 2005)—the result of collaboration between the Australian National University and Geoscience Australia—is suitable for this type of modelling. However, running a nonlinear model capable of resolving local bathymetric