Geoscience Australia, in an open collaboration with the Mathematical Sciences Institute, The Australian National University, is developing a software application, ANUGA, to model the hydrodynamics of floods, storm surges and tsunamis. The free source software implements a finite volume central-upwind Godunov method to solve the non-linear depth-averaged shallow water wave equations. In light of the renewed interest in tsunami forecasting and mitigation, this paper explores the use of ANUGA to model the inundation of the Indian Ocean tsunami of December 2004. The Method of Splitting Tsunamis (MOST) was used to simulate the initial tsunami source and the tsunami's propagation at depths greater than 100m. The resulting output was used to provide boundary conditions to the ANUGA model in the shallow water. Data with respect to 4-minute bathymetry, 2-minute bathymetry, 3-arc second bathymetry and elevation were used in the open ocean, shallow water and on land, respectively. A particular aim was to make use of the comparatively large amount of observed data corresponding to this event, including tide gauges and run-up heights, to provide a conditional assessment of the computational model's performance. Specifically we compared model tsunami depth with data collected at two tide gauges and 18 coastal run-up measurements. Comparison between observed and modelled run-up at 18 sites show reasonable agreement. We also find modest agreement between the observed and modelled tsunami signal at the two tide gauge sites. The arrival times of the tsunami is approximated well at both sites. The amplitude of the first trough and peak is approximated well at the first tide gauge (Taphao-Noi), however the amplitude of the first wave was underestimated at the second gauge (Mercator yacht). The amplitude of subsequent peaks and troughs, at both gauges, are underestimated and a phase lag between the observed and modelled arrival times of wave peaks is evident after the first peak. The performance of the model could be improved by using finer bathymetric data, which at present cannot be obtained by the authors. The bathymetry data used was insufficient. Local topographic features, such as small islands and shoreline elevations near run-up locations are not accurately represented. The arrival time and tsunami height could also be improved by calibrating the tsunami source on observed data such as the satellite transect of Jason 1 following the procedure of Grilli et al. (2006). Improving modelled results through finer bathymetric data and source calibration is the focus of future work.
