The information within this document and associated DVD is intended to assist emergency managers in tsunami planning and preparation activities. The Attorney General's Department (AGD) has supported Geoscience Australia (GA) in developing a range of products to support the understanding of tsunami hazard through the Australian Tsunami Warning System Project. The work reported here is intended to further build the capacity of the NSW State Government in developing inundation models for prioritised locations.

This final paper for the session presents the results of the new draft earthquake hazard assessment for Australia and compares them to the previous AS1170.4 hazard values. Draft hazard maps will be presented for several spectral periods (0.0, 0.2 and 1.0 s) at multiple return periods (500, 2500 and 10,000 years). These maps will be compared with both the current earthquake hazard used in AS1170.4 and with other assessments of earthquake hazard in Australia. In general the hazard in the draft map is higher in the western cratonic parts of Australia than it is in the eastern non-cratonic parts of Australia. Where regional source zones are included, peaks in hazard values in the map are generally comparable to those in the current AS1170.4 map. When seismicity 'hotspot zones are included, as described in the previous paper, several of them produce much higher hazard peaks than any in the AS1170.4 map. However, such hotspots do not affect as large an area as many of those in the current AS1170.4 map. Finally, hazard curves for different cities will also be presented and compared to those predicted by the method outlined in AS1170.4.

Tsunami inundation models are computationally intensive and require high resolution elevation data in the nearshore and coastal environment. In general this limits their practical application to scenario assessments at discrete communiteis. This study explores teh use of moderate resolution (250 m) bathymetry data to support computationally cheaper modelling to assess nearshore tsunami hazard. Comparison with high ersolution models using best available elevation data demonstrates that moderate resolution models are valid (errors in waveheight < 20%) at depths greater than 10m in areas of relatively low sloping, uniform shelf environments. However in steeper and more complex shelf environments they are only valid at depths of 20 m or greater. Modelled arrival times show much less sensitivity to data resolution compared with wave heights and current velocities. It is demonstrated that modelling using 250 m resoltuion data can be useful in assisting emergency managers and planners to prioritse communities for more detailed inundation modelling by reducing uncertainty surrounding the effects of shelf morphology on tsunami propagaion. However, it is not valid for modelling tsunami inundation. Further research is needed to define minimum elevation data requirements for modelling inundation and inform decisions to undertake acquisition of high quality elevaiton data collection.

Geoscience Australia is supporting the exploration and development of offshore oil and gas resources and establishment of Australia's national representative system of marine protected areas through provision of spatial information about the physical and biological character of the seabed. Central to this approach is prediction of Australia's seabed biodiversity from spatially continuous data of physical seabed properties. However, information for these properties is usually collected at sparsely-distributed discrete locations, particularly in the deep ocean. Thus, methods for generating spatially continuous information from point samples become essential tools. Such methods are, however, often data- or even variable- specific and it is difficult to select an appropriate method for any given dataset. Improving the accuracy of these physical data for biodiversity prediction, by searching for the most robust spatial interpolation methods to predict physical seabed properties, is essential to better inform resource management practises. In this regard, we conducted a simulation experiment to compare the performance of statistical and mathematical methods for spatial interpolation using samples of seabed mud content across the Australian margin. Five factors that affect the accuracy of spatial interpolation were considered: 1) region; 2) statistical method; 3) sample density; 4) searching neighbourhood; and 5) sample stratification by geomorphic provinces. Bathymetry, distance-to-coast and slope were used as secondary variables. In this study, we only report the results of the comparison of 14 methods (37 sub-methods) using samples of seabed mud content with five levels of sample density across the southwest Australian margin. The results of the simulation experiment can be applied to spatial data modelling of various physical parameters in different disciplines and have application to a variety of resource management applications for Australia's marine region.

The quality and type of elevation data used in tsunami inundation models can lead to large variations in the estimated inundation extent and tsunami flow depths and speeds. In order to give confidence to those who use inundation maps, such as emergency managers and spatial planners, standards and guidelines need to be developed and adhered to. However, at present there are no guidelines for the use of different elevation data types in inundation modelling. One reason for this is that there are many types of elevation data that differ in vertical accuracy, spatial resolution, availability and expense; however the differences in output from inundation models using different elevation data types in different environments are largely unknown. This study involved simulating tsunami inundation scenarios for three sites in Indonesia, of which the results for one of these, Padang, is reported here. Models were simulated using several different remotely-sensed elevation data types, including LiDAR, IFSAR, ASTER and SRTM. Model outputs were compared for each data type, including inundation extent, maximum inundation depth and maximum flow speed, as well as computational run-times. While in some cases, inundation extents do not differ greatly, maximum depths can vary substantially, which can lead to vastly different estimates of impact and loss. The results of this study will be critical in informing tsunami scientists and emergency managers of the acceptable resolution and accuracy of elevation data for inundation modelling and subsequently, the development of elevation data standards for inundation modelling in Indonesia.

The ArcINFO grid is one of the outputs of a finescale hydrodynamic model, the Simulating WAves Nearshore (SWAN) model (Booij et al., 1999; Ris et al., 1999).The grid describes the modelled maximum orbital velocity (m/s) which can be used as estimation of seabed exposure on the Carnarvon Shelf.

The Tropical Cyclone Risk Model (TCRM) is a statistical-parametric model of tropical cyclone behaviour and effects. A statistical model is used to generate synthetic tropical cyclone events. This is then combined with a parametric wind field model to produce estimates of cyclonic wind hazard.

The major tsunami disaster in the Indian Ocean in 2004, and the subsequent large events off the south coast of Indonesia and in the Solomon Islands, have dramatically raised awareness of the possibility of potentially damaging tsunamis in the Australian region. Since the 2004 Indian Ocean Tsunami (IOT), a number of emergency management agencies have worked with Geoscience Australia to help to develop an understanding of the tsunami hazard faced by their jurisdictions. Here I will discuss both the major tsunamis over the last few years in the region and the recent efforts of Geoscience Australia and others to try to estimate the likelihood of such events in the future. Since 2004, a range of probabilistic and scenario based hazard assessments have been completed through collaborative projects between Geoscience Australia and other agencies in Australia and the region. These collaborations have resulted in some of the first ever probabilistic tsunami hazard assessments to be completed for Australia and for a wide range of other countries in the southwest Pacific and Indian Oceans. These assessments not only estimate the amplitude of a tsunami that could reach the coast but also its probability. The assessments allow crucial questions from emergency managers (such as 'Just how often do large tsunamis reach our coasts?) to be quantitatively addressed. In addition, they also provide a mechanism to prioritise communities for more detailed risk assessments. This work allows emergency managers to base their decisions on the best available science and data for their jurisdiction instead of relying solely on intuition.

Abstract for the final talk in the earthquake hazard map session planned for the 2011 AEES meeting.

Population connectivity research involves investigating the presence, strength and characteristics of spatial and temporal relationships between populations. These data can be used in many different ways: to identify source-sink relationships between populations; to detect critical pathways or keystone habitats; to find natural clusters or biogeographic regions; or to investigate the processes underlying population genetic structure, among others. This information can be of significant value for managers and decision-makers when designing reserve networks, evaluating the potential spread of invasive species. This database represents the first publicly-available collection of national/continental-scale marine connectivity data.