<div>The A1 poster incorporates 4 images of Australia taken from space by Earth observing satellites. The accompanying text briefly introduces sensors and the bands within the electromagnetic spectrum. The images include examples of both true and false colour and the diverse range of applications of satellite images such as tracking visible changes to the Earth’s surface like crop growth, bushfires, coastal changes and floods. Scientists, land and emergency managers use satellite images to analyse vegetation, surface water or human activities as well as evaluate natural&nbsp;hazards.</div>

The Risk Research Group at Geoscience Australia (GA) in Canberra is a multidisciplinary team engaged in the development of risk models for a range of natural hazards that are applicable to Australian urban areas. The Group includes hazard experts, numerical modellers, engineers, economists, and a specialist researching social vulnerability. The risk posed by riverine flooding to residential buildings is an important component of the work undertaken by the Group and is the focus of this paper. In 1975 researcher Richard Black published a report titled Flood Proofing Rural Residences as part of a multidisciplinary investigation of flood risk management in the USA. Black's research produced a number of curves describing combinations of water depth and velocity theoretically required to move a flooded house from its foundations. These so-called 'Black's Curves' have been referenced by numerous researchers worldwide since their publication. The houses used in Black's study are small by modern standards, and construction materials used in Australia can differ from those used in Black's research.

ACRES acquired SPOT 2 satellite images over the Namoi River, between the towns of Walgett and Wee Waa in December 1997 and November 2000. The November 2000 image consists of 12 scenes in which floodwaters, peaking at 8 metres, inundating the region are visible as green and light blue. Extensive flooding is evident. The December 1997 image shows the area of the Namoi River without floodwaters. The Namoi River catchment area is more than 350 kilometres long and stretches from Walcha in the east to Walgett in the west. Other river systems in the region include the Gwydir, Castlereagh, Hunter, Macquarie, Macleay, Manning, Culgoa and Condamine. You can find these rivers on Geoscience Australia's interactive Map of Australia.

Every year floods cause millions of dollars damage to buildings and infrastructure, as well as to agricultural land and crops. They also disrupt business, and affect the safety and health of communities. The losses due to flooding vary widely from year to year and are dependent on a number of factors such as the severity of a flood and its location. Between 1967 and 2005 the average annual direct cost of floods in Australia has been estimated at AUD$377 million (BITRE 2008). This figure is likely to have risen following the widespread and devastating floods across eastern Australia that occurred over the summer of 2010-11.

The increasing availability of high-resolution digital elevation models (DEMs) is leading to improvements in flood analysis and predictions of surface-groundwater interaction in floodplain landscapes. To produce accurate predictions of flood inundation and calculations of flood volume, a 1m resolution LiDAR DEM was initially levelled to the Darling River floodplain by subtracting interpolated floodplain elevation trend surface from the DEM. This produces a de-trended flood-plain surface. Secondly, the levelled DEM surface was adjusted to the water-level reading at the Darling-River gauging station (Site 425012) at the time when the LiDAR was acquired. Flood extents were derived by elevation slicing of the adjusted levelled DEM up to any chosen river level. River-level readings from historical and current events utilised NSW Office of Water real-time river data. The flood-depth dataset is an inverted version of the flood-extent grid. Predicted flood depth and extent were classified by depth/elevation slice ranges of the adjusted de-trended DEM with 25 and 50 cm increments. In summary, the extent and depth of water inundation across the Darling floodplain have been predicted under different flooding scenarios, and validated using satellite data from historical (1990) and recent (2010/11) flood events. In all cases imagery and photo validation proved that predicted extents are accurate. The flood-risk predictions were then applied to a number of river-level scenarios. The flood risk predictions maps have been used as an input into developing recharge potential maps, and are being employed in flood-hazard assessments and infrastructure planning.

In this study, a 1 m resolution LiDAR Digital Elevation Model (DEM) has been used for predictive flood modelling and flood-risk assessment that will inform recharge studies. To produce accurate predictions of flood inundation and calculations of flood volume, the DEM was initially levelled to the Darling River floodplain by subtracting interpolated floodplain elevation trend surface from the DEM. This produces a de-trended floodplain surface. Secondly, the levelled DEM surface was adjusted to the water level reading at the Darling River gauging station (Site 425012), upstream of Weir 32, at the time when the LiDAR was acquired. Flood extents were derived by elevation slicing of the adjusted levelled DEM up to any chosen river level. River-level readings from historical and current events were extracted from the NSW Office of Water real time river data website. The flood-depth dataset is an inverted version of the flood extent grid. Predicted flood depth and extent were classified by depth/elevation slice ranges of the adjusted de-trended DEM with 25 and 50 cm increments. Predicted flood extents have been validated by comparisons to satellite images from the 1990 floods, and photographs of inundation from recent flood events. In all cases imagery and photo validation proved that predicted extents are accurate. The flood-risk predictions were then applied to a number of river level scenarios. These included (1) examination of the extent of flooding at the highest historical level; (2) determination of the river level required to completely inundate the Coonambidgal Formation scroll plain in the GWMAR1 study area (probable maximum recharge potential) and (3) an assessment of flood impacts in 0.5 m increments from 5.5 to 7 m of river level rise at the Site 425012 gauging station. In summary, this flood modelling methodology has been used to predict the extent and depth of water coverage across the Darling floodplain under different scenarios.

The National Flood Risk Informaiton Project (NFRIp) has produced a flyer for the Engineers Australia Convention on 24-28 November 20014 where the Australian Rainfall and Runoff (ARR) guidelines will be promoted. NFRIP funded the revision of the guidelines as part of a $12m funding initiative by the Australia Government. The flyer promotes the three core activities of NFRIP; the Australian Flood Risk Information Portal (AFRIP), revision of Australian Rainfall and Runoff guidelines and Water Observations from Space (WOfS).

This paper introduces the work of the National Flood Risk Advisory Group in providing advice and guidance on the management of flood risk in Australia, in particular its work on the development of a set of national guidelines. The guidelines are included as an appendix and they highlight that communities utilise the support and cooperation of departments and agencies across all levels of government to effectively access the broad range of skills and the funding essential to implement flood risk management solutions. The paper discusses the more important flood risk considerations embodied in the guidelines.

The flood risk in many urban catchments is poorly understood. Legacy stormwater infrastructure is often substandard and anticipated climate change induced sea level rise and increased rainfall intensity will typically exacerbate present risk. In a Department of Climate Change and Energy Efficiency (DCCEE) funded collaboration between Geoscience Australia (GA) and the City of Sydney (CoS), the impacts on the Alexandra Canal catchment have been studied. This work has built upon detailed flood hazard analyses by Cardno commissioned by the CoS and has entailed the development of exposure and vulnerability information. Significantly, the case study has highlighted the value of robust exposure attributes and vulnerability models in the development of flood risk knowledge. The paper describes how vulnerability knowledge developed following the 2011 Brisbane floods to include key building types found in the inner suburb of Sydney. It also describes the systematic field capture of building exposure information in the catchment area and its categorisation into 19 generic building types. The assessment of ground floor heights using the Field Data Analysis Tool (FiDAT) developed at Geoscience Australia is also presented. The selected hazard scenario was a 100 year ARI event with 20% increased rainfall intensity accompanied by a 0.55m sea level rise in Botany Bay. The impact from the selected scenario was assessed in terms of monetary loss for four combinations of vulnerability model suite (GA and NSW Government) and floor height attribution method (assumed 0.15m uniformly and evaluated from LiDAR and street view imagery). It was observed that the total loss is higher in the case of assumed floor heights compared to FiDAT processed floor heights as the former failed to capture increased floor heights for newer construction. However, the loss is lower when only two vulnerability models developed by NSW Government are applied for the entire building stock in the region as two models could not reliably represent the whole building stock.

In this paper a new benchmark for tsunami model validation is pro- posed. The benchmark is based upon the 2004 Indian Ocean tsunami, which provides a uniquely large amount of observational data for model comparison. Unlike the small number of existing benchmarks, the pro- posed test validates all three stages of tsunami evolution - generation, propagation and inundation. Specifically we use geodetic measurements of the Sumatra{Andaman earthquake to validate the tsunami source, al- timetry data from the jason satellite to test open ocean propagation, eye-witness accounts to assess near shore propagation and a detailed inundation survey of Patong Bay, Thailand to compare model and observed inundation. Furthermore we utilise this benchmark to further validate the hydrodynamic modelling tool anuga which is used to simulate the tsunami inundation. Important buildings and other structures were incorporated into the underlying computational mesh and shown to have a large inuence of inundation extent. Sensitivity analysis also showed that the model predictions are comparatively insensitive to large changes in friction and small perturbations in wave weight at the 100 m depth contour.