<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>

Floods are Australia's most expensive natural hazard with the average annual cost of floods 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 development of tools to support the identification and analysis of flood risk is an important first step in reducing the cost of floods in the community. The Australian Government through Geoscience Australia (GA) has been leading the development of tools which assist in flood intelligence, modelling and damage assessment. An overview of three of these tools will be provided in this presentation. Note: Rest of abstract is too long for space provided.

Widespread flooding and associated damage in south-east Queensland during January and February, 2011 have demonstrated the importance of flood risk assessment. Flood risk assessment requires knowledge of the hazard, nature of properties exposed and their vulnerability to flood damage. Flood risk assessment can addresses different aspects of flood risk, i.e., hydrological, structural, economic and social aspects. This report presents the results of work undertaken by Geoscience Australia during 2011-2012 to further the understanding of the vulnerability of Australian buildings to inundation. The work consists of three parts: 1. Development of vulnerability curves for inundation, without velocity, of residential homes of the types encountered during surveys following the January, 2011 flooding in south-east Queensland. 2. Development of vulnerability curves for inundation, without velocity, of building types typical of the Alexandria Canal area of the inner south of Sydney. 3. Development of vulnerability curves for inundation with velocity (storm surge) of residential homes of the types encountered during surveys following TC Yasi, February, 2011.

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.

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 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.

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.

In this study, various hydrochemical approaches were used to understand recharge processes in shallow (<120m) unconsolidated alluvial sediments in a 7,500 km2 area of the Darling River floodplain. Pore fluids were extracted from sediments from 60 sonic-cored bores, and together with surface and groundwater samples, provided a hydrochemical dataset with over 1600 samples and 25 analytes. Major ion chemistry highlights a mixing signature between river waters, the shallow unconfined aquifer and the underlying semi-confined Calivil Formation aquifer. These represent the fresh groundwater resources near the river and are Na-(Ca-Mg)-HCO3-Cl waters. Away from the influence of river leakage, the regional groundwater is more saline and sodic with an evolved Na-Cl-SO4 watertype. The mixing associated with river leakage is also supported by age dating. Stable isotope data show that recharge is episodic and linked to high-flow flood events rather than continuous river leakage, as demonstrated by hydrographic monitoring. The combination of surface water and groundwater sampling, the pore fluid analyses and fuzzy-k means (FCM) cluster analysis, provides a novel, relatively simple but powerful tool to assist with interpretation of groundwater processes. The FCM cluster analysis used analytes that were present in at least 60% of samples and resulted in samples being classified into eight classes (or hydrochemical facies). Pore fluids and groundwater with the greatest affinity to the surface water samples were easily identified. In this way, sites with significant active recharge, principally by river leakage, were mapped. Downhole plots of the pore fluid FCM classes provided additional insights into groundwater processes. Comparing the FCM classification of pore fluids within the target (semi)confined aquifer with those from the overlying clay aquitard and shallow aquifer allowed the assessment of vertical inter-aquifer leakage.

The satellite images below show the dramatic effect on the land of recent heavy rain, causing floodwaters to inundate south-west Queensland. This area is known as the Channel Country and has an extensive braided river system which includes the Georgina River, the Diamantina River and Cooper Creek. Excess water from this area generally feeds into the Lake Eyre system which is a vast drainage basin in Australia's arid interior. Flooding of the magnitude visible on the satellite images can cause Lake Eyre to fill up - something which occurs very rarely.

The map shows the spatial distribution of short-duration rapid-onset floods and long-duration slow-rise floods. The Great Dividing Range in eastern Australia provides a natural separation of slower, wider rivers flowing west from faster, narrower coastal rivers flowing east.