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.

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.

User Manual - Australian Flood Studies Database Search

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.

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.

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.

Floods are Australia's most expensive natural hazard with annual average damages estimated at $377 million. Modelling flood hazard and potential flood impact is therefore an important first step in reducing the cost of floods to the community. The availability of a rigorously tested free software modelling tool for flooding would assist in meeting this objective. ANUGA is a collaborative effort of Geoscience Australia and the Australian National University and has gained increasing interest as an open source two-dimensional flood model. The development of ANUGA for flood modelling purposes has been guided and furthered through close consultation with a number of local government and consulting engineers. This paper highlights case studies where ANUGA has been used for both hydrological and hydraulic modelling. This paper also makes two broad recommendations. The first recommendation is for further model validation against historical flood events. Additional model comparison is also needed, particularly against other two-dimensional models. ANUGA should also be validated against a suite of hydraulic tests to provide confidence in ANUGA's ability to be used as a general purpose hydraulic model. The second broad recommendation is that the ANUGA software is further developed to make it comparable with other two-dimensional flood models. Priorities for this development include the ability to model structures (culverts, pipes and bridges), the addition of a kinematic viscosity term and the inclusion of discharge as an inflow boundary condition. The ability to incorporate variable bed elevation in models, account for water storage in buildings and consider spatially and depth varying Manning's friction 'n' are also important. The development of a graphical (geographical information systems) user interface would make ANUGA more accessible.

<b>This record was retired 15/09/2022 with approval from S.Oliver as it has been superseded by eCat 146091 DEA Water Observations Statistics (Landsat)</b> In previous versions of WOfS, the basic water classifications, statistical summaries and confidence products were contained within one product with several datasets. As of version 2.1.5, WOfS is split into three products: Water Observation Feature Layers (WO_25_2.1.5), Summary Statistics (WO-STATS_25_2.1.5), and Filtered Summary Statistics (WO-FILT-STATS_25_2.1.5). This product is Water Observations from Space - Filtered Statistics (WO-FILT-STATS), consisting of a Confidence layer that compares the WO-STATS water summary to other national water datasets, and the Filtered Water Summary which uses the Confidence to mask areas of the WO-STATS water summary where Confidence is low. The Filtered Water Summary provides the long term understanding of the recurrence of water in the landscape, with much of the noise due to misclassification filtered out. WO-FILT-STATS consists of the following datasets: Confidence: the degree of agreement between water shown in the Water Summary and other national datasets. The Confidence layer provides understanding of whether the water shown in the Water Summary agrees with where water should exist in the landscape, such as due to sloping land or whether water has been detected in a location by other means. Filtered Water Summary: A simplified version of the Water Summary, showing the frequency of water observations where the Confidence is above a cutoff level. This layer gives a noise-reduced view of surface water across Australia. Even though confidence filtering is applied to the Filtered Water Summary, some cloud and shadow, and sensor noise does persist.

With the average annual cost of floods estimated at $377 million, floods are Australia's most expensive natural hazard. As a result, considerable expenditure is made by government and industry to define flood areas in an effort to reduce the impacts of floods. This work typically involves the creation of reports describing the methodology used, data sources and results of hydrological and hydraulic modelling and damage assessments. While numerous reports are developed each year, there was no centralised record of what studies had been undertaken in Australia at a state/territory or national level until the development of the Australian Flood Studies Database in 2004. In 2009 Geoscience Australia reviewed the Australian Floods Studies Database via an online questionnaire. Opinion of the database was sought in three key areas including database functionality and content, and updating the database. The respondents confirmed the usefulness of the existing database content including hydrology and hydraulic scenarios, historical flood events used in the calibration, terrain and floor level surveys, damage assessments, inundation and hazard scenarios, information on what has occurred since a study's completion and related studies. Recurring themes highlighted by the survey respondents include the ability to be able to access the flood study reports and GIS flood layers via the database and be able to input data. Over 170 people completed the survey; 90% of whom were from local government. While only 20% of respondents had used the database, 72% of all respondents to the survey indicated that they would use the database in the future, whether or not they had used the database in the past. Three main recommendations can be concluded from the survey responses. The first recommendation is that the Australian Flood Studies Database is updated and that the lead agency for floodplain management in each State/Territory be responsible for that update on at least an annual basis. The second recommendation is that the database's existing functionality and content is maintained and further enhanced. The final recommendation is that the database is further publicised.