The Paterson National Geoscience Agreement project is using a number of tools to better understand the time-space evolution of the northwest Paterson Orogen in Western Australia. One of these tools, 3D Geomodeller, is an emerging technology that constructs three-dimensional (3D) volumetric models based on a range of geological information. The Paterson project is using 3D Geomodeller to build geologically-constrained 3D models for the northwest Paterson Orogen. This report documents the model building capability and benefits of 3D Geomodeller and highlights some of the geological insights gained from the model building exercise. The principal benefit of 3D Geomodeller is that it provides geoscientists with a rapid tool for testing multiple working hypotheses. The Cottesloe Syncline district was selected as the focus for a trial of the 3D Geomodeller software. The 3D model was built by members of the Paterson Project, as well as model building specialists within Geoscience Australia. The resultant Cottesloe Syncline model including two dimensional sections, maps and images was exported from 3D GeoModeller and transformed into a Virtual Reality Modelling Language (VRML), enabling a wide audience to view the model using readily available software.

Geoscience Australia's Risk & Impact Analysis Group has developed a statistical model of wind hazard utilising the Generalised Pareto Distribution (GPD). The model calculates the return period of severe winds based on daily maximum wind gust observations. The model utilises an automated procedure to partition the data into the hazard constituents (thunderstorms, synoptic winds, tornadoes, etc) based on the World Meteorological Observation Codes 3-hourly coded observations. This observational data set records the archived and present weather at the station site. The model fits the GPD to the station data (daily maximum wind gust) by automating the selection of the appropriate threshold above which data is included in the extreme value distribution. This threshold <em>u</em> is selected as the maximum of all feasible return period values obtained by fitting the GPD. Published comparative findings, including same region results, demonstrate the model can produce similar results in a more efficient, fully computational way. Confidence intervals for return periods are calculated automatically to allow wind analysts to distinguish regions of greater reliability.

The Fitzoy Estuary is one of several macrotidal estuaries in tropical northern Australia that face ecological change due to agricultural activities in their catchments. The biochemical functioning of such macrotidal estuaries is not well understood in Australia, and there is a pressing need to identify sediment, nutrient and agrochemical pathways, sinks and accumulation rates in these extremely dynamic environments. This is particularly the case in coastal northern Queensland because the impact of water quality changes in rivers resulting from vegetation clearing, changes in land-use and modern agricultural practices are the single greatest threat to the Great Barrier Reef Marine Park. This report includes: 1 Aims and Research questions 2 Study Area 3 Climate and Hydrology 4 Geology 5 Vegetation and land use 6 Methods 7 Sampling strategy 8 Water column observations and samples 9 Bottom sediment properties 10 Core and bottle incubations 11 Data analysis 12 Results 13 Discussion 14 The roll of Keppel Bay in accumulating and redirecting sediment and nutrients from the catchment 15 Sediment biogeochemistry 16 Links between primary production, biogeochemistry and sediment dynamics: A preliminary zonation for Keppel Bay 17 Conclusions

Stacking velocities for surveys 1001 (Shell Petrel) and 1053 (Esso R74A) over the Bremer and Denmark Sub-basins were analysed for depth and time.

A holistic inversion algorithm has been developed for time-domain airborne electromagnetic (AEM) data. The algorithm simultaneously recovers a layered earth conductivity structure as well as unmeasured elements of the system geometry. It inverts a complete flight line of data in one inversion. This allows us to take advantage of the expected along-line continuity of conductivity and system geometry, which cannot be exploited when each sample is inverted independently. The conductivity and thickness of each layer and geometry variable is parameterised by the node coefficients of separate cubic-spline basis functions, which implicitly represent smooth continuous along line variations. Each of the cubic splines may have different node spacings that are chosen to adequately represent the expected scale length of lateral variability of conductivity and system geometry. The regularised inversion scheme is formulated to minimise an objective function comprised of data misfit, reference model misfit, and vertical and horizontal roughness terms. The minimisation is implemented via a gradient-based iterative scheme in which a sparse linearised system is solved by the conjugate gradient method within each iteration. The method has been applied to fixed-wing and helicopter AEM data. The results demonstrate that the method produces conductivity models that are geologically credible and consistent with downhole conductivity logs. They also show improved continuity and interpretability in comparison to sample by sample inversions. We found that the estimation of transmitter-receiver separation and receiver pitch geometry parameters was stabilised by the implicit along line continuity constraints.

Conductivity-depth estimates generated using the 1D Geoscience Australia layered earth inversion algorithm (GA-LEI) have been released to the public domain. The GA-LEI has been shown to provide useful mapping of subsurface conductivity features in the Paterson; for example paleovalleys, unconformities and faults. GA-LEI interpretations have been supported by independent borehole conductivity logs, and lithological drill-hole information. The Geoscience Australia Record 2010/12; Geological and energy implications of the Paterson Province airborne electromagnetic (AEM) survey, Western Australia, summarises the AEM processing, inversion, interpretation and implications for mineral exploration using the 1D GA-LEI. There is an inherent assumption in the GA-LEI algorithm that the earth can be represented by a set of 1D layers, which extend to infinite distance in the horizontal plane. This layered earth assumption has some limitations, and has been demonstrated to create artefacts when applied to heterogeneous 3D geological features. 3D inversion methods can potentially overcome some of the limitations of 1D inversion methods, reducing the artefacts of a 1D earth assumption. 3D inversions require much greater computational resources than 1D methods because they have to solve many large systems of equations. In addition, a large sensitivity matrix is computed, which increases memory requirements, and the process must be repeated for multiple iterations. This computational expense has generally limited the application of 3D inversions to AEM datasets, and restricted its practicality as a general mapping tool. The EMVision® inversion generated by TechnoImaging presents a method of running a 3D inversion, with a runtime comparable to 1D inversion methods. The EMVision® algorithm uses a moving footprint to limit the number of data points needed as input to the inversion at any one location. A background conductivity model is chosen to represent the far-field response of the earth, and the data points within the AEM footprint are treated as anomalies with respect to the background. In 2010, Geoscience Australia decided that a comparison of the GA-LEI with the EMVision® inversion would be useful both for geological interpretation and for assessing the benefits of 3D inversion of AEM. A subset of the regional Paterson AEM dataset around the Kintyre uranium deposit was provided to TechnoImaging to create a 3D inversion using EMVision® software. The data subset was a combination of GA data and data owned by Cameco Corporation and the cost of inversion by TechnoImaging was shared by both parties. Under the terms of the agreement between Cameco Corporation and Geoscience Australia there was a moratorium on the data release until 2012.

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.

Recent climate conditions experienced in Australia certainly ring true with the famous words from author, Dorothea Mackellar, ‘of droughts and flooding rains’.

The Tanami 3D model covers a 300x300 km area of the Tanami region, primarily in the Northern Territory but also extending into Western Australia. The model incorporates the whole of the crust from the topographic surface down to the Moho.