Geoscience Australia and the CO2CRC operate a greenhouse gas controlled release facility at an experimental agricultural station maintained by CSIRO Plant Industry in Canberra, Australia. The facility is designed to simulate surface emissions of CO2 and other greenhouse gases from the soil into the atmosphere. Over 10 different near surface monitoring techniques were trialled at the Ginninderra controlled release site during 2012-2013. These included soil gas, soil CO2 flux, soil analysis, eddy covariance, CO2 laser, noble gas tracers, airborne hyperspectral, in-field phenotyping (thermal, hyperspectral and 3D imaging), and microbial soil genomics. Result highlights are presented. Different climatic conditions for the early 2012 release experiment (wet) and late 2013 release experiment (dry) resulted in markedly different sub-surface plume behaviour and surface expression of CO2. The differences between the years are attributed to changes in groundwater levels and drier conditions leading to a larger vadose zone during the 2013 experiment.

The potential for using a single high precision atmospheric station for detecting CO2 leaks has been investigated using a variety of statistical approaches. Geoscience Australia and CSIRO Marine and Atmospheric Research installed an atmospheric monitoring station, Arcturus, in the Bowen Basin, Australia, in 2010 and have collected over 3 years' worth of atmospheric concentration measurements. The facility is designed as a prototype remote baseline monitoring station that could be deployed in areas targeted for commercial scale geological storage of carbon dioxide. Two Picarro gas analysers are deployed in the station to continuously monitor CO2, CH4 and CO2 isotopes. An automated weather station and an eddy covariance flux tower have also been installed at the site. Atmospheric CO2 perturbations, from simulated leaks, have been modelled to determine the minimum statistically significant emissions that can be detected above background concentrations at Arcturus. CO2 leakage was simulated from January to December (2011) using a 3D-coupled prognostic meteorological and pollutant dispersion model (TAPM). Simulations were conducted for various locations, emission rates and distances (1-10 km) from the station. The simulated leaks were simulated using an area source (100 m x 100 m) and a point source located in the optimum wind direction (SSE), which showed the largest perturbation. To better understand the observed CO2 signal, a statistical model combining both a regression and time series model was constructed. The regression model is a time dependent generalised additive model relating the CO2 to other observed atmospheric variables (e.g. wind speed, temperature, humidity). It accounts for seasonal trends through the inclusion of dummy variables. The time series model is based on a seasonal auto-regressive integrated moving average (ARIMA) model, but with the additional complexity of allowing auto-regressive relationships to depend on the time of day. A non-parametric goodness of fit approach using the Kolmogorov-Smirnoff (KS) test was then used to test whether simulated perturbations can be detected against the modelled expected value of the background for certain hours of the day and for particular seasons. The developed regression model allows us to pre-whiten the CO2 time series. Pre-whitening reduces both the variance and skew of the marginal distribution of the signal. This improves the power of the Kolmogorov-Smirnoff (KS) test when attempting to detect simulated perturbations against the background signal. The KS test calculates the probability that the modelled leak perturbation could be caused by natural variation in the background. For hours between 10am and 2pm in the winter of 2011, minimum detectable leaks located 1km from the measurement station improve from 44 to 22 tpd for an area source and 33 to 14 tpd for a point source at a p-value of 0.05. These are very large leaks located only 1 km from the station. Additionally, this approach results in a high false alarm rate of 56%. An alternative p-value could be chosen to reduce the false alarm rate but the overall conclusion is the same. A long term, single measurement station monitoring program that is unconstrained by prior information on possible leaks, and based on detection of perturbations of CO2 alone due to leakage above a (noisy) background signal, is likely to take one or more years to detect leaks of the order of 10kt p.a.

<p>A new finite volume algorithm to solve the two dimensional shallow water equations on an unstructured triangular mesh has been implemented in the open source ANUGA software, which is jointly developed by the Australian National University and Geoscience Australia. The algorithm supports discontinuous-elevation, or 'jumps' in the bed profile between neighbouring cells. This has a number of benefits compared with previously implemented continuous-elevation approaches. Firstly it can preserve stationary states at wet-dry fronts without using any mesh porosity type treatment. It can also simulate very shallow frictionally dominated flow down sloping topography, as typically occurs in direct-rainfall flood models. In the latter situation, mesh porosity type treatments lead to artificial storage of mass in cells and associated mass conservation issues, whereas continuous elevation approaches with good performance on shallow frictionally dominated flows tend to have difficulties preserving stationary states near wet-dry fronts. The discontinuous elevation approach shows good performance in both situations, and mass is conserved to a very high degree, consistent with floating point error. <p>A further benefit of the discontinuous-elevation approach, when combined with an unstructured mesh, is that the model can sharply resolve rapid changes in the topography associated with e.g. narrow prismatic drainage channels, or buildings, without the computational expense of a very fine mesh. The boundaries between such features can be embedded in the mesh using breaklines, and the user can optionally specify that different elevation datasets are used to set the elevation within different parts of the mesh (e.g. often it is convenient to use a raster DEM in terrestrial areas, and surveyed channel bed points in rivers). <p>The discontinuous elevation approach also supports a simple and computationally efficient treatment of river walls. These are arbitrarily narrow walls between cells, higher than the topography on either side, where the flow is controlled by a weir equation and optionally transitions back to the shallow water solution for sufficiently submerged flows. This allows modelling of levees or lateral weirs much finer than the mesh size. <p>A number of benchmark tests are presented illustrating these features of the algorithm, along with its application to urban flood hazard simulation and comparison with field data. All these features of the model can be run in serial or parallel, on clusters or shared memory machines, with good efficiency on 10s - 100s of cores depending on the number of mesh triangles and other case-specific details.

Geoscience Australia produces optimized statistical predictions of seabed sediment distribution for the Australian continental Exclusive Economic Zone. These products are broadly relevant to the work of government policy and research organizations and the offshore oil and gas industry. To better promote the features and relevance of these products, we need to produce 1-3 posters. These will provide graphic examples of the spatial predictions, comparisons between previous and recent versions of this dataset to demonstrate the increase in accuracy and resolution achieved, and provide information about how to access the data. These posters will be used to promote this work at relevant external workshops and conferences. We also need to produce some simple A4 size pamphlets/flyers based on the posters, which can be easily carried and distributed to various audiences. This would increase the awareness of GA's products in marine environmental geosciences, boost the usage of the products by both internal and external clients and promote GA's profile in generating quality geoscience information.

In June 2012 Geoscience Australia was commissioned by Commonwealth Scientific and Industrial Research Organisation (CSIRO) to undertake detailed wind hazard assessments for 14 Pacific Island countries and East Timor as part of the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program. PACCSAP program follows on from work Geoscience Australia did for the Pacific Climate Change Science Program (PCCSP) looking at CMIP3 generation of climate models. The objective of this study is to improve scientific knowledge by examining past climate trends and variability to provide regional and national climate projections. This document presents results from current and future climate projections of severe wind hazard from tropical cyclones for the 15 PACCSAP partner countries describing the data and methods used for the analysis. The severe wind hazard was estimated for current (1981 to 2000) and future (2081 to 2100) climate scenarios. Tropical-cyclone like vortices from climate simulations conducted by CSIRO using six Coupled Model Intercomparison Project phase 5 (CMIP5) models (BCC-CSM1.1, NorESM1-M, CSIRO-Mk3.6, IPSL-CM5A, MRI-CGM3 and GFDL-ESM2M) as well as the International Best Track Archive for Climate Stewardship were used as input to the Geoscience Australia's Tropical Cyclone Risk Model to generate return period wind speeds for the 15 PACCSAP partner countries. The Tropical Cyclone Risk Model is a statistical-parametric model of tropical cyclone behaviour, enabling users to generate synthetic records of tropical cyclones representing many thousands of years of activity. The 500-year return period wind speed is analysed and discussed into more details in this report, since it is used as a benchmark for the design loads on residential buildings. Results indicate that there is not a consistent spatial trend for the changes in 500-year cyclonic wind speed return period when CMIP5 models are compared individually. BCC-CSM1M and IPSL-CM5A presented an increase in the annual TC frequency for East Timor, northern hemisphere and southern hemisphere. On the other hand, NorESM1M showed a decrease in the annual TC frequency for the same areas. The other three models showed a mixed of increase and decrease in their annual TC frequency. When CMIP5 models were analysed by partner county capitals for the 500-year cyclonic wind speed return period, IPSL-CM5A and GFDL-ESM2M models presented an increase in the cyclonic wind speed intensity for almost all capitals analysed with exception of Funafuti (GFDL-ESM2M), which presented a decrease of 0.7% and Honiara (IPSL-CM5A) with a decrease of 1.6%. The tropical cyclone annual frequency ensemble mean indicates an increase in the tropical cyclone frequency within all three regions considered in this study. When looking at individual capitals, a slight increase in the 500-year return period cyclonic wind speed ensemble mean varying between 0.8% (Port Vila) to 9.1% (Majuro) is noticed. A decline around 2.4% on average in the 500-year return period cyclonic wind speed ensemble mean is observed in Dili, Suva, Nukualofa and Ngerulmud. The ensemble spatial relative change did not show any particular consistency for the 500-year cyclonic wind speed. Areas where Marshall Islands and Niue are located presented an increase in the 500-year cyclonic wind speed while a decrease is observed in areas around South of Vanuatu, East of Solomon Islands, South of Fiji and some areas in Tonga. The information from the evaluation of severe wind hazard from tropical cyclones, together with other PACCSAP program outputs, will be used to build partner country capacity to effectively adapt and plan for the future and overcome challenges from climate change.

In this study, we aim to identify the most accurate methods for spatial prediction of seabed gravel content in the northwest Australian Exclusive Economic Zone. We experimentally examined: 1) whether input secondary variables affect the performance of RFOK and RFIDW, 2) whether the performances of RF, SIMs and their hybrid methods are data-specific, and 3) whether model averaging improves predictive accuracy of these methods in the study region. For RF and the hybrid methods, up to 21 variables were used as predictors. The predictive accuracy was assessed in terms of relative mean absolute error and relative root mean squared error based on the average of 100 iterations of 10-fold cross validation. In this study, the following important findings were achieved: - the predictive errors fluctuate with the input secondary variables; - the existence of correlated variables can alter the results of model selection, leading to different models; - the set of initial input variables affects the model selected; - the most accurate model can be missed out during the model selection; - RF, RFOK and RFIDW prove to be the most accurate methods in this study, with RFOK preferred; and these methods are not data-specific, but their models are, so best model needs to be identified; and - Model averaging is clearly data-specific. In conclusion, model selection is essential for RF and the hybrid methods. RF and the hybrid methods are not data-specific, but their models are. RFOK is the most accurate method. Model averaging is also data-specific. Hence best model needs to be identified for individual studies and application of model averaging should also be examined accordingly. RF and the hybrid methods have displayed substantial potentials for predicting environmental properties and are recommended for further test for spatial predictions in environmental sciences and other relevant disciplines in the future. This study provides suggestions and guidelines for improving the spatial predictions of biophysical variables in both marine and terrestrial environments.

This presentation will provide an overview of geological storage projects and research in Australia.

The Clarence-Moreton and the Surat basins in Queensland and northern New South Wales contain the coal-bearing sedimentary sequences of the Jurassic Walloon Coal Measures, composed of up to approximately 600 m of mudstone, siltstone, sandstone and coal. In recent years, the intensification of exploration for coal seam gas (CSG) resources within both basins has led to concerns that the depressurisation associated with future resource development may cause adverse impacts on water resources in adjacent aquifers. In order to identify the most suitable tracers to study groundwater recharge and flow patterns within the Walloon Coal Measures and their degree of connectivity with over- or underlying formations, samples were collected from the Walloon Coal Measures and adjacent aquifers in the northern Clarence-Moreton Basin and eastern Surat Basin, and analysed for a wide range of hydrochemical and isotopic parameters. Parameters that were analysed include major ion chemistry, -13C-DIC, -18O, 87Sr/86Sr, Rare Earth Elements (REE), 14C, -2H and -13C of CH4 as well as concentrations of dissolved gases (including methane). Dissolved methane concentrations range from below the reporting limit (10 µg/L) to approximately 50 mg/L in groundwaters of the Walloon Coal Measures. However, the high degree of spatial variability of methane concentrations highlights the general complexity of recharge and groundwater flow processes, especially in the Laidley Sub-Basin of the Clarence-Moreton Basin, where numerous volcanic cones penetrate the Walloon Coal Measures and may form pathways for preferential recharge to the Walloon Coal Measures. Interestingly, dissolved methane was also measured in other sedimentary bedrock units and in alluvial aquifers in areas where no previous CSG exploration or development has occurred, highlighting the natural presence of methane in different aquifers. Radiocarbon ages of Walloon Coal Measure groundwaters are also highly variable, ranging from approximately 2000 yrs BP to >40000 yrs BP. While groundwaters sampled in close proximity to the east and west of the Great Dividing Range are mostly young, suggesting that recharge to the Walloon Coal Measures through the basalts of the Great Dividing Range occurs here, there are otherwise no clearly discernable spatial patterns and no strong correlations with depth or distance along inferred flow paths in the Clarence-Moreton Basin. In contrast to this strong spatial variability of methane concentrations and groundwater ages, REE and 87Sr/86Sr isotope ratios of Walloon Coal Measures groundwaters appear to be very uniform and clearly distinct from groundwaters contained in other bedrock units. This difference is attributed to the different source material of the Walloon Coal Measures (mostly basalts in comparison to other bedrock units which are mostly composed of mineralogical more variable Paleozoic basement rocks of the New England Orogen). This study suggests that REE and 87Sr/86Sr ratios may be a suitable tracer to study hydraulic connectivity of the Walloon Coal Measures with over- or underlying aquifers. In addition, this study also highlights the need to conduct detailed water chemistry and isotope baseline studies prior to the development of coal seam gas resources in order to differentiate between natural background values of methane and potential impacts of coal seam gas development.

Changes in microbial diversity and population structure occur as a result of increased nutrient loads and knowledge of microbial community composition may be a useful tool for assessing water quality in coastal ecosystems. However, the ability to understand how microbial communities and individual species respond to increased nutrient loads is limited by the paucity of community-level microbial data. The microbial community composition in the water column and sediments was measured across tropical tidal creeks and the relationship with increased nutrient loads assessed by comparing sewage-impacted and non-impacted sites. Diversity-function relationships were examined with a focus on denitrification and the presence of pathogens typically associated with sewage effluent tested. Significant relationships were found between the microbial community composition and nutrient loads. Species richness, diversity and evenness in the water column all increased in response to increased nutrient loads, but there was no clear pattern in microbial community diversity in the sediments. Water column bacteria also reflected lower levels of denitrification at the sewage-impacted sites. The genetic diversity of pathogens indicated that more analysis would be required to verify their status as pathogens, and to develop tests for monitoring. This study highlights how microbial communities respond to sewage nutrients in a tropical estuary. Estuarine, Coastal and Shelf Science

The National Exposure Information System (NEXIS) is a unique modelling capability designed by Geoscience Australia (GA) to provide comprehensive and nationally-consistent exposure information in response to the 2003 COAG commitment to cost-effective, evidence-based disaster mitigation. Since its inception, NEXIS has continually evolved to fill known information gaps by improving statistical methodologies and integrating the best publically-available data. In addition to Residential, Commercial and Industrial building exposure information, NEXIS has recently expanded to include exposure information about agricultural assets providing a wider understanding of how communities can be affected by a potential event. GA's collaboration with the Attorney General's Department (AGD) has involved the consolidation of location-based data to deliver consistent map and exposure information products. The complex information requirements emphasised the importance of having all relevant building, demographic, economic, agriculture and infrastructure information in NEXIS available in a clear and unified Exposure Report to aid decision-makers. The Exposure Report includes a situational map of the hazard footprint to provide geographic context and a listing of detailed exposure information consisting of estimates for number and potential cost of impacted buildings by use, agricultural commodities and cost, the number and social vulnerability of the affected population, and the number and lengths of infrastructure assets and institutions. Developed within an FME workbench, the tool accepts hazard footprints and other report specifics as input before providing an HTML link to the final output in approximately 5 minutes. The consolidation of data and streamlining of exposure information into a simple and uniform document has greatly assisted the AGD in timely evidence-based decision-making during the 2014-15 summer season.