Here we report on the results of a study undertaken in the Flinders Commonwealth Marine Reserve (southeast Australia) designed to test the benefits of two approaches to characterising shelf habitats: (i) MBES mapping of a continuous (~30 km2) area selected on the basis of its potential to include a range of representative seabed habitats , versus; (ii) a novel approach that uses targeted mapping of a greater number of smaller, but spatially balanced, locations using a Generalized Random Tessellation Stratified sample design. We present the first quantitative estimates of habitat type on the shelf of the Flinders reserve, using both survey approaches, based on three MBES analysis techniques. We contrast the quality of information that both survey approaches offer in combination with the three MBES analysis methods. We then consider the implications for future inventory of benthic habitats in shelf environments in the context of monitoring extensive offshore marine reserves.

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

The Australian Flood Risk Information Portal (the portal) is an initiative of the Australian Government, established following the devastating floods across Eastern Australia in 2011. The portal is a key component of the National Flood Risk Information Project (NFRIP), and aims to provide a single point of access to Australian flood information. Currently much of Australia's existing flood information is dispersed across disparate sources, making it difficult to find and access. The portal will host data and tools that allow public discovery, visualisation and retrieval of flood studies, flood maps, satellite derived water observations and other related information, all from a single location. The portal will host standards and guidelines for use by jurisdictions and information custodians to encourage best practice in the development of new flood risk information. While the portal will initially host existing flood information, the architecture has been designed to allow the portal content to grow over time to meet the needs of users. The aim is for the portal to display data for a range of scenarios from small to extreme events, though this will be dependent on stakeholder contributions. Geoscience Australia's Australian Flood Studies Database is the portal's data store of flood study information. The database includes metadata created through a purpose-built data entry application, and over time, information harvested from state-operated catalogues. For each entry the portal provides a summary of the flood study, including information on how the study was done, what data was used, what flood maps were produced and for what scenarios, as well as details on the custodian and originating author. If the study included an assessment of damage, details such as estimates of annual average damage, or the number of properties affected during a flood of a particular likelihood will also be included. During the last phase of development downloadable flood study reports and their associated flood maps have been added to the portal where available. As the portal is populated it will increasingly host mapped flood data, or link to flood data and maps held in authoritative databases hosted by State and Territory bodies. Mapping data to be made accessible through the portal will include flood extents and to a lesser degree information on water depths. The portal will also include water observations obtained from Geoscience Australia's historic archive of Landsat imagery. This data will show whether a particular location was 'wet' at some point during the past 30 years. While this imagery does not necessarily represent the peak of a flood or show water depth, the data will support the validation and verification process of hydrologic and hydraulic flood modelling. This work will prove useful particularly in rural areas where there is little or no flood information. The portal also provides flood information custodians with the ability to either upload mapped data directly to the portal or to make this data accessible via web services. Data management tools and standards, developed through NFRIP, will enable data custodians to map their data to agreed standards for delivery through the portal. A portal framework and supporting principles has been developed to guide the maintenance and development of the portal.

We have developed a Building Fire Impact Model to evaluate the probability that a building located in a peri-urban region of a community is affected/destroyed by a forest fire. The methodology is based on a well-known mathematical technique called Event Tree (ET) modeling, which is a useful graphical way of representing the dependency of events. The tree nodes are the event itself, and the branches are formed with the probability of the event happening. If the event can be represented by a discrete random variable, the number of possible realisations of the event and their corresponding probability of occurring, conditional on the realisations of the previous event, is given by the branches. As the probability of each event is displayed conditional on the occurrence of events that precede it in the tree, the joint probability of the simultaneous occurrence of events that constitute a path is found by multiplication (Hasofer et al., 2007). BFIM contains a basic implementation of the main elements of bushfire characteristics, house vulnerability and human intervention. In the first pass of the BFIM model, the characteristics of the bushfire in the neighboring region to the house is considered as well as the characteristics of the house and the occupants of the house. In the second pass, the number of embers impacting on the house is adjusted for human intervention and wind damage. In the third pass, the model examines house by house conditions to determine what houses have been burnt and their impact on neighboring houses. To illustrate the model application, a community involved in the 2009 Victorian bushfires has been studied and the event post-disaster impact assessment is utilized to validate the model outcomes. MODSIM 2013 Conference

Wind multipliers are factors that transform regional wind speeds into local wind speeds, accounting for the local effects which include topographical, terrain and shielding influences. Wind multipliers have been successfully utilized in various wind related activities such as wind hazard assessment (engineering building code applications), event-based wind impact assessments (tropical cyclones), and also national scale wind risk assessment. The work of McArthur in developing the Forest Fire Danger Index (FFDI: Luke and McArthur, 1978) indicates that the contribution of wind speed to the FFDI is about 45% of the magnitude, indicating the importance of determining an accurate local wind speed in bushfire hazard and spread calculations. For bushfire spread modeling, local site variation (@ 100 metre and also 25 metre horizontal resolution) have been considered through the use of wind multipliers, and this has resulted in a significant difference to the currently utilized regional '10 metre height' wind speed (and further to the impact analysis). A series of wind multipliers have been developed for three historic bushfire case study areas; the 2009 Victorian fires (Kilmore fire), the 2005 Wangary fire (Eyre Peninsula), and the 2001 Warragamba - Mt. Hall fire (Western Sydney). This paper describes the development of wind multiplier computation methodology and the application of wind multipliers to bushfire hazard and impact analysis. The efficacy of using wind multipliers within a bushfire spread hazard model is evaluated by considering case study comparisons of fire extent, shape and impact against post-disaster impact assessments. The analysis has determined that it is important to consider wind multipliers for local wind speed determination in order to achieve reliable fire spread and impact results. From AMSA 2013 conference

Monitoring is a regulatory requirement for all carbon dioxide capture and geological storage (CCS) projects to verify containment of injected carbon dioxide (CO2) within a licensed geological storage complex. Carbon markets require CO2 storage to be verified. The public wants assurances CCS projects will not cause any harm to themselves, the environment or other natural resources. In the unlikely event that CO2 leaks from a storage complex, and into groundwater, to the surface, atmosphere or ocean, then monitoring methods will be required to locate, assess and quantify the leak, and to inform the community about the risks and impacts on health, safety and the environment. This paper considers strategies to improve the efficiency of monitoring the large surface area overlying onshore storage complexes. We provide a synthesis of findings from monitoring for CO2 leakage at geological storage sites both natural and engineered, and from monitoring controlled releases of CO2 at four shallow release facilities - ZERT (USA), Ginninderra (Australia), Ressacada (Brazil) and CO2 field lab (Norway).

Surface Bidirectional Reflectance Distribution Function (BRDF) correction is important for time series based analysis, such as dynamic landcover mapping and monitoring climate change etc. It is thus important to understand characteristics of BRDF and its variation under different cover and climate conditions and its seasonal and annual variation. Many studies suggested that BRDF is related to the characteristics of landcover types, vegetation structure (height and cover) and climate patterns. In this study, 10 years of MODIS BRDF data sets (MOD43A1) from 2001 to 2011 are used to conduct the analysis using landcover data in Australia derived in the same period. The study found that BRDF spectral shape is strongly correlated with the Normalized Difference Vegetation Index (NDVI), but BRDF shape varies significantly between landcover classes, vegetation structure and climate regions. Intra-annual variation of BRDF spectral shape is stronger than the inter-annual variation and seasonal patterns of spectral BRDF shape are different from those of NDVI.

CO2CRC Symposium 2013: Oral presentation as part of a tag-team Ginninderra presentation As part of the controlled release experiments at the Ginninderra test site, a total of 14 soil flux surveys were conducted; 12 during the first experiment (March 2012 - June 2012), and 2 during the second experiment (October - December 2012). The aim was to determine what proportion of the known CO2 that was released could be measured using the soil flux method as a quantification tool. The results of this study enabled us to use the soil flux measurements as a proxy for other CO2 quantification methods and to gain an understanding of how the CO2 migrated within the sub-surface. For experiment one; baseline surveys were conducted pre-release, followed by surveys several times a week during the first stages of the release. The CO2 'breakthrough' was detected only 1 day after the release began. Surveys were then conducted weekly to monitor the flux rate over time. The soil CO2 flux gradually increased in magnitude until almost reaching the expected release rate (128 kg/day measured while the release rate was 144 kg/day) after approximately 4 weeks, and then receded quickly once the controlled release was stopped. Soil gas wells confirm that there is significant lateral migration of the CO2 in the sub-surface, suggesting that there was a degree of accumulation of CO2 in the sub-surface during the experiment.

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. 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. Gaseous CO2 was released 2 m below the ground surface from a slotted, 100 m long horizontal well at a rate of 144 kg/d for at least 8 weeks for both experiments. The most obvious difference between the two release experiments was that CO2 leakage expressed at different locations along the well for the two experiments. As also observed in other controlled release experiments internationally, the surface expression of CO2 during these experiments, as measured using a portable soil flux meter, was restricted to localised spots. For the 2012 (wet) release experiment, the leakage was limited to a small intense primary leak (approximately 12 m in diameter) and a neighbouring small secondary leak. In contrast, the leak from the 2013 (dry) release experiment was broader, spread over a longer length of the release well, and did not attain the very high flux intensities observed in the previous year. An array of 1 m deep soil gas wells provided insight into the migration pathways of CO2 in the sub-surface, showing a much broader dispersion of CO2 in the sub-surface compared to the surface CO2 expression. Krypton tracers confirmed that the spread of the introduced gases in the sub-surface was much greater than the surface expression, with different behaviour observed between the 2012 and 2013 experiments. The differences between the years are attributed to changes in groundwater levels, drier conditions, and a larger vadose zone during the 2013 experiment. Eddy covariance (EC) towers were deployed at the site for both experiments with the objective to detect and quantify CO2 emissions. CO2 leaks were detected above the background and the direction of the leak confirmed. However, analysis showed that current methods of EC are not appropriate for quantifying the CO2 leak, as much of the CO2 flux is lost through advection and diffusion below the measurement height. This is because the footprint of the leak is much smaller than the EC tower's footprint, resulting in a highly heterogeneous system that breaches EC's key assumptions. The results suggest that quantification using EC may not be possible for CO2 leaks with small footprints. An array of atmospheric CO2 sensors was also deployed at the site during the experiments. Application of atmospheric tomographic techniques using the point source sensors appears to be a more effective approach than EC for quantifying CO2 emissions. Broad scale leak detection technologies are necessary for surveying areas beyond high risk sites and is the subject of ongoing research at Ginninderra. Airborne hyperspectral and thermal scanning measurements were taken over CO2-impacted, mature wheat and field pea crops. The CO2 impact on plants was characterised through biochemical analysis and observed changes in plant morphology. High resolution ground-based hyperspectral and thermal measurements were taken over tillering barley and wheat, as well as field pea and canola seedlings. Dry conditions and crop stage strongly influenced the effectiveness of the remote sensing techniques for CO2 leak detection. A comparison between the high resolution ground-based and airborne hyperspectral measurements for detecting CO2 impacted plants will be presented as well as an overall assessment of the leak detection techniques. Submitted to the GHGT-12

Wildfires are one of the major natural hazards facing the Australian continent. Chen (2004) rated wildfires as the third largest cause of building damage in Australia during the 20th Century. Most of this damage was due to a few extreme wildfire events. For a vast country like Australia with its sparse network of weather observation sites and short temporal length of records, it is important to employ a range of modelling techniques that involve both observed and modelled data in order to produce fire hazard and risk information/products with utility. This presentation details the use of statistical and deterministic modelling of both observations and synthetic climate model output (downscaled gridded reanalysis information) in the development of extreme fire weather potential maps. Fire danger indices such as the McArthur Fire Forest Danger Index (FFDI) are widely used by fire management agencies to assess fire weather conditions and issue public warnings. FFDI is regularly calculated at weather stations using measurements of weather variables and fuel information. As it has been shown that relatively few extreme events cause most of the impacts, the ability to derive the spatial distribution of the return period of extreme FFDI values contributes important information to the understanding of how potential risk is distributed across the continent. The long-term spatial tendency FFDI has been assessed by calculating the return period of its extreme values from point-based observational data. The frequency and intensity as well as the spatial distribution of FFDI extremes were obtained by applying an advanced spatial interpolation algorithm to the recording stations' measurements. As an illustration maps of 50 and 100-year return-period (RP) of FFDI under current climate conditions are presented (based on both observations and reanalysis climate model output). MODSIM 2013 Conference