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

This report provides background information about the Ginninderra controlled release Experiment 2 including a description of the environmental and weather conditions during the experiment, the groundwater levels and a brief description of all the monitoring techniques that were trialled during the experiment. Release of CO2 began 26 October 2012 at 2:25 PM and stopped 21 December 2012 at 1:30 PM. The total CO2 release rate during Experiment 2 was 218 kg/d CO2. The aim of the second Ginninderra controlled release was to artificially simulate the leakage of CO2 along a line source, to represent leakage along a fault. Multiple methods and techniques were then trialled in order to assess their abilities to: - detect that a leak was present - pinpoint the location of the leak - identify the strength of the leak - monitor how the CO2 behaves in the sub-surface - assess the effects it may have on plant health Several monitoring and assessment techniques were trialled for their effectiveness to quantify and qualify the CO2 that was release. This experiment had a focus on plant health indicators to assess the aims listed above, in order to evaluate the effectiveness of monitoring plant health and the use of geophysical methods to identify that a CO2 leak may be present. The methods are described in this report and include: - soil gas - airborne hyperspectral surveys - plant health (PhenoMobile) - soil CO2 flux - electromagnetic (EM-31) - electromagnetic (EM-38) - ground penetrating radar (GPR) This report is a reference guide to describe the Ginninderra Experiment 2 details. Only methods are described in this report with the results of the study published in conference papers and future journal articles.

In many areas of the world, vegetation dynamics in semi-arid floodplain environments have been seriously impacted by increased river regulation and groundwater use. With increases in regulation along many rivers in the Murray-Darling Basin, flood volume, seasonality and frequency have changed which has in turn affected the condition and distribution of vegetation. Floodplain vegetation can be degraded from both too much and too little water due to regulation. Over-regulation and increased use of groundwater in these landscapes can exacerbate the effects related to natural climate variability. Prolonged flooding of woody plants has been found to induce a number of physiological disturbances such as early stomatal closure and inhibition of photosynthesis. However, drought conditions can also result in leaf biomass reduction and sapwood area decline. Depending on the species, different inundation and drought tolerances are observed. Identification of groundwater-dependent terrestrial vegetation, and assessment of the relative importance of different water sources to vegetation dynamics, typically requires detailed ecophysiological studies over a number of seasons or years as shown in Chowilla, New South Wales [] and Swan Coastal Plain, Western Australia []. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Quicker, more regional approaches to mapping groundwater-dependent vegetation have consequently evolved with technological advancements in remote sensing techniques. Such an approach was used in this study. LiDAR canopy digital elevation model (CDEM) and foliage projected cover (FPC) data were combined with Landsat imagery in order to characterise the spatial and temporal behaviour of woody vegetation in the Lower Darling Floodplain, New South Wales. The multi-temporal dynamics of the woody vegetation were then compared to the estimated availability of different water sources in order to better understand water requirements.

The Walloon Coal Measures (WCM) in the Clarence-Moreton and the Surat basins in Qld and northern NSW contain up to approximately 600 m of mudstone, siltstone, sandstone and coal. Wide-spread exploration for coal seam gas (CSG) within both basins has led to concerns that the depressurisation associated with the resource development may impact on water resources in adjacent aquifers. In order to predict potential impacts, a detailed understanding of sedimentary basins hydrodynamics that integrates geology, hydrochemistry and environmental tracers is important. In this study, we show how different hydrochemical parameters and isotopic tracers (i.e. major ion chemistry, dissolved gas concentrations, 13C-DIC, 18O, 87Sr/86Sr, 3H, 14C, 2H and 13C of CH4) can help to improve the knowledge on groundwater recharge and flow patterns within the coal-bearing strata and their connectivity with over- or underlying formations. Dissolved methane concentrations in groundwaters of the WCM in the Clarence-Moreton Basin range from below the reporting limit (10 µg/L) to approximately 50 mg/L, and samples collected from nested bore sites show that there is also a high degree of vertical variability. Other parameters such as groundwater age measurements collected along distinct flow paths are also highly variable. In contrast, 87Sr/86Sr isotope ratios of WCM groundwaters are very uniform and distinct from groundwaters contained in other sedimentary bedrock units, suggesting that 87Sr/86Sr ratios may be a suitable tracer to study hydraulic connectivity of the Walloon Coal Measures with over- or underlying aquifers, although more studies on the systematic are required. Overall, the complexity of recharge processes, aquifer connectivity and within-formation variability confirms that a single tracer that cannot provide all information necessary to understand aquifer connectivity in these sedimentary basins, but that a multi-tracer approach is required.

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

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

This dataset provides the spatially continuous data of seabed gravel (sediment fraction >2000 µm), mud (sediment fraction < 63 µm) and sand content (sediment fraction 63-2000 µm) expressed as a weight percentage ranging from 0 to 100%, presented in 0.0025 decimal degree (dd) resolution raster grids format and ascii text file. The dataset covers the Browse region in the Australian continental EEZ. This dataset supersedes previous predictions of sediment gravel, mud and sand content for the basin with demonstrated improvements in accuracy. Accuracy of predictions varies based on density of underlying data and level of seabed complexity. Artefacts occur in this dataset as a result of insufficient samples in relevant regions. This dataset is intended for use at the basin scale. The dataset may not be appropriate for use at smaller scales in areas where sample density is insufficient to detect local variation in sediment properties. To obtain the most accurate interpretation of sediment distribution in these areas, it is recommended that additional samples be collected and predictions updated.

Abstract for a Poster for the CO2CRC Symposium 2013: Atmospheric tomography is a CO2 quantification and localisation technique that uses an array of sampling points and a Bayesian inversion method to solve for the location and magnitude of a CO2 leak. Knowledge of a normalized three-dimensional dispersion plume is required in order to accurately model a leak using many meteorological parameters. A previous small scale (~20 m) study using a high precision Fourier Transform Infrared found that the emission rate was determined to within 3% of the actual release rate and the localisation within 1 m of the correct position. The technique was applied during the CO2CRC Otway Stage 2B residual saturation and dissolution test in August-October 2011. A network of eight independent CO2 sensors (Vaisala GMP343 CO2 probes) were positioned at distances ranging from 154 to 473 m from the well. A 3D sonic anemometer within the measurement area collected wind turbulence data. The results of the study indicate that, through careful data processing, measurements from the reasonably inexpensive (but lower accuracy and lower precision) CO2 sensor array can provide useful data for the application of atmospheric tomography. Results have found that the low precision of the sensors over time becomes a problem due to sensor drift. A reference measurement of CO2 helps to resolve this problem and improves the perturbation signal during data processing. Preliminary inversion modeling results will be shown to show the best estimation of locating a CO2 leakage source for the Otway Stage 2B residual saturation and dissolution test. CO2CRC Symposium 2013, Hobart

This dataset provides the spatially continuous data of seabed gravel (sediment fraction >2000 µm), mud (sediment fraction < 63 µm) and sand content (sediment fraction 63-2000 µm) expressed as a weight percentage ranging from 0 to 100%, presented in 0.0025 decimal degree (dd) resolution raster grids format and ascii text file. The dataset covers the Petrel sub-basin in the Australian continental EEZ. This dataset supersedes previous predictions of sediment gravel, mud and sand content for the basin with demonstrated improvements in accuracy. Accuracy of predictions varies based on density of underlying data and level of seabed complexity. Artefacts occur in this dataset as a result of insufficient samples in relevant regions. This dataset is intended for use at the basin scale. The dataset may not be appropriate for use at smaller scales in areas where sample density is insufficient to detect local variation in sediment properties. To obtain the most accurate interpretation of sediment distribution in these areas, it is recommended that additional samples be collected and interpolations updated.