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

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.

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

Imagine you are an incident controller viewing a computer screen which depicts the likely spread of a bushfire that's just started. The display shows houses and other structures in the fire's path, and even the demographics of the people living in the area, such as the number of people, their age spread, whether households have independent transport, and whether English is their second language. In addition, imagine that you can quantify and display the uncertainty in both the fire weather and also the type and state of the vegetation, visualising the sensitivity of the expected fire spread and impact to these uncertainties. It will be possible to consider 'what if' scenarios as the event unfolds, and reject those scenarios that are no longer plausible. The advantages of such a simulation system in making speedy, well-informed decisions has been considered by a group of Bushfire CRC researchers who have collaborated to produce a 'proof of concept' for such a system, demonstrated initially on three case studies. The 'proof of concept' system has the working name FireDST (Fire Impact and Risk Evaluation Decision Support Tool). FireDST links various databases and models, including the Phoenix RapidFire fire prediction model and building vulnerability assessment models, as well as infrastructure and demographic databases. The information is assembled into an integrated simulation framework through a geographical information system (GIS) interface. Pre-processed information, such as factors that determine the local and regional wind, and also the typical response of buildings to fire, are linked through a database, along with census-derived social and economic information. This presentation provides an overview of the FireDST simulation 'proof of concept' tool and walks through a sample probabilistic simulation constructed using the tool. Handbook MODSIM2013 Conference

Poster for IAH 2013 A major concern for regulators and the public with geological storage of CO2 is the potential for the migration of CO2 via a leaky fault or well into potable groundwater supplies. Given sufficient CO2, an immediate effect on groundwater would be a decrease in pH which could lead to accelerated weathering, an increase in alkalinity and the release of major and minor ions. Laboratory and core studies have demonstrated that on contact with CO2 heavy metals can be released under low pH and high CO2 conditions (particularly Pd, Ni and Cr). There is also a concern that trace organic contaminants could be mobilised due to the high solubility of many organics in supercritical CO2. These scenarios potentially occur in a high CO2 leakage event, therefore detection of a small leak although barely perceptible could provide an important early warning for a subsequent and more substantial impact.

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.

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).

The dry-tropics of central Queensland has an annual bushfire threat season that generally extends from September to November. Fire weather hazard is quantified using either the Forest Fire Danger Index (FFDI) or the Grassland Fire Danger Index (GFDI) (Luke and McArthur, 1978). Weather observations (temperature, relative humidity and wind speed) are combined with an estimate of the fuel state to predict likely fire behaviour if an ignition eventuates. A high resolution numerical weather model (dynamic downscaling) was utilised to provide spatial texture over the Rockhampton region for a range of historical days where bushfire hazard (as measured at the Rockhampton Airport meteorological station) was known to be severe to extreme. From the temperature, relative humidity and wind speeds generated by the model, the maximum FFDI for each simulated day was calculated using a maximum drought factor. Each of these FFDI maps was then normalised to the value of the FFDI at the grid point corresponding to Rockhampton Airport (ensemble produced). The annual recurrance interval (ARI) of FFDI at Rockhampton Airport for the current climate was calculated from observations by fitting Generalised Extreme Value (GEV) distributions. For future climate, we considered three downscaled General Circulation Models (GCM's) forced by the A2 emission scenario for atmospheric greenhouse gas emissions. The spatial pattern of the 50 and 100 year ARI fire danger rating for the Rockhampton region (current and future climate) was determined. In general, a small spatial increase in the fire danger rating is reflected in the ensemble model average for the 2090 climate. This is reflected throughout the Rockhampton region in both magnitude and extent through 2050 to 2090. Cluster areas of higher (future climate) bushfire hazard were mapped for planning applications. Handbook MODSIM2013 Conference

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