Fresh groundwater stored in Australian coastal aquifers is an important resource for humans and the natural environment. Many Australian coastal aquifers are vulnerable to seawater intrusion (SWI)—the landward encroachment of sea water into coastal aquifers—which can significantly degrade water quality and reduce freshwater availability. The increasing demands for fresh water in coastal areas and the anticipated impacts of climate change (such as sea-level rise and variations in rainfall recharge) may result in increases in the incidence and severity of SWI. Comprehensive investigations of SWI are relatively uncommon and the extent of monitoring and investigations specific to SWI are highly variable across the nation. In response to the threat posed by SWI, Geoscience Australia and the National Centre for Groundwater Research and Training, in collaboration with state and territory water agencies, undertook a national-scale assessment of the vulnerability of coastal aquifers to SWI. This assessment identified the coastal groundwater resources that are most vulnerable to SWI, including future consequences of over-extraction, sea-level rise, and recharge–discharge variations associated with climate change. The study focused on assessing the vulnerability of coastal aquifers to the landward migration of the freshwater–saltwater interface, rather than surface waterbodies.

The National Hazard Impact Risk Service for Tropical Cyclone Event Impact provides information on the potential impact to residential separate houses due to severe winds. The information is derived from Bureau of Meteorology tropical cyclone forecast tracks, in combination with building location and attributes from the National Exposure Information System and vulnerability models to define the level of impact. Impact data is aggregated to Statistical Area Level 1, categorised into five qualitative levels of impact.

Vulnerability functions, that relate damage to hazard magnitude are used in risk and impact assessments, mitigation studies and associated cost benefit analyses. The development of vulnerability functions must address the variety of assets exposed to the hazard of interest and the common scarcity of empirical data to calibrate any functions developed using heuristic or analytical methods. This record reports efforts to improve the knowledge of the vulnerability of Australian domestic housing to riverine inundation. The research is focussed on housing types found in the south-east of Queensland although the results can be applied to houses of similar type elsewhere in Australia. In order to address the wide variety of housing types found in the Australian built environment, in this research representative generic housing types are identified from surveyed building exposure. Analytical vulnerability relationships are developed for each from assessments of repair works at different inundation depths. Finally, the analytical vulnerability curves are compared to empirical data derived from repair costs reported by postal surveys of dwellings affected by flooding in Brisbane-Ipswich, January 2011, and Bundaberg, January 2013. Analytical vulnerability curves are presented for twelve generic housing types and two insurance regimes. The process of developing vulnerability curves analytically is compared to empirical data. The empirical data shows that for insured houses, the analytically derived vulnerability curves provide a reasonable estimate of direct losses. However, for uninsured houses the analytical vulnerability curves are shown to overestimate direct losses. The difference may be due to uninsured residents tolerating a greater level of residual damage or undertaking repairs themselves at cheaper rates than those assumed for the analytical work. Although the results display variability, the empirical data indicate that the presented analytical methodology for constructing vulnerability curves yields reasonable curves that would be suitable for modelling impact of riverine flooding on populations of houses provided that adjustments are made to modelled losses for uninsured dwellings.

Modelling the effectiveness of retrofit to legacy houses requires a quantitative estimate of the houses’ vulnerability to severe wind and how the vulnerability is affected by mitigation work. Historical approaches to estimating vulnerability through either heuristic or empirical methods do not quantitatively capture the change in vulnerability afforded by mitigation. To address this information gap the Bushfire and Natural Hazards CRC project “Improving the Resilience of Existing Housing to Severe Wind Events” has augmented a software tool which models damage from wind loads and associated repair cost. In this paper the development process is described including the establishment of a suite of test cases to assess the effectiveness of the software. An example of the validation work is presented along with the augmentation of the software from the previous version. Finally, use of the software in assessing the incremental effectiveness of a range of mitigation strategies in economic terms is described. Abstract submitted to/presented at the19th Australasian Wind Engineering Society Workshop.

Modelling of the risk posed by the impacts of extreme weather events requires knowledge of the vulnerability, or performance, of building assets. Furthermore, to assess the benefits of mitigation an ability to quantitatively model the change in vulnerability associated with mitigation actions is required. In Australia past efforts at establishing vulnerability relationships between building damage and severe wind have centred on empirical techniques, using data from damage surveys or insurance losses, and heuristic techniques. Neither of these methods permits the change in vulnerability afforded by mitigation work to be quantitatively modelled. The Bushfire and Natural Hazards CRC project “Improving the Resilience of Existing Housing to Severe Wind Events” is developing a software tool, Vulnerability and Adaption to Wind Simulation (VAWS), to provide a quantitative vulnerability model for Australian house types. It is based on the premise that overall building damage is strongly related to the failure of key connections. The software uses a Monte Carlo approach whereby numerous realisations of a single generic house type are subjected to an increasing gust wind speed and the loss at each wind speed is calculated. Each realisation of the house varies from others as many key building parameters, such as connection strength, are sampled from probability distributions. For each instance, at each wind speed, the number and type of failed connections are related to damage states and extents of damage which permits the repair cost to be calculated. The repair cost is adjusted for the repair of debris impact damage and water ingress damage. The modelling of mitigation is easily accomplished by rerunning a house modelled with the probability distribution of an upgraded connection’s strength substituted. The software tool provides quantitative measures of reduced vulnerability that can be used in assessing the incremental effectiveness of a range of mitigation strategies in economic terms. Abstract submitted to/presented at AMOS-ICSHMO 2018 (https://www.ametsoc.org/index.cfm/ams/meetings-events/ams-meetings/amos-icshmo-2018/)