Published works

Published works

A spatial decision support system for natural hazard risk reduction policy assessment and planning

TitleA spatial decision support system for natural hazard risk reduction policy assessment and planning
Publication TypeConference Paper
Year of Publication2016
AuthorsRiddell, G, Maier, H, van Delden, H, Newman, J, Zecchin, A, Vanhout, R, Daniell, J, Schafer, A, Dandy, G, Newland, C
Conference NameAFAC16
Date Published08/2016
PublisherBushfire and Natural Hazards CRC
Conference LocationBrisbane

The challenges facing environmental policymakers grow increasingly complex and uncertain as more factors that impact on their ability to manage the environment and its risks need to be considered. Due to a large number of influencing environmental and anthropogenic factors, natural hazard risk is difficult to estimate accurately, and exaggerated by large uncertainty in future socioeconomic consequences. Furthermore, resources are scarce, and the benefits of risk reduction strategies are often intangible. Consequently, a decision support system assisting managers to understand disaster risk has great advantage for strategic policy assessment and development, and is the focus of this extended abstract.
The spatial decision support system (SDSS) presented is being developed in collaboration with several South Australian government departments and funded by the Bushfire and Natural Hazards CRC. It integrates multiple hazard models with a land use model which includes information on population and building stock to consider long term spatial and temporal dynamics of natural hazard risk. The integrated SDSS operates at a 100m resolution with a time-step of one year and can be used to model 20–50 years into the future. Hazards included in the SDSS include riverine flood, coastal inundation, bushfire, heatwave and earthquake. Each is modelled dependent on the relevant physical properties of the hazard and include the impacts of climate change on hydro-meteorological, bushfire and heatwave hazard. The land use model is driven by land use demand (population and jobs), and allocates land accordingly.

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