@article {bnh-3916, title = {Review of literature on decision support systems for natural hazard risk reduction: current status and future research directions}, journal = {Environmental Modelling \& Software}, volume = {96}, year = {2017}, month = {10/2017}, pages = {378-409}, chapter = {378}, abstract = {

Natural hazard risk is largely projected to increase in the future, placing growing responsibility on decision makers to proactively reduce risk. Consequently, decision support systems (DSSs) for natural hazard risk reduction (NHRR) are becoming increasingly important. In order to provide directions for future research in this growing area, a comprehensive classification system for the review of NHRR-DSSs is introduced, including scoping, problem formulation, the analysis framework, user and organisational interaction with the system, user engagement, monitoring and evaluation. A review of 101 papers based on this classification system indicates that most effort has been placed on identifying areas of risk and assessing economic consequences resulting from direct losses. However, less effort has been placed on testing risk-reduction options and considering future changes to risk. Furthermore, there was limited evidence within the reviewed papers on the success of DSSs in practice and whether stakeholders participated in DSS development and use.

}, doi = {10.1016/j.envsoft.2017.06.042}, url = {http://www.sciencedirect.com/science/article/pii/S1364815216311239}, author = {Jeffrey Newman and Holger Maier and Graeme Riddell and Aaron Zecchin and James Daniell and Andreas Schafer and Hedwig van Delden and Bijan Khazai and Michael O{\textquoteright}Flaherty and Charles Newland} } @conference {bnh-2949, title = {A spatial decision support system for natural hazard risk reduction policy assessment and planning}, booktitle = {AFAC16}, year = {2016}, month = {08/2016}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Brisbane}, abstract = {

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{\textendash}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.

}, author = {Graeme Riddell and Holger Maier and Hedwig van Delden and Jeffrey Newman and Aaron Zecchin and Roel Vanhout and James Daniell and Andreas Schafer and Graeme Dandy and Charles Newland} }