@article {bnh-6567, title = {Simulation optimisation for natural hazard risk management}, number = {533}, year = {2020}, month = {01/2020}, institution = {Bushfire \& Natural Hazards CRC}, address = {Melbourne}, abstract = {

In this report, we outline a decision-support framework for natural hazard management that combines the use of simulation and optimisation for exploring what risk reduction measures best achieve management priorities. This framework addressed several needs that practitioners have with regard to risk and adaptation assessment. First, it uses optimisation approaches to screen through and identify those management options that perform best across a number of decision criteria. This is important, as there are a very diverse range of management options which could be combined in an extremely large number of ways to make portfolios of management options and it is difficult to screen through all potential portfolios to shortlist a small number for further consideration. Second, it simulates the effectiveness of management options over long-term planning horizons. This is important, for management options may have long lead-in-times, and/or may have long lifetimes, are not easily/readily changed, and so need to be effective over a broad range of plausible future conditions, which likely include larger populations, increased economic development and climate change. Third, the framework emphasises holistic assessment, wherein the Integrated assessment modelling (IAM) simulates the effect of management options across a number of criteria, therefore allowing practitioners to explore the trade-offs between risk reduction with other community goals, including environmental, social and economic outcomes.


The value of this framework arises from the greater demands that are being placed on planners to effectively manage natural hazard risk, whether from politicians or from the public who have an increasingly reduced appetite for hazard losses. This creates a need for analytic frameworks for exploring how to best manage risk, and this framework addresses this gap.


Through application to a case study, this report shows how the framework is able to increase the effectiveness and efficiency by which IAM can be applied to natural hazard risk management. The role of the optimisation was seen not to be prescriptive, but to enable better exploration of risk management options. The framework was therefore able to provide rich information on the effectiveness of management portfolios by which better risk management plans could be formed.


The case study to which the framework was applied considered coastal flood risk within Greater Adelaide and explored the combinations of zonal exclusion areas along the coast which prevented further development. If unmitigated, coastal risk could increase by 10\% over the next three decades. However, results of the case study application showed that zonal exclusion policies could effectively reduce this growth of coastal risk, however this required excluding further development from 7000 Ha of land along the coast. Saying that, the growth in risk could be limited to 3\% (i.e. a reduction in growth by 60\%), through excluding coastal development from only 1500 Ha.

}, keywords = {natural hazard, optimisation, risk management, simulation}, issn = {533}, author = {Jeffrey Newman and Graeme Dandy and Aaron Zecchin and Hedwig van Delden and Charles Newland and Holger Maier and Graeme Riddell} }