Assessing changing coastal flood risk becomes increasingly uncertain across multi-decadal timeframes. This uncertainty is a fundamental complexity faced in vulnerability assessments and adaptation planning. Robust decision making (RDM) and dynamic adaptive policy pathways (DAPP) are two state-of-the-art decision support methods that are useful in such situations. In this study we use RDM to identify a small set of conditions that cause unacceptable impacts from coastal flooding, signifying that an adaptation tipping point is reached. Flexible adaptation pathways can then be designed using the DAPP framework. The methodology is illustrated using a case study in Australia and underpinned by a geographic information system model. The results suggest that conditions identified in scenario discovery direct the attention of decision-makers towards a small number of
uncertainties most influential on the vulnerability of a community to changing flood patterns. This can facilitate targeted data collection and coastal monitoring activities when resources are scarce. Importantly, it can also be employed to illustrate more broadly how uncontrolled societal development, land use and historic building regulations might exacerbate flood impacts in low-lying urban areas. Notwithstanding the challenges that remain around simulation modelling and detection of environmental change, the results from our study suggest that RDM can be embedded within a DAPP framework to better plan for changing coastal flood risks.
adaptation, climate change, inundation, tipping point, uncertainty, vulnerability