Advancing flood risk mapping from global modelling systems in small islands

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This project aims to advance the mapping of flood hazard and risk in small islands and assess the potential of emerging data sets to identify hotspots of extensive disaster risk and how such data might be used in conjunction with community level information. This will be achieved via three steps: 1) Utilising emerging high-resolution datasets to improve flood risk estimation in SIDS from island to community scales 2) Investigating risk accumulation and everyday hazards/extensive disaster risk at community scale 3) Meeting in the middle: assessing the utility of emerging risk modelling methods for the identification of everyday hazards in SIDS Several emerging high-resolution elevation and population datasets are becoming available that might enable community resolving flood risk modelling in data-sparse but high-risk locations such as SIDS. It is important to identify and understand how these datasets can be used in a flood modelling test case, and whether these datasets can improve flood risk estimates over currently-available datasets. How far can we go with the 'top down' remotely sensed data before we need information from the bottom up community level (e.g. community local knowledge on areas of flooding, drain location, expert knowledge from key actors, ground truth information on infiltration or frequently flooded locations)? How could we incorporate local knowledge to inform our models so that we can take the modelling further than just top-down inference? Where is this intersection between the top-down and the bottom-up and can they be used in synergy? What are the implications of improved risk estimation technology for applications in small catchments including insurance? Skills developed addressing these problems should provide training for a wide range of careers related to disaster risk reduction, risk assessment and catastrophe risk modelling.