Big Data Approaches for coastal flood risk assessment and emergency response

DREAM PhD student Jamie Pollard has published a new paper in WIRES Climate Change that discusses the potential for Big Data Approaches to address the challenges of flood risk assessment and emergency response.

Big Data Approaches (BDAs) refers to the combined use of historic datasets, incoming data streams, and the array of related technologies designed to shed new light on societal and environmental complexities through novel organisational, storage and analytical capabilities.
Two branches of coastal flood risk management are considered. Firstly, coastal flood risk assessment, focusing on better characterisation of hazard sources, facilitative pathways and vulnerable receptors. Secondly, flood emergency response procedures, focusing on forecasting of flooding events, dissemination of warnings and response monitoring.

While these BDAs offer opportunities for improved decision making in varied aspects of both decision chains, they are also accompanied by specific technical contextual, institutional and behavioural barriers. These barriers must be overcome if the BDAs outlined here are to practically and genuinely inform coastal flood risk management.
In addition to specific implementation barriers, two more fundamental challenges have been identified:

• the ability of BDAs to provide useful insights under conditions of incertitude (uncertainty, ambiguity and ignorance), given that coastal flood risk managers of the future must respond to non-analogue environmental conditions.
• the need to identify and cultivate appropriate skill sets among communities of coastal researchers, policy and decision makers.

Having established the potential theoretical and practical gains offered by BDAs in coastal research, the priority now must be to assess the suitability of BDAs in other environmental domains.

Full Open Access Article Here: