Environment

Big Data Approaches for Coastal Flood Risk Assessment and Emergency Response

Researchers have identify a series of ‘Big Data Approaches’ (BDAs) with the potential to shed new light on the complexities and challenges surrounding coastal flood risk management.

Coastal flooding is among the deadliest and costliest hazards faced by modern societies. Furthermore, global trends such as accelerating sea level rise, concentration of people and assets in low-lying areas, and deterioration of protective coastal ecosystems are likely to increase future flood risk.

As reported in the latest Intergovernmental Panel on Climate Change Report, carbon-dependant societal processes have resulted in a degree of ‘lock-in’ to this higher risk future, regardless of stabilization in global mean temperature. Consequently, coastal flood risk managers face a substantial challenge, both in the assessment of coastal flood risk and in executing effective emergency management procedures when flooding occurs.

A critical question to be answered therefore is: ‘What tools do these managers have at their disposal to address future flood risk?’

Seeking to answer this question, researchers from the Universities of Cambridge and Cranfield, in their WIREs Climate Change review, identify a series of ‘Big Data Approaches’ (BDAs) with the potential to shed new light on the complexities and challenges surrounding coastal flood risk management. Considering both risk assessment (prior to a flooding event) and emergency response (during the event itself), the paper identifies numerous opportunities for improved decision making. The paper also provides a critical discussion on possible barriers to implementing the Big Data Approaches identified. The coastal risk management community faces two fundamental challenges: the extent to which BDAs can provide useful insights under various forms of uncertainty and to ensure that the next generation of ‘coastal data scientists’ have the skills necessary to develop and apply BDAs.

 

Kindly contributed by Jamie Pollard.

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