Modelling future flood risks for inland and coastal adaptation planning

Pasquier, Ulysse (2020) Modelling future flood risks for inland and coastal adaptation planning. Doctoral thesis, University of East Anglia.

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Abstract

Floods have historically threatened human and natural systems and the risk they represent is likely to be affected by climate variability and change over the next century. With rising sea levels putting further pressure on low-lying regions, there is a need for a catchment-to-coast understanding of flooding hazard to inform on potential anticipatory measures. Computational flood modelling advances offer opportunities to better support decision-making on flood risk management. While adaptation is increasingly recognised as needed in the face of climatic changes, the implementation of adequate solutions has faced fundamental barriers. This has led to a call for integrated assessments of flood risk that adopt a holistic approach in the depiction of physical flooding processes and engage with local stakeholder knowledge.

Britain’s largest protected wetland – the Broads – and its neighbouring coast, were chosen as a study site to assess future flood risk and stakeholder-defined adaptation measures. A 1D-2D hydraulic model was developed in HEC-RAS to simulate flooding impacts under 21st -century scenarios of extreme sea level, extreme river discharge and for combined events, based on UK Climate Projections (UKCP18). The model was designed iteratively, engaging with local perspectives of flood risk and adaptation, notably during a scientist-stakeholder workshop. The results highlighted the area’s sensitivity to different rates of sea level rise, with inundation extent increasing by 15-135% and river saline incursions up to 30 km inland by 2080. While highly unlikely, combined events were found to exacerbate flooded area by 5-40% and average depth by 1-32%. Stakeholders showed a willingness to act on these threats and deviate from current practices, favouring a protective strategy based on a tidal barrier or storage areas. This research shows the potential for integrated modelling approaches to create an interface for science and practice, producing usable information for decision-makers and thereby promoting action on adaptation

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Science > School of Environmental Sciences
Depositing User: Chris White
Date Deposited: 14 Dec 2023 13:12
Last Modified: 14 Dec 2023 13:12
URI: https://ueaeprints.uea.ac.uk/id/eprint/93979
DOI:

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