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Unravelling the Importance of Uncertainties in Global-Scale Coastal Flood Risk Assessments under Sea Level Rise

Abstract : Global scale assessments of coastal flood damage and adaptation costs under 21st century sea-level rise are associated with a wide range of uncertainties, including those in future projections of socioeconomic development (shared socioeconomic pathways (SSP) scenarios), of greenhouse gas concentrations (RCP scenarios), and of sea-level rise at regional scale (RSLR), as well as structural uncertainties related to the modelling of extreme sea levels, data on exposed population and assets, and the costs of flood damages, etc. This raises the following questions: which sources of uncertainty need to be considered in such assessments and what is the relative importance of each source of uncertainty in the final results? Using the coastal flood module of the Dynamic Interactive Vulnerability Assessment modelling framework, we extensively explore the impact of scenario, data and model uncertainties in a global manner, i.e., by considering a large number (>2000) of simulation results. The influence of the uncertainties on the two risk metrics of expected annual damage (EAD), and adaptation costs (AC) related to coastal protection is assessed at global scale by combining variance-based sensitivity indices with a regression-based machine learning technique. On this basis, we show that the research priorities in terms of future data/knowledge acquisition to reduce uncertainty on EAD and AC differ depending on the considered time horizon. In the short term (before 2040), EAD uncertainty could be significantly decreased by 25 and 75% if the uncertainty of the translation of physical damage into costs and of the modelling of extreme sea levels could respectively be reduced. For AC, it is RSLR that primarily drives short-term uncertainty (with a contribution ~50%). In the longer term (>2050), uncertainty in EAD could be largely reduced by 75% if the SSP scenario could be unambiguously identified. For AC, it is the RCP selection that helps reducing uncertainty (up to 90% by the end of the century). Altogether, the uncertainty in future human activities (SSP and RCP) are the dominant source of the uncertainty in future coastal flood risk
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https://hal-brgm.archives-ouvertes.fr/hal-03746388
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Soumis le : vendredi 5 août 2022 - 11:16:45
Dernière modification le : vendredi 5 août 2022 - 11:26:29

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Jeremy Rohmer, Daniel Lincke, Jochen Hinkel, Gonéri Le Cozannet, Erwin Lambert, et al.. Unravelling the Importance of Uncertainties in Global-Scale Coastal Flood Risk Assessments under Sea Level Rise. Water, MDPI, 2021, 13 (6), pp.774. ⟨10.3390/w13060774⟩. ⟨hal-03746388⟩

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