Multi-sectoral, high-resolution assessment of climate change consequences of coastal flooding

Alexandra Toimil, Iñigo J. Losada (), Pedro Díaz-Simal, Cristina Izaguirre and Paula Camus
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Alexandra Toimil: Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria
Iñigo J. Losada: Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria
Pedro Díaz-Simal: Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria
Cristina Izaguirre: Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria
Paula Camus: Universidad de Cantabria, Parque Científico y Tecnológico de Cantabria

Climatic Change, 2017, vol. 145, issue 3, No 12, 444 pages

Abstract: Abstract In the context of growing concern about the threat of flooding posed by climate change in coastal areas, the Spanish plan for coastal adaptation to climate change gave rise to stringent requirements on risk consequence estimates at the regional scale O (100 km). Within this framework, we propose a methodology that combines high space-time resolution climate information (reanalysis databases and projections), local data on exposure that accounts for the most relevant sectors, site-specific vulnerability functions, and flood risk consequence valuation, gridded at 5 m. This approach involves efficient multiple-forcing flood modeling, in which the connection between climate change and potential inundation is primarily established through the definition of a total water level index. This research tackles challenging issues, including the importance of incorporating the effects of existing coastal defenses and local wave effects in port areas, dealing with data at different spatial scales and sectors in an integrated way, and the impact of discounting. The results provide insights into the possible consequences of inaction for a range of future scenarios based on changes in climate and socio-economics over the most relevant sectors. With the goal of prioritizing adaptive action and the efficient assignment of funds, we propose a weight-based integration of the sectoral value-at-risk through the application of Bayesian techniques and expert judgment. The methodology described here was applied to a pilot case study on the coast of Asturias in northern Spain.

Date: 2017
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DOI: 10.1007/s10584-017-2104-z

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