Camus Braña, Paula

Díaz Simal, Pedro

Losada Rodríguez, Iñigo

Menéndez García, Melisa

Toimil Silva, Alexandra

English

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Geophysical Research AbstractsVol. 21, EGU2019-17340, 2019EGU General Assembly 2019© Author(s) 2019. CC Attribution 4.0 license.A probabilistic framework for the assessment of climate change-drivencoastal erosion riskAlexandra Toimil, Inigo Losada, Paula Camus, Pedro Diaz-Simal, and Melisa MenendezEnvironmental Hydraulics Institute, Universidad de Cantabria, Santander, SpainShoreline recession due to the combined effect of waves, surges, tides and sea level rise (SLR) is increasinglybecoming a major threat to beaches, one of the main seaside tourist destinations worldwide. Given such anuncertain future climate and the climate-sensitive nature of many decisions that affect the long term, there is agrowing need to shift current approaches towards probabilistic frameworks able to consider uncertainty.We develop a methodology to assess climate change-driven coastal erosion risk based on the IPCC risk framework(IPCC, 2014), in which risk results from the interplay of hazard, represented by the coastal dynamics, exposure,described by physical and socioeconomic settings, and vulnerability, associated with the susceptibility andadaptive capacity of the system. The methodology consists of a multitiered process in which these components aredeveloped individually but are finally integrated to derive expected losses.A statistical method to generate beach erosion hazards must take into account that this impact involves two or morerandom variables (i.e. significant wave height, sea level), and that the erosion process depends on storm durationand antecedent beach conditions, which relies in turn on beach recovery between storms. Multiple simulations ofa process-based approach that combine cross section–based equilibrium models and long-shore sinks allow thereconstruction of thousands of potential shoreline evolutions over the 21st century (Toimil et al., 2017).Exposure is defined by the users’ preferences (i.e. when they would rather go to the beach), expressed in termsof effective utilization rates and their purchasing power, as an indicator of how much they value the time forrecreation (Toimil et al., 2018). Concerning vulnerability, aspects related to the typology, the quality (i.e. water,sand and services), and the number and distribution of access points and parking facilities are considered (Toimilet al., 2018).We present a regional approach for the assessment of erosion risks triggered by climate-related extreme eventsand SLR. The framework is applied regionally over the Asturian coast, a 345 km coastline on the Cantabrian Sea(North of Spain), where the risk of loss of beach recreation as a proxy for tourism is provided in probabilistic terms.ReferencesIPCC (2014) Summary for policymakers. In Climate Change 2014: Impacts, Adaptation and Vulnerability.Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of theIntergovernmental Panel on Climate Change [eds. CB Field al.]. Cambridge University Press, Cambridge, UnitedKingdom and New York, NY, USA, 2014, pp. 1-32.Toimil A, Losada IJ, Camus P, Diaz-Simal P. (2017). Managing coastal erosion under climate change at theregional scale. Coastal Engineering, 128, 106–122.Toimil A, Diaz-Simal P, Losada IJ, Camus P (2018) Estimating the risk of loss of beach recreation value underclimate change. Tourism Management 68:387-400.

A probabilistic framework for the assessment of climate change-driven coastal erosion risk

https://repositorio.unican.es/xmlui/bitstream/10902/18703/3/ProbabilisticFrameworkAssessment.pdf

A probabilistic framework for the assessment of climate change-driven coastal erosion risk

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