A rapid, low-cost approach to coastal vulnerability assessment at a national level

Vulnerability is defined as the system’s potential to be damaged by a certain climate change (CC) hazard, and ideally, it has to be assessed by accounting for the different factors controlling the coastal response both in negative (susceptibility) and positive (resilience) terms to changing climatic and/or geomorphic conditions. The lack of an easy-to-use assessment method that requires only readily available data has severely hampered efforts to assess national-scale coastal vulnerability to the potential impacts of CC and population growth in the coastal zone, particularly when project budgets are limited. This study presents a modified version of the Coastal Vulnerability Index (CVI) approach. The main modifications are (1) the introduction of a more physically meaningful representation of the wave effect where storm erosion will only occur when the wave height exceeds a certain threshold value, and (2) an aggregated coastal-vulnerability classification method that comprises exactly the same number of vulnerability classes as that of the individual components of the CVI. As a demonstration, the method is applied to the 4996-km-long peninsular coastline of Spain. Under the worst-case scenario considered (sea-level rise [SLR] of 1 m by 2100), 50% of the Spanish coastline is classified as highly or very highly vulnerable. Given that tourism contributes 10% of the Spanish gross domestic product (GDP), it is noteworthy that high/very high vulnerability (both under low and high emissions scenarios) is indicated for very popular touristic areas along the Mediterranean Coast. These outcomes are likely to enable coastal managers/planners to identify high priority areas for further, more-detailed coastal vulnerability/hazard/ risk quantification studies.Roshanka Ranasinghe is supported by the AXA Research fund and the Deltares Harbour, Coastal and Offshore Engineering Research Programme Bouwen aan de Kust. The work of the third author was done in the framework of the RISES-AM (Grant No. 603396) and PaiRisC-M (CTM2011-29808) research projects funded by the EU and the Spanish Ministry of Economy and Competitiveness, respectively