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Coastal floods are one of the deadliest and costliest of natural hazards, triggering or contributing to economic disruption, displacement, (mental) health implications, environmental disasters, poverty traps, and geomorphic change. In the coming century, coastal communities are projected to face increases in coastal flood risk. To prevent this increase in coastal flood risk, or even reduce risk below today’s levels, adaptation strategies are necessary. To make informed decisions on what measures to take, it is important to better understand the effectiveness of such coastal flood risk adaptation strategies, preferably beyond just monetary terms. Therefore, the overall aim of this thesis is to disentangle drivers of coastal flood risk and assess costs and benefits of adaptation strategies. By doing so, the thesis improves upon conventional flood risk assessments by taking steps into the direction of integrated and holistic assessments that include Nature-based Solutions and valuing of adaptation beyond monetary terms. This thesis uses artificial intelligence in the form of deep learning to construct a model to predict storm surges (which may lead to coastal flooding) at the global scale. Next to this, a risk model has been constructed to assess the effectiveness of adaptation strategies (based on structural measures, Nature-based Solutions, or a combination which is called “hybrid” measures). We assess risk by using projections of sea-level rise, socioeconomic change, subsidence, foreshore vegetation and restoration potential. Next to this we use vulnerability data, like poverty dynamics, to assess effectiveness of adaptation measures beyond monetary values. The results show that EAD increases by a factor of 150 between 2010 and 2080, if no adaptation were to take place, and that 15 countries account for approximately 90% of this increase. Moreover, sea-level rise contributed the most to the increase in coastal flood risk, but socioeconomic change and subsidence also play an important role at the regional scale. Furthermore, the results show that implementing Nature-based Solution, like conservation and restoration of foreshore vegetation, can contribute a large share to reduce flood risk and will next to structural measures, likes dikes and levees, increase the feasibility of adaptation strategies for two-thirds (68%) of the regions assessed. Moreover, we show that restoration of mangroves contribute to the safeguarding of communities by providing coastal flood protection benefits. Therefore, implementing adaptation in low- and middle-income countries could contribute to the resilience of people in poverty, poverty alleviation and help tackle poverty traps. Overall, the results of this thesis contribute to international initiatives such as the Sendai Framework for Disaster Risk Reduction and can be used to inform policy makers and development agencies on risks from global to regional level. In order to bridge the gap between academia and the risk management community, we integrated the results into the Aqueduct Global Floods webtool (www.wri.org/floods). This webtool allows any user to examine current and future risk, as well as the benefits of strucutral flood protection at the sub-national scale. Implementing adaptation measures, such as mangrove restoration, in LMICs could contribute to the resilience of people in poverty, decrease the risk of displacement and migration, and tackle poverty traps. The loss of these ecosystems disproportionally affects vulnerable groups and communities that live close to the coast and often heavily depend on natural resources. The results can help policymakers to assess the threat of coastal flooding and design sustainable adaptation measures considering poverty dynamics. |
