Many tropical, coral reef-lined coasts, are low-lying with elevations less than five meters above mean sea level. Climate-change-driven sea level rise, coral reef decay and changes in (storm) wave climate will lead to greater chance and impacts of wave-driven flooding, posing a heavy threat to these coastal communities. Early warning systems (EWS) are effective for risk management and disaster reduction, however, the vast majority of the world's inhabitants of coral reef-lined coasts have no such system in place. Unfortunately, the complex hydrodynamics and bathymetry of reef-lined coasts make it difficult to establish a global flood prediction model for these areas. This thesis aims to develop a set of 'cluster profiles' that can be used to accurately represent coral reef-lined coasts around the globe. By representing an expansive variety of reef morphology, the cluster profiles are capable of predicting the wave runup over thousands of different coral reef profiles with a fraction of the number. The cluster profiles could be input into a tool such as a Bayesian probabilistic network which can be trained to provide real-time wave runup and flooding predictions given local bathymetry and offshore wave conditions, thus establishing a simplified global flooding EWS. The methodology includes two stages of data reduction. First, cluster analysis techniques are used to group thousands of coral reef profiles into 500 clusters based on morphology alone. Second, agglomerative hierarchical clustering is used to further group the profiles with similar morphology and wave runup response, resulting in a final set of 311 to 45 cluster profiles. Here we show that the cluster profiles are capable of predicting the wave runup for a set of 1000 reef profiles with a mean relative difference of approximately 10\%. The comparison was done using the numerical wave model XBeach with four different wave conditions. The methodology has been developed such that it could be expanded to other coastal environments. A summary of the methodology used in the study is illustrated on the following page.

In the Netherlands flood protection is immensely important for the safety of the nation. The shocking outcome of the 1953 flooding proves this point. In modern days, the development of socioeconomic and climate change factors casts doubt on the effectiveness of conventional approaches to flood risk management. Consequently, this project explored new approaches to flood risk management.
An analysis of climate change effects led to estimation of future loading conditions. Subsequently, a detailed hydrodynamic analysis was conducted. It highlighted the significant levels of uncertainty that climate change introduces into loading conditions. Also, it confirmed the team’s perception, that the Westkapelle case region requires additional safety measures to guarantee an acceptable level of safety in the future. But how to guarantee the acceptable level of safety in the most efficient way? The team adopted the concept of robustness to find an answer. In a keynote publication Mens (2015) describes robustness in the following way: "Robust flood risk systems have some degree of resistance and some degree of resilience: the system can withstand some floods (no response), and for other (larger) floods impacts are limited and the system can recover quickly from the flood impact (response and recovery)." The team set out to include robustness as an integral part of the design process to handle uncertainties. The project shall be seen as an explorative study how this can be done, revolving around Westkapelle as a case study that proves the methodology’s feasibility. Robustness and uncertainty were included on multiple levels throughout the design process. Firstly, the range of uncertainties was quantified. Secondly, the effect, that single parameters have on the magnitude of uncertainties, was assessed. Thirdly, the system’s capacity was analysed to find the required overtopping reduction for guaranteeing sufficient safety. Fourthly, constructive measures were assessed on their robustness potential and satisfaction of stakeholder needs via a Multi Criteria Analysis (MCA). The MCA was then employed to select the type of constructive and non constructive measures to achieve the required levels of overtopping and safety. With the information on uncertainties, the measures were combined to form a robust design, consisting of living breakwater, dike heightening, surface protection and two policy measures. Probabilistic analysis was also done to see the sensitivity of the failure probability to sea level rise in different loading and design scenarios. A thorough comparison between the conventional design, that has been applied to the project location, and the robust design followed. The robust design came out on top. Robustness was found to be an effective tool in countering uncertainties. Where conventional design methodologies are lacking flexibility and precision, the robust design methodology makes use of the system and its resilience to find an optimal solution. Its applicability may not be limited to flood risk management only but stretch out to other civil engineering disciplines.