The increasing demand for energy and the impacts generated by CO₂ emissions make it necessary to harness all possible renewable sources of energy, like wave power. Nevertheless, climate change may generate significant variations in the amount of wave energy available in a certain area. The aim of this paper is to study potential changes in the wave energy resource in the Mediterranean coast of Morocco due to climate change. To do this, wave datasets obtained by four institutes during the Coordinated Regional Climate Downscaling Experiment in the Mediterranean Region (Med-CORDEX) project are used. The future conditions correspond to the RCP4.5 and RCP8.5 scenarios from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The results show that projected future wave power is very similar to that of the present considering the whole area, although at some specific points there are slight changes that are more evident for the RCP8.5 scenario. Another remarkable result of this study is the significant increase of the temporal variability of wave power in future scenarios, in particular for RCP8.5. This will be detrimental for the deployment of wave energy converters in this area since their energy output will be more unevenly distributed over time, thus decreasing their efficiency.

In this paper, the effectiveness of transplanted (either created or restored) seagrass meadows as a coastal protection measure is assessed through a five-step methodology. The analysis is focused on a stretch of the Catalan coast (NW Mediterranean) which is a fetch-limited environment. The results show that even considering conservative values for the meadow parameters (plant diameter, meadow density and canopy height), significant reductions of the annual average wave heights reaching the beach may be obtained, reducing flooding and erosion risks. Therefore, the investment in the conservation and restauration of seagrass meadows for protecting coastal areas from erosion and flooding is a measure that must be considered, due to the multiple benefits that they provide including ecosystem services. In addition, the proposed methodology may be a useful tool for coastal managers to help them in the design of seagrass meadows for coastal protection.

The normality polynomial and multi-linear regression approaches are revisited for estimating the reliability index, its precision, and other reliability-related values for coastal and structural engineering applications. In previous studies, neither the error in the reliability estimation is mathematically defined nor the adequacy of varying the tolerance is investigated. This is addressed in the present study. First, sets of given numbers of Monte Carlo simulations are obtained for three limit state functions and probabilities of failure are computed. Then, the normality polynomial approach is applied to each set and mean errors in estimating the reliability index are obtained, together with its associated uncertainty; this is defined mathematically. The data is also used to derive design points and sensitivity factors by multi-linear regression analysis for given tolerances. Results indicate that power laws define the mean error of the reliability index and its standard deviation as a function of the number of simulations for the normality polynomial approach. Results also indicate that the multi-linear regression approach accurately predicts reliability-related values if enough simulations are performed for a given tolerance. It is concluded that the revisited approaches are a valuable option to compute reliability-associated values with reduced simulations, by accepting a quantitative precision level.