Probabilistic modeling of wave climate and predicting dune erosion

Knowledge about future oceanographic events will assist governments to better manage risk in coastal zones, a crucial task in the light of projected sea level rise, population growth and economic development. In this study, a 31-year data set of deep water wave climate parameters and bathymetry measurements (yearly cross-shore transect surveys) at Noordwijk, the Netherlands, were analyzed (1) to jointly estimate storm events variates of deep water wave conditions, and (2) to probabilistically compute dune erosion volume and the resulting coastal retreat distance with the simulated wave climate and plausible local sea level rise scenarios by 2100. The probabilistic coastline retreat models were applied and adjusted to the study site. Based on the outcomes of this application, a modeling technique can be established to propose a framework for probabilistically describing the coastal risk along the Dutch coast.