C. Den Heijer

Probabilistic modeling of wave climate and predicting dune erosion

ABSTRACT Li, F., van Gelder, P.H.A.J.M., Callaghan, D.P., Jongejan, R.B., den Hijer, C. and Ranasinghe, R., 2013. Probabilistic modelling of wave climate and predicting dune erosion considering sea level rise 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.

OpenEarth : Using Google Earth as outreach for NCK's data

In 2003 various projects at Deltares and the TU-Delft merged their toolboxes for marine and coastal science and engineering into one toolbox, culminating in 2008 in an open source release, known as OpenEarthTools (OET). OpenEarth adopts the wikipedia approach to growth: web 2.0 crowd sourcing. All users are given full write access to help improve the collection. Quality is assured by version control, tracking all changes. OpenEarth started as a social experiment to investigate whether crowd sourcing was possible in our community of marine and coastal researchers. The answer is yes: over 1000 users registered, now enjoying over 5000 contributions from over 100 contributors. The most important asset is a general toolbox to plot any data type in Google Earth. With this toolbox it has become very easy for marine and coastal experts to disseminate their data via Google Earth. It enables the NCK community to make its data available to end-users and the general public with only little effort. They can now consume our data as simple as watching YouTube: DataTube. In this paper it is shown that OpenEarth has added important value by analyzing a wide range of marine and coastal data types from NCK simultaneously in Google Earth. To match the traditional gap between specialist knowledge and end users, Google Earth is shown to be a very powerful tool. The possibilities for outreach by NCK are manifold.

REDUCING UNCERTAINTY IN PREDICTION OF DUNE EROSION DURING EXTREME CONDITIONS

Coastal dunes protect low lying coastal areas against the sea. Extreme waves and water levels during severe storms may cause breaching of the dunes. Consequently, serious damage due to flooding and direct wave attack could occur, resulting in loss of life and property. Proper coastal management implies that reinforcement measures will be taken if the actual safety level does not meet the agreed standard. In order to cope with small probabilities of failure, which are relevant for the Dutch dune coast, a proper safety assessment method is required. Various aspects, which are currently considered as relevant for dune erosion, are not included in the present safety assessment method. This study concerns (1) an approach to reduce the uncertainty in dune erosion prediction as well as (2) a probabilistic sensitivity analysis of various variables that are included in the current Dutch safety assessment method. The aim of the latter part is to get more insight in the influence of the stochastic characteristics of the various variables which are taken into account in the current method. The calculation values which are used for the actual safety assessment, in a semi-deterministic way, are based on a full probabilistic investigation. This full probabilistic investigation has been used as a reference for the present sensitivity analysis, in which all stochastic characteristics have been varied. Both the deterministic DUROS+ model, which is used in the current safety assessment method, as well as the process based DUROSTA model have been applied. Main conclusion is that for both DUROS+ and DUROSTA the stochastic characteristics for the water level and the grain size are the most important for the prediction of dune erosion.