For the design, safety assessment and rehabilitation of coastal structures reliable predictions of wave overtopping are required. Several design formulae exist for simplified types of dikes, rubble-mound breakwaters and vertical breakwaters. Nevertheless, often no suitable prediction methods are available for structures with non-standard shapes.

The Overtopping Neural Network is a conceptual- design tool to estimate wave overtopping discharges for a wide range of coastal structures. Resampling techniques are applied for the assessment of the uncertainties of the predictions. Only one schematisation is used for all types of coastal structures, where not only dikes, rubble- mound breakwaters or vertical breakwaters are defined, but also other non-standard structures are included. Besides the effect of the most common parameters (i.e. wave height, wave period and crest freeboard) also the effects of many other wave and structural characteristics are considered.

The Neural Network is also implemented in the Deltares software tool BREAKWAT, which is a conceptual design tool for several types of Coastal Structures under wave loading, including rubble mound breakwaters with armour layers of rock material or concrete units, berm breakwaters, vertical caisson structures, reef type structures and near-bed structures.

The employed prediction method is based on Neural Network modeling. Neural networks (NN) have proven to be very useful for solving difficult modelling problems, i.e. for the modelling of processes in which the relationship of the individual modelling parameters is unclear while sufficient experimental data is available to identify the relations. Details of the NN and the methodology followed for the development of the prediction tool are described in Van Gent et al. (2007). The model was derived by from about 10,000 physical model tests at several institutes (Aalborg University, Denmark; Danish Hydraulic Institute, Denmark; WL | Delft Hydraulics, The Netherlands; Hydraulic Research Wallingford, UK; Leichtweiss Institute für Wasserbau, WKS+GWK, Germany; Modimar, Italy; University of Edinburgh, United Kingdom; Universidad Politécnica de Valencia, Spain; and others in Iceland, Japan, Norway and U.S.A).

The predictions based on the Overtopping Neural Network can be used for the conceptual design of coastal structures; they may not be used in the final design stage, since the results should be verified based on dedicated physical model tests (Deltares facilities) for the particular wave conditions and structure geometry of the structure to be built.

The Overtopping Neural Network has been co-sponsored by the Commission of the European Communities within the framework of the CLASH project (Crest Level Assessment of coastal Structures by full scale monitoring, neural network prediction and Hazard analysis on permissible wave overtopping, contract EVK3–2001–00058).


Van Gent, M.R.A., H.F.P. van den Boogaard, B. Pozueta and J.R. Medina (2007), Neural network modelling of wave overtopping at coastal structures, Elsevier, Coastal Engineering, Vol.54, pp. 586-593.”