A man-made dune-beach-spit system at the south-east side of the island of Texel (Prins Hendrik site) has been built in 2018–2019 to strengthen the traditional dike. The core of the dune-beach-spit system consists of medium fine sand with a d₅₀ of 0.25–0.3 mm. The beach is covered with an armour (protection) layer of coarse materials with relatively large gravel and shell fractions to reduce wind erosion and thus maintenance costs. In the design phase of the project the aeolian sand transport model of Bagnold was used to estimate the long-term erosion losses of sand at the new dune-beach system. This transport model was validated in the design phase by using detailed sand transport and bed roughness measurements at a nearby site called The Hors. This site is a wide natural beach plain of sand (d₅₀ = 0.23 mm), where 147 high-quality datasets have been collected using a wind mast equipped with 5 cup anemometers and various sand traps. It is shown that the measured sand transport rates at the Hors can be reasonably well represented by the modified Bagnold-equation for dry sand. After completion of the new dune-beach system, a field experiment was performed at the Prins Hendrik site to verify the sediment transport predictions and erosion loss of sand. Data from two permanent wind masts and one short, mobile wind mast were used to derive the effective roughness of (stationary) bed forms. Sand transport rates were measured at various locations using a new trap sampler. The measured sediment transport in the armoured beach zone can be reasonably well represented by the Bagnold-equation using a multi-fraction approach with hiding-exposure coefficient. The predicted transport rates have been used to estimate the annual loss of sand from the Prins-Hendrik site.

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In the present study a new multi-fractional, depth-averaged sediment transport module was developed and embedded into a morphodynamic model for a sand-silt mixed shallow water environment. Subsequently, the model was applied to the case of the Jiangsu coast, which features a silt enriched sedimentary environment bordered by two large-scale geomorphological units: the Old Yellow River Delta (OYRD) in the north and the Radial Sand Ridge Field (RSRF) in the south. Based on this case, the predictive abilities of the present model are
assessed on both the short-term and the long-term. Comparisons with measurements over two successive tidal cycles indicate that the present model produces very good results on short-time scales. The model performance is
extended and further validated by comparing the overall annual Suspended Sediment Concentration (SSC) pattern, the annual morphological changes, the annual sediment budget and the evolution trend of the bed composition. Also, these long-term results agree well with existing observations over the past several decades. Hence, an essential feature of the present modelling approach is the ability to simulate sediment transport and morphological changes over a relatively long time span (i.e., time scale of years) in a sand-silt mixed sedimentary environment, based on its validated short-term performance.@en

Mega-nourishments, aiming at providing long-term coastal safety, nature qualities and recreational space, have been applied recently at the Holland coast and are considered at various other places in the world. Methods to quickly evaluate the potential and lifetime of these coastal mega nourishments are therefore very much desired, which is the main objective of this research. Two types of mega nourishments can be distinguished: feeder-type mega nourishments may erode freely to feed adjacent coasts for a more natural, dynamic dune growth while permanent mega-nourishments are designed to preserve safety levels and need to maintain their size and shape and thus needs to be nourished themselves. The design and impact assessment studies for both types of mega nourishments require detailed morphological studies to determine the morphological evolution. In this paper 2DH (Delft3D) and 1D (UNIBEST-CL+ and LONGMOR) numerical models were calibrated using data of the Sand Motor mega-nourishment and were then applied to model a series of mega-nourishments with various width over length ratios and volumes in order to derive relations and design graphs for erosion rates, life span and maintenance volumes. These relations and design graphs can be used in project initiation phases and feasibility studies. The magnitude of the modelled wave-driven longshore sediment transport rates in 1D coastline models depend on the representation of wave refraction on the lower shoreface, since a distinction should be made between the non-rotating lower shoreface and active surfzone. It was shown that the life time of nourishments is mainly determined by the dimensions of the nourishment and incoming wave energy.

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Most numerical models are run and compared to data in a subjective
manner. This paper demonstrates how model performance statistics can be
used to calibrate and/or validate hydrodynamic models in a more
objective way. Statistics were also used to compare model runs that used
different amounts of field data in order to inform the debate about the
optimum mix of modelling and measurement.
The hydrodynamics around the mouth of the Teign estuary (UK) have been
simulated using two coastal area numerical modelling systems. Model
performance statistics were calculated to assess the accuracy of the
predictions of the measured currents at a number of locations around the
estuary mouth. The relative mean absolute error was used as it is
applicable to vectors as well as scalars and measures all types of
errors. An adjusted relative mean absolute error was also used to reduce
the effect of measurement error. A classification table was adopted that
categorises the results according to the size of the error. In addition,
time series and scatter plots were used to judge the performance of the
modelling systems.
Calm conditions during a spring tide were simulated, as was a relatively
large storm. The two modelling systems gave more or less equal
performances when run in engineering mode (where default values were
used for most of the system settings). In each case, one modelling
system performed better than the other at some locations and worse than
it at other locations. One model was also run using a scientific
approach, where different amounts of information were used to alter the
model settings and sensitivity tests were performed. The model
performance statistics showed that using more data does not necessarily
lead to better model predictions. New methods for incorporating data
into the operation of a model need to be evaluated thoroughly before
they can be used without site-specific calibration.@en