Morphological Modelling of a Nourishment at the Brouwersdam Beach

Morphological modelling of a nourishment at the Brouwersdam beach

R.A. Schrijvershof, BSc.

This report is produced as part of the project KPP B&O Kust

1220040-000

Title Morphological modelling of a nourishment at the Brouwersdam beach

Client Project Pages Universiteit Utrecht 1220040-000 45 Rijkswaterstaat Zee en Delta

Keywords Brouwersdam, morphology, nourishment, UNIBEST-CL+

Summary In the scope of an internship project for the Earth Surface and Water (ESW) master’s programme of Utrecht University a modelling study is performed with the UNIBEST-CL+ coastline model. The study aims at modelling different configurations for the planned nourishment, and it this way, establish a configuration that maximizes the ‘life-expectancy’ of the nourishment. Four different shapes in planform geometry and the effect of varying grain sizes of the used sediment are modelled. Results show that an UNIBEST coastline model is capable of reproducing the observed trends and magnitudes of coastline change if a modified Van Rijn (2004) sediment transport formula is used and a scaling factor of 1.5 in time is applied. The simulations with the nourishments show that different nourishment shapes cause different erosion rates and that if the coastline is positioned further from the original coastline, retreat will increase. The varying grain size diameter simulations shows that an increase in median diameter of sediment (D50) of 25 μm will decrease the retreat rate of the coastline with ~7 m and the decrease in surface area with 5000 m2 after 10 years.

Version Date Author Initials Review Initials Approval Initials 1 27 March Reinier R.A. Dirk-Jan Walstra D.R. 2015 Schrijvershof Marian Lazar M. 2 10 April Reinier R.A. Dirk-Jan Walstra D.R. Claire van C. 2015 Schrijvershof Oeveren

State final

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Contents

1 Introduction 3 1.1 Background 3 1.2 Organisation 3 1.3 Aim of the present report 3 1.4 Definitions 4 1.5 Outline 4

2 Problem analysis 5 2.1 Project location 5 2.2 History of the Grevelingen estuary 5 2.3 Morphological developments 7 2.3.1 The ebb delta 7 2.3.2 The beach 11 2.4 Beach nourishment 14 2.5 Research questions 15

3 Data and modelling 16 3.1 Wave modelling with Delft3D-WAVE 16 3.1.1 Offshore wave climate 16 3.1.2 Bathymetry 17 3.1.3 Computational grids 17 3.2 Morphological modelling with UNIBEST-CL+ 20 3.2.1 Longshore Transport (LT) module 20 3.2.2 CoastLine (CL) module 21 3.2.3 Nourishment configurations 23

4 Results 25 4.1 Wave climates 25 4.2 Hindcast simulations 27 4.3 Forecast simulations 29 4.3.1 Without nourishment 29 4.3.2 Nourishment simulations 30

5 Discussion 34

6 Conclusions 36 6.1 Conclusions 36 6.2 Recommendations 36

References 37

Appendices 38

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List of figures Figure 2.1: Location of the Brouwersdam beach (c), in the Netherlands (a), at the border of the provinces Zuid-Holland and Zeeland (b) (sources: www.d-maps.com, Google Earth, Rijkswaterstaat vaklodingen) ...... 6 Figure 2.2: Tidal currents in the ebb tidal delta of the Grevelingen estuary in 1964 (a) and in 2010 (b). E = ebb-dominant flow, F = flood-dominant flow, W = Wave- dominated (Nipius, 1998; from de Jongste et al., 2013) ...... 7 Figure 2.3: Bathymetry of the Grevelingen ebb delta for the period 1964 – 2010 ...... 10 Figure 2.4: Momentarily coastline position through time ...... 13 Figure 2.5: For the period 1990 – 2014: (a) rates of coastline development along measuring lines in Figure 2.4; (b) change of beach surface area; (c) visualization of the calculation of beach volume; and (d-f) total beach volumes with varying boundaries. (source: JARKUS)...... 14 Figure 3.1: Delft3D-WAVE computational grids: (a) the coarse ‘zeeland’ grid (blue) with the nested medium ‘Brouwersdam’ grid (red), (b) the ‘Brouwersdam’ grid with the nested high resolution ‘Noordzeestrand’ grid (green)...... 19 Figure 3.2: UNIBEST coastline model of 2005 (a) and 2014 (b) ...... 22 Figure 3.3: Nourishment types (Google Earth) ...... 23 Figure 4.1: Wave simulation results modelled on the 2004-2006 bathymetry (left) and the 2004-2010 bahtymetry (right) for offshore wave scenario 84 (a and b), scenario 42 (c and d), and scenario 78 (e and f) ...... 26 Figure 4.2: Overview of JARKUS transect locations ...... 27 Figure 4.3: Observed and simulated coastline development for the period 2005 – 2014 with different sediment transport formulae ...... 28 Figure 4.4: Observed and simulated coastline development for the period 2005 – 2014 with the modified Van Rijn (2004) sediment transport formula ...... 29 Figure 4.5: Coastline change in the period 2014 – 2023 ...... 30 Figure 4.6: Coastline development for different nourishment types ...... 31 Figure 4.7: Nourishment surface area development for different nourishment types ...... 31 Figure 4.8: Decrease in surface area for different grain sizes ...... 32 Figure 4.9: Effect of grainsize on (a) coastline retreat and...... 33 Figure 5.1: Development in surface area for nourishment ...... 35

List of tables Table 3.1: Classification of offshore wave conditions (after Huisman and Luijendijk, 2009) ... 17 Table 3.2: Sediment transport settings for Van Rijn (2004) ...... 21 Table 3.3: Simulation runs with settings ...... 24 Table 4.1: Nourishment development statistics ...... 30 Table 4.2: Fit functions of Figure 4.9 ...... 33

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1 Introduction

1.1 Background The Rijkswaterstaat Coastal Maintenance programme 2012 – 2015 (Dutch: Programma Kustlijnzorg 2012 – 2015) has included a beach nourishment at the south-western side of the Brouwersdam beach. The beach at this location is not included in the, in 1990, established basic coastline (BKL; BasisKustlijn) due to the presence of the dam at this location. Therefore, maintenance of the beach is usually not carried out by Rijkswaterstaat. However, extensive lobbying of stakeholders and a financial contribution of € 250,000 from the concerned provinces and municipalities has enabled the option for a single-time nourishment. This nourishment will consist of a volume of 500.000 m3. A volume of 400.000 m3 became available after shifts in the nourishment programme at the Schouwen-Duiveland (Zeeland) coast, in the context of the PINK (Pilot Innovatief Nederlands Kustbeheer) programme. This nourishment will enable the opportunity for stakeholders to benefit for a longer period of time from the beach and it is therefore important to investigate if there are any feasible measures that will increase the ‘life-expectancy’ of the nourishment. This report describes the study that is concerned with the morphological modelling of the nourishment with the UNIBEST-CL+ coastal modelling package.

Previous work discussing the morphological developments of the beach at the Brouwersdam is Lazar (2007) and Wang (2010). Morphological modelling of the beach at the Brouwersdam has been executed before by Witteveen+Bos (2012) and Huibregtse (2013). Witteveen+Bos (2012) made an assessment on the expected morphological developments of the Grevelingen outer delta (including the beach) as response to the construction of a second tidal inlet system in the northern part of the Brouwersdam. Huibregtse (2013) focussed on modelling the expected morphological developments of the beach without any mitigation measures to be taken. This work was carried out with the UNIBEST-CL+ model and therefore the present research continues on the work of Huibregtse (2013).

1.2 Organisation The present report is produced as final product of an internship for the Earth Surface and Water (ESW) Masters programme of the Department of Physical Geography, at the Faculty of Geosciences, Utrecht University. The internship was carried out at Deltares, Delft. Here, the daily supervision was done by ir. D.R. Walstra and ir. B. Huisman was involved as expert in the UNIBEST modelling package. Supervision from Utrecht University was done by prof. dr. B.G. Ruessink. Furthermore, ir. M. Lazar. was involved in the project from Rijkswaterstaat Zee en Delta.

1.3 Aim of the present report The present study is concerned with the morphological modelling of several (feasible) configurations that can be implemented for the planned nourishment at the Brouwersdam beach. The report elaborates on the problem and quantifies the observed erosional patterns. The methods and results of the modelling procedure are described and analysed, thereby a quantification of the expected erosional patterns are given. The goal of the report is to give a clear recommendation on a nourishment configuration that maximizes the ‘life-expectancy’ of the nourishment for the next ~10 years.

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1.4 Definitions All the quantities in this report are given as S.I. units and derivatives from these units. Water depth is given with respect to the Dutch ordnance datum (Normaal Amsterdams Pijl, NAP). For the direction of wind and waves, the nautical convention is used in degrees, with North as 0°. All geographical locations and maps in the report are given in (x,y) coordinates, in the ‘RijksDriehoekstelsel’ (RD) new. The only exceptions are the location of ‘Europlatform’, which is situated outside the boundaries of the RD coordinate system, and the maps in Appendix C.

1.5 Outline The area of the present project and the observed morphological developments at this area are described in Chapter 2, hereafter the research questions of the project are presented. The set-up of the hydrodynamic (Delft3D-WAVE) and morphological (UNIBEST-CL+) models is described in Chapter 3. Next to this, the calibration and validation of these models is dealt with in this chapter as well. The results of the wave modelling and morphological modelling of different nourishment configurations are presented in Chapter 4. An evaluation on the reliability of the modelled results is presented in Chapter 5, shortcomings of the models are discussed here as well. Finally, conclusions and recommendations are given in Chapter 6.

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2 Problem analysis

2.1 Project location The area of interest for the present project is the beach located at the Brouwersdam. The Brouwersdam is located within the Dutch Delta coast (south-west Netherlands) and separates Lake Grevelingen from the North Sea. The beach is located at the North Sea side of the dam and stretches from the province of Zuid-Holland in the north to the province of Zeeland in the south. An overview of the location within the Netherlands is shown in Figure 2.1a-b, together with several morphological features in the outer delta (Fig. 2.1c). The figure shows the location of the beach itself (Fig 2.1c1), the tidal channels Brouwershavense Gat and Springersdiep (Fig. 2.1c2 and 3, respectively), and the intertidal shoal complex the Bollen van de Ooster (Fig. 2.1c3). Next to these features, there are several (remnants of) shoals and channels in the area. The morphological development of these shoals and channels will be dealt with in Chapter 2.2. The beach at the Brouwersdam is a relatively wide area but has a small narrow stretch of dunes. It is located at an elevation of approximately NAP +2 to +2.5 m. It slopes down from south-west to north-east, causing the north-eastern part of the beach to be situated lower than the south-western part. Therefore, the north-eastern part of the beach is an area that gets flooded during high water and consequently intertidal channels and bars are found here. The cross-shore profile of the beach is quite flat from dune foot to foreshore. At the foreshore, the beach slopes down from approximately NAP +2 m to -2 m, with an approximate mean beach slope of 1:50. The area surrounding the beach is a very shallow area, with exceptions for the tidal channels Springersdiep and Brouwershavense Gat. The sediment at the beach is mainly autonomous sediment from the two former shoals and is predominantly fine sand with a mean D50 of ~210 μm (pers. comm. M. Lazar). The area is very easily accessible for public due to the presence of parking places on the Brouwersdam. This has caused the beach to become a much desired location for several beach and water sports related activities, such as wave-surfing, kite-surfing, kiting and blow- karting. There are a couple of beach houses located at the beach and there are annual activities taking place there as well. This makes the Brouwersdam beach valuable for the local and regional economy as well.

2.2 History of the Grevelingen estuary As a part of the Delta Works, the Grevelingen estuary was closed off from the North Sea by the Brouwersdam. With the completion of the dam in 1971, the 6.5 kilometre long Brouwersdam formed a connection between the municipalities Goeree-Overflakkee (Zuid- Holland) and Schouwen-Duiveland (Zeeland). Because the purpose of the dam was to protect the islands of Goeree and Schouwen-Duiveland, it was required that the dam would be located as far as possible to the west, near the mouth of the estuary. In order to achieve this, and to reduce construction costs, the shoals Kabbelaarsbank and Middelplaat were partly used as foundation of the dam (www.deltawerken.com). These shoals were part of the former ebb tidal delta of the Grevelingen estuary. The construction of the dam yielded a permanent closure of the connection of the Grevelingen estuary with the North Sea. Because the inflow of seawater was already obstructed on the eastern part of the estuary by the construction of the Grevelingendam in 1965, the closure by the Brouwersdam created Lake Grevelingen. A consequence of the closure was that the water would turn gradually into fresh water and that any tidal motion inside the former estuary was removed. However, the unwanted gradual change from a salt water body in to a fresh water lake was avoided by the construction of a sluice complex. This

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sluice complex was built in the southern part of the dam and was finished in 1978. It helped in maintaining a salt/brackish environment inside the lake but tidal motion was only reintroduced to a very small extent (~5 cm), due to the limited discharge capacity (140 m3/s) of the sluices (Huibregtse, 2013).

(b)

Figure 2.1: Location of the Brouwersdam beach (c), in the Netherlands (a), at the border of the provinces Zuid-Holland and Zeeland (b) (sources: www.d-maps.com, Google Earth, Rijkswaterstaat vaklodingen)

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Besides the changes that occurred inside Lake Grevelingen, the closure of the Grevelingen estuary changed the hydrodynamic regime at the outer delta quite drastically. Before the closure, the strong flood current flowed towards the east and entered the estuary through the Brouwershavense Gat tidal channel in the south. The ebb current flowed towards the west and left the estuary through the Springersdiep tidal channel in the north (Figure 2.2a). After construction of the dam the strength of the tidal currents decreased considerably and the direction of the currents got a more circular character. At present, the north directed flood current is concentrated around the central part of the outer delta and the south directed ebb flow is concentrated along the front of the outer delta (Wang, 2010) (Figure 2.2b). This change in strength and direction of the tidal currents caused the area to evolve from a tide- dominated system in to a more wave-dominated nearshore area (Cronin, 2011). The hydrodynamic changes that were induced by the construction of the dam caused the remnants of the shoals Middelplaat and Kabbelaarsbank to migrate towards the dam. The two shoals formed a connection and created in this way the beach (Huibregtse, 2013). Since then, the beach has been subjected to distinct morphological changes. These changes, together with other morphological developments in the outer delta, are elaborated on in the next section.

(a) (b)

Figure 2.2: Tidal currents in the ebb tidal delta of the Grevelingen estuary in 1964 (a) and in front of Lake Grevelingen in 2010 (b). E = ebb-dominant flow, F = flood-dominant flow, W = Wave-dominated (Nipius, 1998; from de Jongste et al., 2013)

2.3 Morphological developments

2.3.1 The ebb delta The hydrodynamic changes that were induced by the closure of the Grevelingen estuary had profound consequences for the morphology of the ebb tidal delta. The bathymetry of the ebb delta, a few years before the closure of the estuary, is shown in Figure 2.3a. This bathymetry is acquired by means of deep water echo soundings (‘Vaklodingen’). These measurements are performed by Rijkswaterstaat and are executed approximately every three years in this area (www.rijkswaterstaat.nl). Near the future location of the Brouwersdam the figure shows

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the locations of the shoals Middelplaat (1a) and Kabbelaarsbank (1b). Here, these two shoals are still separated by a narrow intertidal channel. The intertidal shoal complex at (2) consists of multiple separate shoals here and is mainly north-west to south-east directed. Seawards of this shoal complex is the front of the ebb tidal delta located (i.e. the NAP -5 m depth contour). This front is located approximately 10 kilometres from the coastline and is fed with sediments from the estuary (de Jongste et al., 2013). The main channels through which the tide propagates in and out the estuary are the Brouwershavense Gat (I) in the south and Springersdiep (II) in the north.

Figure 2.3b shows the bathymetry of the ebb delta five years after the completion of the Brouwersdam. The former shoals Middelplaat and Kabbelaarsbank are interconnected and now form a beach in front of the Brouwersdam. Here, the beach is very wide at the southern part of the dam (1a) and very narrow at the northern part (1b), which is due to the initial morphology of the former shoals. The shoal complex at (2) increased in size and height between 1971 and 1974 (de Jongste et al., 2013). Other smaller shoals in the inner part of the delta have been eroded and the sediments are being deposited in the intertidal channels. This has caused the flattening of the two main tidal channels, Brouwershavense Gat and Springersdiep (Lazar, 2007).

The bathymetry of 1998 (Figure 2.3c) shows a continuation of the previously observed trends. The former shoals Middelplaat and Kabbelaarsbank are not distinguishable from each other anymore because they are merged together to form a single morphological unit. The shape of this beach evolved to a convex geometry and has migrated towards the north-east, along the dam. This process of erosion of the beach on the south-west side may well be a part of the general trend of levelling in the area (Lazar, 2007). At (2), two other shoals developed around 1974 and 1980 and orientated parallel to the coastline (Van der Spek, 1987). These shoals merged together in 1992/1994 to form one large shoal of approximately 6-7 km, called ‘De Bollen van de Ooster’ (Snijders, 1998). In the inner part of the delta there are now less separate individual shoals and the bathymetry is more uniform here. The tidal channels show a continued trend of sedimentation. The Springersdiep channel (II) has become shallower and smaller. The tidal channel Brouwershavense Gat (I) decreased as well but has also migrated to the north on the western part, causing a distinct bend in the channel. This bend is caused due to the northward extension of the Krabbengat, which leads to sedimentation near the Brouwershavense Gat channel (Vermaas and Elias, 2013).

The most recent bathymetry of the ebb delta (Figure 2.3d) shows a further north-eastward migration of the beach at the Brouwersdam and a slight change in planform geometry. The area of the tidal flats ‘De Bollen van de Ooster’ has become larger and the shoal increased even further in height. It now forms a boundary between the inner and outer part of the ebb delta and this boundary has rotated parallel to the front of the ebb delta (Wang, 2010). The front of the ebb delta itself has migrated 3 km coast-wards since the construction of the dam (de Jongste et al., 2013). The tidal channels show a continued trend of flattening yet with a smaller rate of sedimentation.

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(a) 1964

1b 1a

(b) 1976

1b 1a

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(d) 2010

Figure 2.3: Bathymetry of the Grevelingen ebb delta for the period 1964 – 2010 (Google Earth, Rijkswaterstaat vaklodingen)

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2.3.2 The beach The bathymetry of the ebb delta showed that the hydrodynamic shift of the Grevelingen estuary has influenced the former shoals Middelplaat and Kabbelaarsbank to form the beach at the Brouwersdam (Figure 2.3). Around 1990 the two shoals merged together and formed the beach with the distinct convex shape. However, the beach has seen some typical morphological development since then. During the past decades there has been severe erosion on the south-west side and, to a lesser extent, accretion on the north-west side. This has caused the beach to ‘walk’ towards the north-east and induced a change in the planform geometry of the beach as well. This change is clearly visualized by the change of the position in the momentarily coastline in the period 1990 – 2014 (Figure 2.4).

These momentarily coastlines are derived from the JARKUS (JAaRlijkse KUStmetingen, Rijkswaterstaat annual coastal measurements) profiles. The JARKUS profiles are height and depth measurements of transects perpendicular to the coastline. These measurements are executed on a yearly basis by Rijkswaterstaat. The purpose of the measurements is to establish the location of the momentarily coastline and to discover long term trends in coastline change (www.rijkswaterstaat.nl).

In Figure 2.4 the position of the coastline is given at NAP 0 m between the JARKUS profiles 12002020 to 12002420. The position is chosen at NAP 0 m because this is the mean water level over a long period of time (1979 – 1991, Appendix B2). Small distortions are present in these coastlines with respect to the real coastlines at that time because accurate coastline positions are only available at the crossing of the coastline and the JARKUS transect. In between transects the coastline is drawn as a straight line, ignoring the curvature of the coastline between these points. However, the JARKUS data is the most complete dataset available for coastline measurements, with respect to the echo soundings (vaklodingen) which are not available on a yearly basis. In addition to that, the position of the coastline does not depend on the water level with these measurements, as it would be with remote sensing imagery.

The figure shows that the south-western side of the beach shows a continuous trend of coastline regression. The sand that is eroded at this part of the beach is most likely transported alongshore and deposited at the north-eastern side of the beach. This has caused a trend of coastline transgression at the north-eastern side. The rates of coastline regression and transgression are measured for every year along the two measuring lines in Figure 2.4. These rates are presented in Figure 2.5a. Here, negative values indicate coastline retreat, and positive values indicate coastline advance. The rate of coastline regression on the south-west side ranges from approximately -10 to -100 m/year and the mean rate in the period 1990 – 2014 is ~ -42 m/year. On the north-east side the trend of coastline transgression is less continuous, with periods of coastline retreat as well. The coastline change varies from -30 to +60 m/year and the mean rate is ~ +13 m/ year. In general the rate of coastline retreat at the south- west side is larger than the rate of coastline advance at the north-east side. This indicates that the beach is not only migrating to the north-east but is losing sediment as well.

To support this finding, the surface area of the beach through time is calculated as well (Figure 2.5b). These surface areas are calculated by means of trapezoidal numerical integration. The area under the RSP line is withdrawn from the area under the coastlines. The figure shows that there is a distinct decrease of approximately 200.000 m2 (= 20 hm2) in surface area of the beach in the period 1990 – 2014. The mean decrease in area in this period is ~ 8000 m2/year (= 0.8 hm2/year). This decrease in beach area supports the finding

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that sediment is lost through time, however, it does not explain where the sediment is going. In Figure 2.3 it could already be seen that the tidal channel Springersdiep is shoaling. Therefore, it is likely that this sediment is deposited in this tidal channel. However, it might be possible as well that the sediment is transported offshore, and is deposited in the shallow areas surrounding the beach.

To investigate if the sediment is solely lost in the Springersdiep or transported in a cross- shore manner as well, the volume of the beach is plotted through time in Figure 2.5d-f with different boundaries to calculate the volumes. The procedure to calculate these volumes is shown by an example in Figure 2.5c. Here, the boundaries, between which the volume of sediment is calculated, are NAP 0 m as the lower boundary and NAP 3 m as the upper boundary (the dune foot). The volumes are calculated for each JARKUS transect for a width of one meter. The total volume of the beach is then calculated by multiplying the volume of each transect of 1 m width with the distance between two transects, which is 200 m. Again, this procedure gives small distortions in the calculations because this method assumes that the coastline is straight in the alongshore direction and that the profile remains uniform over this 200 m. Furthermore, short-term fluctuations are present in the calculations which are probably due to length of the JARKUS profiles. If a certain profile does not extend to the set boundaries, a smaller volume will be calculated. However, more accurate calculations can only be made with the ‘vaklodingen’ but these are not available for every consecutive year.

Figure 2.5d shows that the total beach volume is increasing in the period 1990 – 2014 between the boundaries 0 to 3 m NAP. Between 0 to 1 m NAP and 0 to 2 m NAP this increase is less. Therefore, the increase is due to an increase of volume at the dry part of the beach (above 1-2 m NAP). This is most likely due to dune development. Figure 2.5e shows that the volume below mean sea level (-1 to 0 m NAP and -2 to 0 m NAP) is increasing in the period 2003 – 2014. The volume in the intertidal zone (Figure 2.5f) shows a large decrease in this period. Meanwhile, the total surface area of the beach in this period shows a clear decrease. This means that sediment is eroded at the intertidal zone and transported towards deeper parts and towards the dunes.

Summarizing the previously shown observations we can state that the beach is getting smaller and increases in elevation (dune development). The erosion of the beach takes place at the intertidal zone and this sand is transported seawards to deeper parts and alongshore, which is partly being deposited in the former tidal channel Springersdiep. The decrease in size and increase in height is a development seen at other shoals in the Grevelingen ebb delta as well (Wang, 2010). Because the trends are similar, it is very plausible that the morphological developments at the Brouwersdam beach are part of these general trends of morphological development in the Grevelingen ebb delta, as already discussed by Lazar (2007).

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Figure 2.4: Momentarily coastline position through time (source: Rijkswaterstaat JARKUS measurements)

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(a) (b)

(e) (f)

Figure 2.5: For the period 1990 – 2014: (a) rates of coastline development along measuring lines in Figure 2.4; (b) change of beach surface area; (c) visualization of the calculation of beach volume; and (d-f) total beach volumes with varying boundaries. (source: JARKUS)

2.4 Beach nourishment The aforementioned effects of erosion on the south-west side of the beach cause the beach to lose its functionality for local beach restaurant owners . In order to extent the time that stakeholders can benefit from the beach, Rijkswaterstaat commissioned a beach nourishment of 500.000 m3 (Programma Kustlijnzorg 2012 – 2015). The major part of this volume of sand became available for the beach at the Brouwersdam due to a shift in the nourishment programme of the coast of Schouwen-Duiveland (Rijkswaterstaat Zee en Delta, 2014). Extensive lobbying of local stakeholders and financial participation has enabled the option to increase the volume of the nourishment and the option for Rijkswaterstaat to execute this beach nourishment. However, the Brouwersdam is the main structure for coastal safety at this stretch of the Delta Coast, which means that the maintenance of the Brouwersdam beach is not a part of the coastal safety program. Therefore, this nourishment is a single time fulfilment and not a measure that will be conducted on a regular basis. Therefore, this nourishment is expected to only postpone the disappearance of the south-western side of the beach. Eventually, the nourishment will totally be eroded and there will be no benefits from the supplemented sediment anymore.

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The sediment that will be used for the nourishment is mined from an offshore location at the North Sea. These mine locations are designated as ‘Schouwen 1’ (25586, 421545) and ‘Goeree 1’ (27400, 423088). Rijkwaterstaat Zee en Delta has commissioned a geological survey of the quality and quantity of the sediment in these excavation areas. The lithological studies of the cores are reported and described and the cores are used to produce lithological maps of the source area (Marine Sampling Holland, 2014). These lithological maps are shown in Appendix 3. The top two maps show the grain size composition of only the sand within the sediments of the first meter (left) and the second meter (right) from the bottom downwards. The maps show that the sand in the source area is characterized by a mean D50 that varies from 125 – 500 μm. Besides that, it shows that the top layer (first meter) contains somewhat courser sand. The bottom two maps show the content of fine sediments (silt) in the first (left) and second (right) meter from the bottom downwards. This content is quite small and therefore does not give any problems to mine the sediments. There is, however, some peat in the north-eastern part of the source area. The presence of this peat excludes this part of the mine area for extraction of the sediments (pers. comm. contractor).

2.5 Research questions The previously described effects of morphological change of the beach have led to the intention of the nourishment. This study focusses on modelling this nourishment. Goal of the study is to retrieve a configuration for the nourishment that causes the least amount of erosion for the next decade. This raises a number of questions to be answered:

1. Is it possible to hindcast the observed morphological changes of the beach at the Brouwersdam with the UNIBEST-CL coastline model?

From Huibregtse (2013) it already became clear that the erosional en depositional patterns in the present project location can well be simulated with the UNIBEST-CL+ model. Huibregtse (2013) found that the magnitude of erosion of the south-west side was underestimated and that the sedimentation in the north-east side was overestimated, however, the modelled trends were similar to observations. Although different hydrodynamic data will be used for this study, it is expected that the model will be capable of reproducing the observed erosion patterns.

2. What are the effects of different nourishment configurations on the erosion rate for the next decade?

a. What is the effect of different nourishment shapes? b. What is the effect of variation in grainsize of the used sediment?

The shape of the nourishment might have profound effects on the rate of erosion, and therefore the duration of the nourishment. Increasing the grain size of the sediment would lead generally to a reduction in the rate of erosion because more energetic conditions are required to mobilise the sediment. This is expected for the present situation as well. Goal is to retrieve to what extent the erosion rate can be decreased by increasing the grain size of the sediment.

3. Which type of nourishment configuration is best to implement?

The answer to this question will be the result of question 2 in combination with the criteria from stakeholders and physical constraints with respect to execution of the nourishment.

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3 Data and modelling

This chapter deals with the methods of wave and morphological modelling. The concept of the models is briefly discussed and with that the assumptions of the models are dealt with as well. A more extended elaboration is given on the process of modelling. The modelling process consisted roughly of two phases:

1. Modelling wave evolution from an offshore location point to nearshore locations with the Delft3D-WAVE model (Chapter 3.1) 2. Modelling morphological development of the coastline with the UNIBEST-CL+ modelling package (Chapter 3.2)

The next sections deal with the data that are used as input for the models as well and discusses the settings that were used for the models in order to represent the present project location.

3.1 Wave modelling with Delft3D-WAVE

The morphological modelling with UNIBEST-CL+ requires hydrodynamic (wave) input for the sediment transport calculations. These nearshore wave climates are obtained with the Delft3D-WAVE model. The Delft3D-WAVE model is a model suite that runs the Simulating WAves Nearshore (SWAN) model, which was developed at Delft University of Technology. The SWAN model computes the evolution of random, short-crested waves in coastal regions in deep, intermediate, and shallow water (Delft3D-WAVE manual, 2009). The model requires user-defined input data for offshore wave data and calculates wave propagation, generation by wind, non-linear wave-wave interactions, and wave dissipation for a given bottom topography. Wave induced sediment transport is not calculated in this module of Delft3D and consequently, the bathymetry is stationary during the computations.

3.1.1 Offshore wave climate The model requires wave and wind input as initial boundary conditions, the offshore wave climate. The offshore wave climate for this research was adopted from Huisman and Luijendijk (2009). The project location of their research is close to the present location and therefore this offshore wave climate could well be used. The wave measurements are from the measuring buoy ‘Europlatform’ (51°59'51.54"N; 3°16'34.54"E), which is approximately 50 km offshore from the beach at the Brouwersdam. The long term statistics of the water level measurements at this wave buoy are given in Appendix B1. This measuring station was chosen because it is the nearest measuring point where also wave direction is available for a long time sequence. For the schematization of the wave climate 21 years of wave height measurements were used, from the period 1979 – 2002. For the wind data, 22 years (1983 – 2005) were used. The schematization of the wave measurements was done as follows: at first the data was separated between sea (local wind generated) and swell (generated further away) waves. The data was separated by the relation:

( ) (3.1)

Here, Hs is the significant wave height and Tp is the peak period. The coefficients B and C depend on the maximum steepness of the waves. For the ‘Europlatform’ data these

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coefficients were found to be best presented as B = 1.8 and C = -0.45. After this division the data was separated in bins of similar wave conditions. These similar wave conditions are ranges of characteristic wave height, wave period, and wave direction. Measured wave heights smaller than 0.35 m were not used. Wind measurements were binned in that same bin that corresponded to the wave measurements. The total duration of the measurements was scaled to represent one year. Hence, the number of measurements in a bin is a measure for the duration of those wind and wave conditions. The bin sizes of the wind and wave conditions for each bin are presented in Table 3.1.

Because the area surrounding the Brouwersdam is a very shallow tidal basin, surge levels due to local wave set-up might be important for the water level at the beach. Therefore, the surge level was added to the schematized wave climate. These surge levels are obtained from another measuring station which is quite close to the beach. This is the ‘Brouwershavense Gat 08’ measuring buoy (46555, 419092). The long term statistics of this wave buoy are presented in Appendix B2. The surge level due to wave set-up is calculated by extracting the astronomical tide level from the measured water level at this wave buoy. The total number of wave conditions, with their representative values of wave and wind characteristics, is given in Appendix A.

Table 3.1: Classification of offshore wave conditions (after Huisman and Luijendijk, 2009)

Class I II III IV V VI VII VIII IX X XI XII Significant 0.35- 1- 2.5- 4- 5.5- Hs (m) >7 wave height 1 2.5 4 5.5 7 Peak wave T (s) 1-5 5-10 >10 period p Wave 15- 45- 75- 105- 135- 165- 195- 225- 255- 285- 315- 345- Dir. ( N) direction 45 75 105 135 165 195 225 255 285 315 345 15

3.1.2 Bathymetry The Delft3D-WAVE model requires a given bathymetry over which wave evolution is simulated. The sources of these bathymetries are the Rijkswaterstaat ‘vaklodingen’. The bathymetries that are produced from these echo sounding measurements are the product of various processing and interpolation steps and have a maximum resolution of 20 x 20 m. The bathymetries used for wave modelling are presented in Appendix D. The bathymetry that covers the entire model domain (‘Zeeland’ grid) is from 2004 (Fig. D.1). This bathymetry is replaced by a more recent bathymetry closer to the shore, where more recent data was available. In this way a bathymetry was created that consisted of 2004 and 2006 data for the hindcast model (Fig. D.2). The bathymetry that was created for the forecast model consists of 2004 and 2010 data (Figure D.3). Very close to the coast, these bathymetries were supplemented with the JARKUS data as well. This was done because the bottom topography is most dynamic in the nearshore area and JARKUS data is available for every year. This was done with JARKUS measurements from 2006 for the hindcast model and with JARKUS measurements from 2014 for the forecast model.

3.1.3 Computational grids The modelling of the evolution of short-crested waves from the chosen offshore location point to the nearshore requires a computational grid on which the computations are executed. This grid needs to be substantial larger than the location of interest due to the ‘shadow’ zone on both sides of the incident wave direction. This ‘shadow’ zone is caused by the import of zero energy from the lateral boundaries, causing a disturbance of the wave field (Delft3D manual).

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At the area surrounding the project location the water depth is shallow, and the bathymetry varies substantially. Therefore, the wave computations should be executed on a high resolution spatial grid because the evolution of wave characteristics is highly dependent on the local bathymetry. However, applying such a dense spatial grid over the entire domain would require tremendous processing power, and time. Therefore, this dense spatial grid is nested in other computational grids with a lower resolution. The wave computations further offshore, where the water depth is larger and the bathymetry less important for wave evolution are executed on a computational grid with a lower resolution. Because the variations in the wave field are small here, this does not affect the propagation of wave evolution to the nearshore. For the Delft3D-WAVE model three rectangular computational grids are defined. The largest grid with the largest spatial resolution is the ‘Zeeland’ grid (Figure 3.1a, blue). The resolution of this coarse grid is 500 x 500 m. The resolution of the bathymetry measurements that are used here is 40 x 40 m. The resolution of the bathymetry measurements needs to be smaller than the resolution of the grid because the measurements are averaged on to the grid nodes. The medium ‘Brouwersdam’ grid is nested in this larger grid. The ‘Brouwersdam’ grid has a spatial resolution of 150 x 150 m. The spatial resolution of the bathymetry applied here is 20 x 20 m. The most detailed grid, the ‘Noordzeestrand’ grid has a spatial resolution of 50 x 50 m. The same bathymetry is used here as for the medium ‘Brouwersdam’ grid but the bathymetry is supplemented with the cross-shore JARKUS transects as stated before.

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(a)

(b)

Figure 3.1: Delft3D-WAVE computational grids: (a) the coarse ‘zeeland’ grid (blue) with the nested medium ‘Brouwersdam’ grid (red), (b) the ‘Brouwersdam’ grid with the nested high resolution ‘Noordzeestrand’ grid (green).

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3.2 Morphological modelling with UNIBEST-CL+

The UNIBEST model consists of two separate modules. The first one is the Longshore Transport (LT) module. This module computes the magnitude of longshore sediment transport, induced by tides and/or waves, distributed across a cross-shore profile. It does these computations for a variety of coastline angles and this results in a set of longshore sediment transports (S) for several coastline orientations (Φ). An approximation of these values gives a so called S-Φ curve. These curves are used as input for the Coastline (CL) module. Subsequently, the CL-module computes the evolution of the coastline for a given timeframe, based on the longshore transport computations provided by the LT-module. Because the LT-module provides the results as S-Φ curves, the CL-module is able to simulate coastline change very computationally efficient because a change in coastline orientation does not require new transport computations.

3.2.1 Longshore Transport (LT) module In order to execute the longshore transport computations, the LT-module of UNIBEST requires some data on which the computations are executed. The first input parameter of the model is the cross-shore profile of the coastline to be modelled. This may be an arbitrary profile or an existing measured profile. At this profile, the dynamic boundary has to be set. The dynamic boundary is the point up to which the profile is rotated by the model when the coastline orientation changes. Secondly, the model needs a wave climate for each cross- shore profile. These wave climates are imposed on the seaward boundary of the cross-shore profile. Subsequently, the LT-module computes 1D wave evolution over the cross-shore profile by means of the Battjes and Janssen (1978) wave dissipation model. Wave energy changes due to shoaling, breaking, bottom refraction, and friction are taken into account in this model. The strength of the wave-induced longshore current is derived through a linearized version of the bottom friction term for waves and currents combined. The distribution of these current velocities across the beach profile is derived from the momentum equation and takes in to account the effects of bottom friction, the gradient of radiation stress and the tidal surface slope alongshore (UNIBEST-CL+ manual) The computations of wave- and tide-induced longshore sediment transport are executed by user-defined sediment transport formulae. There are a couple of sediment transport formulae available within the model. Of these formulations, the following are applicable for the transport on a sandy beach: - Bijker (1971) - Van Rijn (1992) - Van Rijn (1993) - Van Rijn (2004) - Soulsby/Van Rijn (1997) - CERC (1984) - Kamphuis (2000) Either of these transport formulations have different input parameters, yet the most important ones are the parameters that characterize the distribution of the grain size of the sediment (D10, D50, D90). Furthermore, the model uses a wave-current interaction model and requires some parameters for wave breaking, bottom friction, and bottom roughness.

Settings For the LT-module computations the JARKUS transects provided the cross-shore profiles for the beach and schematized profiles were constructed for the nourishments. These abstract profiles were constructed with a flat sea bottom at NAP -2 m, a foreshore slope of 1:50, and a flat beach profile from foreshore to dune foot at NAP +2 m. The nearshore wave climates

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were extracted from the output results (the wave simulations) from the Delft3D-WAVE model at the locations of the seaward boundary of the profiles. These nearshore wave climates consisted of 117 different modelled scenarios (equal to the number of schematized offshore scenarios) and contributed to a total duration of one year. The seaward boundaries of the profiles varied between 100 and 250 m from the coastline at NAP 0 m. The dynamic boundary of the profiles was set at 150 m or 50 m if the seaward boundary was closer than 150 m. The longshore sediment transport was calculated with the Van Rijn (2004) sediment transport formula. This formula is appropriate for bed and suspended load of sand and fine sediments. The formula approximates the total transport due to waves and currents as a function of:

〈 〉 (3.2) 〈 〉 (3.3)

with: qs,c1 = time-averaged current-related suspended load transport rate in the current direction qs,c2 = time-averaged current-related suspended load transport rate in the wave direction qs,w = time-averaged wave-related suspended load transport rate qb,c = time-averaged bed-load transport vector in current direction qb,w = time-averaged bed-load transport vector in wave direction

The other parameters required for the longshore transport computations were set to default values except for the D50 and the scaling factors (Table 3.2). The settings of the scaling factors will be dealt with in Chapter 4.2. The wave-current interaction model was set as a linear interaction model. Other wave parameters (for wave breaking and bottom friction) are very hard to determine for a specific site and were therefore set on default (literature) values as well.

Table 3.2: Sediment transport settings for Van Rijn (2004) Para- Description Value Unit meter D10 10% grain diameter 120 μm D50 50% grain diameter 210 μm D90 90% grain diameter 300 μm DSS 50% grain diameter of 160 μm suspended sediment 2 ρs Sediment density 2650 kg/m 2 ρw Seawater density 1025 kg/m Φp Porosity 0.4 - T Temperature 15 °C S Salinity 30 ppm

3.2.2 CoastLine (CL) module The CL-module is based on the single line theory, which describes the position of the coastline as a single line. The change of this line is solely a function of longshore transport gradients and the fundamental assumption made is that the beach profile does not change in time, and consequently is always in equilibrium. This means that during coastline regression/transgression the profile is moved horizontally with respect to the initial position. The part of the profile that is moved is defined by the active profile height, a user-defined area of the profile. The single line theory describes the position of the coastline in time shore- normal to a defined x-axis. This x-axis is the length of a user-defined reference line. In this way the position of the coastline can be described by a continuity equation:

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(3.4)

with: y = coastline position w.r.t the reference line t = time Qs = total longshore transport x = alongshore position hp = active profile height, qb = sediment source/sink

Here, the magnitude of the total longshore transport (Qs) on a certain location can be described by an equation of motion:

(3.5)

with: s1 = variation of longshore transport as a function of coastline orientation ϕ = coastline orientation Qs0 = the initial longshore transport

When the equation of motion is substituted in the continuity equation the diffusion equation is obtained that describes the coastline position in time as a function of location, longshore transport, and the active profile height.

(3.6)

Settings Two types of models were set-up for the Brouwersdam site. The first one is a model that represents the beach at the Brouwersdam during the situation of 2005 (Figure 3.2a). This model was used to hindcast the evolution of the coastline for the past decade (2005 – 2014). The model was calibrated and these calibration parameters were used for the forecast (2014) model, which is shown in Figure 3.2b. This model was used to implement the nourishments with different configurations. The coastlines in these CL models are derived from the NAP 0 m location of the JARKUS transects (similar to Figure 2.4). The underlying remote sensing imagery was used to ‘adjust’ the coastline in between JARKUS points.

(a) (b)

Figure 3.2: UNIBEST coastline model of 2005 (a) and 2014 (b)

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At the position of the Brouwersdam, a revetment is included in the model. No erosion can take place beyond this revetment. At the most southern en most northern position of the model, boundary conditions are defined. In the south this boundary condition is set as y constant, which means no coastline change can take place here. In the north this boundary condition is set as angle constant, which means that sedimentation can take place but that the coastline orientation is fixed. The models were run for a chosen time frame. The imposed sediment transport computations were computed for one year. Consequently, a multiple year coastline simulation repeats the one-year cycle multiple times.

3.2.3 Nourishment configurations The modelling of the nourishments was done for four different shapes (Figure 3.3). These different nourishment types are only different in planform geometry, the shape of the profiles is similar and sediment transport parameters are equal as well. Of these different shapes, nourishment type I is the most realistic one with respect to stakeholder criteria and physical constraints. Nonetheless, it is informative to study the effect of different types. The modelling of nourishments with different grain sizes was done with nourishment type I. Appendix C shows that the grain size of the sediment in the source area is characterized by a mean D50 that varies from 125 – 500 μm. Therefore grain size simulations are executed with a grainsize varying from 125 to 500 μm with increments of 25 μm. The grain size distribution of the sediments (D10, D50, D90) was analysed from the grain size sieve curves from the geological survey (Marine Sampling Holland, 2014). This analysis provided that the mean range between the D10 and the D50 of the sediment is ~110 μm and that the mean range between the D50 and the D90 of the sediment is ~160 μm. These ranges were used for the varying grain size simulations. The hindcast simulation, the forecast simulations, the simulations with the different nourishment types and the simulations with the varying grain sizes resulted in a total of 22 simulations. The number and the settings of these simulations are listed in in Table 3.3.

Type I Type II

Type III Type IV

Figure 3.3: Nourishment types (Google Earth)

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Table 3.3: Simulation runs with settings

Simulation Type Surface area D10 D50 D90 Slope Simulation time (m²) (μm) (μm) (μm) (-) (yrs) 1 2005 871,104 120 210 300 var 15 2 2014 650,652 120 210 300 var 15 3 I 170,320 120 210 300 1:50 15 4 II 152,170 120 210 300 1:50 15 5 III 166,860 120 210 300 1:50 15 6 IV 168,310 120 210 300 1:50 15 7 I 152,170 50 125 285 1:50 15 8 I 152,170 50 150 310 1:50 15 9 I 152,170 65 175 335 1:50 15 10 I 152,170 90 200 360 1:50 15 11 I 152,170 115 225 385 1:50 15 12 I 152,170 140 250 410 1:50 15 13 I 152,170 165 275 435 1:50 15 14 I 152,170 190 300 460 1:50 15 15 I 152,170 215 325 485 1:50 15 16 I 152,170 240 350 510 1:50 15 17 I 152,170 265 375 535 1:50 15 18 I 152,170 290 400 560 1:50 15 19 I 152,170 315 425 585 1:50 15 20 I 152,170 340 450 610 1:50 15 21 I 152,170 365 475 635 1:50 15 22 I 152,170 390 500 660 1:50 15

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4 Results

The results of the hydrodynamic and morphological models are presented in this chapter. Chapter 4.1 deals with the results of the hydrodynamic modelling and presents several examples of the model simulations. Chapter 4.2 handles the results of the morphological hindcast modelling of the beach at the Brouwersdam. The model settings that give a good representation for the beach are discussed here. These settings were subsequently used for the forecast morphological models. The forecast modelling section (Chapter 4.3) deals with the modelled morphological development of the beach without any measures and with different nourishment configurations. These results are subsequently used to provide an assessment on the questions stated in Chapter 2.5

4.1 Wave climates The Delft3D-WAVE simulations were performed on the 2004-2006 bathymetry for the hindcast scenario and the 2004-2010 bathymetry for the forecast scenario. The 117 schematized offshore wave conditions (Appendix A) were used for each of these scenarios. The results were two sets of 117 different wave simulations. It would be excessive to show all the results of these simulations and therefore a selection of results is shown in Figure 4.1. The figure shows simulated significant wave height (Hsig) on the detailed ‘Noordzeestrand’ grid with the 2006 bathymetry (left) and with the 2010 bathymetry (right). Significant wave height is shown because this wave parameter is used in the longshore transport computations for the computation of wave driven transport. The results are shown for a scenario with minimal offshore wave height (Fig. 4.1a-b), mean offshore wave height (Fig. 4.1c-d), and maximum offshore wave height (Fig. 4.1e-f) of the entire range of schematized offshore wave conditions. The colour scales are different for each wave condition but are similar for the 2006 and 2010 scenarios for a single offshore wave condition in order to enable comparison between wave simulations. The figures show that there is not much difference between modelled nearshore wave evolution for the 2006 and 2010 bathymetry. This is as expected because the bathymetry did not change significantly in such a short period of time. The 2006 model results show that there are also waves simulated inside Lake Grevelingen, with respect to the 2010 model results where there are no waves inside the lake. This is because bathymetry measurements were also available inside Lake Grevelingen for the 2006 dataset and not for the 2010 dataset. These wave computations inside Lake Grevelingen do not have any effect on the wave evolution in the ebb delta. Furthermore, the figures show that the simulated wave height in the Grevelingen ebb delta depends largely on significant offshore wave height (different offshore scenarios) but also for a large degree on the peak offshore wave direction. The wave height is reduced considerably in this region and this is especially the case during scenario 78. The wave fields for this offshore wave scenario show that the shoal complex ‘De Bollen van de Ooster’ have a profound shielding effect for the Grevelingen ebb delta region if the peak offshore wave direction is north-west (Appendix A). A wave height of approximately three meter is then reduced to one meter by the shoal complex. Because most energetic wave conditions originate from the north-west, the area of the Grevelingen ebb delta is protected from these energetic conditions.

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2006 2010

(a) Hsig,off = 0.47, Φ = 154° (b)

(e) Hsig,off = 6.19, Φ = 339° (f)

Figure 4.1: Wave simulation results modelled on the 2004-2006 bathymetry (left) and the 2004-2010 bahtymetry (right) for offshore wave scenario 84 (a and b), scenario 42 (c and d), and scenario 78 (e and f)

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4.2 Hindcast simulations The morphological hindcast model (Figure 3.2a) represents the coastline (NAP 0 m) of the beach at the Brouwersdam in 2005. The model is used to simulate coastline change for the period 2005 – 2014. The performance of the model simulations is compared with the observed coastline change along the lines of the JARKUS transects. The observed coastline change along these lines is calculated by means of the change of the NAP 0 m position of the JARKUS transects in this period with respect to the 2005 (initial) position. An overview of the position of the JARKUS lines, with their transect identification number, is given in Figure 4.2.

Figure 4.2: Overview of JARKUS transect locations

The comparison between observed coastline change and modelled results is shown in Figure 4.3. Here, multiple simulations are shown with each of the sediment transport formulae described earlier in Chapter 3.2.1 in order to reveal which formula gives most accurate results. In this figure, the horizontal axis shows the longshore position along the Brouwersdam, expressed as the identification number of the JARKUS transects. The height of the bars shows the magnitude of coastline change along the line of this JARKUS transect in meters. Here, negative numbers indicate coastline retreat and positive numbers indicate coastline advance. The red bars show the observed coastline change in the period 2005 up to and including 2014 and the other bars show the coastline change for each of the simulations. Each of these simulations is a first, non-calibrated, assessment to hindcast the observed change with a specific transport formula. It can be seen that the extent of coastline change varies considerable for different transport formulae. This is because the magnitude of longshore transport varies a lot for different formulae as well. The agreement of modelled and observed magnitude of coastline change can be seen by the bars but a quantification of the agreement is given by the r2 values as well, which are indicated in the legend. These values show that six of the seven simulations perform rather poor. The best agreement is found for the simulation with the CERC (1984)

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formula. This simulation performs actually quite well with respect to the other ones (r2 = 0.88). However, this formulation is independent for differences in grain size and only depends on the wave conditions, which is highly impractical for the grain size simulations with the nourishments. The Kamphuis (2000) formula shows a reasonable performance as well but the formulation of this sediment transport formula only includes a parameter for the D50 (and no other grain size fractions) and lacks the possibility to include a calibration factor. This would eliminate the opportunity to improve modelling results and therefore this formula is not preferred as well. The Van Rijn (2004) formula shows a more or less similar trend of coastline development but the magnitude of coastline change is several orders to small, causing a poor performance. However, this formulation includes the option to modify the formula in UNIBEST and can be adjusted for differences in grain size diameter as well. The modification of this formula encompasses a calibration with sediment transport scaling factors. These sediment transport scaling factors simply multiply the calculated transport with this factor. There are in total four scaling factors, for the current- and wave- related suspended and bedload transport. With these scaling factors the Van Rijn (2004) formula is modified for the present situation by setting them all to a value of ten.

Figure 4.3: Observed and simulated coastline development for the period 2005 – 2014 with different sediment transport formulae

The simulations were repeated with this modified formula. A similar figure (Figure 4.4) shows the performance of the hindcast model with this modified Van Rijn (2004) sediment transport formula for different time frames. The agreement of observed and modelled results is again given in the legend by the r2 values and shows a significantly better performance of the model simulations. The values show that a simulation of 15 years with the modified Van Rijn (2004) formula gives the closest agreement with the observed coastline change (r2 = 0.93). This implies that the model is able to reproduce the 10 year coastline regression/transgression trend quite accurate but only in a simulation time of 15 years. Effectively it means that the observed pattern of a simulation is actually the effect we would observe in 2/3 of the time of

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that simulation. Therefore, a scaling factor of 1.5 (in time) is required for the simulations. This scaling factor will be used for the forecast simulations as well. Moreover, the figure shows that the sedimentation trend on the north-eastern side of the beach is represented less accurate by the model than the erosion trends on the south- western part. The morphology of the beach here is much more complicated than on the western part and this might be the cause that the model performs less well here. If only the south-western part of the beach is considered (JarkusID 2420 to 2240), then the accuracy of the modelled results is even larger for the 15 year simulations (r2 = 0.98). For the nourishment simulations it is not a problem that the model performs less well for the north-eastern part because the focus is on the erosion rate of the nourishment at the south-western side of the beach and not on the sedimentation rate at the north-eastern part.

Figure 4.4: Observed and simulated coastline development for the period 2005 – 2014 with the modified Van Rijn (2004) sediment transport formula

4.3 Forecast simulations

4.3.1 Without nourishment Figure 4.5 shows the simulated development of the coastline without a nourishment implemented. It shows that the erosion on the south-western side continues and that there will be some sedimentation on the north-eastern part as well. The sedimentation trend is suddenly interrupted from one transect to another, this is most likely caused due to the northern boundary of the model, that does not extend northwards from JARKUS transect 2020. Next to this, the figure shows that the erosional pattern on the south-western part is not gradually decreasing towards the hinge point between erosion and sedimentation. This hinge point has also shifted north-eastwards with respect to the period 1990 – 2014. In this period, the hinge point was located at JarkusID 2240 – 2220, for the forecast simulations it is located between JarkusID 2140-2120. Furthermore, the present simulations provide that the mean coastline retreat rate along the south-west measuring line (Figure 2.4) is ~30 m/yr for the period 2014 - 2023. This is less than the observed coastline retreat of ~42 m/yr over the period 1990 -2014 (Chapter 2.3.2). This decrease in retreat rate for the next decade might be caused by the model. In spite of the calibrations, the model might still not totally be able to

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reproduce the extent of erosion. Or erosion might decrease because the beach is evolving towards an equilibrium morphology.

Figure 4.5: Coastline change in the period 2014 – 2023

4.3.2 Nourishment simulations

Nourishment types The four different nourishment types (Figure 3.3) were implemented in the 2014 UNIBEST model and the development of the coastline was simulated for a period of 15 years, which corresponds to a 10 year event. The position of the coastline through time was measured along the south-west measuring line (Figure 2.4) and this is shown in Figure 4.6. In this figure, the conversion factor of 1.5 in time is already applied on the horizontal axis. Therefore, the values indicate not simulation years but real years. The different curves show clearly that if the coastline is further away from the initial 2014 coastline (e.g. type II), the retreat is larger the first few years with respect to a coastline that is positioned close to the 2014 coastline (e.g. type III). This is presumably due to the width of the coastline. The nourishment types that are stretched along the dam, are less wide in the direction perpendicular to the dam. Therefore, the coastline changes rapidly because sediment is not trapped and is transported to the other parts of the beach. This leads to differences in the mean retreat rate over the period of 10 years. The mean coastline retreat rates for this period are listed in Table 4.1. These rates considered, nourishment type I or III would be a configuration that will be most beneficial for stakeholders because a potential beach house would be able to use a location at the southern part of the beach for a longer period of time.

Table 4.1: Nourishment development statistics

Coastline Surface area Type retreat rate decrease (m/yr) (% of initial/yr) I -26 -6.5 II -40 -6.3 III -24 -7.8 IV -60 -5.6

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Figure 4.6: Coastline development for different nourishment types

In Figure 4.7a, the development in surface area of solely the nourishments (without the other parts of the beach) is visualized for the four nourishment types. These areas are calculated by means of trapezoidal numerical integration. The area of the beach of 2014 is subtracted from the beach area including the nourishment, but excluding developments on the north- eastern part of the beach. The curves show that the size of each nourishment type decreases quite fast, yet at different rates. However, because the nourishments are not exactly the same size at the start of the simulations it is a bit difficult to compare the rates in decrease of surface area. Therefore, a scaled decrease is given in Figure 4.7b. Here, the initial area of the nourishment is set as 100% and the development is given as fraction of this initial surface. In this figure it is clearly visible that there is a clear difference in erosion rate for the different nourishment types. More than 40% of the initial nourishment is still present after ten years if type IV is constructed, and only a bit more than 20% remains if type III is used. However, it must be noted that the UNIBEST model might not totally be capable of simulating the type IV nourishment correctly because the model only performs well for straight coastlines without too much deviations. Consequently, the simulations of type I, II, and III provide more reliable results. Nourishment types I and II show a more or less similar erosion rate which is smaller than for type III and therefore it can be concluded that it would be most beneficial to construct nourishment type I or II.

(a) (b)

Figure 4.7: Nourishment surface area development for different nourishment types

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Grain size simulations The simulations with different grain size distributions were executed on the type I nourishment. This is done because the modelling of this type shows a stable coastline development (i.e. continuous trends) and has a configuration that is most likely to be constructed. During the simulations the grain size varied from 125 μm to 500 μm with a range of 110 μm for D10-D50 and 160 μm for D50-D90 (Table 3.3). The development in surface area through time of solely the nourishment is shown in Figure 4.8. Each line represents a simulation with a specific grain size distribution. It shows that an increase in grain size of the nourished sediment will decrease the erosion rate during a period of 10 years. A nourishment that consists of sediment with a mean D50 of 125 μm will be totally eroded in 10 years. If the nourishment consists of sediment with a mean D50 of 500 μm, less than half of the surface area of the nourishment will be eroded after 10 years. This effect, of an increase in grain size on erosion rate, is quantified in Figure 4.9. Figure 4.9a shows the distance of the momentarily coastline after 10 years in meters with respect to the 2014 coastline along the south-west measuring line (Figure 2.4) and Figure 4.9b shows the size of the area of the nourishment after 10 years for the different grain size simulations. Both these curves show a distinct hinge point at D50 = 225 μm. This hinge point is caused by the Van Rijn (2004) sediment transport formula. In this formula, the calculated transport is separated in two different regimes by the Mobility parameter (ψ), which depends on grain size. Four linear fits are used to schematize the relations between grain size and coastline retreat rate or decrease in surface area. The functions of these fits are listed in table Table 4.2. These fits indicate the reduction of erosion rate with increasing grain size. However, the fit that describes the relation for 225 μm ≤ D50 ≤ 500 μm is probably the best indication for the reduction rate because the sediment at the source area consists predominantly of sand with a grain size that lies in this range. Summarizing this, it means that if the sediment of the nourishment is increased by 25 μm when it is supplied on the beach, there will be ~ 7 m less coastline regression and ~ 5000 m2 (= 0.5 hm2) less decrease in surface area of the nourishment after 10 years. Therefore, it would be beneficial to use sediment from the source area that is as coarse as possible.

Figure 4.8: Decrease in surface area for different grain sizes

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Figure 4.9: Effect of grainsize on (a) coastline retreat and (b) decrease in surface area after 10 years.

Table 4.2: Functions of linear fits in Figure 4.9 Distance to 2014 coastline Surface area Fit (D50 =125 – 225 μm) 1.1646 * D50 – 137.2377 844.0564 * D50 – 1.3144e5 Fit (D50 =225 – 500 μm) 0.2740 * D50 + 69.1494 183.7947 * D50 + 1.8078e4

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5 Discussion

The morphological coastline model UNIBEST-CL+ is shown to be very well capable of reproducing the observed coastline developments at the south-western part of the beach at the Brouwersdam. Huibregtse (2013) found that his UNIBEST-CL+ model could reproduce the trends of coastline development but that the magnitude was underestimated at the south- western part and overestimated at the north-eastern part. Closest agreement was found if the Bijker (1971) sediment transport formula was used. In this study, the Bijker (1971) formula did not produce significantly better results than the Van Rijn (2004) sediment transport formula. The Van Rijn (2004) formula was seen to provide best results if the longshore sediment transport was scaled by a factor ten. There can be a couple of reasons that the non-scaled calculated transport was a lot smaller than in reality:

- the simulated wave climate was less energetic than in reality, - wave driven longshore transport is not the main contributor for sediment transport along the beach, - the general disability of sediment transport formulae to predict transport very accurately.

In order to provide a quantification of the effect of differences in the wave climate, new simulations with a more energetic and less energetic offshore wave climate are shown in Figure 5.1a. For this purpose Delft3D-WAVE simulations are repeated with a schematized offshore wave climate that is 10% more energetic (Hs and Tp +10%) and 10% less energetic (Hs and Tp – 10%). Subsequently, the morphological simulations are repeated for the type I nourishment. The figure shows that there is only a slight change in development of the type I nourishment. After 10 years the difference is only ~5% in the development of the total surface area of the nourishment. It is therefore unlikely that the under estimation of sediment transport is due to the modelled wave climate. Huibregtse (2013) discusses that the differences between modelled and observed results are the result of complex flow patterns near the beach, as the flood current is north-directed along the beach and the ebb current flows mainly at the front of the ebb tidal area (as discussed in Chapter 2.2 as well). Therefore, implementation of tidal currents might increase sediment transport and therefore eliminate the need for the inclusion of sediment transport scaling factors. Tidal current can be implemented in the LT-module of UNIBEST but this would require hydrodynamic (Delft3D) simulations that simulate tidal propagation as well. This would complicate the hydrodynamic modelling considerably and was beyond the scope of the present internship project.

The forecasted simulated continued erosion and sedimentation on the south-west and north- east side of the beach, respectively, is as expected because these trends were also observed for the period 1990 – 2014. Lazar (2007) discusses that the beach will migrate further towards the north-east and form a continuous stretch of coast, up to Goeree. The model seems to evolve towards such a morphology. The rate of erosion was seen, however, to decrease from ~42 m/yr (period 1990 – 2014) to ~30 m/yr (period 2014 – 2023). A decrease in erosion rate was also reported by Huibregtse (2013) on the basis of his simulations. Therefore it might well be possible that this decrease is due to the beach evolving towards an equilibrium morphology.

The simulations of the nourishments showed that all different types of nourishment were eroded by more than 50% after 10 years. Therefore, the nourishments are not expected to cease erosion on the south-west side of the beach but only postpone the eventual

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disappearance of the beach here. However, the predicted rates at which the nourishments will disappear are a bit insecure. The rates found here are based on the model which is calibrated with the Van Rijn (2004) sediment transport formula. It was already seen that the choice of sediment transport formula gives a relatively large range in modelled results and therefore, a large range in erosion rates. The magnitude of longshore transport is also affected by the description between waves and currents. The interaction between waves and currents is described by a built-in model in UNIBEST. Several models are present for this purpose because at present still a high degree of uncertainty exists for these formulations. The choice of wave-current interaction model affects model results significantly as well because specific models calculate larger roughness values, which will increase transport magnitude. The effect of different wave-current interaction models is indicated by a repetition of the nourishment type I model for different models (Figure 5.1b). It can be seen that this effect is far larger than the effect of the wave climate. The difference between the wave- current interaction model that causes the least and the most amount of erosion is ~45%. The trends of coastline development are therefore quite reliable but the rates at which these developments happen are, as stated before, a bit uncertain when based on the present model.

(a) (b)

Figure 5.1: Development in surface area for nourishment type I with different wave-current interaction models

Future research on the morphological development of the beach at the Brouwersdam should take developments at the dam into account. Plans are being set-up to construct a tidal inlet sluice at the northern part of the dam, including a tidal power plant. An assessment on the morphological development of the Grevelingen ebb delta (including the beach) was already done by Wang (2010), and modelling the morphological behaviour due to a power plant was done by Witteveen+Bos (2012). Witteveen+Bos (2012) concluded that the construction of a tidal power plant in the Brouwersdam can increase the migration rate of the beach but that this trend will be interrupted if the beach reaches the inlet sluice. As a mitigation measure, they suggested the construction of a groyne perpendicular to the dam and south of the inlet sluice in order to counter-affect the deterioration of the beach. The UNIBEST-CL+ modelling package includes options to model the effect of groynes on coastline behaviour. Therefore, the effect of a groyne on the beach at the Brouwersdam can be modelled with the present model as a first indication of expected morphological development due to a groyne.

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6 Conclusions

6.1 Conclusions

A morphological model study at a nourishment at the beach at the Brouwersdam was performed with the UNIBEST-CL+ modelling package. Goal was to reveal a nourishment configuration that maximizes the ‘life-expectancy’ of the nourishment. The presented results of the simulations have shown that:

1. The UNIBEST-CL+ hindcast model is able to reproduce the trends of coastline regression and transgression if a modified (scaled) Van Rijn (2004) formula is used and a scaling factor of 15 in time is applied. In this way, an accuracy of modelled and observed results of r2 = 0.93 can be achieved.

2. The effect of different nourishment configurations is that:

a. different nourishment shapes (planform geometries) lead to differences in erosion rate. The coastline will retreat faster if it is positioned further from the original coastline, and b. a larger grain size will decrease the rate of erosion of the nourishment. Results show that an increase of 25 μm of the used sediment will decrease the coastline retreat along the south-west measuring line with 7 m and the decrease in surface area of the nourishment with 5000 m2 after a period of ten years.

3. In order to increase the ‘life-expectancy’ of the nourishment a type I or type II configuration should be constructed. The sediment should be as coarse as possible in order to reduce erosion rates.

6.2 Recommendations The nourishment that will be implemented at the south-western part of the beach at the Brouwersdam will eventually disappear due to the erosion. In order to increase the ‘life- expectancy’ of the nourishment, sediment should be used which is coarser than the autonomous material (~210 μm). The maps in Appendix C show that the first top meter of the source area contains somewhat coarser material. Therefore it is recommended to mine the sediment from this top layer. The shape of the nourishment affects erosion rate as well but taking physical constraints and social desires in to account, a nourishment type I is recommended. An initial assessment on the morphological development of the beach, due to the construction of a groyne, could be carried out with the UNIBEST-CL+ model as well because the model has proven to be able to reproduce trends of coastline behaviour at this location quite accurately. However, as detailed flow patterns are likely to be important for the morphological development at the beach, particularly at the north-eastern side, it is advised to perform more comprehensive studies with more detailed models. A model that could potentially perform well for this location is Delft3D-FLOW.

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References

Battjes, J.A. and Janssen, J.P.F.M., 1978. Energy loss and set-up due to breaking of random waves. Journal of Coastal Engineering Cleveringa, J., 2008. Morphodynamics of the Delta coast (south-west Netherlands) – Quantitative analysis and phenomenology of the morphological evolution 1964-2004. Emmeloord: Alkyon. Cronin, K., 2011. Grevelingen ebb tidal delta – analysis (internal memo). Delft: Deltares Huibregtse, W.P., 2013. Morphological analysis of the beach at the Brouwersdam. Master thesis, Department of Hydraulic Engineering, Faculty of Civil Engineering and Geosciences, TU Delft. Huisman, B.J.A. and Luijendijk, A.P., 2009. Sand demand of the Eastern Scheldt - Morphology around the barrier. Delft: Deltares Jongste, de, L., Dusseljee, D., Smit, M., Jansen, M., 2013. Morphological impact on eb-tidal deltas of reintroducing tide in a former estuary. Rotterdam: Witteveen+Bos Lazar, M., 2007. Morfologische ontwikkelingen strand Brouwersdam, Memo AXW-010607, Rijkswaterstaat, Directie Zeeland Marine Sampling Holland,, 2014. Onderzoek zandwingebieden Goeree 1, Schouwen 1, Bergen-Egmond A Kustwaarts, Texel Zuid-Den Helder. Rijkswaterstaat Zee en Delta, 2014. Convenant pilot “slimmer omgaan met zand op Schouwen”. Eindconcept 15 april 2014. Snijders, G.H., 1998, Morfologische ontwikkeling Voordelta 1980-1997, Rapport RIKZ-98.019 Spek, van der, A.J.F., 1987. Inventariserend morfologisch onderzoek Voordelta; beschrijving van de ontwikkeling van de buitendelta’s van Haringvliet en Grevelingen. Rijkswaterstaat Vermaas, T. and Elias, E., 2014. Evaluatie verlegging Krabbengat 1987/1991/1996. Delft: Deltares Wang, Z.B., 2010. Morfologische effecten van een getijdecentrale in de Brouwersdam. Delft: Deltares Witteveen+Bos, 2012. Morfologische analyse Voordelta. Rotterdam: Witteveen+Bos

Manuals

Deltares, 2009. Delft3D manual, Simulation of short-crested waves with SWAN. Delft: Deltares Deltares, 2011. UNIBEST-CL+ manual, Manual for version 7.1 of the shoreline model UNIBEST-CL+. Delft: Deltares

Websites www.deltawerken.com www.getijdencentralebrouwersdam.nl www.rijkswaterstaat.nl

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Appendices

Appendix A; Schematized offshore wave climate

Peak Wind Wind Cond. h Hs Tp wave velocity direction direction at 10 m

(m) (m) (s) (°N) (m/s) (°N) 1 -0.06 0.63 4.41 1.35 5.78 32.68 2 -0.11 0.66 4.28 29.37 5.65 58.56 3 -0.15 0.64 4.15 59.13 6.01 84.69 4 -0.16 0.67 4.03 90.14 5.44 104.26 5 -0.16 0.67 3.84 119.85 5.93 117.33 6 -0.13 0.64 3.82 151.11 5.8 124.09 7 -0.1 0.66 3.87 182.66 6.29 137.07 8 -0.05 0.71 3.99 212.96 5.51 173.37 9 -0.01 0.69 4.16 238.54 5.71 211.18 10 0 0.66 4.23 269.02 5.73 240.67 11 -0.01 0.65 4.3 300.43 6.1 267.85 12 -0.02 0.64 4.41 330.82 5.71 327.24 13 -0.01 1.22 4.72 1.28 6.24 21.92 14 -0.13 1.21 4.69 29.75 5.3 51.33 15 -0.27 1.25 4.65 59.84 5.17 83.84 16 -0.3 1.28 4.57 90.93 5.49 103.41 17 -0.33 1.25 4.41 119.5 5.54 113.77 18 -0.19 1.31 4.39 151.7 5.35 139.73 19 -0.16 1.33 4.44 183.87 6.34 140.51 20 -0.05 1.33 4.56 213.71 5.65 181.07 21 0.02 1.3 4.63 237.15 6.11 219.56 22 0.09 1.29 4.65 267.87 6.32 259.76 23 0.11 1.24 4.67 299.65 5.85 298.6 24 0.11 1.23 4.72 330.73 6.67 336.74 25 -0.08 0.93 5.22 2.07 5.56 19.57 26 -0.15 0.93 5.22 27.01 6.76 66.08 27 -0.19 0.93 5.18 58.66 5.69 89.19 28 -0.02 0.92 5.22 84.1 9.72 88.09 29 -0.17 0.94 5.2 123.39 8.53 105.14 30 -0.05 0.94 5.14 149.28 6.94 81 31 -0.06 0.93 5.24 185.38 6.44 103.59 32 0.02 0.94 5.19 214.72 4.42 135.15 33 0.08 0.93 5.19 238.95 6.1 229.92 34 0 0.92 5.21 269.89 6.06 225.83

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Peak Wind Wind Cond. h Hs Tp wave velocity direction direction at 10 m

(m) (m) (s) (°N) (m/s) (°N) 35 0 0.93 5.23 301.29 3.81 254.76 36 0.01 0.94 5.21 330.75 5.6 296.42 37 -0.01 1.65 6 358.75 5.88 13.72 38 -0.17 1.64 5.76 28.98 5.64 56.62 39 -0.3 1.68 5.68 58.28 5.68 81.23 40 -0.37 1.65 5.54 86.82 6.11 88.77 41 -0.22 1.61 5.41 117.98 5.82 107.1 42 -0.07 1.86 5.53 153.89 5.72 122.01 43 -0.1 1.81 5.49 186.13 6.15 135.42 44 -0.02 1.84 5.58 216.57 4.67 189.69 45 0.1 1.82 5.68 236.67 5.36 227.9 46 0.19 1.78 5.67 269.4 5.73 260.5 47 0.18 1.74 5.79 301.32 5.26 283.92 48 0.14 1.76 6.07 332.44 5.49 323.89 49 0.19 2.99 7.34 356.86 5.8 11.72 50 -0.26 2.95 6.98 29.49 6.11 48.86 51 -0.45 2.79 6.73 56.02 5.81 78.28 52 -0.71 2.7 6.14 86.63 7.56 96.75 53 0.19 2.85 6.2 123.37 8.15 78.03 54 -0.09 3.16 6.36 150.27 5.71 103.32 55 -0.05 3.02 6.3 185.12 7.26 115.09 56 -0.08 2.92 6.4 217.38 5.31 190.16 57 0.17 3.01 6.67 236.09 5.35 230.75 58 0.52 3.09 6.71 269.74 5.63 275.68 59 0.55 3.05 6.83 299.73 5.45 301.96 60 0.48 3.04 7.3 332.22 4.9 334.39 61 0.52 4.46 8.64 355.83 4.23 18.09 62 0 4.24 8.26 28.26 7.67 40.29 63 0.53 4.69 8 71 10.3 20 64 0.68 4.56 8 145.5 10.1 81 65 -0.25 4.16 7.8 179 7.15 270 66 -0.17 4.3 7.49 219.24 4.38 195.01 67 0.3 4.4 7.74 239.46 5.18 235.83 68 0.83 4.51 7.71 270.38 6.73 283.6 69 0.95 4.42 7.85 299.8 5.3 299.02 70 0.97 4.43 8.47 331.39 5.45 330.27 71 1.22 5.58 9.2 350 1 350 72 0.45 5.76 7.9 210 8.2 200

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Peak Wind Wind Cond. h Hs Tp wave velocity direction direction at 10 m

(m) (m) (s) (°N) (m/s) (°N) 73 0.38 5.98 8.9 239.8 2.64 245.99 74 0.79 5.81 8 284 5 300 75 0.82 5.89 8.9 289 1 290 76 1.55 5.85 9.41 332.02 8.68 328.73 77 1.12 5.59 10.2 346 10.9 350 78 1.43 6.19 10.2 339 10.8 340 79 -0.08 0.53 5 0.27 5.02 49.61 80 -0.11 0.53 5 27.86 5.88 90.4 81 -0.13 0.6 5 63.11 6.39 95.35 82 -0.01 0.56 5 92 3.8 81 83 -0.06 0.49 5 121.82 7.36 81 84 -0.13 0.47 5 154 15.8 190 85 -0.1 0.53 5 185.51 5.08 155.09 86 -0.08 0.57 5 210.85 7.84 119.85 87 0 0.61 5 242.65 4.05 175.39 88 -0.07 0.58 5 269.92 3.87 171.99 89 -0.03 0.56 5 300.96 5.33 216.78 90 -0.05 0.57 5 330.5 5.39 276.37 91 -0.1 0.71 6.02 358.5 5.4 58.68 92 -0.13 0.71 5.74 26.03 6.49 82.89 93 -0.14 0.68 5.86 59.51 7.33 90.65 94 -0.14 0.68 5.85 86.58 7.92 89.52 95 -0.08 0.66 5.83 120.03 6.81 98.01 96 -0.08 0.64 5.88 151.81 5.83 106 97 -0.07 0.67 5.79 182.34 7.18 91.22 98 -0.05 0.69 5.67 211.42 7.13 104.73 99 -0.02 0.68 5.68 241.96 5.81 145.06 100 -0.05 0.69 5.79 270.89 6.17 155.54 101 -0.06 0.68 5.75 302.2 5.85 166.76 102 -0.06 0.69 6.02 334.02 5.33 218.29 103 -0.09 1.28 6.7 357.23 5.76 9.56 104 -0.16 1.24 6.48 27.22 6.67 73.74 105 -0.16 1.21 6.51 60.43 8.81 83.2 106 -0.15 1.21 6.58 89.59 6.18 84.08 107 -0.04 1.32 6.75 122.91 5 81 108 -0.06 1.35 6.64 148.46 3.35 98.9 109 -0.02 1.38 7.16 181.75 4.03 78 110 0.01 1.15 6.21 212.48 4.93 73.61

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Peak Wind Wind Cond. h Hs Tp wave velocity direction direction at 10 m

(m) (m) (s) (°N) (m/s) (°N) 111 0.12 1.14 6.07 240.11 6.34 159.86 112 0.04 1.22 6.44 273.47 7.54 109.18 113 -0.03 1.24 6.52 302.45 6.21 152.32 114 -0.03 1.32 6.76 334.92 5.44 278.84 115 0.11 2.75 8.73 349.67 5.27 330.68 116 0.21 2.72 8.7 335.21 3.32 268.66 117 -0.44 0.74 12.6 344 13.8 240

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Appendix B1; Water level statistics at wave buoy Europlatform

Source: http://www.rijkswaterstaat.nl/images/Referentiewaarden%20waterstanden_tcm174- 326696.pdf

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Appendix B2; Water level statistics at wave buoy Brouwershavense Gat 08

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Appendix C: Lithological maps of the source area

Lithological maps of the Source area (Marine Sampling Holland, 2014) Brouwersdam

Deltares Fig. C

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Bathymetry of the coarse ‘Zeeland’ model. Bathymetry data from 2004 Brouwersdam

Deltares Fig. D.1

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Bathymetry of the medium ‘Brouwersdam’ model. Bathymetry data from 2006 vaklodingen Brouwersdam

Deltares Fig. D.2

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Bathymetry of the medium ‘Brouwersdam’ model. Bathymetry data from 2010 vaklodingen Brouwersdam

Deltares Fig. D.3

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