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- 10.1016/j.coastaleng.2019.103628
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Abstract
Coastal Engineering 156 (2020) 103628 Contents lists available at ScienceDirect Coastal Engineering journal homepage: http://www.elsevier.com/locate/coastaleng Field-based decadal wave attenuating capacity of combined tidal flats and salt marshes a, b, c, * a d, e b Pim W.J.M. Willemsen , Bas W. Borsje , Vincent Vuik , Tjeerd J. Bouma , Suzanne J.M. H. Hulscher University of Twente, Water Engineering & Management, P.O. Box 217, 7500 AE, Enschede, the Netherlands NIOZ Royal Netherlands Institute for Sea Research and Utrecht University, Department of Estuarine and Delta Systems, P.O. Box 140, 4400 AC, Yerseke, the Netherlands Deltares, Department of Ecosystems and Sediment Dynamics, P.O. Box 177, 2600 MH, Delft, the Netherlands Delft University of Technology, Faculty of Civil Engineering and Geosciences, P.O. Box 5048, 2600 GA, Delft, the Netherlands HKV Consultants, P.O. Box 2120, 8203 AC, Lelystad, the Netherlands ARTICLE INFO ABSTRACT Keywords: Foreshores consisting of both bare tidal flats and vegetated salt marshes are found worldwide and they are well Wave attenuation studied for their wave attenuating capacity. However, most studies only focus on the small scale: just some Coastal protection isolated locations in space and only up to several years in time. In order to stimulate the implementation of Building with Nature foreshores serving as reliable coastal defense on a large scale, we need to quantify the decadal wave attenuating Foreshore capacity of the foreshore on the scale of an estuary. To study this, a unique bathymetrical dataset is analyzed, Salt marsh covering the geometry of the Westerschelde estuary (The Netherlands) over a time-span of 65 years. From this Nature Based Flood Defense dataset, six study sites were extracted (both sheltered sites and exposed sites to the prevailing wind direction) SWAN and divided into transects. This resulted in 36 transects covering the entire foreshore (composed of the bare tidal flat and the vegetated salt marsh). The wave attenuation of all transects under daily conditions (with and without vegetation) and design conditions (i.e. events statistically occurring once every 10,000 years) was modelled. Overall, the spatial variability of the geometry of a single foreshore was observed to be much larger than the temporal variability. Temporal changes in salt marsh width did not follow the variability of the entire foreshore. Both under daily and design conditions, vegetation contributes to decreasing wave energy and decreases the variability of incoming wave energy, thereby decreasing the wave load on the dike. The southern foreshores, sheltered from the prevailing wind direction, were more efficient in wave attenuation than the exposed northern foreshores. A linear relation between marsh width and wave attenuation over a period of 65 years was observed at all marshes. The present study provides insights needed to calculate the length of a salt marsh to obtain a desired minimum wave attenuating capacity. 1. Introduction zone, as an insurmountable consequence of climate change (Donnelly et al., 2004; Knutson et al., 2010; Lin et al., 2012; IPCC, 2014). As a Estuaries are complex landscapes shaped by bio-physical interactions result, estuaries become increasingly vulnerable to flooding and com- and anthropogenic influences. They are located at the interface of fresh munities inhabiting these areas are in need of improved flood riverine and saline coastal waters, providing a range of ecosystem ser- protection. vices such as habitat provision, food production, space for recreation The population and economic value of the estuaries hinterland are and accessibility over water (e.g. Barbier et al., 2010). However, living generally protected by conventional coastal engineering solutions, such near estuaries also comes with flood risks from riverine and coastal as groins, revetments, breakwaters and sea walls. Those conventional sources. Nevertheless, the population density in these areas is high and measures are increasingly challenged by regional and global changes, still growing (Small and Nicholls, 2003; Syvitski et al., 2009). Moreover, including climate change-induced Sea Level Rise (SLR), increased storm extreme storm events and sea level rise increase flood risks in the coastal intensity and land subsidence (Syvitski et al., 2009). These conventional * Corresponding author. University of Twente, Water Engineering & Management, P.O. Box 217, 7500 AE, Enschede, the Netherlands. E-mail address: [email protected] (P.W.J.M. Willemsen). https://doi.org/10.1016/j.coastaleng.2019.103628 Received 10 July 2019; Received in revised form 23 December 2019; Accepted 29 December 2019 Available online 2 January 2020 0378-3839/© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 solutions are static and do not adapt to a changing climate (Borsje et al., foreshore to wave attenuation under extreme scenarios and under daily 2011; Temmerman et al., 2013). scenarios, that have not been measured before. In section 4 the main Foreshores, consisting of a bare tidal flat and vegetated salt marsh, findings of this paper are discussed. We end by drawing some conclu- can serve as add-on to conventional coastal defenses (Kirwan et al., sions in Section 5. 2010; Gedan et al., 2011; Moller et al., 2014). Firstly, salt marshes occur widely in tempered climate zones (Mcowen et al., 2017), so they can be 2. Bathymetrical field data analysis and wave modelling applied globally. Secondly, foreshores can dissipate wave energy due to the bottom profile and vegetation (e.g. Vuik et al., 2016), consequently 2.1. Long-term foreshore elevation being suitable to attenuate wave energy in front of a dike. Thirdly, marshes are sustainable and in that they can cope, to a certain extent, Historical elevation data of foreshores, from the subtidal up to the with SLR (Kirwan and Megonigal, 2013; Kirwan et al., 2016). By dissi- higher elevated parts, which are only submerged during extreme high pating hydrodynamic energy, sediment is trapped in the marsh, enabling water, is scarce. In general, bathymetrical data representing the subtidal vertical growth of the bed (Bouma et al., 2007; Van Wesenbeeck et al., area has sufficient coverage. However, the data coverage for the higher 2008). elevated vegetated salt marsh is often lacking. In addition, long-term Thus, salt marshes have high potential for a contribution to coastal (50þ year) datasets with consecutively collected elevation data is protection, despite the uncertainty as a consequence of using vegetation even more scarce. Nevertheless, such datasets are available for the entire and thereby introducing intrinsic biological factors (Bouma et al., 2014). Westerschelde estuary in the Netherlands. In the Westerschelde estuary, Moreover, salt marshes and tidal flats might be cost-effective locally and multiple foreshores are present (Fig. 1), which can be differentiated by more flexible and thereby suitable for adaptive coastal management the prevailing wind direction being southwest. This results in a di- compared to conventional coastal engineering solutions (Turner et al., chotomy of wind exposure, with foreshores at the northern shores being 2007; Broekx et al., 2011; Cheong et al., 2013), which is a prerequisite exposed and foreshores at the southern shores being sheltered from the for dealing with flood risks due to climate change (Gersonius et al., prevailing wind direction (Callaghan et al., 2010). The long-term wave 2013). attenuating capacity of six foreshores, three at the exposed and three at So far, the significant wave attenuating capacity of foreshores within the sheltered shores in the Westerschelde (Fig. 1), was analyzed. the time scale of events (e.g. extreme storm events) is proven for specific Elevation data for those nearshore areas were captured in extensive aspects in wave flumes (e.g. Coops et al., 1996), and give mechanical bathymetrical datasets, called ‘Vaklodingen’. The data was collected understanding of vegetation stiffness (Bouma et al., 2005), standing since 1925–1935 by the Ministry of Infrastructure and the Environment biomass, (Bouma et al., 2010), extreme storms (Moller et al., 2014) and (former Ministry of Transport Public Works and Water Management). wave-current interaction (Maza et al., 2015). Field studies give insights After post-processing, the data is stored in grids with a cell size of 20 � in wave attenuation with realistic conditions on a larger scale (Moller, 20 m (De Kruif, 2001; Wiegman et al., 2005). The vertical accuracy of 2006; Yang et al., 2012; Vuik et al., 2016). These studies prove the the Vaklodingen data was 0.54 m in the 1950s increasing to 0.11 m since significant wave attenuating capacity for a specific setting of a foreshore 2001 (Marijs and Par� ee, 2004). for a specific moment in time: a snapshot. Within the timescale of sea- We constructed two-dimensional transects, to enable assessment of sons, field measurements at transects perpendicular to the marsh edge the wave attenuating capacity (cf. Horstman et al., 2014). Bathymetrical between salt marsh and tidal flat suggest a relative stable salt marsh with data from the Vaklodingen was interpolated over the transects. The di- a more variable seaward situated tidal flat (Andersen et al., 2006; Vuik rection of the transects was parallel to the wave direction under design et al., 2018a; Willemsen et al., 2018). Moreover, at this seasonal time- conditions (i.e. extreme event statistically occurring once every 10,000 scale, measurements over a stretch of salt marsh (50 m width), suggest a years), obtained from a database with the results of 2D wave simula- continuous contribution of the marsh to wave attenuation (Vuik et al., tions, carried out in the context of dike safety assessments in the 2018a). Netherlands (Gautier and Groeneweg, 2012; Groeneweg and Van Although all these studies actually measure the wave attenuation, Nieuwkoop, 2015). Transects that interfered with the land boundary, they still focus on the relative small scale, i.e. some isolated locations in due to the position of the study site in the curvature of the dike, were space and at most up to several years in time, and they do not capture excluded (i.e. the average design wave direction for a foreshore was just extreme conditions over long-term salt marsh settings. Moreover, to our landward directed due to the shape of the foreshore). The alongshore knowledge superimposing extreme conditions over long-term foreshore spacing between transects (i.e. number of transects over a certain settings measured in the field, to give unique long-term insights, has not alongshore foreshore length) was selected in a way to capture the been done before. The long-term persistence of wave-attenuating eco- alongshore variability of the geometry and wave attenuation. This systems has been identified as a key-bottle neck hampering application spacing was based on a transect refinement study (section 2.2.3). For of intertidal habitats for coastal protection (Bouma et al., 2014). determining the foreshore width, mean high water spring (MHWS) was Moreover, wave attenuation is known to be highly location-specific, used to represent the landward boundary. The seaward boundary of the depending on bio-physical settings such as foreshore width and the ge- foreshore was represented by mean low water spring (MLWS). Both ometry of both the vegetated salt marsh and bare tidal flat (Vuik et al., water levels were assumed to be static over time, although an increase of 2016). Hence, the key question addressed in this paper is: what is the the tidal amplitude over time has been observed in the Westerschelde variability of foreshores, consisting of salt marshes and adjacent tidal (Taal et al., 2015), possibly changing the boundaries of the transects as a flats, in an estuary over a decadal time-scale; and to what extent can consequence. However, the hydrodynamic input parameters also change foreshores safely act as additional defense measure? We will quantify with a changing tidal amplitude, as it is assumed resulting in only minor the long-term (50þ years) variability of the wave attenuating capacity of changes to the wave attenuating capacity. Missing data causing foreshores in a full estuary, by combined long-term large-scale bathy- incomplete transects at the intertidal or higher parts were interpolated metrical field data and numerical model analysis for calculating wave over time per transect (cf. Vuik et al., 2019). In case the first year to be attenuation. analyzed from a certain transect was incomplete, the known position of The structure of this paper is as follows. In Section 2 the study area is the dike toe was used for spatial interpolation, after which temporal introduced, followed by a description of the long-term bathymetrical interpolation was applied. data. Consecutively the numerical model analysis for calculating wave attenuation is described, including vegetation representation and the 2.2. Modelling wave attenuation scenarios that were assessed. Section 3 presents the variability of the bathymetry of the foreshore, followed by the contribution of the Wave attenuation over the foreshore was computed using the 2 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 Fig. 1. Six analyzed foreshores (top and bottom panels) in the Westerschelde, indicated with red dots (center), located in the Southwestern part of the Netherlands (see inlay in center panel). Bathymetrical data of 2014 is presented in the center panel (elevation in meter with respect to mean sea level). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Fig. 2. Schematic overview of the foreshore, con- sisting of a bare tidal flat (dark grey), vegetated salt marsh (light grey) and dike (black) for obtaining wave attenuation under different scenarios. Hydro- dynamic parameters used are: mean high water spring (MHWS), mean high water neap (MHWN), mean low water spring (MLWS), water level (h), significant wave height (H ) and the Nikuradse m0 roughness length (k ). Scenarios assessed were: (1) daily without explicitly accounting for vegetation by using a single Nikuradse roughness length k , N,bare flat (2) daily with explicitly accounting for vegetation by using a different Nikuradse roughness length for the bare foreshore (k ) and the bed of the N, bare flat vegetated foreshore under the vegetation (k N, veg. ) and explicitly taking into account vege- marsh daily tation structures, (3) design conditions by using a different Nikuradse roughness length for the bare foreshore (k ) and for the vegetated fore- N, bare flat shore (k marsh design) by taking into account N, veg. stem breakage and hydrodynamic parameters under design conditions. 3 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 Table 1 Characteristics of the analyzed foreshores and input values for wave modelling. Study site Local water level boundaries Vaklodingen data Local design conditions MLWS MHWN/ MHWS/Daily Period of data Number of Design Design wave Design wave Design wave (m) marsh edge water level (m) availability (year - years included water level height (m) period (s) direction (⁰) (m) year) ( ) (m) h h h – – h H T dir MLWS MHWN daily norm m0,design m-1,0,design 1. Zuidgors 2.31 1.85 2.63 1955–2015 37 6.04 1.655 4.725 233 2. Baarland 2.28 1.83 2.62 1955–2015 37 6.13 1.72 4.35 238 3. Zimmerman- 2.46 2.14 3.04 1951–2015 51 6.71 1.82 4.15 212 polder 4. Hoofdplaat 2.06 1.59 2.34 1950–2015 42 5.78 2.36 4.55 323 5. Paulina 2.16 1.73 2.54 1955–2015 41 5.89 2.15 4.7 344 6. 2.25 1.81 2.61 1955–2015 52 6.32 2.56 4.95 301 Hellegatpolder spectral wave model SWAN (Simulating WAves Nearshore; Booij et al., characteristics have been averaged to obtain general values for the mean 1999; Ris et al., 1999). In this model, the vegetation module for wave vegetation height (h ), stem density (N ), stem thickness (b ) and veg v,0 v,0 attenuation was developed by Mendez and Losada (2004) and imple- these values were used as input for SWAN (Table 2). The general char- mented in SWAN by Suzuki et al. (2012). The model was calibrated, acteristics derived from both salt marshes were assumed to be repre- validated and applied previously on two foreshores in the southwestern sentative for the whole Westerschelde. delta of the Netherlands: 3. Zimmermanpolder (Bath) at the exposed Under daily conditions, the long-term contribution of vegetation to northern shore and 6. Hellegatpolder at the sheltered southern shore the wave attenuating capacity of foreshores was assessed by explicitly (Fig. 1), where energy dissipation (i.e. wave heights) by foreshores including and excluding vegetation in wave modelling. The scenario under storm conditions was accurately simulated using the SWAN model including vegetation was assumed to be representative for summer (Vuik et al., 2016). In the current study the wave attenuating capacity of conditions with maximum biomass, while the scenario excluding vege- foreshores under different conditions was assessed. Daily occurring tation was assumed to be representative for winter conditions, with environmental settings (with and without vegetation) and environ- minimum vegetation biomass. Daily conditions without vegetation in mental settings based on design conditions (event with a statistical scenario 1 (panel 1, Fig. 2) were represented with a constant Nikuradse recurrence time of 1/10,000 year) were used (Fig. 2). Under design roughness length scale (k ) of 0.001 m for the entire profile (Vuik N,bare flat conditions, it was assumed that vegetation present at the marsh was bent et al., 2019), for only assessing the contribution of the morphology. The over or broken and lying flat at the bed (Vuik et al., 2018a, 2018b). Nikuradse values used, are derived from Manning roughness coefficients presented in Wamsley et al. (2010), by using the conversion equation in 2.2.1. Vegetation characteristics and bottom roughness Bretschneider et al. (1986). Vegetation was explicitly included in the The marsh edge position was determined by using a tidal benchmark, model in scenario 2 (panel 2, Fig. 2). Daily conditions with vegetation since the marsh edge position was recorded for the full period of data. In were represented with a Nikuradse roughness length scale of 0.001 m at literature, the seaward marsh edge has often been approximated by the bare tidal flat (k ) and 0.02 m at the vegetated foreshore (k N,bare flat N, using a tidal benchmark (McKee and Patrick, 1988; Bakker et al., 2002; ) representing the bed under the vegetation (Vuik et al., veg. marsh daily D’Alpaos et al., 2007; Balke et al., 2016). The tidal benchmark mean 2016, Table 2). Under design conditions, scenario 3 (panel 3, Fig. 2), the high water neap (MHWN) has been used previously to define the marsh roughness at the marsh due to broken vegetation was represented by a edge (Doody, 2007), and this benchmark was used to study salt marsh Nikuradse roughness length scale k of 0.05 m (Wamsley N,veg. marsh design dynamics in the Westerschelde as well (Van der Wal et al., 2008). et al., 2010), whereas the roughness at the bare tidal flat in front of the Therefore, the tidal benchmark MHWN from Van der Wal et al. (2008) marsh (k ) was represented again with the value of 0.001 m (Vuik N,bare flat was adopted in the present study to define the salt marsh edge (Table 1). et al., 2019). So following Vuik et al. (2019), vegetation in scenario 3 Vegetation characteristics at the marsh edge were obtained by Vuik was not included in SWAN using the vegetation module, but using an et al. (2016), for the brackish salt marsh Zimmermanpolder (3; called adapted Nikuradse roughness length. Bath in Vuik et al. (2016)) and more salty salt marsh Hellegatpolder (6). The brackish species Scirpus maritimus was found at Zimmermanpolder 2.2.2. Hydrodynamic boundary conditions (3), while the salty species Spartina anglica was found at Hellegatpolder Hydrodynamic boundary conditions for approximating the daily (6). More mixed vegetation was present at the higher marsh, but was not wave attenuating capacity (panel 1 & 2, Fig. 2) representing the water taken into account, because a major part of the waves is attenuated at level were derived from tidal characteristics. Mean High Water Spring the marsh edge, especially under daily conditions. Collected vegetation (MHWS), being the highest common occurring water level at which Table 2 General input parameters for wave modelling. Parameter Symbol Value Unit Source Daily wave height H 0.2 m Callaghan et al. (2010); Hu et al. (2015a) m0,daily Daily wave period T 3 s Hu et al. (2015b) m-1,0,daily Mean vegetation height h 0.24 m Vuik et al. (2016) veg Vegetation stem density N 865 1/m Vuik et al. (2016) v,0 Vegetation stem thickness B 5.1 mm Vuik et al. (2016) v,0 Nikuradse roughness length scale for bare tidal flats k 0.001 m Vuik et al. (2019) N,bare flat Nikuradse roughness length scale for salt marsh under design conditions k 0.05 m Vuik et al. (2019); Wamsley et al. (2010) N,veg.marsh design Nikuradse roughness length scale for salt marsh under daily conditions k 0.02 m Vuik et al. (2016) N,veg. marsh daily Bulk drag coefficient C 1.0 – Suzuki and Arikawa (2010) Transect spacing SpacT 250 m Transect refinement (section 2.2.3.) 4 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 large parts of the salt marsh contribute to wave attenuation, was derived plants will be limited, and we assumed the drag force will resemble that from Van der Wal et al. (2008). Daily wave characteristics used, were of rigid cylinders, for which a value of approximately 1.0 is appropriate H ¼ 0.2 m and T ¼ 3 s (Callaghan et al., 2010; Hu et al., (Suzuki and Arikawa, 2010). Therefore, C ¼ 1.0 is taken into account in m0,daily m-1,0,daily D 2015a, 2015b) (Table 2; Fig. 2). Energy gain due to wind was not all SWAN simulations for daily conditions explicitly including vegeta- accounted for in the calibrated SWAN model (Vuik et al., 2016), since tion (scenario 2). wind input was assumed to be insignificant over small foreshore lengths. The hydrodynamic boundary conditions under design conditions 2.2.3. Transect refinement (panel 3, Fig. 2; Table 1) were obtained from the WTI (legal assessment To assess the wave attenuating capacity of a foreshore, the landscape instrument; in Dutch: ‘wettelijk toetsingsinstrumentarium’) (Gautier was represented using transects parallel to the design wave direction and Groeneweg, 2012; Groeneweg and Van Nieuwkoop, 2015) repre- (center panel, Fig. 3). The spacing between the transects (i.e. the senting an event statistically occurring once every 10,000 year. This alongshore distance between two transects) was selected in a way that safety level has been used previously to assess the safety of the Dutch the spatial variability of the foreshores was fully captured. The geometry dikes. Both water levels and wave characteristics are available along of the foreshore for a specific transect and associated wave attenuating every 250 m of coastline. Water levels, wave period and wave height at capacity was calculated for transects with a different alongshore the eastern and western side of each study site were averaged, thereby spacing, i.e. the distance between transects was measured over the avoiding hydrodynamic parameters that were influenced by the topog- landward stretch of the dike to be able to relate the results to dike safety. raphy of the study site (e.g. by refraction and shoaling) (top panel, An initial spacing of 1000 m was selected, because the alongshore length Fig. 3). The design wave direction was selected at the center of the salt of the foreshores just exceeded 1000 m at some foreshores. A transect marsh (Table 1). Herein is the wave direction the result of the wind spacing of 1000 m does not include the minimum and maximum transect direction and rotation due to refraction. width of the foreshore, and as a consequence neither the full variability Bulk drag coefficients C were derived in Vuik et al. (2016) by cal- in wave attenuation. The same holds for a transect spacing of 500 m. The ibrating the SWAN model for optimal reproduction of measured wave full variability of the foreshore was captured by a transect spacing of attenuation by vegetation. However, these calibrated values were meant 250 m, a smaller spacing of e.g. 125 m did not add more detail. So a to describe wave attenuation during storms, for which flexibility of transect spacing of 250 m was selected to capture the maximum vari- vegetation plays an important role. This resulted in values significantly ability with the largest spacing (i.e. least amount of transects) for below 1.0. The current study explicitly includes vegetation structures for computational efficiency (bottom panels, Fig. 3). wave attenuation under daily conditions (panel 2, Fig. 2), with small waves and low water depth. In these circumstances, bending of the 3. Results 3.1. Long-term foreshore geometry 3.1.1. Temporal variability The foreshore geometry was assessed by analyzing historical bed level data. The cross-shore width of both the vegetated salt marsh and complete foreshore (between MLWS and MHWS) were found to be variable over space and time. The width of the vegetated part did not follow the total width of the foreshore per definition. At a representative transect at Paulinapolder, the width of the total foreshore increased by a Fig. 3. The method for assessing wave attenuation at the foreshore Zuidgors for a single transect and a single year. The top panel shows locations (blue dots) where significant wave heights under design conditions were provided (Gautier and Groeneweg, 2012; Groeneweg and Van Nieuwkoop, 2015). Hydrodynamic characteristics (water level, wave height, wave direction) at both alongshore boundaries of the foreshores were averaged to obtain boundary conditions for the wave model (black circles; top panel). The bed elevation was derived from the Vaklodingen dataset (background colors in center panel indicate the ba- thymetry of 2014). Transects parallel to the design wave direction with an alongshore spacing of 250 m, measured at the dike, are indicated with black lines (center panel). The blue line (center panel) highlights transect 8, for which Fig. 4. Change in width of foreshore (horizontal axis) in time (vertical axis) for the temporal variation of wave attenuation is shown (bottom left panel). The the 6 foreshores studied. The color indicates the elevation with respect to mean vertical dashed blue line (bottom left panel) highlights the last year assessed sea level, whereas the black line indicates the marsh edge and the grey line (2015). The wave attenuating capacity in the last year 2015 for all nine tran- mean low water spring (MLWS). Per foreshore, a representative transect is sects at the marsh is highlighted with the blue line (left vertical axis; bottom chosen and followed in time, as shown for Zimmerman in 2015 (top right). right panel). The black line indicates the width of the assessed foreshore, Abbreviations indicate locations as indicated in Fig. 1; red letters highlight whereas the green line indicates the width of the vegetated salt marsh (both on exposed sites, while black letters highlight sheltered sites from the prevailing the right vertical axis). (For interpretation of the references to color in this wind direction. (For interpretation of the references to color in this figure figure legend, the reader is referred to the Web version of this article.) legend, the reader is referred to the Web version of this article.) 5 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 Baarland (largest). While the range becomes constant or even decreases over the long-term, the median of the change shows different behavior per entire foreshore. A continuous increase was observed at Baarland (0–60 m), Zimmermanpolder (5–130 m), and Hoofdplaat (0–33 m), while a decreasing marsh width was observed at Paulinapolder (0 to 115 m) and Hellegatpolder (0 to 55 m). At Zuidgors (between -5 m and 25 m) the median change was observed to vary around zero (Ap- pendix A). It was striking that in general, the largest increase in marsh width change (between 10th and 90th percentile) occurred in periods between 1 and 10 years and 11 and 20 years (Fig. 6). This observation in combination with a flattening range between the maximum and mini- mum marsh width change over the long-term might indicate an increasing stability over a longer period. 3.1.2. Spatial variability At Zuidgors, the average width of the salt marsh (483 m; see Ap- pendix A; table 9, for the average width of the vegetated salt marsh and bare tidal flat of all foreshores) was observed to be much smaller than the width of the total foreshore (1116 m) (Fig. 5). However, the width of the vegetated salt marsh in a single year was highly variable, showing Fig. 5. Change in width of the foreshore (vertical axis) over time (horizontal differences of up to 600 m over an alongshore salt marsh stretch of axis) in which distinction is made in salt marsh width (green area) and total 2000m (Fig. 5). The most western part of the foreshore at Zuidgors foreshore width (grey area) The shading indicates the minimum and maximum showed less variability in foreshore width compared to the eastern part, width, the thick line in the center of the shading indicates the spatial mean probably due to the geographical features surrounding the foreshore. width and the dotted line indicates the overall mean width. Abbreviations One of the main features is the presence of a channel in front of the indicate locations as indicated in Fig. 1; red letters highlight exposed sites, foreshore (Fig. 1; top panels, Fig. 3). The vegetated foreshore part at the while black letters highlight sheltered sites from the prevailing wind direction. eastern side of the center has more landward accommodation space, due (For interpretation of the references to color in this figure legend, the reader is to the shape of the dike. Due to the contribution of those boundaries, the referred to the Web version of this article.) spatial variability remained stable (Figs. 4 and 5). Geographical features like dikes and jetties, did also drive the spatial variability within a single year at the other locations. At Baarland, Zimmermanpolder and Pauli- 100 m over 60 years. Nevertheless the width of the salt marsh was highly napolder, the salt marsh width is smaller at the alongshore edges of variably with a minimum width of 80 m and a maximum width of 310 m marsh, while being larger at the central part of the marsh due to the in the first decades (Fig. 4 location PAU). Moreover, at Zimmerman- recessed dike, similar to Zuidgors. At Hoofdplaat and Hellegatpolder polder the total foreshore width in the first decade was decreasing (from jetties and an outflow channel affect the spatial variability of the salt 1530 m to 1140 m), while the width of the vegetated part was increasing marsh. At Baarland the spatial variability of both the total foreshore and with tens of meters (Fig. 4, location ZIM). Zooming in on the single the salt marsh remained small, with some peaks up to a 1000 m for the foreshores, the average width (averaged over all transects of the fore- foreshore and hundreds of meters at the salt marsh. The little variability shore) of the bare tidal flat was always larger than the average width of might be caused by a small channel appearing close to the salt marsh the adjacent vegetated salt marsh, i.e. on average the part of the fore- edge (Fig. 1). At Zimmermanpolder the spatial variability of the salt shore covered by vegetation does never exceed 50% (Fig. 5). The part of marsh was approximately 200 m, whereas the spatial variability of the the foreshore covered by vegetation was relatively high at Zuidgors and total foreshore reached 1200 m. The spatial variability of the foreshores Paulinapolder, exceeding 32%, while below 20% at the other foreshores. at the sheltered shores remained constant (Fig. 5), being 300–500 m for In general the mean width of the salt marsh remained stable (except both the total foreshore and salt marsh at Hellegatpolder and Paulina- during the last decade at Baarland), whereas the mean width of the total polder, while both the average width and variability increased at foreshore showed a more dynamic behavior (Fig. 5). At Zuidgors, Hoofdplaat (Fig. 5). Baarland, Zimmermanpolder and Hellegatpolder changes of hundreds of meters occurred within a period of 5 years only. The latter is supported 3.1.3. Spatial versus temporal variability by strong changes of the total foreshore width observed at a single The width of transects between MLWS and MHWS of a single fore- representative transect in periods of a few years only, e.g. in the first shore was highly variable, e.g. at Zuidgors ranging between 600 m and decades of the analysis at Zimmermanpolder (ZIM) and Hellegatpolder 1500 m (Fig. 3). However, the spatial variability remained constant over (HEL) and the last decade at Baarland (BAA) (Fig. 4). time, i.e. the range of the width of all transects of a single foreshore The change of the width of the vegetated salt marsh over a period of a remained stable (Fig. 5). The spatial variability of the salt marsh at single year remained small, with a change of maximum tens of meters in Zuidgors slightly decreased with tens of meters only, this was observed the range of the 10th and 90th percentile (Appendix A). Both positive more distinct at the sheltered site Hellegatpolder with approximately and negative outliers of hundreds of meters were observed over a single 200 m, whereas an increasing spatial variability was observed at year (Fig. 6; Appendix A). The marsh width change increased with Hoofdplaat both for the total foreshore and salt marsh. The average total increasing length of observation periods, i.e. the longer the observation foreshore width increased with 250 m, while the variability increased period, the larger the difference between maximum and minimum width from less than 100–600 m. Those changes might have been the result of of the salt marsh width, indicating a continuous change over the entire accretion between the jetties and/or changes in the seaward navigation period. However, when observing the change over the longest periods channel. Large differences of spatial variability over time was observed (marsh width change over more than 30 years), the change in width at Zimmermanpolder, in the first decades. Nevertheless the variability of decreased. Moreover, the range between minimum and maximum the foreshore in a single year decreased from a maximum of 1200–260 change was largest over the periods between 11 and 20 and 21 and 30 m, while the width of the salt marsh remained constant over time years, with differences between the minimum and maximum of (Fig. 5). Most striking was the temporal variability at Baarland, where 100–200 m at e.g. Hoofdplaat (smallest) and almost a kilometer at the total foreshore width increased from approximately 1400–2800 m 6 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 and the salt marsh width increased from 40 m to 860 m, while the spatial variability was small. In general, the average width of foreshore parts of a single foreshore was larger in space than in time, i.e. the width of the foreshore (parts) remained constant over time while more variation was observed over a single foreshore in a single year (Fig. 5). However there were exceptions, the temporal variation at Baarland was larger than the spatial variation, probably due to a small channel in front of the foreshore undershooting MLWS, only appearing in a part of the assessed period. The, in general larger, spatial variability indicated that the alongshore variability of the geometry caused by geographical boundaries (e.g. dikes and channels), was larger than the variability of a single transect influenced by hy- drodynamics, morphodynamics and vegetation growth. The latter im- plies that a large part of the variability of the foreshore geometry captured in a single observation, represents the variability of the width of the foreshore (parts) over the long-term (60–70 years). 3.1.4. Exposed shores versus sheltered shores The average width of foreshores, parallel to the design wind direc- tion, in the Westerschelde ranged between 344 m and 2130 m (Fig. 5), Fig. 6. Marsh width change (vertical axis) over a period of a single year, pe- with an average vegetated part ranging between 7% and 42% of the total riods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years (hor- foreshore width. The average width of the foreshores at the northern izontal axis). The white marker indicates the median, the 10th and 90th shores (1583 m), exposed to the prevailing wind direction, of the percentile are highlighted by the black bar, while the whiskers at the top and Westerschelde was larger than at the southern shores (652 m), sheltered bottom of the black bar indicate the maximum and minimum change over a from the prevailing wind direction. Therefore the foreshores at the specific period. Abbreviations indicate locations as indicated in Fig. 1; red sheltered shores consisted of a steeper gradient, since the width was letters highlight exposed sites, while black letters highlight sheltered sites from measured between two vertical positions fixed in time (MHWS and the prevailing wind direction. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) MLWS). The average salt marsh width at the exposed shores was 280 m, whereas 151 m at the sheltered shores. This is a vegetated part of 18% and 23% respectively. In general the smaller sheltered foreshores showed a smaller marsh width change over the assessed period. How- capacity of the foreshore and decreased the variability of wave attenu- ever, it appeared that the marsh at the sheltered foreshores were ating capacity of the foreshore, thereby decreasing the wave load at the retreating (PAU and HEL) or slightly increasing (HOO). The marshes at dike. the exposed foreshores were relative stable (ZUI) or even expanding (BAA and ZIM), in spite of their location exposed to the prevailing wind 3.2.2. Design conditions direction (Fig. 6). Under design conditions, a significant contribution to the wave attenuation was observed for all transects (Fig. 7). The largest contri- 3.2. Long-term wave attenuating capacity bution to wave attenuation under design conditions was observed at foreshores with a wide vegetated part. For foreshores with a relatively The wave attenuation was calculated for three different scenarios, small vegetated part, the bare tidal flat was a large contributor to wave (1) attenuation under daily conditions over the transects, (2) attenua- attenuation (up to 18%) (Fig. 8). In general, a constant baseline atten- tion under daily conditions over the transects, explicitly accounting for uation of 2%–18% was the result of wave attenuation by the tidal flat. vegetation, and (3) attenuation under design conditions over the tran- Whereas attenuation as a result of the salt marsh was more variable, sects, accounting for broken vegetation (Fig. 2). The wave attenuating more or less following the width of the salt marsh. At most foreshores, capacity of a single transect was defined as the smallest value found for the spatial variability of the wave attenuation in a single year (spatially; the wave attenuation for the assessed period, to indicate the natural e.g. 5%–20% at Zuidgors), exceeded the temporal variability of a single capacity of the foreshore, without additional management. Those values transect over the entire measurement period. However, this cannot be for all transects of a single foreshore, result in a characteristic range of adopted as a general rule, e.g. at Baarland the temporal variability was the wave attenuating capacity of a single foreshore. The transect with larger than the spatial variability. Moreover, in some years the spatial the smallest wave attenuation marks the lower limit of the range. variability of the wave attenuating capacity could have been neglected, while the temporal variability of a single transect over the assessed 3.2.1. Daily conditions period was 20% (comparing a vertical spatial and horizontal temporal The range of wave attenuation under daily conditions (scenario 1) cross-section in Fig. 7). was large, between 10% and 100% at the exposed shores and 0% and A general relation between width of the foreshore and wave atten- 100% at the sheltered shores. The large wave attenuation was almost uation under design conditions was not found. However, when dis- entirely the result of attenuation at the salt marsh. Inclusion of vegeta- tinguishing the wave attenuation by the vegetated salt marsh and bare tion (scenario 2), representing summer conditions, leads to higher wave tidal flat, a unique relation per foreshore was observed. The wave attenuation and a lower variability, especially at the foreshores located attenuation of the salt marsh was found to be a function of the width of at the exposed shores. The attenuation ranged between 60% and 100%, the salt marsh (Fig. 8). The longer the salt marsh, the larger the wave with only a single lower peak at Zuidgors and Baarland of approximately attenuation under design conditions, given a maximum observed marsh 30%–40%. Under both scenarios for daily conditions, the waves were length of approximately 1000 m. A fit of the relation showed a rather almost always fully attenuated by the foreshore, probably due to depth- strong approximation (R : ZUI is 0.61; BAA is 0.99; ZIM is 0.87; HOO is induced wave breaking. Nevertheless, this was at least partly accom- 0.76; PAU is 0.86; HEL is 0.86), with the smallest R at Zuidgors, also plished by the presence of vegetation, stabilizing the profile. The com- indicated by the 95%-confidence interval (Fig. 8; coefficients for the parison of the wave attenuation for both scenarios under daily linear model y ¼ ax þ b are presented in Appendix B, where y is the wave conditions indicates that vegetation increased the wave attenuating 7 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 Fig. 8. Contribution of both foreshore parts to wave attenuation under design conditions (i.e. extreme event statistically occurring once every 10,000 years) for all transects and years. The width of the bare (grey asterisk) and vegetated foreshore (black dot) are indicated at the horizontal axis, their contribution to the wave attenuation under design conditions is plotted at the vertical axis. The colored thick line per panel, indicates the fit of the relation between vegetated foreshore width and wave attenuation and the colored thin lines indicate the 95% confidence interval. Abbreviations indicate locations as indicated in Fig. 1; red letters highlight exposed sites, while black letters highlight sheltered sites from the prevailing wind direction. The three numbers in each panel charac- terize the foreshore, from top to bottom: the extreme water level, extreme wave height and the wave height/water level ratio respectively. All relations are summarized in the bottom right panel. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) energy; (3) under design conditions, foreshores located at shores shel- tered from the prevailing wind direction were more efficient in wave Fig. 7. Wave attenuation (i.e. % of incoming wave; indicated by colors) under attenuation than foreshores located at exposed shores, which might be design conditions (i.e. extreme event statistically occurring once every 10,000 related to the geometry of the foreshore. Moreover, the bare tidal flat years) for both the vegetated part of the foreshore (panels with “veg.” behind caused a baseline wave attenuation, while the additional contribution of location name) and the total foreshore. The time is indicated at the horizontal the vegetated salt marsh appeared to be related to marsh width: the axis, whereas the different transects are presented at the vertical axis. Abbre- larger the marsh width, the larger the wave attenuation. viations indicate locations as indicated in Fig. 1; red letters highlight exposed sites, while black letters highlight sheltered sites from the prevailing wind di- rection. (For interpretation of the references to color in this figure legend, the 4.1. Contribution of foreshores to coastal safety reader is referred to the Web version of this article.) The protective value of (vegetated) foreshores by wave attenuation has been proven in recent years, even under extreme conditions (Barbier et al., 2008; Gedan et al., 2011; Shepard et al., 2011; Moller et al., 2014). attenuation, x is the vegetated marsh width and a and b are the linear However, the protective value depends on the bio-geomorphological coefficients). A clear distinction was observed between the foreshores at settings of the foreshore (Vuik et al., 2018b), which vary over time the exposed and sheltered shores of the Westerschelde. The wave height, (Bouma et al., 2014). Based on long-term field data and modelling, this water level ratio under extreme conditions was also larger at the shel- study emphasizes the presence of an added value for coastal safety under tered shores, due to slightly lower water levels and larger waves, which all bio-geomorphological settings present in an entire estuary (e.g. 6 might possibly affect the effectiveness of the wave attenuation. The foreshores, a total of 36 transects, over 65 years). Whereas previous wave attenuation at the sheltered foreshores was larger per meter of salt studies calculate the wave attenuating capacity for a single setting, marsh, despite the shorter width of both the total foreshore and salt multiple settings not using long-term field measurements and/or the marsh. So the effectiveness of wave attenuation under design conditions, short-term (e.g. Bouma et al., 2010; Yang et al., 2012; Moller et al., per meter marsh width, was observed to be larger for the foreshores with 2014; Vuik et al., 2016). This study quantifies the range of wave a smaller width. attenuating capacity under different scenarios for salt marsh settings measured in the field over the long-term. Moreover a minimum wave 4. Discussion attenuating capacity was observed from 6% to 12% at the exposed northern shores and 3%–27% at the sheltered southern shores under The decadal persistence of wave-attenuating ecosystems was iden- design conditions (Table 3; Fig. 8). Even wave attenuation under daily tified as key-bottle neck hampering application of intertidal foreshores conditions always benefits from the presence of vegetation by increasing for coastal protection (Bouma et al., 2014). In this study, the decadal the wave attenuating capacity and narrowing the bandwidth of wave attenuating capacity of foreshores under daily and extreme con- incoming waves (i.e. wave height), decreasing the wave load at the dike ditions was studied estuarine-wide. The key-findings were: (1) fore- continuously over 65 years (Fig. 9). shores always contribute to wave attenuation both under daily and Only the existence of the vegetated foreshores over a period of 60–70 design conditions; (2) under daily conditions, vegetation contributes to years, already proves the resilience of those ecosystems to external decreasing wave energy and decreases the variability of incoming wave (anthropogenic) influences. Moreover, the width of the foreshore (parts) 8 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 Fig. 9. Summary of the range of wave attenuation averaged per foreshore and the range of width of the vegetated salt marsh. Spatial mean (white dot) and variability (minimum and maximum indicated by the bar) of the wave attenuating capacity under design conditions (orange), daily conditions with explicitly accounting for vegetation (green) and daily conditions without vegetation (grey) and the related coverage of vegetation relative to the total length of the foreshore (yellow). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) specifically assessed in this study remained quite similar over time study, the location of the seaward marsh edge was based on tidal (Fig. 5). The resulting wave attenuation varied over space (transects) characteristics. However, the marsh edge is determined by multiple bio- and time (development over the assessed period), but delivers a physical processes: it has been hypothesized that the location of the continuous contribution to the wave attenuation (Fig. 9). Nevertheless, marsh edge is driven by both bed level change and inundation period the development of foreshores might be less stable in other estuaries, e. (Bouma et al., 2016; Willemsen et al., 2018). This might lead to a marsh g. rapidly expanding near the mouth of the Yangtze river, China (Yang edge, slightly off MHWN. Moreover, it is assumed that the marsh edge et al., 2001; Zhang et al., 2004), or retreating foreshores affecting the instantly replies to a changing morphology, which is not possible due to contribution to wave attenuation. Results of the current study delivers a time lag between bio-physical feedback mechanisms (Poppema et al., prove and builds upon previous studies emphasizing the instantaneous 2019). However, field measurements on vegetation presence were not contribution of foreshores to coastal protection (Turner et al., 2007; available for all the years. So a general tidal characteristic was assumed, Kirwan et al., 2010; Gedan et al., 2011). Insights in short to similar to previous studies (McKee and Patrick, 1988; Bakker et al., medium-term (days to several years) vegetation establishment and 2002; D’Alpaos et al., 2007; Doody, 2007; Van der Wal et al., 2008). It is growth, defining the marsh edge and partly the wave attenuating ca- expected that this does not or only slightly affect the wave attenuating pacity, have been obtained (Bouma et al., 2016; Willemsen et al., 2018; capacity, since the marsh edge expands or retreats only meters to tens of Poppema et al., 2019). However long-term limits (design period) of meters over a period of a single to a few years (Van der Wal et al., 2008). vegetation growth defining the local range of the width of the vegetated So it might be expected that the relation between vegetation width and foreshore need to be studied, to exploit the relation between the width of wave attenuation becomes even more pronounced when using a more the vegetated foreshore and wave attenuation (Fig. 8). This might result precise location of the marsh edge. eventually in parameter values contributing to stable practical imple- By comparing wave attenuation between scenario 1 (excluding mentation of foreshores as add-on in coastal protection schemes and vegetation) and scenario 2 (explicitly accounting for vegetation), the managing the foreshore to supply, maintain and possibly increase the increasing contribution of vegetation presence was assessed. A clear minimum wave attenuating capacity. bandwidth of the wave attenuating capacity was observed with and without vegetation (Fig. 9). Increasing presence of vegetation resulted in an increased maximum wave attenuating capacity at all assessed fore- 4.2. The location of the marsh edge shores. Moreover, at the northern shores the minimum wave attenuating capacity increased as well, thereby decreasing the uncertainty of the This study highlights the importance of the boundary between the wave attenuating capacity due to the presence of vegetation. The latter, bare tidal flat and vegetated salt marsh, since both foreshore parts have a probably due to the absence of the very short (vegetated) foreshore parts different role in attenuating waves under design conditions. The tidal at the northern shores. The wave attenuating capacity of the short flat causes a baseline wave attenuation, while unique linear relations foreshores occurring at the southern shores, might be less dominated by were found between the marsh width and the wave attenuation. In this 9 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 the presence of vegetation. long-term wave attenuating capacity of the foreshore under a range of hydrodynamic conditions can be studied. 4.3. Wave attenuating capacity of a foreshore profile 4.4. Implications for global application of nature based flood defenses The contribution of the foreshore to water safety is determined by Nature Based Flood Defenses (NBFD) are gaining ground globally the foreshore bathymetry and (state of the) vegetation (Vuik et al., 2018b). However, both bathymetry and vegetation cover are changing (Cheong et al., 2013; Temmerman et al., 2013). Although the area of vegetated foreshores declines (e.g. Valiela et al., 2001), the worldwide over time and space, due to naturally occurring bio-physical dynamics (Bouma et al., 2014). Bed level change and inundation time determine occurrence of both mangroves and salt marshes is large (Giri et al., 2011; the cross-shore location of the marsh edge (Bouma et al., 2014; Wil- Mcowen et al., 2017). A stable vegetated foreshore contributes to coastal lemsen et al., 2018), which can change several hundreds of meters over safety under design conditions. By combining an already existing fore- the assessed period of 60–70 years, but only tens of meters over a period shore with a landward dike, or encourage the growth of a vegetated of multiple years. The long-term change has been observed to change the foreshore in front of an already existing dike, existing infrastructure can wave attenuation of a single foreshore transect. be more efficiently utilized for coastal protection. By combining previ- The cross-shore location of the marsh edge is known to show cyclic ous literature and the knowledge gained in the current study a contri- alternations between landward retreat and seaward expansion (Allen, bution can be made to the design and maintenance of hybrid coastal 2000; Singh Chauhan, 2009). Consequently, implying that the minimum defense structures, which is a next step in implementing NBFD. This and maximum wave attenuating capacity might be found by knowing hybrid coastal protection infrastructure can benefit from the knowledge gained in this study. The protective value of the already present fore- the extremes of the cyclic behavior. However, cyclic alternations have not been observed in this study. Moreover, all foreshores have shore or the needed width of the vegetated foreshore under extreme conditions can be estimated, and with that the increase of the dike location-specific parameters in addition to the width of the vegetated foreshore affecting the wave attenuating capacity. Yet, the width of the height that might be prevented. The natural variability of the marsh salt marsh determines the major part of the wave attenuating capacity width over a specific period (Fig. 6), indicates the long-term stability and takes into account local settings when zooming in on a single and instantaneous (1 year) changes. When using foreshores as coastal foreshore by the steepness of the relation (Fig. 8). defense, the effect of too large long-term variability on wave attenuation Differences in wave attenuation of foreshore transects were observed might be counteracted by maintenance. By using the relation of the between foreshores located at the exposed northern and sheltered range of wave attenuation under different scenarios and the foreshore southern shores (Table 3; Fig. 8). The wave attenuating capacity was width, quantified in the current study, one might estimate the added larger at the exposed shores (Table 3), although the effectivity (i.e. wave value of maintaining a certain foreshore width. However, accommoda- attenuation per meter foreshore) was larger at the sheltered shores tion space, which should not be accounted for in the minimum wave (Fig. 8). This might be explained by the shape of the foreshore profile, attenuating capacity of the foreshore, is needed for instantaneous changes driven by e.g. extreme weather events. Maintaining vegetated which is shorter and consequently steeper at the southern shores. Moreover, geographic features as (maintained) channels and landward foreshores to use their wave attenuating capacity, sustains the dikes are hard boundaries affecting the shape of the profile. The wave ecosystem services provided as well. Moreover, by stimulating the height/water depth - relation under design conditions is larger at the growth and expansion of existing, realigned and new vegetated fore- southern shores, locally resulting in a larger impact of the bottom on the shores, ecosystem services such as habitat provision, food production, wave attenuation, as studied by Maza et al. (2015). Contrasting with the space for recreation and accessibility over water (e.g. Barbier et al., study of Maza et al. (2015), currents were not included, although they 2010) might expand as well. Although the precise relation between might affect wave attenuation over a vegetated area. However, due to vegetated foreshore width and wave attenuation under extreme condi- the geographical boundaries (e.g. dikes, jetties) in the Westerschelde tions is location-specific, this study already gives insights in the band- estuary surrounding the studied foreshores, it was assumed that currents width of this linear relation and thereby an estimate of the value for have a minor influence. To our knowledge, experiments including cur- coastal protection. rents with extremes close to parameter values in the current study (water levels up to 6.71 m at the boundary and 4.47 m at the marsh edge 5. Conclusions and wave heights up to 2.56 m) are not available. Nevertheless, to better understand the long-term wave attenuating capacity of foreshores under Bathymetrical data was analyzed to assess the variability of the ge- extreme conditions it is recommended to study the influence of currents ometry of foreshores. This data was combined with bio-physical pa- on long-term wave attenuating under extreme conditions at different rameters to calculate the wave attenuation at six study sites in the field sites. Westerschelde, the Netherlands, over a period of 60–70 years, which is The foreshore is shaped due to exposure to wind direction, with the longer than the lifetime of hard coastal protection structures. Six fore- southern shores more sheltered to the dominant wind direction (Call- shores were analyzed, three at the northern shores exposed to the pre- aghan et al., 2010), although foreshores at the southern shores are vailing wind direction and three at the southern shores sheltered from exposed to high waves more often (i.e. largest average wave heights) the prevailing wind direction of the estuary. A clear distinction was and are exposed to the longest fetches (Van der Wal et al., 2008). So, the applied to separate the bare tidal flat and vegetated salt marsh, allowing steep and short foreshores at the southern shores sheltered from the to explicitly study the contribution of the vegetated foreshore (i.e. the prevailing wind direction are exposed to the on average largest waves salt marsh). The foreshores were assessed to unravel the key question of and longest fetches, shaping these foreshores. Regardless the vegetated this study: what are the dynamics of foreshores in an estuary over a part of those foreshores are highly effective in attenuating waves, more decadal time-scale and to what extent can foreshores safely act as effective than the northern foreshores exposed to the dominant wind additional defense measures? direction with smaller wave heights, wave height/water depth - relation The total foreshore width at the exposed shores appeared to be and fetch. This implies the existence of a feedback mechanism between longer than at the sheltered shores, resulting in steeper profiles at the hydrodynamics, foreshore shape and wave attenuation. To better un- sheltered shores. In general, the mean value and the temporal variability derstand the feedback between hydrodynamics (currents and waves), of the foreshore width and marsh width remained relatively constant long-term morphology, ecology and wave attenuation on the spatial over time. Although the foreshore width remained relatively constant, scale of a landscape, a process-based 2dh or 3d model can provide in- the width of the salt marsh did not follow the dynamics of the total width sights in the dynamics of the foreshore as a whole. Moreover the of the foreshore at the individual transects. In general, the temporal 10 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 variability of the salt marsh width increased in the first decades, but coastal defense. flattens subsequently, indicating a constant variability of the width over the long-term. The spatial variability of the foreshore geometry was CRediT authorship contribution statement observed to be larger than the temporal variability, implying that a large part of the variability captured in a single observation in time, might Pim W.J.M. Willemsen: Conceptualization, Methodology, Soft- represent the variability of the width of the foreshore (parts) over the ware, Formal analysis, Investigation, Data curation, Writing - original long-term (60–70 years). draft, Writing - review & editing, Visualization, Project administration. The vegetation present at the foreshore decreased the variability of Bas W. Borsje: Conceptualization, Writing - review & editing, Visuali- the wave attenuation under daily conditions, thereby increasing the zation, Supervision, Funding acquisition. Vincent Vuik: Methodology, reliability of the contribution of the foreshore to coastal safety. A Software, Validation, Writing - review & editing. Tjeerd J. Bouma: Data continuous contribution to the coastal safety was found under design curation, Writing - review & editing, Supervision, Funding acquisition. conditions, decreasing the wave load at the landward dike. A clear Suzanne J.M.H. Hulscher: Resources, Writing - review & editing, Su- distinction was observed between the foreshores at the exposed northern pervision, Funding acquisition. and sheltered southern shores of the Westerschelde. The wave attenu- ation at the sheltered shores was larger per meter of salt marsh, despite Acknowledgements the shorter width of both the total foreshore and salt marsh. So the long- term effectiveness of wave attenuation under design conditions (i.e. This work is part of the research program BE SAFE, which is financed wave attenuation per meter of vegetated salt marsh) was observed to be by the Netherlands Organization for Scientific Research (NWO) (grant larger for the foreshores with a smaller width and steeper profile. In 850.13.010). Additional financial support has been provided by Del- general, the tidal flat caused a baseline wave attenuation under all cir- tares, Boskalis, Van Oord, Rijkswaterstaat, World Wildlife Fund, and HZ cumstances, while a linear relation was found between the wave University of Applied Science. Bas W. Borsje was supported by the attenuation and the width of the salt marsh, given a maximum observed Netherlands Organization for Scientific Research (NWO-STW-VENI; marsh length of approximately 1000 m. The longer the vegetated salt 4363). Data and scripts in support of this manuscript are available at marsh, the larger the wave attenuation. The relations found, valid for an https://doi.org/10.4121/uuid:4c25347f-f71e-466b-be3c-1fe8f8d87 entire foreshore, can contribute to designing hybrid structures for 84c. Appendix A Table 3 Marsh width change over a period of a single year, periods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years, for Zuidgors. Zuidgors (ZUI) Median (m) Minimum (m) Maximum (m) 10th percentile (m) 90th percentile (m) 1 year 0 160 120 30 15 1–10 years 0 210 280 65 40 11–20 years 5 225 310 105 100 21–30 years 10 165 365 100 175 31–40 years 25 135 350 84 235 41–50 years 15 160 375 100 230 Table 4 Marsh width change over a period of a single year, periods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years, for Baarland. Baarland (BAA) Median (m) Minimum (m) Maximum (m) 10th percentile (m) 90th percentile (m) 1 year 0 35 295 5 95 1–10 years 5 35 915 5 194 11–20 years 50 20 930 5 715 21–30 years 30 15 945 15 725 31–40 years 40 10 955 20 740 41–50 years 60 20 965 40 800 Table 5 Marsh width change over a period of a single year, periods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years, for Zimmermanpolder. Zimmermanpolder (ZIM) Median (m) Minimum (m) Maximum (m) 10th percentile (m) 90th percentile (m) 1 year 5 55 45 5 10 1–10 years 10 75 105 15 50 11–20 years 45 65 195 5 105 21–30 years 75 25 225 30 160 31–40 years 105 30 265 55 185 41–50 years 130 30 285 65 210 11 P.W.J.M. Willemsen et al. Coastal Engineering 156 (2020) 103628 Table 6 Marsh width change over a period of a single year, periods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years, for Hoofdplaat. Hoofdplaat (HOO) Median (m) Minimum (m) Maximum (m) 10th percentile (m) 90th percentile (m) 1 year 0 25 50 5 15 1–10 years 5 45 90 5 35 11–20 years 20 40 115 15 65 21–30 years 20 45 125 15 80 31–40 years 20 50 125 20 90 41–50 years 33 50 130 25 110 Table 7 Marsh width change over a period of a single year, periods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years, for Paulinapolder. Paulinapolder (PAU) Median (m) Minimum (m) Maximum (m) 10th percentile (m) 90th percentile (m) 1 year 0 100 130 15 25 1–10 years 0 215 215 80 45 11–20 years 10 285 170 135 25 21–30 years 55 305 45 200 10 31–40 years 95 325 20 255 10 41–50 years 115 340 20 260 10 Table 8 Marsh width change over a period of a single year, periods between 1 and 10, 11 and 20, 21 and 30, 31 and 40 and 50 years, for Hellegatpolder. Hellegatpolder (HEL) Median (m) Minimum (m) Maximum (m) 10th percentile (m) 90th percentile (m) 1 year 0 35 65 10 5 1–10 years 0 155 215 35 15 11–20 years 10 160 270 85 10 21–30 years 35 215 115 95 10 31–40 years 45 205 115 125 0 41–50 years 55 205 110 140 15 Table 9 Average width (m) of the marsh and bare tidal flat over the assessed period and all transects per foreshore. Location Average width marsh (m) Average width bare tidal flat (m) Zuidgors (ZUI) 483 634 Baarland (BAA) 152 1977 Zimmermanpolder (ZIM) 205 1253 Hoofdplaat (HOO) 69 275 Paulinapolder (PAU) 258 552 Hellegatpolder (HEL) 125 677 Appendix B Table 10 Coefficients for determining relation between the vegetated marsh width and wave attenuation. The relation can be determined using y ¼ ax þ b, where a and b are linear coefficients, y is the wave attenuation and x is the width of the marsh. Location Coefficient a Coefficient b Zuidgors (ZUI) 0.0273 0.8726 Baarland (BAA) 0.0235 0.9051 Zimmermanpolder (ZIM) 0.0222 1.8731 Hoofdplaat (HOO) 0.1232 1.3113 Paulinapolder (PAU) 0.0453 3.3875 Hellegatpolder (HEL) 0.0643 3.0042 Poppema, D.W., Willemsen, P.W.J.M., de Vries, M.B., Zhu, Z., Borsje, B.W., Hulscher, S.J. References M.H., 2019. Experiment-supported modelling of salt marsh establishment. Ocean Coast Manag. 168, 238–250. https://doi.org/10.1016/j.ocecoaman.2018.10.039. 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