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Figure 2. Figure showing the data sources and outputs of the MI-SAFE tool; data sources and calculations are explained below. Data sources indicated with an * are EO-based products from the FAST project. Hs = significant wave height; ERA-Interim = wave exposure dataset; XBeach = model for wave propagation, long waves and mean flow, sediment transport and morphological changes of the nearshore area, beaches, dunes and backbarrier during storms; GlobCover = global land use maps; CLC (Corine Land Cover) = European land use maps; GEBCO(General Bathymetric Chart of the Oceans) = bathymetry; TFA = ; SRTM(Shuttle Radar Topography Mission) = elevation
Links to methodological videos and public documents:
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Coastal and nearshore topography is important factor determining the risk of flooding and thus features highly in the MI-SAFE application. The elevation of the surface over which the tides and waves travel determines how high the water level and the waves will be when they reach the most landward lying natural or artificial barrier. In addition, the type of surface and type of barrier determines how easily it is altered by tides and waves and how likely it is to suffer erosion. Hard rock coasts that rise up from the sea are less likely to suffer erosoin than soft cliffs or sandy coasts. Topography and sediment stability therefore are very important factors. Several datasets are identified as useful for the characterisation of topography in FAST, these are:Topography is an important element of the risk of flooding and thus in the MI
-SAFE application. Hard rock coasts that rise up from the sea are less vulnerable for flooding than soft sloping sandy coasts. Topography therefore is a very important factor. Several datasets are identified as useful for FAST, these are:- SRTM Topography (http://srtm.usgs.gov/)
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For the global version of the MI-SAFE toolbox viewer a derivative product called SRTM15_plus is used. It offers a continuous global coverage of bathymetry and topography. The SRTM15_plus dataset is created by the Scripps Institution of Oceanography (http://topex.ucsd.edu/index.html). This dataset is mainly used for viewing purposes since it is a continuous dataset at global level. For use in the MI-SAFE application viewer a more detailed dataset is created using the SRTM3 v4 and GEBCO data (see Figure 3, vertical accuracy is about 15 m). The finest resolution of approximately 90 meter is combined where GEBCO is rescaled to 90 meter and interpolated to the SRTM tiles. To reduce computation time this is done for tiles along the OSM shoreline of the coast.
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Precise elevation of the intertidal (foreshore) is crucial in the performance of the MI-SAFE toolviewer, because this is the area where the actual wave attenuation takes place.
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Intertidal vegetation is derived from the CLC class Salt marshes (421): areas submerged by high tides where vegetation dominates. The cover of such marshes can vary considerably between locations and throughout the year (Figure 14). For example, Spartina spp stands can well be 70 cm high during summer, whereas Salicornia spp. can be nearly absent in winter. The properties as observed by Möller et al (2014) were selected as representative, because they are for a mixed marsh typical for North-Western Europe and because they were measured with wave attenuation studies in mind rather than just observing biomass. Moreover, the drag coefficient of that particular vegetation cover has been derived from large-scale flume experiments under (near) real world wave conditions.
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Reed beds are of interest for inland locations such as lakes that are often fringed by reed beds, and for the Romanian study sites of FAST where large reeds grow in coastal lagoons. The CLC map does not account for reed beds as such, but are based on class 411 Inland marsh. As a result, the MI-SAFE tool viewer will apply reed bed properties to every inland marsh, also the ones predominantly made up of lower shrubs, and might overestimate the wave attenuation capacity of such marshes.
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The composition, and consequently tree size, of riparian forests differs considerably among floodplains but willows are very common in European floodplains. The age and size of willows depends strongly on the management of floodplains: in natural rivers they are older and taller than along strictly managed rivers, where they can be cut regularly to prevent flooding as a result of the additional hydraulic resistance they cause. Such managed areas are more likely to be of interest, and the MI-SAFE tool viewer should not overestimate the wave attenuating effect. Therefore, the willow dimensions are chosen to be representative of relatively young, regularly trimmed trees. Data are available from sites in the Netherlands: commonly found regularly cut pollard willows (‘knotwilgen’) of several years old and young willows (less than 1 year old) of a field especially planted for wave attenuation in front of a levee near Fort Steurgat, Werkendam (Figure 16).
Like willows, the tree size and density in mangrove forests varies substantially among forests, depending on species composition and age of the forest. For the MI-SAFE toolviewer, the properties of the trees occurring at the seaward side (regular inundation, high salinity) of the mangrove forest are the most relevant because this is where most of the wave attenuation takes place. Moreover, further inland, the forest likely becomes more heterogeneous and mixed with terrestrial species. The two globally representative species for this zone are the red mangrove (Rhizophora spp.), which is characterized by prop roots (Figure 16d), and the black mangrove (Avicennia spp.), which is characterized by pneumatophores (Figure 16e). As deducing the type and size of mangrove trees from EO data is not (yet) possible, the MI-SAFE tool viewer relies on literature observations of dimensions of these two species, as summarized by Janssen (2016). To avoid overestimation of wave attenuation in young or very cyclic mangrove forests, the mangrove dimensions are chosen to be representative of young, pioneering mangroves up to 3 m tall.
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The global methods to derive vegetation information give a broad overview of whether there is vegetation and the type of vegetation. However, with each of these types, the characteristics can vary spatially and temporally. To incorporate these variations into the MI-SAFE toolviewer, EO-based maps of the biophysical characteristics of the vegetation were created in different seasons and are visible in the data layers of the tool.
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A core biophysical variable for the MI-SAFE viewer is Leaf Area Index of the marsh. Leaf Area Index refers to green leaf area per unit ground area. It is derived from Sentinel-2 MSI level 2B biophysical products. The algorithm for Leaf Area Index implemented in such level 2 products is based on a neural network approach, trained on a database of vegetation characteristics and associated Sentinel-2 top of canopy reflectances. The product as implemented in the MI-SAFE viewer refers to Leaf Area Index of the marsh only (where marsh is defined for NDVI>0.3). Areas outside the saltmarsh, either subtidal area or emerged tidal flat are set to 0, and land is masked. The maps can be produced for any vegetated foreshore, but in the MI-SAFE viewer, layers refer to the case study sites. See Figure 17 for examples for FAST case study sites in the Netherlands (Paulina) and Romania (Jurilovca) and Figure 18 for an example of seasonal variation of the marsh at Tillingham (UK).
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MI-SAFE tool services
The MI-SAFE tool viewer provides two main services on a global level:
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MI-SAFE provides detailed information (10-20 m resolution) for FAST case study sites (Expert version). For other foreshore areas in the world the MI-SAFE viewer reverts to the global datasets mentioned above under 'MI-SAFE data' (Educational).
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In order to quantify wave attenuation by vegetation for a given salt marsh or mangrove coastline, the MI-SAFE viewer uses the numerical modeling software XBeach (van Rooijen et al., 2016). Xbeach is a depth-averaged, two-dimensional process-based model that solves the time dependent short wave action balance for the entire wave group, suitable for simulating wave attenuation over foreshores. XBeach has three wave energy dissipation processes relevant for MI-SAFE simulations: dissipation due to (depth-induced) wave breaking, dissipation due to bottom friction and dissipation due to vegetation. XBeach also has three simulation modes, from simple to advanced: stationary, surfbeat and non-hydrostatic. The stationary mode is fast but lacks wave groups (surfbeat) that are important for wave height variations near shore. The non-hydrostatic mode is physically the most complete but at substantial computational cost. The surfbeat mode does represent the effects of wave groups at reasonable computational cost and represents the effects of vegetation via the well known relations of Mendez & Losada (2004), and is therefore selected as the most useful mode for this application.
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In the table below (Table 4) it is shown how the different vegetation types are characterised in XBeach input parameters. Note that these basic assumptions are used if only global information is available in the Educational version of the tool viewer at present. In the Expert version, the local EO data are used to derive vegetation properties.
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For the Educational version, XBeach was used to generate a lookup table of attenuated wave heights for a range of possibly occurring combinations of nearshore waves and water levels, foreshore slopes and -widhts and vegetation types. The MI-SAFE tool viewer searches this table using the conditions at the selected site as input, resulting in a reduced wave height at the end of the vegetation where the levee is supposed to be. Subsequently, this reduced wave height is used to calculate a reduction in required crest height of the supposed standard levee, in comparison with a bare foreshore under the same forcing.
For the Expert version of the MI-SAFE toolviewer, a number (typically 6) of ~ 2 km long transects has been defined at each study site, running from the nearshore to the position of the levee estimated from EO images. At some sites (NL, UK) the foot of the levee can be clearly distinguished, on other FAST field sites (RO, ES) the relevant end of a transect is more difficult to define. For all transects, dedicated site-specific XBeach simulations have been performed using the local bed level, hydraulic boundary conditions and vegetation cover. Just like in the Educational version, this results in the attenuated wave height at the foot of the levee that is used to calculate the required crest height, but with much greater precision because the actual situation is simulated rather than a substantial simplification.
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Given the lack of information on global levee properties, the calculations of required crest height in the MI-SAFE viewer are based on the (conservative) assumption that most levees have a basic configuration of a 1:3 outer slope without a berm and without substantial roughness or crest elements. For the design parameters at the toe of the levee, MI-SAFE calculates the wave height and water level (Figure 21) for the actual situations and a situation with an unvegetated foreshore. Subsequently, the MI-SAFE viewer uses these design parameters to compute the required crest height (relative to the still water level h) for both situations.
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Not yet mentioned is the back end of the dissemination platform which plays an important role in the data management of FAST. Figure 22 is a schematic representation of the MI-SAFE tool viewerl architecture. The base of the architecture is represented by a version control system based on subversion.
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Figure 22. Schematic representation of MI-SAFE tool viewer architecture.
Subversion is used to store raw data, tools and imagery. Raw data and imagery can be placed in the storage layer whether or not after processing. The communication layer is middle-ware that converts data from the storage layer to web services, OGC WMS, OGC WCS, OGC WFS and OGC CAT ready to be disseminated via the viewer.
The MI-SAFE tool viewer consists of several components, already mentioned above. The pictures below, Figures 23 and give a good overview of the MI-SAFE interface and infrastructure.
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Figure 23. Screen shot of the MI-SAFE tool viewer interface, 'Data' page. 1 = map canvas, 2 = layer selection, 3 = shortcuts to data from the FAST study sites, 4= search bar to navigate for a place of interest, 5 = zoom buttons, the + sign enables toggling between several background layers, 6 = quick access to metadata of the layer selected. Selected layers become green. Hovering over the link displays the abstract of the layer, 7 = legend of the last layer toggled on, switch between legends on toggled layers can be done by clicking on the legend icon on the right of the layer name, 7 = short cuts to FAST project Facebook and Twitter pages.
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Figure 24. Screen shot of the MI-SAFE tool viewer interface, 'Results' page. 9 = MI-SAFE tool result showing several tabs: conditions --> physical condition on the study site or any particular place on the world (in the latter case resolution of the conditions visualised is less then for the study sites), confidence --> displays the quality of the information in terms of confidence, context --> gives context to the information displayed, sensitivity --> model result, 10 = Shortcuts to several sub pages where detailed information can be found, 11 = presentation screen indicating the effect of vegetation to wave attention (short version of the the outcomes of the tool results), 12 = project information.
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The results part enables users to draw a profile of the coast. When a user queries a location in the MI-SAFE tool viewer combines data from four parameters to assess the effect of the foreshore on wave attenuation:
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4) The local vegetation type and cover.
The MI-SAFE tool viewer enables via WPS data retrieval over the profile via OGC services. To acquire these data for a queried location (point), the tool first determines a transect perpendicular to the nearest coastline. This transect runs 1000 m inland of MSL and 1000 m seaward; the area of interest where most wave attenuation occurs. This data is then used to query a pre calculated table of model results. The wave attenuation thus obtained is compared to the wave attenuation over a similar but bare transect. The result is shown indicating whether or not vegetation is existent and or contributes to wave attenuation.
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