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Introduction

The MI-SAFE software and webviewer are developed under the EU funded FP7 project FAST (Foreshore Assessment using Space Technology). The MI-Safe viewer depicts the estimated contribution of coastal vegetation to wave height attenuation for user-selected coastal locations anywhere in the world. MI-SAFE is thus based on global datasets made available via open spatial services and presented in the web-viewer. The data from these global datasets are used to query the results of a modelling exercise conducted with XBeach for a range of different types of vegetated foreshores and a range of exposure to waves and tides. The results can be used to assess the requirements for the design of coastal flood protection measures with and without vegetation fronting those measures; they give a first estimate of the potential risk reduction that coastal vegetation has to offer with respect to specific coastal flood events on any particular shore across the world. 

For background information about the tool, the project and all the partners involved, please visit our website - http://www.fast-space-project.eu/

MI-SAFE data

Elevation

Global SRTM coupled with GEBCO

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/)

-       GEBCO Bathymetry (http://www.gebco.net/data_and_products/gridded_bathymetry_data/)

-       ASTER (http://asterweb.jpl.nasa.gov/gdem.asp)

For the global version of the MI-SAFE toolbox 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 a more detailed dataset is created using the SRTM3 v4 and GEBCO data. 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.

Correction with vegetation  (why, how and where with links to deliverables/products) (Arjen Haag)

Method using water levels  (why, how and where with links to deliverables/products) (Ed)

• SRTMplus 15

Waves

Field measurements 

To acquire the results of the modelling exercise conducted with XBeach for a range of different types of vegetated foreshores and a range of exposure to waves and tides, the XBeach model was validated and calibrated against detailed water level data recorded using high frequency (4 Hz) dynamic water pressure measurements to resolve even small (2 Hz frequency) waves through the use of bed-mounted pressure sensors at a series of eight vegetated foreshores in Europe, ranging from reed beds in Romania (outer Danube Delta) to Sarcocornia salt marsh (Bay of Cadiz), and NW European estuarine and open coast salt marsh (The Netherlands and United Kingdom respectively). Data recording took place with a telemetered data logging system that captured waves and water levels during almost every inundation of the vegetated foreshores from early autumn to late spring over one year. The Romanian field sites Jurilovca (Razelm) and Histria (Sinoe) experienced continuous inundation, albeit with varying water levels, such that data acquisition at these sites varied from that at the United Kingdom, Netherlands, and Spanish sites with wave records triggered every 8 hours (three times per day). Water pressure records acquired in this way were processed into water depths, wave spectra, and summary wave statistics by the University of Cambridge, using tried and tested programming routines (Möller et al. 1996).

Data and metadata for all the calibration sites of the FAST project is available at: …..

Era interim, translated to nearshore depth limited waves  (why, how and where with links to deliverables/products) (Kees)

• era interim wave return periods

Wave data for return periods (T_r) of 1, 10 and 50 years are extracted from the ERA-interim dataset. Waves are generally lower in the tropics (e.g. less than 2 m between -30° to + 30°) than in temperate zones (where H_s>5m between 40°-70°). A table with worldwide mean and median values of H_S and T_p, extracted from the ERA-interim dataset for return periods of 1, 10 and 50 years is given below:

The picture below gives a global view of wave heights for a return period of 1 year.

As the ERA-Interim wave data is based on offshore characteristics, waves are translated to onshore conditions by comparing the waves from ERA-Interim with a depth limited wave. If the depth limited wave height is smaller, this wave height is used for calculations whereas the period is maintained. The wave direction is not taken into account explicitly; the wave direction is assumed to be coast-normal, as it would be during a worst-case-scenario storm, for which an assessment of the protection function of the foreshore is likely to be most important. 

Water levels 

Wave attenuation over foreshores is typically most relevant during storm conditions that create a surge (water level set-up) in combination with high tidal levels. For the MI-Safe tool, a water level that has a probability of occurrence of 10%, i.e. once in 10 years, is considered to be the most relevant: This represents a storm that is both frequent enough to be relevant to users’ needs for planning coastal protection (a 1/100 or 1/1000 year condition may seem too extreme) and severe enough to be a serious threat to coastal regions. The representative water levels or hydraulic boundary conditions are derived from a global D-Flow Flexible Mesh model (Muis et al., 2016) that includes tides, storms and hurricanes. The output of this model is mapped to DIVA segments, so local anomalies can occur for coasts with irregular shapes (bays, estuaries). More extreme or locally tailored conditions can be studied using the more advanced versions of the MI-SAFE tool, which can take into account hydraulic boundary conditions that are specified by users -e.g. in local coastal management guidelines- or derived from dedicated modelling or field observations at the relevant location.

Vegetation

Field data  

To acquire the results of the modelling exercise conducted with XBeach for a range of different types of vegetated foreshores (and a range of exposure to waves and tides), detailed information was obtained on the vegetation of all the vegetated foreshores at which the XBeach model was tested (see above). For each of the eight sites (two each in Romania, Spain, The Netherlands, and the UK), vegetation species richness, percentage cover, and height was recorded seasonally in 1 x 1 m² survey plots over a period of one year. In addition, a ‘photoframe’ was used to  capture the density of the vegetation layer as seen from the side (and as experienced by water flowing over the surface). The vegetation photographed in this way also harvested (an area of 20 cm x 60 cm) to determine its biomass and, where appropriate (grass species), the number of stems per unit surface area. At the Romanian sites, tall reed was present and a sub-sample of stems was harvested from each survey location instead of using the photo frame area for harvesting.

Data and metadata for all the calibration sites in the FAST project is available at:……

Earth Observation products of vegetation  

We provide the following vegetation products derived from Earth Observation: vegetation presence/absence (a global product), vegetation type (a product on European scale), and biophysical characteristics of the vegetation (examples for the case study sites).

The latter include NDVI, the normalised difference vegetation index, of both the saltmarsh and the adjacent mudflat and waters. Values range from -1 to 1. On the saltmarsh, higher values indicate larger biomass, density and health of the saltmarsh, and different vegetation types. On the mudflat, higher values indicate higher biomass of microphytobenthos biomass, higher biomass, density and health or different types of macroalgae and seagrass. Negative values typically indicate water. Below are examples for NDVI derived from atmospherically corrected Sentinel-2 MSI images at case study sites in the Netherlands (Paulina) and Romania (Jurilovca). In these products, land is masked. Spatial resolution of the product is 10 m.

A core biophysical variable for MI-SAFE is Leaf Area Index of the marsh, derived from Sentinel-2 MSI level 2 products. The product as implemented here refers to Leaf Area Index (i.e., green leaf area per unit ground area) of the marsh only. Areas outside the saltmarsh, either subtidal area or emerged tidal flat are set to 0, and land is masked. Below are examples for Leaf Area Index of the marsh at case study sites in the Netherlands (Paulina) and Romania (Jurilovca). Spatial resolution of the product is 10m. In MI-SAFE, Leaf Area Index of the marsh is used to calculate wave attenuation on the marsh.

Yes/no vegetation map  (why, how and where with links to deliverables/products) (Josh/Ebi)

• global landcover
• global distribution of mangroves

MI-SAFE services

MI-Safe provides ....for case study sites. For other foreshore areas in the world MI-Safe reverts to ....

Casting a transect in MI-SAFE

When a user queries a location in the MI-SAFE tool combines data from four parameters to assess the effect of the foreshore on wave attenuation (See Figure Below):

1)      The local (sea)bed level;

2)      The local water level, including tides and storm surge;

3)      The local wave conditions;

4)      The local vegetation type and cover.

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. If relevant vegetation is encountered along this transect, the upper indicator on the left of the screen turns green; if not, red. The properties encountered along this transect are used to find the nearest match in a table that contains wave attenuation results for many thousands of combinations of conditions. The wave attenuation thus obtained is compared to the wave attenuation over a similar but bare transect. If the difference is considerable, i.e. more than the average in this dataset, the lower green indicator turns green too. If the difference is small, the lower indicator displays a red cross.

Surge levels used for the MI-SAFE Expert tool 

For the Expert version of the MI-Safe tool, locally derived hydraulic boundary conditions have been used wherever available (NL and UK sites) to have the closest resemblance with actual flood defense design conditions. Elsewhere, the same global D-Flow Flexible Mesh model (Muis et al., 2016) as used for the Educational version is used to derive representative water levels, but for a return period of 1/100 years instead of 1/10 years because the former is closer to realistic design values. For more advanced studies using MI-Safe, it is possible to derive localized hydraulic boundary conditions via a combination of hydraulic modelling and historical analysis in case these conditions are not known.

Wave conditions used for the MI-SAFE Expert tool (Iris/Kees, perhaps you can still use some of text below?)

For waves, a similar reasoning as for surge was followed, leading to the selection of a 1 in 10 year wave height and period. These representative waves are derived from the ERA-interim 40-year reanalysis (ECWMF, 2014).

Schematisation of vegetation types for the MI-SAFE Expert tool (Iris, perhaps you can still use some of text below?).

The MI-SAFE tool needs to function without (yet) having the detailed vegetation properties that are to be determined from EO data. Therefore, where possible, vegetation types are derived from existing maps such as the Corine Land Cover (CLC) 2012 and Globcover maps and the characteristics of these vegetation types are based on published data, including that derived from the FAST project calibration sites. End-users wishing to improve on the model calibration / drag that we have developed in the FAST project, should contact their respective country partner (who could then contact UCam if needed) to discuss implementation of wave measurements at their field site to allow special calibration of the MI-SAFE tool for their specific site.

General approach (move this to wave model/ XBeach part?)

XBeach requires four parameters to represent the presence of vegetation:

1)      Length or height h (m);

2)      width or diameter d (m);

3)      number of stems per horizontal area n (m^-2);

4)      drag coeffient C_D (-).

Additionally, these can be varied over any number of layers over the vertical to represent plants with a complex morphology (van Rooijen et al. 2016). Worth noticing is that from these parameters, XBeach calculates a ‘vegetation factor’ that is a multiplication of diameter, number and C_d. As a consequence, 200 stems of 1 mm diameter have the same effect as 100 stems of 2 mm diameter.

For deriving representative properties, three principles were followed:

1)      The vegetation factor should be relatively conservative, so as not to give an overly optimistic estimate of wave attenuation. Thus, plant dimensions are chosen with winter conditions and relatively small individuals in mind. The choice of the drag coefficient beforehand is troublesome, because this not only depends on the plant properties but also on the hydrodynamic conditions. Therefore, a relatively conservative estimate is made with large waves (that give large Reynolds/Keulegan-Carpenter numbers that are associated with low drag coefficient values) and the flexibility of the vegetation in mind. This will be refined once more reliable drag coefficient estimators are available, e.g. based on observations from the FAST field sites.

2)      The vegetation factor should be representative for all occurrences of a particular type across Europe, not for a specific site.

3)      The vegetation factor should be large enough and differ enough between vegetation types to meaningfully differentiate the effects of different vegetation covers from each other.

Note that these basic assumptions are used if only global information is available in the Educational version of the tool at present. In the Expert version, the local EO data will be used to derive vegetation properties.

Intertidal vegetation (salt marshes)

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. 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 (Table 1), 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.

Inland marsh (reed beds)

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 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.

For the moment, the properties of the reed beds at the Romanian sites (Table 1) have been used because these are readily available and because they represent the situation at the study site, which enables a comparison with local observations of wave attenuation. It should be noted that these are possibly taller reeds than usually found along lake banks.

Riparian willow forests (broadleaved forest)

All areas classified by CLC as ‘broad leaved deciduous forests’ (class 311) are considered to be willow forests if they are located in Europe, where no mangroves occur. The CLC class also contains many forests far from any large water body, but these are not relevant as they will not be queried by users of the MI-Safe tool. Forests hardly occur directly adjacent to the coastline, and if they do they are usually coniferous so they will not lead to a false positive identification as willow forest. As a consequence, riparian forests are the most likely forests to be identified in this class.

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 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. 

The wave model: XBeach (Jasper, done)

In order to quantify wave attenuation by vegetation for a given salt marsh or mangrove coastline, MI-Safe 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.

The example in Figure XX below shows the importance of these processes on the FAST Tillingham (UK) field site, in combination with observations at this site as studied for FAST Deliverable 5.4 ('Prototype linkage of general rules for engineering requirements of dike design'). The thick black line indicates the bed level along a coast-normal transect, the thick green line the different vegetation covers observed. The thin black line represents the wave height change over the transect without bed friction or vegetation presence, i.e. purely depth-induced breaking. The thin blue, red and green lines represent wave height change in the presence of vegetation, for a range of vegetation drag coefficients. The dashed blue line represents wave height change in case of high bed friction due to very irregular small-scale bed topography (ridges and swales < 1m). Under these mild conditions (small waves, relatively low water depth), the attenuation by bed forms at the marsh edge dominates wave attenuation whereas under more extreme conditions (higher waves, deeper water) the attenuation by vegetation over the marsh plain will become more important.

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 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 MI-Safe, a number (typically 6) of ~ 2km 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 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.

The viewer (Gerrit, Amrit, Arjen, Ed, perhaps you can still use some of this text below?)

The viewer is build up of 3 main parts; the canvas where the maps are shown, the data part where a selection of layers can be toggled on or of and the results. The results part enables users to draw a profile of the coast. Via OGC services (a WPS in this case) data is extracted over the profile. This data is then classified for certain characteristics, such as elevation, water levels, wave charateristics and vegetation presence and type. This data is then used to query the table of model results. The result is shown  indicating whether or not vegetation is existent and or contributes to wave attenuation. 

The case study sites

United Kingdom 

Tillingham: This field site is a macro-tidal (Mean spring tidal range of ca 4.8 m) open coast or outher estuarine salt marsh of the UK east coast (Southern North Sea) on the Dengie Peninsula in Essex. The estuaries of the Rivers Blackwater and Crouch lie to the north and south of the peninsula. The exposed marshes of this peninsula extend up to a maximum width of ca 700 m and are fronted by extensive intertidal mudflats, with an earthen embankment landward of them and low lying agricultural land behind this defence. Over the past 100 – 150 years the marshes have experienced several phases of advance and retreat. Marsh surfaces are composed of clayey silts and are approximately horizontal, with elevations of between 2.4 – 2.7 m ODN (Ordnance Datum Newlyn, which approximates to mean sea level). The Dengie Peninsula currently experiences rates of sea level rise of approximately 2 - 3 mm a^-1 (Burningham and French 2011). The vegetation here is typical of UK east coast salt marsh with Aster tripolium, S. anglica, Suaeda maritima and Salicornia europaea present in the seaward areas. Higher up and further landwards, a canopy of P. maritima and A. portulacoides with E. athericus occurring on levees along creek margins is present. These species form mixed canopies but also exist in distinct mono-specific patches of several square metres in size, such that approximately uniform vegetation types can be found in close proximity to each other. Offshore wave heights have been estimated as averaging 1.09 m (on Long Sand Head, 42 km NE of Tillingham), with wave heights larger in winter (January), when mean monthly maxima reach 1.45 – 1.70 m (Herman 1999).

Donna Nook: This site lies to the immediate south of the Humber Estuary on the East coast of the UK. It comprises a foreshore that consists of mixed clays, silts, and mud deposits and is occupied by a salt marsh in the upper regions. The marshes here extend out to a width of ca 750m, with high exposure to winds from the north-east. The tidal range is 8.1m at Immingham, providing water depths above the marsh surface at highest astronomical tide of between 0.9 and 1.4m. Vegetation here consists of mixed north-western European salt marsh species (Atriplex, Puccinnellia, Elymus, Aster, Salicornia, and others). The marshes are flanked by extensive (> 1000m wide) tidal flats to seaward and dunes and/or earth embankments on their landward margin. Evidence suggests a marsh progradation rate of 1-1.5m per year over at least the past 5-10 years, through sediment derived from updrift (the Humber estuary and further north). Landward of the salt marsh for which data for FAST was obtained lies a recent managed realignment site (regulated tidal exchange through a breach in the most seaward embankment to create natural habitat to landward).

The Netherlands 

The Westerschelde estuary is located in the southwest of the Netherlands. The Westerschelde has a macrotidal regime; discharge is relatively low compared to the tidal prism of the estuary. Wind-driven waves are particularly important at the mouth, where fetch is longer. The Westerschelde has a salinity gradient from saline at the mouth near Vlissingen, to brackish at the Belgian border. The bed material typically consists of sandy sediments, but particularly the foreshores fringing the estuary tend to be muddier. The estuary is affected by human impact, such as dredging to facilitate navigation to the ports of Vlissingen, Terneuzen and Antwerp. The Westerschelde also has a high ecological value, particularly due to its multi-channel system surrounding tidal flats and shoals, that accommodate a rich benthic community, providing food to birds and (flat)fish. At the higher parts of these tidal flats, saltmarshes can develop, consisting of Spartina spp in the more saline parts to Phragmites spp. in the brackish areas. We focused on two case study sites, one sheltered saltmarsh (Paulinapolder), dominated by Spartina spp. and one wave-exposed eroding saltmarsh site (Zuidgors), consisting particularly of Elymus spp. and Atriplex spp.

Spain (Gloria)

Could you include some background information on the case study areas, i.e. a short description of the vegetation, natural wave climate, extreme conditions and any other relevant information? A starting point would be the case study descriptions in the DoW, but they do need to be updated.

Romania 

Razelm-Sinoe Lagoon System is included in the Danube Delta, that is the final part of the Danube River. The average annual precipitation in the Razelm - Sinoe Lagoon is 350-400 mm/year, with a large evaporation which should lead to the raising of the ground water, saturated by chlorides and sulphates, and, consequently, to humid soils salinization.

The climate of the Lagoon System is continental, with hot dry summers and very cold winters. The water bodies from the lagoon system happen to be partly or entirely frozen during winter, with frizzing periods varying from days to week. Complete ice cover for long periods, however, is rare. The Lagoon System is located in one of the windiest areas in Romania.

During the past century, the system has been subject to major changes due to human interventions. These changes resulted into a complete change of the Lagoon specific ecosystems compared to its pristine state. Throughout a series of hydro-technical interventions, the Lagoon System has been transformed into a fresh water reservoir, to be used for agriculture and fresh water aquaculture, considered at that time much more viable economically.

The planned functioning regime of this hydrotechnic system was:

-                      between April 1 - June 1, water accumulates up to the level of +80cm;

-                      from June 1 to August 15, level maintained at +80 cm;

-                      between August 15 and September 15, the level - descended between +30 +50 cm to ease the fishing (fishing continues until October 30);

-                      between November 1 and March 30, the level of retention - maintained at +50cm (to “protect” the northern compartment from the brackish waters of Sinoe Lagoon).

All these hydrotechnical interventions have automatically led to drastic changes of the hydrological, hydrochemical and biological conditions of these lacustrine and lagoon ecosystems.

Variations of the maximum and minimum water level regime

The hydrologic regime of the lagoon system is characterized by two specific elements, namely:

-       a seasonal variation related to the seasonal variation of the Danube River regime (via the water regime of the Sf. Gheorghe branch)

-       a variation related to the changes in the wind direction and intensity. The wind plays a major role in the water and sediments circulation between the parts of the lagoon system but also in the exchange at the remaining inlets (Edighiol and Periboina).

The highest frequency of strong winds is from N and NE – and under these conditions large water masses are circulated from the north of Razelm to the south, which determines an increase of the levels at Jurilovca or Canal 5 and a level decrease at Sarichioi or Sarinasuf.

Quantitative descriptors and their respective indicators for presenting hydrological status of the Razelm - Sinoe  lagoon.