Die Kuste, 81 (2014), 369-392 
378 
4 Functional seabed model 
The term “Functional Seabed Model (FSM)” is introduced to describe a database for 
morphodynamic analyzes which include data-based models of annual bathymetries and 
sediment properties for any location and time within die study site. Moreover, die FSM 
also depicts the temporal evolution of the seabed. The two-dimensional models of die 
annual badiymetries and sediment properties were generated by appropriate interpolation 
and approximation methods (MlLBRADT 2011). 
At present, die FSM provides information on: 
• topography (batiiymetry), 
• thickness of die mobile sediment layer, 
• porosity, 
• grain size distribution, 
• organic matter content, 
• resistance of consolidated sediments and 
• bedforms. 
Firstly, the Functional Seabed Model consists of a time-invariant model (so-called ‘Ъаск- 
ground layer”) which comes into operation for interpolation or approximation when sur 
vey data are missing for a specific site. The topographic background layer includes die 
model grid of BAW for die North Sea and summarizes bathymetric data up to 1989. The 
background layer of die sediment diickness dates back to 1985 and has been estimated, 
via the depth of erosion between the years 1985 and 2009, to be at least 1 m. Porosity was 
set to 25 %, organic matter to 5 %. The FSM suggests that consolidated sediment under 
lies die mobile sand cover which itself cannot be mobilized. 
Cumulative grain size distributions are typically used in die FSM. A representative 
distribution of d50 (median) based on the combination of grain size data from BSF1 and 
model runs was modelled for the background layer. This resulted in a consistent d50 
layer, especially in the estuaries and in die tidal flats for which grab samples are not avail 
able in a sufficient spatial resolution. 
Secondly, die FSM embodies a time-variant module which was developed using a 
multi database system. It produces annual digital terrain models (Fig. 5) to provide die 
user with quasi-synoptic topographies from die coastline down to a water depth of app. 
20 m. Moreover, each annual batiiymetry is linked witii layers for spatial uncertainty, e.g. 
spatial confidence (Fig. 6) and minimum distance with respect to die dataset in time.