Nature Based Solutions - Digital Twin scenario data

Overview Data Description This dataset contains analysis data derived from scenario simulations of Nature-based Solutions (NbS) for coastal risk mitigation, developed within the framework of the European Digital Twin Ocean (EDTO, European Digital Twin Ocean - Powered by EDITO - EDITO) project—specifically under Work Package 7. The dataset includes regional coastal GeoTIFF files for two study areas: the German Bight and the Ghanaian coast. These files can be interactively explored via the related EDITO platform application (Datalab EDITO). Simulation Setup Underlying simulations were conducted using a coupled modeling approach integrating the hydrodynamic model SCHISM (https://doi.org/10.1016/j.ocemod.2016.05.002), the wave model WWM, the sediment transport model SED3D and a vegetation module that accouns for the effect of vegetation on hydro and wave dynamics, all coupled within the SCHISM framework(ccrm.vims.edu/schismweb/). The used grid configuration for the two studies areas are as follows: German Bight: The grid setup follows Jacob et al. (2023) [DOI: 10.1007/s10236-023-01577-5]. The model area consists of 476 k nodes and 932 k triangular and quadrangular elements, with the horizontal resolution, varying between a maximum of 1.5 km at the open boundary and a minimum of 50 m in the estuaries. The vertical dimension is resolved using 21 terrain-following sigma coordinates. Ghana: The model grid consists of 256,462 elements and 29,713 nodes, with spatial resolution ranging from 50 meters (finest nearshore elements) to 5 kilometers (coarsest open boundary elements). Bathymetry data were sourced from EMODnet. The vertical discretization uses the flexible LSC² vertical coordinate system with up to 63 layers in deep areas and an average of 12 layers across the domain. Vegetation Scenarios Three parameters were varied across 3x3 scenarios in addition to vegetation less reference scenario (Veg_CNTRL): Vegetation density Table 1: Vegetation density in scenario experiments Density German Bight Ghana Low density 450 seagrass stems/m² 0.25 mangroves/m² Medium density 1,530 seagrass stems/m² 0.5 mangroves/m² High density 7,360 seagrass stems/m² 1.0 mangroves/m² Vertical distribution zones, defined as: Lower zone: [1 m, –3 m] Middle zone: [2 m, –2 m] Upper zone: [3 m, –1 m] wit respect to still water level. Data Analysis Simulations were analyzed by quantifying the 95th percentile temporal profiles of key hydrodynamic variables during: January 2022 for Ghana October 2017 for the German Bight Variables analyzed include: Significant wave height (Hs) Bottom stress Bottom-layer suspended particulate matter (SPM) concentration In addition, a simplified erosion risk estimate was derived based on sediment class composition and critical shear stress time exceedance ratio relative to simulation period, categorized into four bins: Table 2: Risk levels Bin Percentage Risk Level 0 0% No risk 1 25% Low risk 2 50% Increased risk 3 >70% High risk Provided Data The scenario based analysis data is provided for a coastal subset area corrseponding to the following domain boundaries: Spatial Bounding Boxes of GeoTIFF Data Table 3: Data extent Setup Longitude min Longitude max Latitude min Latitude max German Bight 6.5° E 8.1° E 53.35° N 53.8° N Ghana 0.1° W 0.8° E 1.25° N 5.9° N File and Folder Structure Each vegetation scenario is stored in a dedicated folder named according to the scenario’s characteristics, for example: GB_lower_position_high_density GH_upper_position_medium_density Each folder contains cloud-optimized GeoTIFF outputs representing simulation results, such as: File Example Description GB_lower_position_high_density_bottomStress_reduction_cog.tif Absolute reduction in 95th percentile bottom stress (Pa) GB_lower_position_high_density_sigWaveHeight_reduction_cog.tif Absolute reduction in significant wave height (m) GB_lower_position_high_density_totalSuspendedLoad_reduction_cog.tif Absolute reduction in bottom layer suspended particulate matter GB_lower_position_high_density_CriticalBottomStressRatioBin_cog.tif Erosion risk classification in four bins (0–3) GB_lower_position_high_density_CriticalBottomStressRatioBinChange2Reference_cog.tif Change in erosion risk bin relative to reference scenario Reference Scenario The reference scenario (without vegetation) erosion risk map is provided as: Veg_CNTRL_CriticalBottomStressRatioBin_cog.tif