Grid-based global coastal zone datasets for coastal impact analysis

Global coastal impact and adaptation analysis in the context of climate change induced sea-level rise needs precise and standardized datasets. Here, such datasets and their construction are presented. Starting from a high-resolution global digital elevation model, the coastline is extracted with taking into account river mouths and lagoons taken from a global surface water dataset. The global low-elevation coastal zone (LECZ) is derived by determining all grid cells hydrological connected to the coastline. Recent surge-data is combined with sea-level rise scenarios to partition the global LECZ into local floodplains. Latest socio-economic and land-use data is used to partition and classify these local floodplains. As local impacts and adaptation responses are not spatially uniform, but depend on a range of conditions including: i) biophysical conditions such as natural boundaries between floodplains (e.g. hills, rocks, etc.) and coastal geomorphology (e.g. sandy versus rocky shores), ii) technical conditions such as existing flood protection infrastructure (e.g. dike rings in the Netherlands), and ii) socio-economic conditions such as administrative boundaries, land use and urban extent (e.g. rural versus urban areas), latest land-use, beach and wetland datasets are used to partition the coastline of each floodplain into a network of coastline segments which can be used for assessing local shoreline management options.

The generated datasets contain about 1.6 million km of coastline distributed over 87,600 islands. The LECZ comprises 3.14 million km² and partitioning this LECZ with surge and sea-level rise data into floodplains for coastal impact modelling finds about 221,800 floodplains with at least 0.05 km² area.