Impacts from sea-level rise are among the most crucial impacts of climate change. Global sea levels have been rising in the past century, and will almost certainly accelerate through the 21st century and beyond due to global warming (Nicholls, 2010). The mean rate of sea-level rise from 1993 to 2009 measured by satellites has been 3.3 +/-0.4 mm per year Ablain et al., 2009). The estimates for future sea-level rises by 2100 diverge, yet have generally increased in projected rises since the publication of the Fourth Assessment Report of the IPCC in 2007. Such newer estimates now range from approx. 30 to approx. 200cm, depending on the assumed future developments that in turn drive climate change. Changes in the large sea currents and regional processes such as sediment accumulation or drainage and groundwater withdrawal can respectively offset or exacerbate these rates. The main impact of sea-level rise is submergence of land, i.e. "land loss", and increased flooding in coastal areas. Such direct biophysical impacts can cause a variety of socioeconomic impacts, which are considered to be overwhelmingly negative (Nicholls, 2007). This map focuses on the impact of submergence of land. This map displays the percentage of land that will be potentially inundated (i.e. "under water") in the case of a 1m sea-level rise. The areas with an elevation of 1m above sea-level and below, which are connected to the sea are the areas potentially lost. The percentages are based on total areas of the sub-national political administration units in question, namely districts. The darker the legend color in the map is, the larger the total area or area lost is relative to the administration units (click on the legend button to visualize it). In summary, what you see on the map is land potentially lost through a sea-level rise of 1m without protective measures. This would create direct and indirect socioeconomic impacts, as stated above. Note the heterogeneity and range of land lost among the districts. Depending on how and where human activities are concentrated accordingly strongly determines the degree of impacts this potential land loss would have in case no protective measures are taken. The map displays a scenario for existing conditions. This means it is assumed that no adaptation measures to protect land from future sea-level rise will be made during the time it takes to reach a 1m sea-level rise. Furthermore, no current protective coastal infrastructures already in place are considered, such as dikes. The information presented in the map also embodies uncertainty within itself. This information is important in order to avoid common misconceptions of such maps. The map can be drawn upon for getting a general idea of potential losses in a district as a whole rather than in local situations, of which districts are likely to be affected more than others, of and for comparing such losses across a country. The map should not be drawn upon for attempting to zoom in too far and determine whether farms, houses, infrastructure etc. will be submerged. Note: Please avoid over-interpreting the maps. Maps only have a certain explanatory power. For example, the data presented on the interactive world map is not applicable for highly localized projections, forecasts, and "ground truthing" events and processes there. Please make use of the ci:grasp glossary to clarify terms you are unfamiliar with. Please file a request for features (link) if we have missed to explain a term in our glossary It is helpful to discover whether and where adaption measures are currently taking place, and what type of impacts they address. You can search for them via the interactive world map's adaptation filters, and combine them with an impact map. Alternatively, you can search for adaptation projects via the list of projects. Please refer to the ci:grasp list of references for an ample body of scientific literature. The references in the text throughout the platform are collected there.
The basis on which the potential land loss is calculated is high resolution elevation data for the whole country (SRTM 90). This SRTM 90 data from tiles was merged to obtain a digital elevation model (DEM) for the country in question. The areas which exhibited elevation of 1m above sea-level were extracted from the DEM based on raster connectivity as mentioned by Poulter and Halpin (2008). The areas with an elevation of 1m above sea-level and below that are connected to the sea or to tiles with these properties are the areas potentially lost. Resulting values were aggregated to the district level. The classification legend was adjusted according to the range of results in the country in question. The GADM version 1.0 dataset was used to define administrative level 2 boundaries of the countries.