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.
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 potential economic damage in coastal communities.
A considerable portion of global GDP is produced in coastal zones. In addition, it is widely reported that many coastal locations are experiencing population and GDP growth that is higher than their national averages (Hausmann 2001), This suggests a net coastward migration of economic activities increasing the human exposure to the effects of sea-level rise and climate change (Nicholls 2002).
The maps displays the estimated percentage of GDP below 2m elevation in relation to the total GDP associated with the rural and urban areas of the region. The map shows the rural and urban areas that are likely to be more impacted by future sea-level rise if current population and GDP values were maintained. It is assumed that no protection infrastructures like coastal defenses are in place and no adaptation measures like re-location of people and assets is made.
By displaying the percentage of GDP below 2m one can differentiate the relative impacts of sea-level rise both in urban and rural areas. For example, notice that rural areas of similar size produce different amounts of expected impacts. The same can be said regarding urban areas. This highlights that future impacts are not only related to uncertain developments on rising sea-levels, but, to a large extent, determined by the concentration of population and economic activities in low lying areas.
Due to data availability an equal distribution of GDP across each administrative unit is assumed. Thus, the map does not capture the full variability on GDP values that can co-exist within the same geographical unit, instead it denotes that higher values of GDP are likely to be encountered on areas with a large concentration of population. This information is important in order to avoid common misconceptions of such maps.
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.
• This map builds on the results from estimations of people at risk from sea-level rise (to be named consistently) where number of people living below the Xm elevation mark was estimated.
• Values of GDP per capita (in $PPP) on administrative level 1 where gathered from different sources such as statistical agencies. Due to lack of more precise data the GDP values on administrative level 1 where assumed uniformly distributed across the administrative region.
• Estimated numbers of people at risk from sea-level rise where then multiplied by GDP per capita values in order to obtain the GDP below one meter elevation
• Lastly, GDP per capita numbers where differentiated between rural and urban areas using information on the spatial extent of rural and urban areas from the Global Rural-Urban Mapping Project (GRUMP) in the year 2000.