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Sea Level Rise dataset

Authors:Susmita Dasgupta
Web Address:Environment and Energy Research
Topics:Environment
Report Number:WPS4901
Citation: 

Sea-level rise (SLR) due to climate change is a serious global threat: The scientific evidence is now overwhelming. Continued growth of greenhouse gas emissions and associated global warming could well promote SLR of 1m in this century, and unexpectedly rapid breakup of the Greenland and West Antarctic ice sheets might produce a 3-5m SLR.  In this research, we have assessed the consequences of continued SLR for 84 coastal developing countries. Geographic Information System (GIS) software has been used to overlay the best available, spatially-disaggregated global data on critical impact elements (land, population, agriculture, urban extent, wetlands, and GDP), with the inundation zones projected for 1-5m SLR.

Country-level impacts have been summarized in the Excel Workbook “SLR-Impacts”.

  • The Excel Workbook is divided into Worksheets to match the major critical impact elements: land, population, GDP, agriculture, urban extent, and wetlands.
  • Absolute impacts of 1-5m SLR are presented in Columns D-H.
  • Percentage Impacts are presented in Columns I-M.

Original data sources for assessments of impacts:

DimensionDataset nameUnitResolutionSource(s)
Coastline and country boundaryWVS1:250,000NOAA/NASA
ElevationSRTM 90m DEM V2km2 90mCIAT 
PopulationGPW-3Population counts1kmCIESIN
Economic activityGDP2000million US dollars5kmWorld Bank, based on Sachs et al. (2001)
Urban areasGRUMP V1km21kmCIESIN
Agricultural LandGAE-2km21kmIFPRI 
WetlandsGLWD-3km21kmCESR, Lehner, B. and Döll, P. (2004)

Limitations of the research: 

  1. The digital elevation (90m DEM V2) data used in this analysis gives altitude in 1-meter increments, preventing us from sub-meter SLR modeling. One can interpolate the elevation data we have used for sub-meter SLR modeling, but in that case, precision of the estimates would be difficult to justify.  The potential use of LIDAR survey (laser-based elevation measurement from low-flying aircraft) was beyond scope of our analysis.
  2. Lack of spatially disaggregated secondary information on indicators prevented us from including small islands in this analysis.
  3. The impacts of SLR have been assessed using existing population, socio-economic conditions and patterns of land use, rather than attempting to predict their future states.  Human activity is generally increasing more rapidly in coastal areas and thus the impacts of SLR will be more pronounced in these areas.  This effect is countered by adaptation measures, which we also do not attempt to estimate in this exercise. Adaptation measures from the purely technological (e.g., sea defenses), to managerial (e.g., altering land-use planning, relocation), to policy (e.g., planning regulations) are often context, location and community-specific.  Thus in our analysis, we refrain from generalizing any adaptive measures across our sub-set of developing countries.

This research was carried out by the World Bank in 2006, and was funded by the Canadian Trust Fund (TF030569) sponsored by the Canadian International Development Agency (CIDA). 

Access to Dataset
  • SLR dataset (MS Excel file, 205kb)





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