Climatic Change

, Volume 151, Issue 3–4, pp 413–426 | Cite as

Regionalisation of population growth projections in coastal exposure analysis

  • Jan-Ludolf MerkensEmail author
  • Daniel Lincke
  • Jochen Hinkel
  • Sally Brown
  • Athanasios Thomas Vafeidis


Large-area coastal exposure and impact analysis has focussed on using sea-level rise (SLR) scenarios and has placed little emphasis on socioeconomic scenarios, while neglecting spatial variations of population dynamics. We use the Dynamic Interactive Vulnerability Assessment (DIVA) Framework to assess the population exposed to 1 in 100-year coastal flood events under different population scenarios, that are consistent with the shared socioeconomic pathways (SSPs); and different SLR scenarios, derived from the representative concentration pathways (RCPs); and analyse the effect of accounting for regionalised population dynamics on population exposure until 2100. In a reference approach, we use homogeneous population growth on national level. In the regionalisation approaches, we test existing spatially explicit projections that also account for urbanisation, coastal migration and urban sprawl. Our results show that projected global exposure in 2100 ranges from 100 million to 260 million, depending on the combination of SLR and population scenarios and method used for regionalising the population projections. The assessed exposure based on the regionalised approaches is higher than that derived from the reference approach by up to 60 million people (39%). Accounting for urbanisation and coastal migration leads to an increase in exposure, whereas considering urban sprawl leads to lower exposure. Differences between the reference and the regionalised approaches increase with higher SLR. The regionalised approaches show highest exposure under SSP5 over most of the twenty-first century, although total population in SSP5 is the second lowest overall. All methods project the largest absolute growth in exposure for Asia and relative growth for Africa.



The authors would like to express their thanks to the editor and the reviewers for their valuable comments. We would also like to thank Maureen Tsakiris for illustrating Fig. 1.

Supplementary material

10584_2018_2334_MOESM1_ESM.docx (4.5 mb)
ESM 1 (DOCX 4644 kb)


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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of GeographyKiel UniversityKielGermany
  2. 2.Global Climate Forum e.V. (GCF)BerlinGermany
  3. 3.Division of Resource Economics, Albrecht Daniel Thaer-Institute and Berlin Workshop in Institutional Analysis of Social-Ecological Systems (WINSHumboldt-UniversityBerlinGermany
  4. 4.Faculty of Engineering and the EnvironmentUniversity of SouthamptonSouthamptonUK
  5. 5.Tyndall Centre for Climate Change ResearchSouthamptonUK

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