Regionalisation of population growth projections in coastal exposure analysis.

Merkens, J.L., Lincke, D., Hinkel, J., Brown, S. and Vafeidis, A.T., 2018. Regionalisation of population growth projections in coastal exposure analysis. Climatic Change. (In Press)

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DOI: 10.1007/s10584-018-2334-8


Large-area coastal exposure and impact analysis has focussed on using sea-level rise (SLR) scenarios and has placed little emphasis on ocioeconomic 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 onsistent 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 SP5 is the second lowest overall. All methods project the largest absolute growth in exposure for Asia and relative growth for Africa.

Item Type:Article
Group:Faculty of Science & Technology
ID Code:31490
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:23 Nov 2018 14:50
Last Modified:23 Nov 2018 14:50


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