A Review of Estimating Population Exposure to Sea-level Rise and the Relevance for Migration

This review analyses global or near-global estimates of population exposure to sea-level rise and related hazards and examines subsequent estimates of population migration due to this exposure.
Multiple Authors
A man in coastal Bangladesh looks out over the sea which once was the land people in his village used to live on. Sea level rise related erosion is a common struggle for people in low-lying coastal areas of Bangladesh that pushes them to move, adapt and manage around. Credit: Sonja Ayeb-Karlsson


Sea-level rise (SLR) interacts with other climatic factors – such as intensifying storms and wave action – with consequences already observed including infrastructure damage, coastal erosion, salination of freshwater, and land habitat loss. Future SLR is projected to affect human health and wellbeing, cultural and natural heritage, freshwater, biodiversity, agriculture, and fisheries.

Various attempts have been made at the global scale to assess populations exposed to SLR. While these assessments use different definitions, approaches and scenarios, they seek to estimate the number of people who might be directly exposed to SLR and related impacts.

Despite the possibility for various forms of adaptation to SLR, with many people and populations already planning for adaptation in situ, human mobility has been widely positioned as a deterministic certainty whereby climatic and environmental hazards such as SLR force people away from their coastal homes. The first Intergovernmental Panel on Climate Change (IPCC) Assessment Report estimated that half a million people in archipelago and island countries might live in sites at risk of submergence or loss of land by 2100, contributing to increased numbers of so-called ‘climate refugees.’ In 2011, it was estimated that if 2 meters of global mean sea-level rise is realised by 2100, a risk of ‘forced displacement’ exists for up to 187 million people.

To indicate the advantages and limitations of the studies available, and to better direct future work in this area, this paper reviews and discusses datasets and analytical methods for estimating global or near-global population exposure to SLR, with a specific focus on suggestions about SLR-related population mobility attributed to SLR and associated impacts.

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Three databases – Web of Science, Scopus, and Google Scholar – were searched for publications published up until April 2020 that provide quantitative estimates of population exposure to SLR and associated hazards. The full-text search string used was English only: population* AND coast* AND flood* AND “sea level*” AND (global OR international* OR worldwide) AND (model* OR indic*) followed by snowball sampling of citations in publications found. The selected publications were restricted to those published in English and with a focus on global or near-global estimates. Publications with a regional or smaller-scale focus were excluded. Wider searches were not conducted to capture all grey literature on that rationale that the wider material had not necessarily been validated through scientific investigation. No time limit was placed on the searches, but the selected publications range from 1993 to 2019. Manual screening – by title, abstract and then full text – was completed to identify eligible publications.

33 publications met the inclusion criteria: 30 peer reviewed journal articles, 1 book, 1 working paper and 1 report. The final study selection of 33 publications resulted in 11 publications estimating population exposure to specific levels of global mean sea-level rise, 13 publications estimating populations living in coastal floodplains, and 12 publications estimating populations living in low elevation coastal zones or near-coastal zones. These publications were analysed by extracting the key information, permitting a synthesis of what is known about this review’s research topic of estimating population exposure to SLR and the relevance for migration. There was a focus on the publications’ aims, sources of information (data sets) and analysis methods, time frames considered for forecasts, scenarios and numbers for population exposure, any assumptions or implications related to migration, and the data or analysis challenges mentioned.


There are numerous challenges in measuring population exposure to SLR and related impacts. Estimates are based on gridded datasets that include digital elevation models, flooding and extreme sea-levels, and population distribution. Final estimates depend on the input data, and decisions about key parameters such as time horizons, warming scenarios, and ecological or socioeconomic processes and feedbacks including adaptation measures assumed. The four main challenges include:

  1. Estimates of populations exposed to SLR rely on land elevation data to define zones of inundation or potential hazard parameters.
  2. Estimates of coastal floodplains and potential coastal flooding require datasets on extreme sea levels.
  3. Estimates of population exposure to SLR require population distribution datasets.
  4. Many studies set specified levels of future global mean sea-level risebased on different emission and warming pathways over the coming decades, centuries, and millennia.

In short, reliability of the estimates of both current and future population exposure to global mean sea-level riseand related hazards depend on the reliability of input datasets, with precision not always reflecting accuracy.

Lessons Learnt

While noting the challenges of estimating population exposure to SLR and related hazards, most global estimates are in the order of tens or hundreds of millions of people exposed to coastal inundation and coastal flooding for different timeframes and scenarios.

Twenty of the 33 publications reviewed in this article discuss connections between population migration and SLR. Other studies that focus on wider SLR-related hazards such as coastal flooding have also suggested migration will be a key response. However, given that exposure to SLR is not a reliable proxy indicator for migration, none of these studies rigorously or reliably quantifies the number of people who might be expected to move due to SLR. Beyond estimates of exposure, the connections between SLR and migration are complex and uncertain.

Whether or not improved global estimates of population exposure to SLR are needed for policy and decision-making is debatable. This review argues that:

  1. despite the uncertainties and unknowns, it is clear that coastal changes and consequences for populations will be large and require significant action,
  2. it is essential to consider risks and plan for diverse adaptive responses to SLR and associated hazards, including human mobility and preferences to remain and adapt or accommodate risk,
  3. it is important not to repeat myths or reproduce discursive narratives that uphold global power relations, especially those relating to ‘climate refugees’.

This review concludes that global and near-global estimates of SLR-related population exposure and their relevance for migration highlight (i) widespread impacts of human-caused climate change with global mean sea-level rise affecting a significant proportion of the human population and (ii) challenging circumstances for deciding how to act, considering the wide-ranging options from population stabilisation to engineering coastlines to moving away from the current shores. These decisions might be helped by improved spatial distribution and resolution of global datasets to enable more reliable quantitative assessments of population exposure to SLR and related impacts. But decision-making should not wait for data improvements, instead planning now for various decision pathways. Meanwhile, people in low elevation coastal zones are increasingly reporting environmental changes that are potentially attributable to SLR.

At the local scale, more effort is needed to understand the complex interactions between localised SLR and related hazards, local social contexts and potential strategies regarding demographics, migration, and (im)mobility.

See the full publication for much more detail, includingkey areas for further research.


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