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A global analysis of subsidence, relative sea-level change and coastal flood exposure

Nature Climate Change volume 11, pages 338–342 (2021)Cite this article

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Abstract

Climate-induced sea-level rise and vertical land movements, including natural and human-induced subsidence in sedimentary coastal lowlands, combine to change relative sea levels around the world’s coasts. Although this affects local rates of sea-level rise, assessments of the coastal impacts of subsidence are lacking on a global scale. Here, we quantify global-mean relative sea-level rise to be 2.6 mm yr−1 over the past two decades. However, as coastal inhabitants are preferentially located in subsiding locations, they experience an average relative sea-level rise up to four times faster at 7.8 to 9.9 mm yr−1. These results indicate that the impacts and adaptation needs are much higher than reported global sea-level rise measurements suggest. In particular, human-induced subsidence in and surrounding coastal cities can be rapidly reduced with appropriate policy for groundwater utilization and drainage. Such policy would offer substantial and rapid benefits to reduce growth of coastal flood exposure due to relative sea-level rise.

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Fig. 1: Cumulative distribution of contemporary length-weighted and population-weighted coastal relative SLR rates.
Fig. 2: Average relative SLR rate for 23 coastal world regions.
Fig. 3: Global population in the coastal floodplain from 2015 to 2050.

Data availability

All datasets used in the production of this paper are available from: https://doi.org/10.5281/zenodo.4434773 (ref. 65). The sea-level data are referenced under the following: https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612. It is freely available from: http://www.esa-sealevel-cci.org/products. Source data are provided with this paper.

Code availability

The R code used to produce the numbers, tables and figures is available from: https://doi.org/10.5281/zenodo.4434773 (ref. 65). Source data are provided with this paper.

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Acknowledgements

We thank J. Ericson for sharing his dataset on delta subsidence. R.J.N. was supported under the Deltas, Vulnerability and Climate Change: Migration and Adaptation project (International Development Research Centre (IDRC), Canada, 107642) under the Collaborative Adaptation Research Initiative in Africa and Asia programme with financial support from the UK Government’s Department for International Development, the IDRC, Canada and the PROTECT Project. The views expressed in this work are those of the creators and do not necessarily represent those of the Department for International Development and IDRC or their boards of governors. We thank the ESA CCI sea level project for providing the level 4 sea-level data and Centre National d’Etudes Spatiales (CNES) for providing the level 2 data from the Topex and Jason 1, 2 and 3 satellites. Other portions of this research were made possible by support from the European Union through the projects Responses to coastal climate change: Innovative Strategies for high End Scenarios – Adaptation and Mitigation (RISES-AM) funded by the European Commission’s Seventh Framework Programme, 2007–2013, under the grant agreement number 603396), and Green growth and win-win strategies for sustainable climate action (GREEN-WIN) and CO-designing the Assessment of Climate CHange costs (COACCH), both of which are funded by European Union’s Horizon 2020 research and innovation programme under grant agreement numbers 642018 and 776479, respectively. Further funding was received through two projects, INSeaPTION and ISIpedia, which are part of European Research Area for Climate Services (ERA4CS), an ERA-NET initiative by JPI Climate, and funded by the Research Council for Sustainable Development (Formas), Sweden; Federal Ministry of Education and Research (BMBF), Germany (grant numbers 01LS1711C and 01LS1703A); Federal Ministry of Science, Research and Economy (BMWFW), Austria; Innovation Fund Denmark (IFD); Ministry of Economic Affairs and Digital Transformation (MINECO), Spain; and National Research Agency (ANR), France, with co-funding by the European Union (grant 690462). This publication was supported by PROTECT. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 869304, PROTECT contribution number 8.

Author information

Authors and Affiliations

  1. Tyndall Centre for Climate Change Research, University of East Anglia (UEA), Norwich, UK

    Robert J. Nicholls

  2. Global Climate Forum, Berlin, Germany

    Daniel Lincke & Jochen Hinkel

  3. Division of Resource Economics, Thaer-Institute of Agricultural and Horticultural Sciences, Faculty of Life Sciences, Humboldt-University, Berlin, Germany

    Jochen Hinkel

  4. Berlin Workshop in Institutional Analysis of Social-Ecological Systems (WINS), Humboldt-University, Berlin, Germany

    Jochen Hinkel

  5. Department of Life and Environmental Sciences, Faculty of Science and Technology, Bournemouth University, Bournemouth, UK

    Sally Brown

  6. Kiel University, Department of Geography, Kiel, Germany

    Athanasios T. Vafeidis & Jan-Ludolf Merkens

  7. LEGOS, Université de Toulouse, CNES, CNRS, UPS, IRD, Toulouse, France

    Benoit Meyssignac

  8. School of Engineering, University of Southampton, Southampton, UK

    Susan E. Hanson

  9. School of Geographic Sciences, East China Normal University, Shanghai, China

    Jiayi Fang

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Contributions

R.J.N., D.L. and J.H. designed and conducted the analysis and wrote the main paper. They also prepared the city-subsidence and glacial–isostatic-adjustment data. S.B. and S.E.H. contributed to the city-subsidence data and prepared the data on delta subsidence. A.T.V. and J.-L.M. prepared the socioeconomic data. B.M. provided the satellite sea-level data and the expertise on climate-induced coastal sea-level rise. J.F. contributed to the city-subsidence data from Asia, especially China. All authors read paper drafts and approved the final version.

Corresponding author

Correspondence to Robert J. Nicholls.

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The authors declare no competing interests.

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Peer review information Nature Climate Change thanks Devin Galloway, Nobuo Mimura and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Cumulative distribution of contemporary coastal relative SLR.

(a) length-weighted, (b) population-weighted. Each panel shows climate-induced SLR alone, and then progressively adds the other components comprising: (1) GIA, (2) GIA and delta subsidence combined, and (3) GIA, delta subsidence and uncontrolled city subsidence combined. For uncontrolled city subsidence, the uncertainty is considered by using a low and high estimate. For length weighting, the main change occurs due to adding the GIA component, which reduces the median and mean SLR. Considering delta and city subsidence has little effect as only 6.5 percent and 0.8 percent of the world’s coast length are affected. For population weightings, adding GIA also has an effect, but it is smaller than for length weighting being −0.3 mm/yr on mean SLR. This reflects that the coastal population is preferentially located in areas where GIA causes subsidence, which counters the effect GIA has when considering length weighting. Adding delta and then uncontrolled city subsidence has a major effect reflecting the large populations in these areas. In the median, these two components add 1.19 mm/yr and an additional 0.62 mm/yr of SLR rise, respectively. The asymmetric distribution of the high-end tail leads to a larger effect on the mean SLR at 1.6 mm/yr due to delta subsidence alone, and an additional 2.7 to 4.8 mm/yr due to city subsidence alone (Table 1).

Source data

Extended Data Fig. 2 Sea-level rise components versus coastal population density for all the coastal segments considered in the analysis.

These comprise (a) climate-induced sea-level rise only, (b) GIA only, (c) high estimates of uncontrolled city subsidence only, (d) delta subsidence only, and (e) the sum of all four components considered previously. The linear best fit and the explained variance are shown in each case. While the explained variance with such a linear fit is small, the slopes are significantly different from zero in all cases.

Source data

Extended Data Fig. 3 Global total of people living in the coastal flood plain from 2015 to 2050 under a range of socio-economic and climate scenarios.

These comprise five different SSP-based regionalised population scenarios (SSP1 to SSP5), and no climate-induced SLR and the RCP2.6 and RCP8.5 SLR scenarios, respectively. Assumptions concerning geological components of relative SLR are as follows: Column (a) No geological component, Column (b) GIA only, Column (c) GIA and delta subsidence, Column (d) GIA, delta and uncontrolled city subsidence. Column (e) GIA, delta and controlled city subsidence (to a maximum of 5 mm/yr). The lower, middle and upper population estimates in (d) and (e) reflect uncertainty in the rates of city subsidence (see Fig. 1). All simulations start in 1995. The results indicate little variation between SSPs to 2050.

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Supplementary Tables 1–4 and references.

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Nicholls, R.J., Lincke, D., Hinkel, J. et al. A global analysis of subsidence, relative sea-level change and coastal flood exposure. Nat. Clim. Chang. 11, 338–342 (2021). https://doi.org/10.1038/s41558-021-00993-z

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