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New estimates of flood exposure in developing countries using high-resolution population data

Author

Listed:
  • Andrew Smith

    (Fathom, The Engine Shed, Station Approach)

  • Paul D. Bates

    (Fathom, The Engine Shed, Station Approach
    School of Geographical Sciences, University of Bristol)

  • Oliver Wing

    (Fathom, The Engine Shed, Station Approach
    School of Geographical Sciences, University of Bristol)

  • Christopher Sampson

    (Fathom, The Engine Shed, Station Approach)

  • Niall Quinn

    (Fathom, The Engine Shed, Station Approach)

  • Jeff Neal

    (Fathom, The Engine Shed, Station Approach
    School of Geographical Sciences, University of Bristol)

Abstract

Current estimates of global flood exposure are made using datasets that distribute population counts homogenously across large lowland floodplain areas. When intersected with simulated water depths, this results in a significant mis-estimation. Here, we use new highly resolved population information to show that, in reality, humans make more rational decisions about flood risk than current demographic data suggest. In the new data, populations are correctly represented as risk-averse, largely avoiding obvious flood zones. The results also show that existing demographic datasets struggle to represent concentrations of exposure, with the total exposed population being spread over larger areas. In this analysis we use flood hazard data from a ~90 m resolution hydrodynamic inundation model to demonstrate the impact of different population distributions on flood exposure calculations for 18 developing countries spread across Africa, Asia and Latin America. The results suggest that many published large-scale flood exposure estimates may require significant revision.

Suggested Citation

  • Andrew Smith & Paul D. Bates & Oliver Wing & Christopher Sampson & Niall Quinn & Jeff Neal, 2019. "New estimates of flood exposure in developing countries using high-resolution population data," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-09282-y
    DOI: 10.1038/s41467-019-09282-y
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    Cited by:

    1. Md. Monirul Islam & Shusuke Matsushita & Ryozo Noguchi & Tofael Ahamed, 2022. "A damage-based crop insurance system for flash flooding: a satellite remote sensing and econometric approach," Asia-Pacific Journal of Regional Science, Springer, vol. 6(1), pages 47-89, February.
    2. Mark Bawa Malgwi & Jorge Alberto Ramirez & Andreas Zischg & Markus Zimmermann & Stefan Schürmann & Margreth Keiler, 2021. "A method to reconstruct flood scenarios using field interviews and hydrodynamic modelling: application to the 2017 Suleja and Tafa, Nigeria flood," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(2), pages 1781-1805, September.
    3. Bikram Manandhar & Shenghui Cui & Lihong Wang & Sabita Shrestha, 2023. "Urban Flood Hazard Assessment and Management Practices in South Asia: A Review," Land, MDPI, vol. 12(3), pages 1-29, March.
    4. Banick, Robert & Heyns, Andries M. & Regmi, Suraj, 2021. "Evaluation of rural roads construction alternatives according to seasonal service accessibility improvement using a novel multi-modal cost-time model: A study in Nepal's remote and mountainous Karnali," Journal of Transport Geography, Elsevier, vol. 93(C).
    5. Tsang, Michele & Scott, Darren M., 2020. "An integrated approach to modeling the impact of floods on emergency services: A case study of Calgary, Alberta," Journal of Transport Geography, Elsevier, vol. 86(C).
    6. Chaowei Xu & Hao Fu & Jiashuai Yang & Lingyue Wang, 2022. "Assessment of the Relationship between Land Use and Flood Risk Based on a Coupled Hydrological–Hydraulic Model: A Case Study of Zhaojue River Basin in Southwestern China," Land, MDPI, vol. 11(8), pages 1-24, July.
    7. Zhenjie Liu & Jun Li & Haonan Chen & Lizhe Wang & Jun Yang & Antonio Plaza, 2024. "Prediction of changes in war-induced population and CO2 emissions in Ukraine using social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    8. Andrés Fortunato & Helmut Herwartz & Ramón E. López & Eugenio Figueroa B., 2022. "Carbon dioxide atmospheric concentration and hydrometeorological disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(1), pages 57-74, May.
    9. Eric Tate & Md Asif Rahman & Christopher T. Emrich & Christopher C. Sampson, 2021. "Flood exposure and social vulnerability in the United States," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 435-457, March.
    10. Maruyama Rentschler,Jun Erik & Avner,Paolo & Marconcini,Mattia & Su,Rui & Strano,Emanuele & Bernard,Louise Alice Karine & Riom,Capucine Anne Veronique & Hallegatte,Stephane, 2022. "Rapid Urban Growth in Flood Zones : Global Evidence since 1985," Policy Research Working Paper Series 10014, The World Bank.
    11. Max Tesselaar & W. J. Wouter Botzen & Timothy Tiggeloven & Jeroen C. J. H. Aerts, 2023. "Flood insurance is a driver of population growth in European floodplains," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    12. Jun Rentschler & Melda Salhab & Bramka Arga Jafino, 2022. "Flood exposure and poverty in 188 countries," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    13. Beth Tellman & Cody Schank & Bessie Schwarz & Peter D. Howe & Alex de Sherbinin, 2020. "Using Disaster Outcomes to Validate Components of Social Vulnerability to Floods: Flood Deaths and Property Damage across the USA," Sustainability, MDPI, vol. 12(15), pages 1-28, July.
    14. Jie Fan & Baoyin Liu & Xiaodong Ming & Yong Sun & Lianjie Qin, 2022. "The amplification effect of unreasonable human behaviours on natural disasters," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    15. Cascade Tuholske & Andrea E. Gaughan & Alessandro Sorichetta & Alex de Sherbinin & Agathe Bucherie & Carolynne Hultquist & Forrest Stevens & Andrew Kruczkiewicz & Charles Huyck & Greg Yetman, 2021. "Implications for Tracking SDG Indicator Metrics with Gridded Population Data," Sustainability, MDPI, vol. 13(13), pages 1-21, June.

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