09 Apr 2021

09 Apr 2021

Review status: this preprint is currently under review for the journal NHESS.

Global Flood Exposure from Different Sized Rivers

Mark V. Bernhofen1, Mark A. Trigg1, P. Andrew Sleigh1, Christopher C. Sampson2, and Andrew M. Smith2 Mark V. Bernhofen et al.
  • 1School of Civil Engineering, University of Leeds, LS2 9JT, United Kingdom
  • 2Fathom, Square Works, 17-18 Berkeley Square, BS8 1HB, United Kingdom

Abstract. There is now a wealth of data to calculate global flood exposure. Available datasets differ in detail and representation of both global population distribution and global flood hazard. Previous studies of global flood risk have used datasets interchangeably without addressing the impacts using different datasets could have on exposure estimates. By calculating flood exposure to different sized rivers using a model independent geomorphological approach, we show that limits placed on the size of river represented in global flood models result in global flood exposure estimates that differ by greater than a factor of 2. The choice of population dataset is found to be equally important and can have enormous impacts on national flood exposure estimates Up-to-date, high resolution population data is vital for accurately representing exposure to smaller rivers and will be key in improving the global flood risk picture. Our results inform the appropriate application of these datasets and where further development and research is needed.

Mark V. Bernhofen et al.

Status: open (until 21 May 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-102', Serena Ceola, 30 Apr 2021 reply

Mark V. Bernhofen et al.

Data sets

River Flood Susceptibility Map Bernhofen M. V.; Trigg M. A.; Sleigh P. A.; Sampson C. C.; Smith A. M.

Mark V. Bernhofen et al.


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Short summary
The use of different global datasets to calculate flood exposure can lead to differences in global flood exposure estimates. In this study, we use three global population datasets and a simple measure of a river’s flood susceptibility (based on the terrain alone) to explore how the choice of population data and the size of river represented in global flood models affects global and national flood exposure estimates.