Articles | Volume 21, issue 9
https://doi.org/10.5194/nhess-21-2829-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-21-2829-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global flood exposure from different sized rivers
School of Civil Engineering, University of Leeds, LS2 9JT, Leeds, UK
Mark A. Trigg
School of Civil Engineering, University of Leeds, LS2 9JT, Leeds, UK
P. Andrew Sleigh
School of Civil Engineering, University of Leeds, LS2 9JT, Leeds, UK
Christopher C. Sampson
Fathom, Square Works, 17–18 Berkeley Square, BS8 1HB, Bristol, UK
Andrew M. Smith
Fathom, Square Works, 17–18 Berkeley Square, BS8 1HB, Bristol, UK
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This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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How rainfall is distributed over the course of a storm can critically shape flooding, erosion, and water resource impacts. This study reviews nearly fifty metrics used to describe storm patterns and tests their performance when rainfall events are processed differently or are at different resolutions. Our results reveal which metrics are most robust, how they overlap or diverge, and introduce a unifying framework that clarifies storm structure for future research and applied use.
Ben Maybee, Cathryn E. Birch, Steven J. Böing, Thomas Willis, Linda Speight, Aurore N. Porson, Charlie Pilling, Kay L. Shelton, and Mark A. Trigg
Nat. Hazards Earth Syst. Sci., 24, 1415–1436, https://doi.org/10.5194/nhess-24-1415-2024, https://doi.org/10.5194/nhess-24-1415-2024, 2024
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This paper presents the development and verification of FOREWARNS, a novel method for regional-scale forecasting of surface water flooding. We detail outcomes from a workshop held with UK forecast users, who indicated they valued the forecasts and would use them to complement national guidance. We use results of objective forecast tests against flood observations over northern England to show that this confidence is justified and that FOREWARNS meets the needs of UK flood responders.
Paul D. Bates, James Savage, Oliver Wing, Niall Quinn, Christopher Sampson, Jeffrey Neal, and Andrew Smith
Nat. Hazards Earth Syst. Sci., 23, 891–908, https://doi.org/10.5194/nhess-23-891-2023, https://doi.org/10.5194/nhess-23-891-2023, 2023
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We present and validate a model that simulates current and future flood risk for the UK at high resolution (~ 20–25 m). We show that UK flood losses were ~ 6 % greater in the climate of 2020 compared to recent historical values. The UK can keep any future increase to ~ 8 % if all countries implement their COP26 pledges and net-zero ambitions in full. However, if only the COP26 pledges are fulfilled, then UK flood losses increase by ~ 23 %; and potentially by ~ 37 % in a worst-case scenario.
Oliver E. J. Wing, Andrew M. Smith, Michael L. Marston, Jeremy R. Porter, Mike F. Amodeo, Christopher C. Sampson, and Paul D. Bates
Nat. Hazards Earth Syst. Sci., 21, 559–575, https://doi.org/10.5194/nhess-21-559-2021, https://doi.org/10.5194/nhess-21-559-2021, 2021
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Global flood models are difficult to validate. They generally output theoretical flood events of a given probability rather than an observed event that they can be tested against. Here, we adapt a US-wide flood model to enable the rapid simulation of historical flood events in order to more robustly understand model biases. For 35 flood events, we highlight the challenges of model validation amidst observational data errors yet evidence the increasing skill of large-scale models.
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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 affect global and national flood exposure estimates.
The use of different global datasets to calculate flood exposure can lead to differences in...
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