Preprints
https://doi.org/10.5194/gmd-2020-280
https://doi.org/10.5194/gmd-2020-280

Submitted as: model description paper 26 Nov 2020

Submitted as: model description paper | 26 Nov 2020

Review status: a revised version of this preprint was accepted for the journal GMD.

Model cascade from meteorological drivers to river flood hazard: flood-cascade v1.0

Peter Uhe1,2, Daniel Mitchell1,2, Paul D. Bates1,2, Nans Addor3,4, Jeff Neal1,2, and Hylke E. Beck5 Peter Uhe et al.
  • 1Cabot Institute for the Environment, University of Bristol, Bristol, UK
  • 2School of Geographical Sciences, University of Bristol, Bristol, UK
  • 3Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
  • 4Geography, College of Life and Environmental Sciences, University of Exeter, Exeter, UK
  • 5Department of Civil and Environmental Engineering, Princeton University, Princeton, USA

Abstract. There is an urgent need for the climate community to translate their meteorological drivers into relevant hazard estimates. This is especially important for the climate attribution and climate projection communities as we seek to understand how anthropogenic climate change has, and will, impact our society. This can be particularly challenging because there are often multiple specialized steps to model the hazard. Current climate change assessments of flood risk typically neglect key processes, and instead of explicitly modeling flood inundation, they commonly use precipitation or river flow as proxies for flood hazard. Here, we lay out a clear methodology for taking meteorological drivers, e.g., from observations or climate models, through to high-resolution (~ 90 m) river flooding (fluvial) hazards. The meteorological inputs (precipitation and air temperature) are transformed through a series of modeling steps to yield, in turn, surface runoff, river flow, and flood inundation. We explore uncertainties at different modeling steps. The flood inundation estimates can then be directly related to impacts felt at community and household levels to determine exposure and risks from flood events. The approach uses global data-sets and thus can be applied anywhere in the world, but we use the Brahmaputra river in Bangladesh as a case study in order to demonstrate the necessary steps in our hazard framework.

Peter Uhe et al.

 
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Peter Uhe et al.

Model code and software

flood-cascade: Version 1 Peter Uhe https://doi.org/10.5281/zenodo.4269581

Peter Uhe et al.

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Short summary
We present a cascade of models to compute high-resolution river flooding. This takes meteorological inputs e.g., rainfall and temperature from observations or climate models, and takes them through a series of modelling steps. This is relevant to evaluating current day and future flood risk and impacts. The model framework uses global data-sets, allowing it to be applied anywhere in the world.