Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 30, issue 1
Articles | Volume 30, issue 1
https://doi.org/10.5194/hess-30-183-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-183-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 30, issue 1
Research article
 | 
14 Jan 2026
Research article |  | 14 Jan 2026

Quantifying uncertainty in flood predictions due to river bathymetry estimation

Martin Nguyen, Matthew D. Wilson, Emily M. Lane, James Brasington, and Rose A. Pearson

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Short summary
River depth is crucial in flood modelling, yet often unavailable. Estimation methods can fill this gap but have errors that can affect flood modelling outputs. Our study quantified flood-prediction uncertainty due to these errors. Between Uniform Flow and Conceptual Multivariate Regression formulas, river depths from the former have higher uncertainty than the latter. Among parameters used in these equations, river width corresponds to the largest uncertainty, followed by the flow and slope.
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