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

Related authors

Wave forecast investigations on downscaling, source terms, and tides for Aotearoa New Zealand
Rafael Santana, Richard Gorman, Emily Lane, Stuart Moore, Cyprien Bosserelle, Glen Reeve, and Christo Rautenbach
Geosci. Model Dev., 18, 4877–4898, https://doi.org/10.5194/gmd-18-4877-2025,https://doi.org/10.5194/gmd-18-4877-2025, 2025
Short summary
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023,https://doi.org/10.5194/gmd-16-2415-2023, 2023
Short summary
Scenario-based modelling of waves generated by sublacustrine explosive eruptions at Lake Taupō, New Zealand
Matthew W. Hayward, Emily M. Lane, Colin N. Whittaker, Graham S. Leonard, and William L. Power
Nat. Hazards Earth Syst. Sci., 23, 955–971, https://doi.org/10.5194/nhess-23-955-2023,https://doi.org/10.5194/nhess-23-955-2023, 2023
Short summary
Multilayer modelling of waves generated by explosive subaqueous volcanism
Matthew W. Hayward, Colin N. Whittaker, Emily M. Lane, William L. Power, Stéphane Popinet, and James D. L. White
Nat. Hazards Earth Syst. Sci., 22, 617–637, https://doi.org/10.5194/nhess-22-617-2022,https://doi.org/10.5194/nhess-22-617-2022, 2022
Short summary

Cited articles

Alessandrini, V., Bernardi, G., and Todini, E.: An operational approach to real-time dynamic measurement of discharge, Hydrol. Res., 44, 953–964, https://doi.org/10.2166/nh.2013.138, 2013. a
Andreadis, K. M., Schumann, G. J.-P., and Pavelsky, T.: A simple global river bankfull width and depth database, Water Resour. Res., 49, 7164–7168, https://doi.org/10.1002/wrcr.20440, 2013. a
Andreadis, K. M., Brinkerhoff, C. B., and Gleason, C. J.: Constraining the Assimilation of SWOT Observations With Hydraulic Geometry Relations, Water Resour. Res., 56, e2019WR026611, https://doi.org/10.1029/2019WR026611, 2020. a
Araújo, A. and Hedley, N.: Bathymetric data visualization – A review of current methods, practices and emerging interface opportunities, The International Hydrographic Review, 29, 150–163, https://doi.org/10.58440/ihr-29-2-a29, 2023. a
Awadallah, M. O. M., Juárez, A., and Alfredsen, K.: Comparison between Topographic and Bathymetric LiDAR Terrain Models in Flood Inundation Estimations, Remote Sens., 14, 227, https://doi.org/10.3390/rs14010227, 2022. a
More articles (53)
Download
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.
Read more
Share