Articles | Volume 28, issue 22
https://doi.org/10.5194/hess-28-5031-2024
https://doi.org/10.5194/hess-28-5031-2024
Research article
 | 
26 Nov 2024
Research article |  | 26 Nov 2024

A comprehensive uncertainty framework for historical flood frequency analysis: a 500-year-long case study

Mathieu Lucas, Michel Lang, Benjamin Renard, and Jérôme Le Coz

Related authors

smash v1.0: a differentiable and regionalizable high-resolution hydrological modeling and data assimilation framework
François Colleoni, Ngo Nghi Truyen Huynh, Pierre-André Garambois, Maxime Jay-Allemand, Didier Organde, Benjamin Renard, Thomas De Fournas, Apolline El Baz, Julie Demargne, and Pierre Javelle
Geosci. Model Dev., 18, 7003–7034, https://doi.org/10.5194/gmd-18-7003-2025,https://doi.org/10.5194/gmd-18-7003-2025, 2025
Short summary
A distributed hybrid physics–AI framework for learning corrections of internal hydrological fluxes and enhancing high-resolution regionalized flood modeling
Ngo Nghi Truyen Huynh, Pierre-André Garambois, Benjamin Renard, François Colleoni, Jérôme Monnier, and Hélène Roux
Hydrol. Earth Syst. Sci., 29, 3589–3613, https://doi.org/10.5194/hess-29-3589-2025,https://doi.org/10.5194/hess-29-3589-2025, 2025
Short summary
River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements
Jessica Marggraf, Guillaume Dramais, Jérôme Le Coz, Blaise Calmel, Benoît Camenen, David J. Topping, William Santini, Gilles Pierrefeu, and François Lauters
Earth Surf. Dynam., 12, 1243–1266, https://doi.org/10.5194/esurf-12-1243-2024,https://doi.org/10.5194/esurf-12-1243-2024, 2024
Short summary
Changes in Mediterranean flood processes and seasonality
Yves Tramblay, Patrick Arnaud, Guillaume Artigue, Michel Lang, Emmanuel Paquet, Luc Neppel, and Eric Sauquet
Hydrol. Earth Syst. Sci., 27, 2973–2987, https://doi.org/10.5194/hess-27-2973-2023,https://doi.org/10.5194/hess-27-2973-2023, 2023
Short summary
Concentrations and fluxes of suspended particulate matter and associated contaminants in the Rhône River from Lake Geneva to the Mediterranean Sea
Hugo Lepage, Alexandra Gruat, Fabien Thollet, Jérôme Le Coz, Marina Coquery, Matthieu Masson, Aymeric Dabrin, Olivier Radakovitch, Jérôme Labille, Jean-Paul Ambrosi, Doriane Delanghe, and Patrick Raimbault
Earth Syst. Sci. Data, 14, 2369–2384, https://doi.org/10.5194/essd-14-2369-2022,https://doi.org/10.5194/essd-14-2369-2022, 2022
Short summary

Cited articles

Apel, H., Thieken, A. H., Merz, B., and Blöschl, G.: Flood risk assessment and associated uncertainty, Nat. Hazards Earth Syst. Sci., 4, 295–308, https://doi.org/10.5194/nhess-4-295-2004, 2004. 
Benito, G., Lang, M., Barriendos, M., Llasat, M. C., Francés, F., Ouarda, T., Thorndycraft, V., Enzel, Y., Bardossy, A., Cœur, D., and Bobée, B.: Use of Systematic, Palaeoflood and Historical Data for the Improvement of Flood Risk Estimation. Review of Scientific Methods, Nat. Hazards, 31, 623–643, https://doi.org/10.1023/B:NHAZ.0000024895.48463.eb, 2004. 
Benson, M. A.: Use of historical data in flood-frequency analysis, Eos T. Am. Geophys. Un., 31, 3, 419–424, https://doi.org/10.1029/TR031i003p00419, 1950. 
Cunnane, C.: Unbiased plotting position – a review, J. Hydrol., 37, 205–222, https://doi.org/10.1016/0022-1694(78)90017-3, 1978. 
Download
Short summary
The proposed flood frequency model accounts for uncertainty in the perception threshold S and the starting date of the historical period. Using a 500-year-long case study, inclusion of historical floods reduces the uncertainty in flood quantiles, even when only the number of exceedances of S is known. Ignoring threshold uncertainty leads to underestimated flood quantile uncertainty. This underlines the value of using a comprehensive framework for uncertainty estimation.
Share