Articles | Volume 21, issue 3
https://doi.org/10.5194/nhess-21-1071-2021
https://doi.org/10.5194/nhess-21-1071-2021
Research article
 | 
23 Mar 2021
Research article |  | 23 Mar 2021

The uncertainty of flood frequency analyses in hydrodynamic model simulations

Xudong Zhou, Wenchao Ma, Wataru Echizenya, and Dai Yamazaki

Related authors

An extensive spatiotemporal water quality dataset covering four decades (1980–2022) in China
Jingyu Lin, Peng Wang, Jinzhu Wang, Youping Zhou, Xudong Zhou, Pan Yang, Hao Zhang, Yanpeng Cai, and Zhifeng Yang
Earth Syst. Sci. Data, 16, 1137–1149, https://doi.org/10.5194/essd-16-1137-2024,https://doi.org/10.5194/essd-16-1137-2024, 2024
Short summary
AltiMaP: altimetry mapping procedure for hydrography data
Menaka Revel, Xudong Zhou, Prakat Modi, Jean-François Cretaux, Stephane Calmant, and Dai Yamazaki
Earth Syst. Sci. Data, 16, 75–88, https://doi.org/10.5194/essd-16-75-2024,https://doi.org/10.5194/essd-16-75-2024, 2024
Short summary
Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water
Jan Polcher, Anthony Schrapffer, Eliott Dupont, Lucia Rinchiuso, Xudong Zhou, Olivier Boucher, Emmanuel Mouche, Catherine Ottlé, and Jérôme Servonnat
Geosci. Model Dev., 16, 2583–2606, https://doi.org/10.5194/gmd-16-2583-2023,https://doi.org/10.5194/gmd-16-2583-2023, 2023
Short summary
Methodology for constructing a flood-hazard map for a future climate
Yuki Kimura, Yukiko Hirabayashi, Yuki Kita, Xudong Zhou, and Dai Yamazaki
Hydrol. Earth Syst. Sci., 27, 1627–1644, https://doi.org/10.5194/hess-27-1627-2023,https://doi.org/10.5194/hess-27-1627-2023, 2023
Short summary
Assimilation of transformed water surface elevation to improve river discharge estimation in a continental-scale river
Menaka Revel, Xudong Zhou, Dai Yamazaki, and Shinjiro Kanae
Hydrol. Earth Syst. Sci., 27, 647–671, https://doi.org/10.5194/hess-27-647-2023,https://doi.org/10.5194/hess-27-647-2023, 2023
Short summary

Related subject area

Hydrological Hazards
How to mitigate flood events similar to the 1979 catastrophic floods in the lower Tagus
Diego Fernández-Nóvoa, Alexandre M. Ramos, José González-Cao, Orlando García-Feal, Cristina Catita, Moncho Gómez-Gesteira, and Ricardo M. Trigo
Nat. Hazards Earth Syst. Sci., 24, 609–630, https://doi.org/10.5194/nhess-24-609-2024,https://doi.org/10.5194/nhess-24-609-2024, 2024
Short summary
Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam
Laurence Hawker, Jeffrey Neal, James Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, and Pham Khanh Nam
Nat. Hazards Earth Syst. Sci., 24, 539–566, https://doi.org/10.5194/nhess-24-539-2024,https://doi.org/10.5194/nhess-24-539-2024, 2024
Short summary
CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale
Andrea Abbate, Leonardo Mancusi, Francesco Apadula, Antonella Frigerio, Monica Papini, and Laura Longoni
Nat. Hazards Earth Syst. Sci., 24, 501–537, https://doi.org/10.5194/nhess-24-501-2024,https://doi.org/10.5194/nhess-24-501-2024, 2024
Short summary
Current and future rainfall-driven flood risk from hurricanes in Puerto Rico under 1.5 and 2 °C climate change
Leanne Archer, Jeffrey Neal, Paul Bates, Emily Vosper, Dereka Carroll, Jeison Sosa, and Daniel Mitchell
Nat. Hazards Earth Syst. Sci., 24, 375–396, https://doi.org/10.5194/nhess-24-375-2024,https://doi.org/10.5194/nhess-24-375-2024, 2024
Short summary
Using integrated hydrological–hydraulic modelling and global data sources to analyse the February 2023 floods in the Umbeluzi Catchment (Mozambique)
Luis Cea, Manuel Álvarez, and Jerónimo Puertas
Nat. Hazards Earth Syst. Sci., 24, 225–243, https://doi.org/10.5194/nhess-24-225-2024,https://doi.org/10.5194/nhess-24-225-2024, 2024
Short summary

Cited articles

Aerts, J. P. M., Uhlemann-Elmer, S., Eilander, D., and Ward, P. J.: Comparison of estimates of global flood models for flood hazard and exposed gross domestic product: a China case study, Nat. Hazards Earth Syst. Sci., 20, 3245–3260, https://doi.org/10.5194/nhess-20-3245-2020, 2020. a
Akaike, H.: A new look at the statistical model identification, IEEE T Automat. Contr., 19, 716–723, 1974. a
Alvisi, S. and Franchini, M.: A grey-based method for evaluating the effects of rating curve uncertainty on frequency analysis of annual maxima, J. Hydroinform., 15, 194–210, https://doi.org/10.2166/hydro.2012.127, 2013. a
Bales, J. D. and Wagner, C. R.: Sources of uncertainty in flood inundation maps, J. Flood Risk Manag., 2, 139–147, https://doi.org/10.1111/j.1753-318X.2009.01029.x, 2009. a
Bernhofen, M. V., Whyman, C., Trigg, M. A., Sleigh, P. A., Smith, A. M., Sampson, C. C., Yamazaki, D., Ward, P. J., Rudari, R., Pappenberger, F., Dottori, F., Salamon, P., and Winsemius, H. C.: A first collective validation of global fluvial flood models for major floods in Nigeria and Mozambique, Environ. Res. Lett., 13, 104007, https://doi.org/10.1088/1748-9326/aae014, 2018. a
Download
Short summary
This article assesses different uncertainties in the analysis of flood risk and found the runoff generated before the river routing is the primary uncertainty source. This calls for attention to be focused on selecting an appropriate runoff for the flood analysis. The uncertainties are reflected in the flood water depth, inundation area and the exposure of the population and economy to the floods.
Altmetrics
Final-revised paper
Preprint