Articles | Volume 21, issue 3
Nat. Hazards Earth Syst. Sci., 21, 1071–1085, 2021
https://doi.org/10.5194/nhess-21-1071-2021
Nat. Hazards Earth Syst. Sci., 21, 1071–1085, 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 et al.

Related authors

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
EGUsphere, https://doi.org/10.5194/egusphere-2022-690,https://doi.org/10.5194/egusphere-2022-690, 2022
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
EGUsphere, https://doi.org/10.5194/egusphere-2022-412,https://doi.org/10.5194/egusphere-2022-412, 2022
Short summary
Irrigation, damming, and streamflow fluctuations of the Yellow River
Zun Yin, Catherine Ottlé, Philippe Ciais, Feng Zhou, Xuhui Wang, Polcher Jan, Patrice Dumas, Shushi Peng, Laurent Li, Xudong Zhou, Yan Bo, Yi Xi, and Shilong Piao
Hydrol. Earth Syst. Sci., 25, 1133–1150, https://doi.org/10.5194/hess-25-1133-2021,https://doi.org/10.5194/hess-25-1133-2021, 2021
Short summary
A new uncertainty estimation approach with multiple datasets and implementation for various precipitation products
Xudong Zhou, Jan Polcher, Tao Yang, and Ching-Sheng Huang
Hydrol. Earth Syst. Sci., 24, 2061–2081, https://doi.org/10.5194/hess-24-2061-2020,https://doi.org/10.5194/hess-24-2061-2020, 2020
Short summary
ORCHIDEE-ROUTING: revising the river routing scheme using a high-resolution hydrological database
Trung Nguyen-Quang, Jan Polcher, Agnès Ducharne, Thomas Arsouze, Xudong Zhou, Ana Schneider, and Lluís Fita
Geosci. Model Dev., 11, 4965–4985, https://doi.org/10.5194/gmd-11-4965-2018,https://doi.org/10.5194/gmd-11-4965-2018, 2018
Short summary

Related subject area

Hydrological Hazards
Rare flood scenarios for a rapidly growing high-mountain city: Pokhara, Nepal
Melanie Fischer, Jana Brettin, Sigrid Roessner, Ariane Walz, Monique Fort, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 22, 3105–3123, https://doi.org/10.5194/nhess-22-3105-2022,https://doi.org/10.5194/nhess-22-3105-2022, 2022
Short summary
Brief communication: Impact forecasting could substantially improve the emergency management of deadly floods: case study July 2021 floods in Germany
Heiko Apel, Sergiy Vorogushyn, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 22, 3005–3014, https://doi.org/10.5194/nhess-22-3005-2022,https://doi.org/10.5194/nhess-22-3005-2022, 2022
Short summary
Brief communication: Western Europe flood in 2021 – mapping agriculture flood exposure from synthetic aperture radar (SAR)
Kang He, Qing Yang, Xinyi Shen, and Emmanouil N. Anagnostou
Nat. Hazards Earth Syst. Sci., 22, 2921–2927, https://doi.org/10.5194/nhess-22-2921-2022,https://doi.org/10.5194/nhess-22-2921-2022, 2022
Short summary
Comprehensive space–time hydrometeorological simulations for estimating very rare floods at multiple sites in a large river basin
Daniel Viviroli, Anna E. Sikorska-Senoner, Guillaume Evin, Maria Staudinger, Martina Kauzlaric, Jérémy Chardon, Anne-Catherine Favre, Benoit Hingray, Gilles Nicolet, Damien Raynaud, Jan Seibert, Rolf Weingartner, and Calvin Whealton
Nat. Hazards Earth Syst. Sci., 22, 2891–2920, https://doi.org/10.5194/nhess-22-2891-2022,https://doi.org/10.5194/nhess-22-2891-2022, 2022
Short summary
A new index to quantify the extremeness of precipitation across scales
Paul Voit and Maik Heistermann
Nat. Hazards Earth Syst. Sci., 22, 2791–2805, https://doi.org/10.5194/nhess-22-2791-2022,https://doi.org/10.5194/nhess-22-2791-2022, 2022
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