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

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
Understanding the water cycle over the upper Tarim Basin: retrospecting the estimated discharge bias to atmospheric variables and model structure
Xudong Zhou, Jan Polcher, Tao Yang, Yukiko Hirabayashi, and Trung Nguyen-Quang
Hydrol. Earth Syst. Sci., 22, 6087–6108, https://doi.org/10.5194/hess-22-6087-2018,https://doi.org/10.5194/hess-22-6087-2018, 2018
Short summary

Related subject area

Hydrological Hazards
Improving flood damage assessments in data-scarce areas by retrieval of building characteristics through UAV image segmentation and machine learning – a case study of the 2019 floods in southern Malawi
Lucas Wouters, Anaïs Couasnon, Marleen C. de Ruiter, Marc J. C. van den Homberg, Aklilu Teklesadik, and Hans de Moel
Nat. Hazards Earth Syst. Sci., 21, 3199–3218, https://doi.org/10.5194/nhess-21-3199-2021,https://doi.org/10.5194/nhess-21-3199-2021, 2021
Short summary
Assessment of direct economic losses of flood disasters based on spatial valuation of land use and quantification of vulnerabilities: a case study on the 2014 flood in Lishui city of China
Haixia Zhang, Weihua Fang, Hua Zhang, and Lu Yu
Nat. Hazards Earth Syst. Sci., 21, 3161–3174, https://doi.org/10.5194/nhess-21-3161-2021,https://doi.org/10.5194/nhess-21-3161-2021, 2021
Short summary
Evaluating integrated water management strategies to inform hydrological drought mitigation
Doris E. Wendt, John P. Bloomfield, Anne F. Van Loon, Margaret Garcia, Benedikt Heudorfer, Joshua Larsen, and David M. Hannah
Nat. Hazards Earth Syst. Sci., 21, 3113–3139, https://doi.org/10.5194/nhess-21-3113-2021,https://doi.org/10.5194/nhess-21-3113-2021, 2021
Short summary
Global riverine flood risk – how do hydrogeomorphic floodplain maps compare to flood hazard maps?
Sara Lindersson, Luigia Brandimarte, Johanna Mård, and Giuliano Di Baldassarre
Nat. Hazards Earth Syst. Sci., 21, 2921–2948, https://doi.org/10.5194/nhess-21-2921-2021,https://doi.org/10.5194/nhess-21-2921-2021, 2021
Short summary
Global flood exposure from different sized rivers
Mark V. Bernhofen, Mark A. Trigg, P. Andrew Sleigh, Christopher C. Sampson, and Andrew M. Smith
Nat. Hazards Earth Syst. Sci., 21, 2829–2847, https://doi.org/10.5194/nhess-21-2829-2021,https://doi.org/10.5194/nhess-21-2829-2021, 2021
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