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https://doi.org/10.5194/nhess-2020-272
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-272
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  26 Aug 2020

26 Aug 2020

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This preprint is currently under review for the journal NHESS.

Uncertainty in flood frequency analysis of hydrodynamic model simulations

Xudong Zhou1, Wenchao Ma1, Wataru Echizenya2, and Dai Yamazaki1 Xudong Zhou et al.
  • 1Institute of Industrial Science, The University of Tokyo, 4-6-1, Komaba, Meguro-ku, Tokyo, 153-8505, Japan
  • 2Corporate Planning Department, MS&AD InterRisk Research & Consulting, Inc., 2-105, Kanda Awajicho, Chiyoda-ku, Tokyo 101-0063, Japan

Abstract. Assessing the risk of a historical-level flood at a large scale is essential for regional flood protection and resilience establishment. Due to limitations on the spatiotemporal coverage of observations, the risk assessment relies on model simulations thus is subject to uncertainties from various physical processes in the chain of the flood frequency analysis (FFA). This study assessed the FFA performance as well as the uncertainties with different combinations of FFA variables (river water depth and water storage), fitting distributions and runoff inputs based on the flood characteristics estimated by a global hydrodynamic model CaMa-Flood. Results show that fitting performance is better if FFA is conducted on river water depth and if Wakeby function is selected as the fitting distribution. Deviations in the runoff inputs are the main source of the uncertainties in the estimated flooded water depth based on point analysis. This deviation is relevant to the model ability to reproduce the mean state of annual maximum flood extent and it is almost homogeneous for different flood return period. The uncertainty resulted from fitting distributions increases from the regular period to the rarer floods. The regional investigation of high-resolution inundation area over the lower Mekong River basin shows similar statistics as the point analysis, implying a large uncertainty with 20 % deviation in the total inundation area between different runoff inputs. Regional validation of the CaMa-Flood with two other flood hazard maps proves the reliability of the inundation in space and values. Global analysis on the floodplain water depth implies an increasing contribution of uncertainties in fitting distribution to the total uncertainties for rarer floods in almost all land grids. While the changes in contribution of uncertainties in runoff inputs differentiates in regions. The much higher contribution of runoff uncertainty for rarer floods in wet/flat regions necessitates special attention on rainfall-runoff model calibration (or runoff bias correction) if gauge discharge observations are available. Different adaptions to the large floods are needed for regions with different flood water depth and with different inundation agreements among simulations.

Xudong Zhou et al.

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Short summary
This article assessed 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 our attention to select an appropriate runoff for the flood analysis. The flood hazard map provided by CaMa-Flood has been evaluated with the uncertainty and two other maps, indicating the applicability of CaMa-Flood for global and regional flood assessment.
This article assessed different uncertainties in the analysis of flood risk and found the runoff...
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