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Preprints
https://doi.org/10.5194/nhess-2020-79
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-79
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 26 Mar 2020

Submitted as: research article | 26 Mar 2020

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This preprint is currently under review for the journal NHESS.

Downsizing parameter ensembles for simulations of extreme floods

Anna E. Sikorska-Senoner1, Bettina Schaefli2,a, and Jan Seibert1,3 Anna E. Sikorska-Senoner et al.
  • 1University of Zurich, Department of Geography, Zürich, Switzerland
  • 2University of Lausanne, Institute of Earth Surface Dynamics, Lausanne, Switzerland
  • 3Swedish University of Agricultural Sciences, Department of Aquatic Sciences and Assessment, Uppsala, Sweden
  • anow at: University of Bern, Institute of Geography, Bern, Switzerland

Abstract. For extreme flood estimation, simulation-based approaches represent an interesting alternative to purely statistical approaches, particularly if hydrograph shapes are required. Such simulation-based methods are adapted within continuous simulation frameworks that rely on statistical analyses of continuous streamflow time series derived from a hydrologic model fed with long precipitation time series. These frameworks are, however, affected by high computational demands, particularly if floods with return periods > 1000 years are of interest or if modelling uncertainty due to different sources (meteorological input or hydrologic model) is to be quantified. Here, we propose three methods for reducing the computational requirements for the hydrological simulations for extreme flood estimation, so that long streamflow time series can be analysed at a reduced computational cost. These methods rely on simulation of annual maxima and on analyzing their simulated range to downsize the hydrological parameter ensemble to a small number suitable for continuous simulation frameworks. The methods are tested in a Swiss catchment with 10 000 years of synthetic streamflow data simulated with a weather generator. Our results demonstrate the reliability of the proposed downsizing methods for robust simulations of extreme floods with uncertainty. The methods are readily transferable to other situations where ensemble simulations are needed.

Anna E. Sikorska-Senoner et al.

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Anna E. Sikorska-Senoner et al.

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Latest update: 31 May 2020
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Short summary
This work proposes methods for reducing the computational requirements of hydrological simulations for the estimation of very rare floods that occur on average less than once in 1000 years. These methods enable the analysis of long time streamflow series (here for example 10 000 years) at low computational costs with representing modelling uncertainty. They are to be used within continuous simulation frameworks with long input time series and are readily transferable to similar simulation tasks.
This work proposes methods for reducing the computational requirements of hydrological...
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