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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/nhess-2019-340
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-340
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 02 Jan 2020

Submitted as: research article | 02 Jan 2020

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A revised version of this preprint was accepted for the journal NHESS and is expected to appear here in due course.

Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs weather generator based approach

Benjamin Winter1,2, Klaus Schneeberger1,2, and Sergiy Vorogushyn3 Benjamin Winter et al.
  • 1Institute of Geography, University of Innsbruck, Innrain 52f, A-6020 Innsbruck, Austria
  • 2alpS, Grabenweg 68, A-6020 Innsbruck, Austria
  • 3GFZ German Research Centre for Geosciences, Hydrology Section, Telegrafenberg, D-14473 Potsdam, Germany

Abstract. Flood risk assessment is an important prerequisite for risk management decisions. To estimate the risk, flood damages need to be either systematically recorded over long period or they need to be modelled for a series of synthetically generated flood events. Since damage records are typically rare, time series of plausible, spatially coherent event precipitation or peak discharges need to be generated to drive the chain of process models. In the present study, synthetic flood events are generated by two different approaches to model flood risk in a meso-scale alpine study area (Vorarlberg, Austria). The first approach is based on the semi-conditional multi-variate dependence model applied to discharge series. The second approach is based on the continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator and using an hourly disaggregation scheme. The results of the two approaches are compared in terms of simulated spatial patterns and overall flood risk estimates. It could be demonstrated that both methods are valid approaches for risk assessment with specific advantages and disadvantages. Both methods are superior to the traditional assumption of a uniform return period, where risk is computed by assuming a homogeneous return period (e.g. 100-year flood) across the entire study area.

Benjamin Winter et al.

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Benjamin Winter et al.

Benjamin Winter et al.

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Latest update: 29 May 2020
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Short summary
In this manuscript two different methods to generate spatially coherent flood events for probabilistic flood risk modelling are compared. On one hand, a semi-conditional multi-variate dependence model applied to discharge observations and on other hand, a continuous hydrological modelling of synthetic meteorological fields generated by a multi-site weather generator. The results of the two approaches are compared in terms of simulated spatial patterns and overall flood risk estimates.
In this manuscript two different methods to generate spatially coherent flood events for...
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