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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 07 May 2019

Submitted as: research article | 07 May 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Hydrology and Earth System Sciences (HESS).

Temporal rainfall disaggregation using a micro-canonical cascade model: Possibilities to improve the autocorrelation

Hannes Müller-Thomy1,* Hannes Müller-Thomy
  • 1Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology, Karlsplatz 13/222, 1040 Vienna, Austria
  • *previously published under the name Hannes Müller

Abstract. In urban hydrology rainfall time series of high resolution in time are crucial. Such time series with sufficient length can be generated through the disaggregation of daily data with a micro-canonical cascade model. A well-known problem of time series generated so is the underestimation of the autocorrelation. In this paper two cascade model modifications are analysed regarding their ability to improve the autocorrelation. Both modifications are based on a state-of-the-art reference cascade model. In the first modification, a position-dependency is introduced in the first disaggregation step. In the second modification the position of a wet time step is redefined in addition. Both modifications led to an improvement of the autocorrelation, especially the position redefinition. Simultaneously, two approaches are investigated to avoid the generation of time steps with too small rainfall intensities, the conservation of a minimum rainfall amount during the disaggregation process itself and the mimicry of a measurement device after the disaggregation process. The mimicry approach shows slight better results for the autocorrelation and hence was kept for a subsequent resampling investigation using Simulated Annealing. For the resampling, a special focus was given to the conservation of the extreme rainfall values. Therefore, a universal extreme event definition was introduced to define extreme events a priori without knowing their occurrence in time or magnitude. The resampling algorithm is capable of improving the autocorrelation, independent of the previously applied cascade model variant. Also, the improvement of the autocorrelation by the resampling was higher than by the choice of the cascade model modification. The best overall representation of the autocorrelation was achieved by method C in combination with the resampling algorithm. The study was carried out for 24 rain gauges in Lower Saxony, Germany.

Hannes Müller-Thomy
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Hannes Müller-Thomy
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Latest update: 13 Nov 2019
Publications Copernicus
Short summary
The simulation of highly dynamic floods requires high-resolution rainfall time series. Observed time series of that kind are often too short, so rainfall generation is the only solution. The applied rainfall generator tends to underestimate the process memory of the rainfall. By modifications of the rainfall generator and a subsequent optimization method the process memory is improved significantly. Flood simulations are expected to be more trustable using the so generated rainfall time series.
The simulation of highly dynamic floods requires high-resolution rainfall time series. Observed...