Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model?

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Müller-Thomy, H.; Sikorska-Senoner, A.E.: Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model?. In: Hydrological Sciences Journal 64 (2019), Nr. 12, 1471. DOI: https://doi.org/10.1080/02626667.2019.1638926

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/10161

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Sum total of downloads: 85




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Abstract: 
Flood peaks and volumes are essential design variables and can be simulated by precipitation–runoff (P–R) modelling. The high-resolution precipitation time series that are often required for this purpose can be generated by various temporal disaggregation methods. Here, we compare a simple method (M1, one parameter), focusing on the effective precipitation duration for flood simulations, with a multiplicative cascade model (M2, 32/36 parameters). While M2 aims at generating realistic characteristics of precipitation time series, M1 aims only at accurately reproducing flood variables by P–R modelling. Both disaggregation methods were tested on precipitation time series of nine Swiss mesoscale catchments. The generated high-resolution time series served as input for P–R modelling using a lumped HBV model. The results indicate that differences identified in precipitation characteristics of disaggregated time series vanish when introduced into the lumped hydrological model. Moreover, flood peaks were more sensitive than flood volumes to the choice of disaggregation method. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 35 41.18%
2 image of flag of United States United States 25 29.41%
3 image of flag of China China 6 7.06%
4 image of flag of Russian Federation Russian Federation 3 3.53%
5 image of flag of Ireland Ireland 3 3.53%
6 image of flag of Indonesia Indonesia 3 3.53%
7 image of flag of Netherlands Netherlands 2 2.35%
8 image of flag of United Kingdom United Kingdom 2 2.35%
9 image of flag of India India 1 1.18%
10 image of flag of Czech Republic Czech Republic 1 1.18%
    other countries 4 4.71%

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