Articles | Volume 22, issue 10
https://doi.org/10.5194/hess-22-5259-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-22-5259-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Oct 2018
Research article |
| 15 Oct 2018
| 15 Oct 2018
Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?
Hannes Müller-Thomy
CORRESPONDING AUTHOR
Institute of Hydrology and Water Resources Management, Leibniz Universität Hannover, 30175 Hanover, Germany
Institute of Hydraulic Engineering and Water Resources Management, Vienna University of Technology, Vienna, 1040, Austria
previously published under the name Hannes Müller
Markus Wallner
bpi Hannover – Beratende Ingenieure, 30177 Hanover, Germany
Kristian Förster
Institute of Hydrology and Water Resources Management, Leibniz Universität Hannover, 30175 Hanover, Germany
Institute of Geography, University of Innsbruck, Innsbruck, 6020, Austria
alpS – Centre for Climate Change Adaptation, Innsbruck, 6020, Austria
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Cited
15 citations as recorded by crossref.
- Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs. weather-generator-based approach B. Winter et al. 10.5194/nhess-20-1689-2020
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- Propagation of uncertainties in interpolated rainfields to runoff errors Y. Gyasi-Agyei 10.1080/02626667.2019.1593989
- Using reanalysis precipitation data for developing intensity-duration-frequency curves in a poorly gauged city F. Wambura 10.1016/j.ejrh.2024.102005
- Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model? H. Müller-Thomy & A. Sikorska-Senoner 10.1080/02626667.2019.1638926
- Climate change–induced variations in future extreme precipitation intensity–duration–frequency in flood-prone city of Adama, central Ethiopia D. Bulti et al. 10.1007/s10661-021-09574-1
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- Disaggregation of rainfall from daily to 1-hour scale through integrated MMRC-copula modelling P. Biswas & U. Saha 10.1016/j.jhydrol.2024.132338
- CON-SST-RAIN: Continuous Stochastic Space–Time Rainfall generation based on Markov chains and transposition of weather radar data C. Andersen et al. 10.1016/j.jhydrol.2024.131385
- Daily vs. hourly simulation for estimating future flood peaks in mesoscale catchments M. Beylich et al. 10.2166/nh.2021.152
- Simulating sub-hourly rainfall data for current and future periods using two statistical disaggregation models: case studies from Germany and South Korea I. Vorobevskii et al. 10.5194/hess-28-391-2024
- Modelling the interplay of future changes and wastewater management measures on the microbiological river water quality considering safe drinking water production K. Demeter et al. 10.1016/j.scitotenv.2020.144278
- Can we estimate flood frequency with point-process spatial-temporal rainfall models? Y. Chen et al. 10.1016/j.jhydrol.2021.126667
- Temporal rainfall disaggregation using a micro-canonical cascade model: possibilities to improve the autocorrelation H. Müller-Thomy 10.5194/hess-24-169-2020
- Modelling forest snow processes with a new version of WaSiM K. Förster et al. 10.1080/02626667.2018.1518626
14 citations as recorded by crossref.
- Event generation for probabilistic flood risk modelling: multi-site peak flow dependence model vs. weather-generator-based approach B. Winter et al. 10.5194/nhess-20-1689-2020
- Integrating an hourly weather generator with an hourly rainfall SWAT model for climate change impact assessment in the Ru River Basin, China X. Yang et al. 10.1016/j.atmosres.2020.105062
- Propagation of uncertainties in interpolated rainfields to runoff errors Y. Gyasi-Agyei 10.1080/02626667.2019.1593989
- Using reanalysis precipitation data for developing intensity-duration-frequency curves in a poorly gauged city F. Wambura 10.1016/j.ejrh.2024.102005
- Does the complexity in temporal precipitation disaggregation matter for a lumped hydrological model? H. Müller-Thomy & A. Sikorska-Senoner 10.1080/02626667.2019.1638926
- Climate change–induced variations in future extreme precipitation intensity–duration–frequency in flood-prone city of Adama, central Ethiopia D. Bulti et al. 10.1007/s10661-021-09574-1
- Introduction of k-means clustering into random cascade model for disaggregation of rainfall from daily to 1-hour resolution with improved preservation of extreme rainfall P. Deka & U. Saha 10.1016/j.jhydrol.2023.129478
- Disaggregation of rainfall from daily to 1-hour scale through integrated MMRC-copula modelling P. Biswas & U. Saha 10.1016/j.jhydrol.2024.132338
- CON-SST-RAIN: Continuous Stochastic Space–Time Rainfall generation based on Markov chains and transposition of weather radar data C. Andersen et al. 10.1016/j.jhydrol.2024.131385
- Daily vs. hourly simulation for estimating future flood peaks in mesoscale catchments M. Beylich et al. 10.2166/nh.2021.152
- Simulating sub-hourly rainfall data for current and future periods using two statistical disaggregation models: case studies from Germany and South Korea I. Vorobevskii et al. 10.5194/hess-28-391-2024
- Modelling the interplay of future changes and wastewater management measures on the microbiological river water quality considering safe drinking water production K. Demeter et al. 10.1016/j.scitotenv.2020.144278
- Can we estimate flood frequency with point-process spatial-temporal rainfall models? Y. Chen et al. 10.1016/j.jhydrol.2021.126667
- Temporal rainfall disaggregation using a micro-canonical cascade model: possibilities to improve the autocorrelation H. Müller-Thomy 10.5194/hess-24-169-2020
1 citations as recorded by crossref.
Latest update: 09 May 2025
Short summary
Rainfall time series are disaggregated from daily to hourly values to be used for rainfall–runoff modeling of mesoscale catchments. Spatial rainfall consistency is implemented afterwards using simulated annealing. With the calibration process applied, observed runoff statistics (e.g., summer and winter peak flows) are represented well. However, rainfall datasets with under- or over-estimation of spatial consistency lead to similar results, so the need for a good representation can be questioned.
Rainfall time series are disaggregated from daily to hourly values to be used for...
