Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 24, issue 1
Articles | Volume 24, issue 1
https://doi.org/10.5194/hess-24-169-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-169-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 1
Research article
 | 
14 Jan 2020
Research article |  | 14 Jan 2020

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

Hannes Müller-Thomy

Viewed

Total article views: 2,816 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,956 805 55 2,816 154 52 49
  • HTML: 1,956
  • PDF: 805
  • XML: 55
  • Total: 2,816
  • Supplement: 154
  • BibTeX: 52
  • EndNote: 49
Views and downloads (calculated since 07 May 2019)
Cumulative views and downloads (calculated since 07 May 2019)

Viewed (geographical distribution)

Total article views: 2,816 (including HTML, PDF, and XML) Thereof 2,343 with geography defined and 473 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 26 Sep 2023
Download
Short summary
Simulation of highly dynamic floods requires high-resolution rainfall time series. Observed time series of that kind are often too short; 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 optimisation method the process memory is improved significantly. Flood simulations are expected to be more trustable using the rainfall time series generated like this.
Read more