Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 5
Articles | Volume 28, issue 5
https://doi.org/10.5194/hess-28-1147-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-1147-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 5
Research article
 | 
07 Mar 2024
Research article |  | 07 Mar 2024

A D-vine copula-based quantile regression towards merging satellite precipitation products over rugged topography: a case study in the upper Tekeze–Atbara Basin

Mohammed Abdallah, Ke Zhang, Lijun Chao, Abubaker Omer, Khalid Hassaballah, Kidane Welde Reda, Linxin Liu, Tolossa Lemma Tola, and Omar M. Nour

Viewed

Total article views: 3,136 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,444 616 76 3,136 80 92
  • HTML: 2,444
  • PDF: 616
  • XML: 76
  • Total: 3,136
  • BibTeX: 80
  • EndNote: 92
Views and downloads (calculated since 10 Aug 2023)
Cumulative views and downloads (calculated since 10 Aug 2023)

Viewed (geographical distribution)

Total article views: 3,136 (including HTML, PDF, and XML) Thereof 3,041 with geography defined and 95 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 15 Nov 2025
Download
Short summary
A D-vine copula-based quantile regression (DVQR) model is used to merge satellite precipitation products. The performance of the DVQR model is compared with the simple model average and one-outlier-removed average methods. The nonlinear DVQR model outperforms the quantile-regression-based multivariate linear and Bayesian model averaging methods.
Read more
Share