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

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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.
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