Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 29, issue 16
Articles | Volume 29, issue 16
https://doi.org/10.5194/hess-29-3833-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-3833-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 29, issue 16
Research article
 | 
18 Aug 2025
Research article |  | 18 Aug 2025

An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics

Zeli Tan, Donghui Xu, Sourav Taraphdar, Jiangqin Ma, Gautam Bisht, and L. Ruby Leung

Viewed

Total article views: 2,630 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,093 479 58 2,630 110 85 89
  • HTML: 2,093
  • PDF: 479
  • XML: 58
  • Total: 2,630
  • Supplement: 110
  • BibTeX: 85
  • EndNote: 89
Views and downloads (calculated since 03 Feb 2025)
Cumulative views and downloads (calculated since 03 Feb 2025)

Viewed (geographical distribution)

Total article views: 2,630 (including HTML, PDF, and XML) Thereof 2,630 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 19 Dec 2025
Download
Short summary
Flow depth and velocity determine various river functions, but their high-resolution simulations are expensive. Here, we developed a downscaling approach that can provide fast and accurate estimation of high-resolution river hydrodynamics. The 84-fold acceleration achieved by the method makes reliable flood risk analysis that needs hundreds or thousands of model runs feasible. More importantly, it provides an opportunity to couple large-scale hydrodynamics with local processes in river models.
Read more
Share