Articles | Volume 29, issue 16
https://doi.org/10.5194/hess-29-3833-2025
https://doi.org/10.5194/hess-29-3833-2025
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

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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.
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