Articles | Volume 22, issue 11
https://doi.org/10.5194/hess-22-5759-2018
https://doi.org/10.5194/hess-22-5759-2018
Research article
 | 
09 Nov 2018
Research article |  | 09 Nov 2018

Hybridizing Bayesian and variational data assimilation for high-resolution hydrologic forecasting

Felipe Hernández and Xu Liang

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Latest update: 01 Mar 2024
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Short summary
Predicting floods requires first knowing the amount of water in the valleys, which is complicated because we cannot know for sure how much water there is in the soil. We created a unique system that combines the best methods to estimate these conditions accurately based on the observed water flow in the rivers and on detailed simulations of the valleys. Comparisons with popular methods show that our system can produce realistic predictions efficiently, even for very detailed river networks.