The Cryosphere
The Cryosphere
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Articles | Volume 20, issue 2
Articles | Volume 20, issue 2
https://doi.org/10.5194/tc-20-1427-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-1427-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 2
Research article
 | 
03 Mar 2026
Research article |  | 03 Mar 2026

Improving snow water equivalent modelling: a comparative study of hybrid machine learning techniques

Oriol Pomarol Moya, Madlene Nussbaum, Siamak Mehrkanoon, Philip D. A. Kraaijenbrink, Isabelle Gouttevin, Derek Karssenberg, and Walter W. Immerzeel

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Short summary
Two hybrid Machine Learning (ML) approaches predicting daily Snow Water Equivalent (SWE) were evaluated across ten Northern Hemisphere sites. By integrating meteorological data with Crocus snow model simulations, these hybrid models outperformed both standalone Crocus and traditional ML models. Notably, augmenting measured SWE data with Crocus simulations significantly improved performance at unseen locations, offering a promising new approach to long-term SWE prediction.
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