Articles | Volume 25, issue 6
https://doi.org/10.5194/hess-25-3017-2021
https://doi.org/10.5194/hess-25-3017-2021
Research article
 | 
04 Jun 2021
Research article |  | 04 Jun 2021

Investigating ANN architectures and training to estimate snow water equivalent from snow depth

Konstantin F. F. Ntokas, Jean Odry, Marie-Amélie Boucher, and Camille Garnaud

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Latest update: 13 Mar 2025
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Short summary
This article shows a conversion model of snow depth into snow water equivalent (SWE) using an ensemble of artificial neural networks. The novelty is a direct estimation of SWE and the improvement of the estimation by in-depth analysis of network structures. The usage of an ensemble allows a probabilistic estimation and, therefore, a deeper insight. It is a follow-up study of a similar study over Quebec but extends it to the whole area of Canada and improves it further.
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