Articles | Volume 25, issue 5
https://doi.org/10.5194/hess-25-2685-2021
https://doi.org/10.5194/hess-25-2685-2021
Research article
 | 
20 May 2021
Research article |  | 20 May 2021

A note on leveraging synergy in multiple meteorological data sets with deep learning for rainfall–runoff modeling

Frederik Kratzert, Daniel Klotz, Sepp Hochreiter, and Grey S. Nearing

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Latest update: 21 Jul 2024
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Short summary
We investigate how deep learning models use different meteorological data sets in the task of (regional) rainfall–runoff modeling. We show that performance can be significantly improved when using different data products as input and further show how the model learns to combine those meteorological input differently across time and space. The results are carefully benchmarked against classical approaches, showing the supremacy of the presented approach.