Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-6041-2021
https://doi.org/10.5194/hess-25-6041-2021
Research article
 | 
25 Nov 2021
Research article |  | 25 Nov 2021

A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration

Jiancong Chen, Baptiste Dafflon, Anh Phuong Tran, Nicola Falco, and Susan S. Hubbard

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Latest update: 28 Feb 2024
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Short summary
The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent neural network to estimate evapotranspiration (ET) and ecosystem respiration (Reco) with only meteorological and remote-sensing inputs. We developed four use cases to demonstrate the applicability of HPM. The results indicate HPM is capable of providing ET and Reco estimations in challenging mountainous systems and enhances our understanding of watershed dynamics at sparsely monitored watersheds.