Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 24, issue 11
Articles | Volume 24, issue 11
https://doi.org/10.5194/hess-24-5187-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-5187-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 11
Research article
 | 
10 Nov 2020
Research article |  | 10 Nov 2020

Assimilating shallow soil moisture observations into land models with a water budget constraint

Bo Dan, Xiaogu Zheng, Guocan Wu, and Tao Li

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Latest update: 04 Nov 2024
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Short summary
Data assimilation is a procedure to generate an optimal combination of the state variable in geoscience, based on the model outputs and observations. The ensemble Kalman filter (EnKF) scheme is a widely used assimilation method in soil moisture estimation. This study proposed several modifications of EnKF for improving this assimilation. The study shows that the quality of the assimilation result is improved, while the degree of water budget imbalance is reduced.
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