Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 26, issue 24
Articles | Volume 26, issue 24
https://doi.org/10.5194/hess-26-6311-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-6311-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 24
Research article
 | 
16 Dec 2022
Research article |  | 16 Dec 2022

Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture

Sinan Li, Li Zhang, Jingfeng Xiao, Rui Ma, Xiangjun Tian, and Min Yan

Supplement

https://doi.org/10.5194/hess-26-6311-2022-supplement

Data sets

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data (https://fluxnet.org/data/fluxnet2015-dataset/) G. Pastorello, C. Trotta, E. Canfora, et al. https://doi.org/10.1038/s41597-020-0534-3

Monthly groundwater table depth, soil moisture, evapotranspiration dataset with high spatial resolution over the Heihe River Basin (1981-2013) Z. Xie https://doi.org/10.11888/Hydro.tpdc.270888

Model code and software

Open source distribution of the computer simulation model LPJmL C. Müller, W. von Bloh, and R. Gieseke https://github.com/PIK-LPJmL/LPJmL

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Short summary
Accurate estimation for global GPP and ET is important in climate change studies. In this study, the GLASS LAI, SMOS, and SMAP datasets were assimilated jointly and separately in a coupled model. The results show that the performance of joint assimilation for GPP and ET is better than that of separate assimilation. The joint assimilation in water-limited regions performed better than in humid regions, and the global assimilation results had higher accuracy than other products.
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