Assimilating spatiotemporal MODIS LAI data with a particle filter algorithm for improving carbon cycle simulations for bamboo forest ecosystems

Xuejian Li; Huaqiang Du; Fangjie Mao; Guomo Zhou; Ning Han; Xiaojun Xu; Yuli Liu; Di'en Zhu; Junlong Zheng; Luofan Dong; Meng Zhang

doi:10.1016/j.scitotenv.2019.133803

Assimilating spatiotemporal MODIS LAI data with a particle filter algorithm for improving carbon cycle simulations for bamboo forest ecosystems

Sci Total Environ. 2019 Dec 1:694:133803. doi: 10.1016/j.scitotenv.2019.133803. Epub 2019 Aug 6.

Authors

Xuejian Li¹, Huaqiang Du², Fangjie Mao¹, Guomo Zhou¹, Ning Han¹, Xiaojun Xu¹, Yuli Liu¹, Di'en Zhu¹, Junlong Zheng¹, Luofan Dong¹, Meng Zhang¹

Affiliations

¹ State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China; Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China; School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China.
² State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China; Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China; School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China. Electronic address: dhqrs@126.com.

PMID: 31756841
DOI: 10.1016/j.scitotenv.2019.133803

Abstract

Bamboo forests are an important part of the forest ecosystem, which has strong carbon sequestration potential and plays an important role in the global carbon cycle. As a key parameter for simulating the carbon cycle using forest ecosystem models, the quality of leaf area index (LAI) data has a direct influence on the accuracy of modelling results. Here, we used the particle filter (PF) algorithm and PROSAIL model to assimilate MODIS LAI products, which were then used to drive a boreal ecosystem productivity simulator model to simulate the bamboo forest carbon cycle. The results showed that the relationship between the assimilated and observed LAI values was very significant, with an R² of 0.95 and an RMSE of 0.28, greatly improving the precision of MODIS LAI products. The R² values for the gross primary productivity (GPP), net ecosystem exchange (NEE), and total ecosystem respiration (TER) simulated by the assimilated LAI values and observed carbon fluxes were 0.65, 0.45 and 0.70, respectively, and the RMSE values were 1.10 g C m^-2 day^-1, 1.00 g C m^-2 day^-1 and 0.35 g C m^-2 day^-1, respectively. Compared with the results of the carbon cycle simulated by non-assimilated LAI, the R² values of the GPP, NEE and TER values that were simulated by assimilated LAI increased by 27.5%, 45.2% and 6.1%, and the RMSE values decreased by 29.9%, 23.7% and 22.2%, respectively. Therefore, coupling the PF and PROSAIL models can greatly improve the simulation precision for the large-scale bamboo forest carbon cycle. This study laid the foundation for simulating the carbon cycle over a large-scale bamboo forest based on low-resolution data in the future.

Keywords: BEPS model; Bamboo forest; Carbon cycle; Data assimilation; PROSAIL model; Particle filter.

MeSH terms

Algorithms*
Carbon
Carbon Cycle*
Ecosystem*
Environmental Monitoring / methods*
Forests*
Models, Biological
Plant Leaves
Sasa*
Trees

Substances

Carbon