多层土壤观测数据同化的森林碳、水通量模拟

为充分考虑森林生态系统土壤水分的垂直运动及改善碳、水通量的模拟精度，利用Biome-BGC MuSo模型模拟了长白山森林通量站点的碳、水通量，该模型包含了多层土壤模块、物候模块以及管理模块；其次，利用集合卡尔曼滤波算法将站点观测的多层土壤参数同化到Biome-BGC MuSo模型中，并用站点涡动通量数据进行了验证。结果表明：与Biome-BGC模型模拟结果相比，Biome-BGC MuSo改善了站点净生态系统交换量（Net ecosystem exchange, NEE）、生态系统呼吸量（Ecosystem respiration, ER）和蒸散发（Evapotranspiration, ET）模拟精度，站点观测的时序土壤温度和水分数据同化到Biome-BGC MuSo后，碳、水通量模拟结果有了进一步的提升（NEE: R² = 0.70, RMSE = 1.16 gC·m^–2·d^–1; ER: R² = 0.85, RMSE = 1.97 gC·m^–2·d^–1 ; ET: R² = 0.81, RMSE = 0.70 mm·d^–1）。数据-模型同化策略为森林生态系统碳、水同量的模拟提供了科学的方法。

Forest Carbon and Water Fluxes Simulation Using Multi-layer Soil Parameters Assimilation

A strategy of forest carbon and water fluxes simulation was proposed aiming at taking into account soil vertical movements and improving the simulation of forest carbon and water fluxes. Forest carbon and water fluxes at Changbai Mountain forest site was simulated using Biome-BGC MuSo model, which was composed of multi-layer soil module, phenology module and management module. Then multi-layer soil observed parameters were assimilated into Biome-BGC MuSo model, and modeled carbon and water fluxes were evaluated against eddy covariance data. The results demonstrated that Biome-BGC MuSo improved simulations of Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER), and evapotranspiration (ET). After data assimilation, carbon and water fluxed were improved at the Changbai Mountain forest site (NEE: R² = 0.70, RMSE = 1.16 gC·m^–2·d^–1; ER: R² = 0.85, RMSE = 1.97 gC·m^–2·d^–1; ET: R² = 0.81, RMSE = 0.70 mm·d^–1). Data-model assimilation provides scientific technology in simulation of forest carbon and water fluxes.