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遥感技术与应用  2019, Vol. 34 Issue (5): 950-958    DOI: 10.11873/j.issn.1004-0323.2019.5.0950
林业遥感专栏     
多层土壤观测数据同化的森林碳、水通量模拟
刘克俭1(),闫敏2,冯琦1
1. 中国人民公安大学公安遥感应用工程技术研究中心,北京 100083
2. 中国科学院遥感与数字地球研究所数字地球重点实验室,北京 100094
Forest Carbon and Water Fluxes Simulation Using Multi-layer Soil Parameters Assimilation
Kejian Liu1(),min Yan2,qi Feng1
1. People’s Public Security University of China, Beijing 100038, China
2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
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摘要:

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。

关键词: 土壤温度土壤水分Biome-BGC MuSo集合卡尔曼滤波    
Abstract:

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.

Key words: Soil temperature    Soil moisture    Biome-BGC MuSo    Ensemble Kalman filter
收稿日期: 2019-03-19 出版日期: 2019-12-05
ZTFLH:  TP79  
作者简介: 刘克俭(1969-),男,山东烟台人,副教授,主要从事遥感技术与应用研究。E-mail:liukejian@ppsuc.edu.cn
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引用本文:

刘克俭,闫敏,冯琦. 多层土壤观测数据同化的森林碳、水通量模拟[J]. 遥感技术与应用, 2019, 34(5): 950-958.

Kejian Liu,min Yan,qi Feng. Forest Carbon and Water Fluxes Simulation Using Multi-layer Soil Parameters Assimilation. Remote Sensing Technology and Application, 2019, 34(5): 950-958.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.5.0950        http://www.rsta.ac.cn/CN/Y2019/V34/I5/950

图1  长白山森林通量站2003~2007年NEE模拟结果季节变化与涡动通量数据的对比图
NEE

年均值

(gC·m–2·yr–1)

春季均值

(gC·m–2·yr–1)

夏季均值(gC·m–2·yr–1)

秋季均值

(gC·m–2·yr–1)

冬季均值(gC·m–2·yr–1)
EC359.9627.99323.3415.77-3.67
BGC275.0112.44254.1931.48-23.11
MuSo414.6623.46381.5726.33-16.69
DA413.5815.01372.9442.16-16.52
表1  长白山森林通量站2003~2007年NEE年均及季节均值
图2  长白山森林通量站2003~2007年ER模拟结果季节变化及其与涡动通量数据的对比图
ER

年均值

(gC·m–2·yr–1)

春季均值

(gC·m–2·yr–1)

夏季均值

(gC·m–2·yr–1)

秋季均值

(gC·m–2·yr–1)

冬季均值

(gC·m–2·yr–1)

EC1 035.55148.48578.43255.7352.92
BGC1 868.55346.941 004.88426.5990.14
MuSo1 613.73222.39925.59362.09103.66
DA1 467.05200.71850.30332.6483.41
表2  长白山森林通量站2003~2007年ER年均及季节均值
图3  长白山森林通量站2003~2007年ET模拟结果季节变化及其与涡动通量数据的对比图
ET

年均值

(mm·yr–1)

春季均值

(mm·yr–1)

夏季均值

(mm·yr–1)

秋季均值

(mm·yr–1)

冬季均值

(mm·yr–1)

EC448.52126.13304.43111.0217.58
BGC313.0455.78153.0991.0913.08
MuSo381.4171.46212.5686.7210.67
DA450.4885.05245.31106.3913.74
表3  长白山森林通量站2003~2007年ET年均及季节均值
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