双集合卡尔曼滤波LAI同化结合BEPS模型的竹林生态系统碳通量模拟

doi:10.13287/j.1001-9332.201612.005

应用生态学报 ›› 2016, Vol. 27 ›› Issue (12): 3797-3806.doi: 10.13287/j.1001-9332.201612.005

双集合卡尔曼滤波LAI同化结合BEPS模型的竹林生态系统碳通量模拟

李雪建^1,2, 毛方杰^1,2, 杜华强^1,2*, 周国模^1,2, 徐小军^1,2, 李平衡^1,2, 刘玉莉^1,2, 崔璐^1,2

¹浙江省森林生态系统碳循环与固碳减排重点实验室, 浙江临安 311300;
²浙江农林大学环境与资源学院, 浙江临安 311300

收稿日期:2016-05-24 出版日期:2016-12-18 发布日期:2016-12-18
通讯作者: * E-mail: dhqrs@126.com
作者简介:李雪建,男,1991年生,硕士研究生. 主要从事森林资源遥感监测与信息技术研究. E-mail: 1394405247@qq.com
基金资助:
本文由浙江省杰出青年科学基金项目(LR14C160001)、国家自然科学基金项目(31670644,31370637,31500520)、浙江省自然基金项目(LQ15C160003)、浙江农林大学农林碳汇与生态修复研究中心研究基金项目和浙江省林学一级重中之重学科学生创新计划项目(201511)资助

Simulating of carbon fluxes in bamboo forest ecosystem using BEPS model based on the LAI assimilated with Dual Ensemble Kalman Filter

LI Xue-jian^1,2, MAO Fang-jie^1,2, DU Hua-qiang^1,2*, ZHOU Guo-mo^1,2, XU Xiao-jun^1,2, LI Ping-heng^1,2, LIU Yu-li^1,2, CUI lu^1,2

¹Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang, Lin’an 311300, Zhejiang, China;
²School of Environmental and Resources Science, Zhejiang A&F University, Lin’an 311300, Zhejiang, China

Received:2016-05-24 Online:2016-12-18 Published:2016-12-18
Contact: * E-mail: dhqrs@126.com
Supported by:
The work was supported by the Natural Science Foundation for Distinguished Young Scholars of Zhejiang Province (LR14C160001), the National Na-tural Science Foundation of China (31670644, 31370637, 31500520), the Natural Science Foundation of Zhejiang Province (LQ15C160003), the Research Center of Agricultural and Forestry Carbon Sinks and Ecological Environmental Remediation, Zhejiang A&F University, and the Key Discipline of Forestry of Creative Technology Project of Zhejiang Province (201511).

摘要/Abstract

摘要： 叶面积指数(LAI)是森林生态系统碳循环研究的重要观测数据,也是驱动森林生态系统模型模拟碳循环的重要参数.本文以毛竹林和雷竹林为研究对象,首先利用双集合卡尔曼滤波,同化两种竹林生态系统观测站点2014—2015年MODIS LAI时间序列数据,然后将同化的高质量毛竹LAI和雷竹LAI作为输入数据驱动BEPS模型,模拟两种竹林生态系统总初级生产力(GPP)、净生态系统碳交换量(NEE)和总生态系统呼吸(TER)等碳循环数据,并用通量站实际观测值评价模拟结果;另外,还对比不同质量LAI对碳循环模拟的影响.结果表明: 双集合卡尔曼滤波同化得到的毛竹林和雷竹林LAI与实测LAI之间的相关关系极为显著,R²分别为0.81和0.91,且均方根误差和绝对偏差均较小,极大地提高了MODIS LAI的产品精度;在同化得到的LAI驱动下,BEPS模型模拟的毛竹林GPP、NEE和TER与实际观测值之间的R²分别为0.66、0.47和0.64,雷竹林分别为0.66、0.45和0.73,模拟结果均好于三次样条帽盖算法平滑LAI模拟得到的GPP、NEE和TER,其中,毛竹林、雷竹林NEE的模拟精度提高幅度最大,分别为11.2%和11.8%.

Abstract: LAI is one of the most important observation data in the research of carbon cycle of forest ecosystem, and it is also an important parameter to drive process-based ecosystem model. The Moso bamboo forest (MBF) and Lei bamboo forest (LBF) were selected as the study targets. Firstly, the MODIS LAI time series data during 2014-2015 was assimilated with Dual Ensemble Kalman Filter method. Secondly, the high quality assimilated MBF LAI and LBF LAI were used as input dataset to drive BEPS model for simulating the gross primary productivity (GPP), net ecosystem exchange (NEE) and total ecosystem respiration (TER) of the two types of bamboo forest ecosystem, respectively. The modeled carbon fluxes were evaluated by the observed carbon fluxes data, and the effects of different quality LAI inputs on carbon cycle simulation were also studied. The LAI assimilated using Dual Ensemble Kalman Filter of MBF and LBF were significantly correlated with the observed LAI, with high R² of 0.81 and 0.91 respectively, and lower RMSE and absolute bias, which represented the great improvement of the accuracy of MODIS LAI products. With the driving of assimilated LAI, the modeled GPP, NEE, and TER were also highly correlated with the flux observation data, with the R² of 0.66, 0.47, and 0.64 for MBF, respectively, and 0.66, 0.45, and 0.73 for LBF, respectively. The accuracy of carbon fluxes modeled with assimilated LAI was higher than that acquired by the locally adjusted cubic-spline capping method, in which, the accuracy of mo-deled NEE for MBF and LBF increased by 11.2% and 11.8% at the most degrees, respectively.

李雪建, 毛方杰, 杜华强, 周国模, 徐小军, 李平衡, 刘玉莉, 崔璐. 双集合卡尔曼滤波LAI同化结合BEPS模型的竹林生态系统碳通量模拟[J]. 应用生态学报, 2016, 27(12): 3797-3806.

LI Xue-jian, MAO Fang-jie, DU Hua-qiang, ZHOU Guo-mo, XU Xiao-jun, LI Ping-heng, LIU Yu-li, CUI lu. Simulating of carbon fluxes in bamboo forest ecosystem using BEPS model based on the LAI assimilated with Dual Ensemble Kalman Filter[J]. Chinese Journal of Applied Ecology, 2016, 27(12): 3797-3806.

参考文献

[1] Sun R, Chen JM, Zhu QJ, et al. Spatial distribution of net primary productivity and evapotranspiration in Changbaishan Natural Reserve, China, using Landsat ETM+ data. Canadian Journal of Rremote Sensing, 2004, 30: 731-742
[2] Xu X-J (徐小军), Zhou G-M (周国模), Du H-Q (杜华强), et al. Interannual variability of Moso bamboo forest GPP and its driving factors: A case study of Anji County. Acta Ecologica Sinica (生态学报), 2016, 36(6): 1-9 (in Chinese)
[3] Zhang T-L (张廷龙), Sun R (孙睿), Zhang R-H (张荣华), et al. Simulation of water and carbon fluxes in Harvard forest area based on data assimilation me-thod. Chinese Journal of Applied Ecology (应用生态学报), 2013, 24(10): 2746-2754 (in Chinese)
[4] Chen JM, Black TA. Defining leaf area index for non-flat leaves. Plant, Cell and Environment, 1992, 15: 421-429
[5] Jonckheere I, Fleck S, Nackaerts K, et al. Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, 2004, 121: 19-35
[6] Xu C, Liu M, An S, et al. Assessing the impact of urbanization on regional net primary productivity in Jiang-yin County, China. Journal of Environmental Management, 2007, 85: 597-606
[7] Ma H, Song JL, Wang JD, et al. Improvement of spatially continuous forest LAI retrieval by integration of discrete airborne LiDAR and remote sensing multi-angle optical data. Agricultural and Forest Meteorology, 2014, 189/190: 60-70
[8] Liu ZL, Chen JM, Jin GZ, et al. Estimating seasonal variations of leaf area index using litterfall collection and optical methods in four mixed evergreen-deciduous fore-sts. Agricultural and Forest Meteorology, 2015, 209/210: 36-48
[9] Chen JM, Cihlar J. Retrieving leaf area index of boreal conifer forests using Landsat TM images. Remote Sensing of Environment, 1996, 55: 153-162
[10] Xiao ZQ, Liang SL, Wang JD, et al. Real-time retrieval of Leaf Area Index from MODIS time series data. Remote Sensing of Environment, 2011, 115: 97-106
[11] Wang D-W (王东伟), Wang J-D (王锦地), Liang S-L (梁顺林). Retrieving crop leaf area index by assimilation of MODIS data into crop growth model. Science China Earth Science (中国科学:地球科学), 2010, 40(1): 73-83 (in Chinese)
[12] Li X-J (李喜佳), Xiao Z-Q (肖志强), Wang J-D (王锦地), et al. Dual Ensemble Kalman Filter assimilation method for estimating time series LAI. Journal of Remote Sensing (遥感学报), 2014, 18(1): 27-44 (in Chinese)
[13] Fang HL, Wei SS, Liang SL. Validation of MODIS and CYCLOPES LAI products using global field measurement data. Remote Sensing of Environment, 2012, 119: 43-54
[14] Quaife T, Lewis P, Dekauwe M, et al. Assimilating canopy reflectance data into an ecosystem model with an Ensemble Kalman Filter. Remote Sensing of Environment, 2008, 112: 1347-1364
[15] Mo XG, Chen JM, Ju WM, et al. Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter. Ecological Modelling, 2008, 217: 157-173
[16] Zhu L, Chen JM, Qin QM, et al. Optimization of ecosystem model parameters using spatio-temporal soil moisture information. Ecological Modelling, 2009, 220: 2121-2136
[17] Zhao YX, Chen SN, Shen SH. Assimilating remote sensing information with crop model using Ensemble Kalman Filter for improving LAI monitoring and yield estimation. Ecological Modelling, 2013, 270: 30-42
[18] Chen X-G (陈先刚), Zhang Y-P (张一平), Zhang X-Q (张小全), et al. Carbon stock changes in bamboo stands in china over the last 50 years. Acta Ecologica sinica (生态学报), 2008, 28(11): 5218-5227 (in Chinese)
[19] Zhou GM, Meng CF, Jiang PK, et al. Review of carbon fixation in bamboo forests in China. Botanical Review, 2011, 77: 262-270
[20] Zheng B-S (郑炳松), Jin A-W (金爱武), Cheng X-J (程晓建), et al. Study on the photosynthetic characte-ristics of Lei bamboo leaves. Journal of Fujian College of Forestry (福建林学院学报), 2001, 21(4): 359-362 (in Chinese)
[21] Lin X-C (林新春), Yuan X-L (袁晓亮), Lin R (林绕), et al. Studies on floral biology of phyllostachys violascens. Journal of Fujian College of Forestry (福建林学院学报), 2010, 30(4): 333-337 (in Chinese)
[22] Liu Y-F (刘玉芳), Chen S-L (陈双林), Li Y-C (李迎春), et al. Environmental stress on physiological plasticity of bamboo: A review. Journal of Zhejiang A&F University (浙江农林大学学报), 2014, 31(3): 473-480 (in Chinese)
[23] Chen Y-F (陈云飞), Jiang H (江洪), Zhou G-M (周国模), et al. Estimation of CO₂ fluxes and its seasonal variations from the effective management Lei bamboo (Phyllostachys violascens). Acta Ecologica Sinica (生态学报), 2013, 33(11): 3434-3444 (in Chinese)
[24] Chen JM, Deng F, Chen MZ. Locally adjusted cubic-spline capping for reconstructing seasonal trajectories of a satellite-derived surface parameter. IEEE Transaction on Geoscience and Remote Sensing, 2006, 44: 2230-2238
[25] Liu YB, Ju WM, Chen JM, et al. Spatial and temporal variations of forest LAI in China during 2000-2010. Chinese Science Bulletin, 2012, 57: 2846-2856
[26] Gu C-Y (谷成燕), Du H-Q (杜华强), Zhou G-M (周国模), et al. Retrieval of leaf area index of Moso bamboo forest with Landsat Thematic Mapper image based on PROSAIL canopy radiative transfer model. Chinese Journal of Applied Ecology (应用生态学报), 2013, 24(8): 2248-2256 (in Chinese)
[27] Sun S-B (孙少波), Du H-Q (杜华强), Li P-H (李平衡), et al. Retrieval of leaf net photosynthetic rate of moso bamboo forests using hyperspectral remote sensing based on wavelet transform. Chinese Journal of Applied Ecology (应用生态学报), 2016, 27(1): 49-58 (in Chinese)
[28] Lu G-F (陆国富), Du H-Q (杜华强), Zhou G-M (周国模), et al. Dynamic change of Phyllostachys edulis forest canopy parameters and their relationships with photosynthetic active radiation in the bamboo shooting growth phase. Journal of Zhejiang A&F University (浙江农林大学学报), 2012, 29(6): 844-850 (in Chinese)
[29] Sun C (孙成), Jiang H (江洪), Zhou G-M (周国模), et al. Variation characteristics of CO₂ flux in Phyllostachys edulis forest ecosystem in subtropical region of China. Chinese Journal of Applied Ecology (应用生态学报), 2013, 24(10): 2717-2724 (in Chinese)
[30] Dickinson RE, Tian YH, Liu Q, et al. Dynamics of leaf area for climate and weather models. Journal of Geophy-sical Research, 2008, 113: 1-10
[31] Huang M (黄玫), Ji J-J (季劲钧), Cao M-K (曹明奎), et al. Modeling study of vegetation shoot and root biomass in China. Acta Ecologica Sinica (生态学报), 2006, 26(12): 4156-4163 (in Chinese)
[32] Jacquemoud S, Baret F. PROSPECT: A model of leaf optical properties spectra. Remote Sensing of Environment, 1990, 34: 75-91
[33] Feret JB, François C, Asner GP, et al. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment, 2008, 112: 3030-3043
[34] Verhoef W. Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model. Remote Sensing of Environment, 1984, 16: 125-141
[35] Verhoef W, Bach H. Coupled soil-leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA ra-diance data. Remote Sensing of Environment, 2007, 109: 166-182
[36] Evensen G. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research: Oceans, 1994, 99: 10143-10162
[37] Evensen G. The Ensemble Kalman Filter: Theoretical formulation and practical implementation. Ocean Dynamics, 2003, 53: 343-367
[38] Running SW, Coughlan JC. A general model of forest ecosystem processes for regional applications. I. Hydrologic balance, canopy gas exchange and primary production processes. Ecological Modelling, 1988, 42: 125-154
[39] Liu J, Chen JM, Cihlar J, et al. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sensing of Environment, 1997, 62: 158-175
[40] Liu J, Chen JM, Cihlar J, et al. Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data. Journal of Geophysical Research: Atmospheres, 1999, 104: 27735-27754
[41] Chen JM, Liu J, Cihlar J, et al. Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications. Ecological Modelling, 1999, 124: 99-119
[42] Liu J, Chen JM, Cihlar J. Mapping evapotranspiration based on remote sensing: An application to Canada’s landmass. Water Resources Research, 2003, 39: 1189-1192
[43] Chen JM, Chen XY, Ju WM, et al. Distributed hydrological model for mapping evapotranspiration using remote sensing inputs. Journal of Hydrology, 2005, 305: 15-39
[44] Farquhar G, Caemmerer Sv, Berry J. A biochemical model of photosynthetic CO₂ assimilation in leaves of C3 species. Planta, 1980, 149: 78-90
[45] Hatfield JL, Thomason IJ. Biometeorology in Integrated Pest Management. New York: Academic Press, 1982
[46] Zhang F-M (张方敏), Ju W-M (居为民), Chen J-M (陈镜明), et al. Study on evapotranspiration in east Asia using the BEPS ecological model. Journal of Natural Resources (自然资源学报), 2010, 25(9): 1596-1606 (in Chinese)
[47] Wang P-J (王培娟), Sun R (孙睿), Zhu Q-J (朱启疆), et al. Improvement on the abilities of BEPS under accidented terrain. Journal of Image and Graphics (中国图象图形学报), 2006, 11(7): 1017-1025 (in Chinese)
[48] Wang P-J (王培娟), Xie D-H (谢东辉), Zhang J-H (张佳华), et al. Application of BEPS model in estimating winter wheat yield in North China Plain. Transactions of the Chinese Society of Agricultural Engineering (农业工程学报), 2009, 25(10): 148-153 (in Chinese)
[49] Feng XF, Liu GH, Chen JM, et al. Net primary productivity of China’s terrestrial ecosystems from a process model driven by remote sensing. Journal of Environmental Management, 2007, 85: 563-573
[50] Wang SQ, Zhou L, Chen JM, et al. Relationships between net primary productivity and stand age for several forest types and their influence on China’s carbon ba-lance. Journal of Environmental Management, 2011, 92: 1651-1662
[51] Huang Q-M (黄启民), Yang D-D (杨迪蝶), Gao A-X (高爱新). A study on photosynthesis of bamboo. Scientia Silvae Sinicae (林业科学), 1989, 25(4): 366-369 (in Chinese)
[52] Wu Z-Z (吴志庄), Du X-H (杜旭华), Xiong D-L (熊德礼), et al. A comparative study on photosynthetic characteristics of different types of bamboos. Ecology and Environmental Sciences (生态环境学报), 2013, 22(9): 1523-1527 (in Chinese)
[53] Zhou GM, Meng CF, Jiang PK, et al. Review of carbon fixation in bamboo forests in China. The Botanical Review, 2011, 77: 262-270
[54] Chen XG, Zhang XQ, Zhang YP, et al. Changes of carbon stocks in bamboo stands in China during 100 years. Forest Ecology and Management, 2009, 258: 1489-1496
[55] Wang J (王仁), Chen T-H (陈财辉), Chen S-Y (陈信佑), et al. Estimating aboveground biomass and carbon sequestration of moso bamboo growth under selection cutting after 2 years. Quarterly Journal China Fores-try (林业研究季刊), 2010, 32(3): 35-44 (in Chinese)
[56] Yen TM. Comparing aboveground structure and above-ground carbon storage of an age series of moso bamboo forests subjected to different management strategies. Journal of Forest Research, 2015, 20: 1-8
[57] Mao FJ, Li PH, Zhou GM, et al. Development of the BIOME-BGC model for the simulation of managed Moso bamboo forest ecosystems. Journal of Environmental Management, 2016, 172: 29-39

双集合卡尔曼滤波LAI同化结合BEPS模型的竹林生态系统碳通量模拟

Simulating of carbon fluxes in bamboo forest ecosystem using BEPS model based on the LAI assimilated with Dual Ensemble Kalman Filter

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics

本文评价