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基于VPM与MOD17产品的中国农田生态系统总初级生产力估算比较
引用本文:牛忠恩,闫慧敏,陈静清,黄玫,王绍强.基于VPM与MOD17产品的中国农田生态系统总初级生产力估算比较[J].农业工程学报,2016,32(4):191-198.
作者姓名:牛忠恩  闫慧敏  陈静清  黄玫  王绍强
作者单位:1. 中国科学院地理科学与资源研究所,北京 100101; 中国科学院大学资源与环境学院,北京 100049;2. 中国科学院地理科学与资源研究所,北京,100101
基金项目:中国科学院战略性先导科技专项项目(XDA05050602);中国科学院重点部署项目(KSZD-EW-Z-021-02);国家自然科学基金重点项目(41430861)
摘    要:VPM(vegetation photosynthesis model)与PSN(photosynthesis)模型是2个基于MODIS数据估算生态系统总初级生产力(gross primary productivity,GPP)的光能利用率模型,该文对比了VPM和PSN模型在中国农田生态系统估算中的结果并对其差异形成的原因进行了分析。研究表明:1)在位于冬小麦-夏玉米二熟区的中国科学院禹城综合试验站以及种植春玉米的盈科灌区绿洲站,与碳通量观测数据相比,VPM模拟结果分别高估3.82%、12.08%,基于PSN模型利用MODIS数据计算的MOD17产品则分别低估53.35%、63.03%;2)在中国农田生态系统,MOD17产品普遍低于VPM模拟结果,在西北、东北及黄淮海等地区约低于50%以上,在南方地区低于不到30%;3)在中国北方旱作区,MOD17产品与VPM模拟结果呈强相关关系,相关系数为0.85,模型中的最大光能利用率参数是导致MOD17产品在北方旱作种植区低于VPM模拟结果的主要原因。

关 键 词:模型  估算  农作物  最大光能利用率  总初级生产力  VPM  MOD17产品
收稿时间:2015/8/26 0:00:00
修稿时间:1/4/2016 12:00:00 AM

Comparison of crop gross primary productivity estimated with VPM model and MOD17 product in field ecosystem of China
Niu Zhong''en,Yan Huimin,Chen Jingqing,Huang Mei and Wang Shaoqiang.Comparison of crop gross primary productivity estimated with VPM model and MOD17 product in field ecosystem of China[J].Transactions of the Chinese Society of Agricultural Engineering,2016,32(4):191-198.
Authors:Niu Zhong'en  Yan Huimin  Chen Jingqing  Huang Mei and Wang Shaoqiang
Institution:1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China,1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China and 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Abstract:Abstract: Gross primary productivity (GPP) of terrestrial ecosystem is an important variable in studies of climate change and carbon cycle. Accurate estimation of GPP is crucial to understand ecosystem response to climate variability and change. The eddy covariance (EC) technique provides the best approach to measure net carbon dioxide (CO2) change at site scale, which can be employed in GPP calculation. However, the EC technique only provides integrated CO2 flux measurements over footprints with sizes and shapes that vary with the tower height, canopy physical characteristics and wind velocity. Satellite remote sensing has played an increasing role in the characterization of vegetation structure and the estimation of GPP, because it can overcome the lack of extensive flux tower observations in large areas. Among all the predictive methods, the light use efficiency (LUE) model may have the most potential to adequately address the spatial and temporal dynamics of GPP because of its theoretical basis and practicality, such as the vegetation photosynthesis model (VPM) and photosynthesis (PSN) model. The VPM is based on remote sensing and eddy covariance data, and has been validated in 21 sites of 10 kinds of terrestrial ecosystems. The PSN model is utilized to calculate the GPP and net primary productivity product, called MOD17, based on MODIS images provided by Goddard Space Flight Centre, National Aeronautics and Space Administration (NASA) of the USA. The VPM and PSN model have been widely used in the world, however little is known about the differences of the simulation results between these models. In this study, we used the maximum light use efficiency of flux site and PSN model to run the VPM (called FLUX-VPM and PSN-VPM), respectively. Then, we compared the simulation results of FLUX-VPM, PSN-VPM and MOD17 product with flux observation GPP (called Obs-GPP). Results showed that in Yucheng station where winter wheat/maize rotation was adopted and Yingke station where maize was planted, the correlation coefficient (r), root mean square error (RMSE) and modeling efficiency (EF) between GPP estimated by FLUX-VPM and Obs-GPP were 0.92, 1.30 g/(m2·a), 0.84 and 0.97, 1.13 g/(m2·a), 0.91, respectively, and GPP values were overestimated by 3.8% and 12.1%, respectively. The r, RMSE and EF between GPP estimated by PSN-VPM and Obs-GPP were 0.91, 2.66 g/(m2·a), 0.31 and 0.96, 3.30 g/(m2·a), 0.27, respectively, and GPP values were underestimated by 59.9% and 52.8%, respectively. The r, RMSE and EF between GPP from MOD17 product and Obs-GPP were 0.90, 2.87 g/(m2·a), 0.32 and 0.97, 2.75 g/(m2·a), 0.49, respectively, and GPP values were underestimated by 54.3% and 63.0%, respectively. PSN-VPM and MOD17 product used the same maximum light use efficiency, while the difference existed in the model structure and input data. Meanwhile, PSN-VPM and FLUX-VPM were only difference in the maximum light use efficiency. GPP values estimated with PSN-VPM and MOD17 product were almost the same, which had substantial underestimation of GPP compared with FLUX-VPM and Obs-GPP. It suggested that the maximum light use efficiency may be the primary cause of underestimation of MOD17 product compared to FLUX-VPM. In the regional scale, the GPP values of MOD17 product had considerably underestimated compared to the ones estimated by VPM. Serious underestimation mainly occurred in the Northwest, Northeast and Huang-Huai-Hai Regions of China, with an underestimation of more than 50%. While in southern China the underestimation was below 30%. MOD17 product and GPP estimated by VPM had good positive correlation in dry-farming land of northern China with correlation coefficient of 0.85, while in northern paddy field, southern dry-farming land, and southern paddy field with weak correlation coefficient of 0.46, 0.14 and 0.10, respectively. The deviation from GPP estimated by the VPM and MOD17 product in northern China was almost the same as the error which caused by the maximum light use efficiency in site scale, and GPP estimated by the VPM were linearly associated with MOD17 product in northern dry-farming land of China. So we can presume that the maximum light use efficiency is probably the primary cause of the underestimation of MOD17 product in dry-farming land of northern China, compared to GPP estimated by the VPM. Last, the uncertainty of different models needs further studies in northern paddy field, southern dry-farming land, and southern paddy field in China.
Keywords:models  estimation  crops  maximum light use efficiency  gross primary productivity  VPM  MOD17 product
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