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	Uncertainty in simulating gross primary production of cropland ecosystem from satellite-based models
	Yuan W. P.; Cai, W. W.; Nguy-Robertson, A. L.; Fang, H. J.; Suyker, A. E.; Chen, Y.; Dong, W. J.; Liu, S. G.; Zhang, H. C.
	2015
关键词	Light use efficiency MODIS EC-LUE MODIS-GPP VPM Maize Soybean leaf-area index net primary productivity global food security use efficiency climate-change terrestrial ecosystems soil-moisture modis evapotranspiration vegetation
英文摘要	Accurate estimates of gross primary production (GPP) for croplands are needed to assess carbon cycle and crop yield. Satellite-based models have been developed to monitor spatial and temporal GPP patterns. However, there are still large uncertainties in estimating cropland GPP. This study compares three light use efficiency (LUE) models (MODIS-GPP, EC-LUE, and VPM) with eddy-covariance measurements at three adjacent AmeriFlux crop sites located near Mead, Nebraska, USA. These sites have different croprotation systems (continuous maize vs. maize and soybean rotated annually) and water management practices (irrigation vs. rainfed). The results reveal several major uncertainties in estimating GPP which need to be sufficiently considered in future model improvements. Firstly, the C4 crop species (maize) shows a larger photosynthetic capacity compared to the C3 species (soybean). LUE models need to use different model parameters (i.e., maximal light use efficiency) for C3 and C4 crop species, and thus, it is necessary to have accurate species-distribution products in order to determine regional and global estimates of GPP. Secondly, the 1 km sized MODIS fPAR and EVI products, which are used to remotely identify the fraction of photosynthetically active radiation absorbed by the vegetation canopy, may not accurately reflect differences in phenology between maize and soybean. Such errors will propagate in the GPP model, reducing estimation accuracy. Thirdly, the water-stress variables in the remote sensing models do not fully characterize the impacts of water availability on vegetation production. This analysis highlights the need to improve LUE models with regard to model parameters, vegetation indices, and water-stress inputs. (C) 2015 Elsevier B.V. All rights reserved.
出处	Agricultural and Forest Meteorology
卷	207
页	48-57
收录类别	SCI
语种	英语
ISSN号	0168-1923
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/39014]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Yuan W. P.,Cai, W. W.,Nguy-Robertson, A. L.,et al. Uncertainty in simulating gross primary production of cropland ecosystem from satellite-based models. 2015.

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