In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interaction...In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.展开更多
To compare the grain yield and growth behaviors of hybrid rice, field experiments were conducted in a subtropical environment in Changsha, Hunan Province, China, and in two tropical environments in Gazipur and Habigan...To compare the grain yield and growth behaviors of hybrid rice, field experiments were conducted in a subtropical environment in Changsha, Hunan Province, China, and in two tropical environments in Gazipur and Habiganj in Bangladesh during 2009 to 2011. Three hybrid rice cultivars were grown under three nitrogen （N） management treatments in each experiment. The results showed that grain yield was significantly affected by locations, N treatments and their interaction but not by cultivars. Changsha produced 8-58% higher grain yields than Bangladesh locations. Sink size （spikelet number per unit land area） was responsible for these yield differences. Larger panicle size （spikelet number per panicle） contributed to greater sink size in Changsha. Aboveground total biomass was greater in Changsha than in Bangladesh locations, whereas harvest index was higher in Bangladesh locations than in Changsha. Crop growth rate （CGR） was greater at Changsha than Bangladesh locations during vegetative phase, while the difference was relatively small and not consistent during the later growth phases. Higher leaf area index and leaf area duration were partly responsible for the greater CGR in Changsha. Real-time N management （RTNM） produced lower grain yields than fixed-time N management in more than half of the experiments. Our study suggested that further improvement in rice yield in the tropical environments similar to those of Bangladesh will depend mainly on the ability to increase panicle size as well as CGR during vegetative phase, and the chlorophyll meter threshold value used in RTNM needs to be modified according to environmental conditions and cultivar characteristics to achieve a desirable grain yield.展开更多
Leaf area index (LAI) is an important parameter in monitoring crop growth. One of the methods for retrieving LAI from remotely sensed observations is through inversion of canopy reflectance models. Many model inversio...Leaf area index (LAI) is an important parameter in monitoring crop growth. One of the methods for retrieving LAI from remotely sensed observations is through inversion of canopy reflectance models. Many model inversion methods fail to account for variable LAI values at different crop growth stages. In this research, we use the crop growth model to describe the LAI changes with crop growth, and consider a priori LAI values at different crop growth stages as constraint information. The key approach of this research is to assimilate multiple canopy reflectance values observed at different growth stages and a priori LAI values into a coupled crop growth and radiative transfer model sequentially using a variational data assimilation algorithm. Adjoint method is used to minimize the cost function. Any other information source can be easily incorporated into the inversion cost function. The validation results show that the time series of MODIS canopy reflectance can greatly reduce the uncertainty of the inverted LAI values. Compared with MODIS LAI product at Changping and Shunyi Counties of Beijing, this method has significantly improved the estimated LAI temporal profile.展开更多
基金supported by the National Basic Research Program under Grant Nos.2010CB428403, 2010CB951001, and 2009CB421407the National Natural Science Foundation of China under Grant Nos. 41075062 and 40821092
文摘In this study, the Crop Estimation through Resource and Environment Synthesis model （CERES3.0） was coupled into the Biosphere-Atmosphere Transfer Scheme （BATS）, which is called BATS CERES, to represent interactions between the land surface and crop growth processes. The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models. Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2. Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions, but also the feedbacks to land surface processes. For quantitative evaluation of the effects of crop growth and development on surface fluxes in China, two numerical experiments were conducted over continental China： one by BATS CERES and one by the original BATS. Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation, which lead to less canopy interception, vegetation transpiration, total evapotranspiration, top soil moisture, and more soil evaporation, surface runoff, and root zone soil moisture. These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region. In addition, the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture, hence improve the simulation of land surface fluxes.
基金supported by the National Basic Research Program of China (2009CB118603)the Green Super Rice (GSR) Project from the International Rice Research Institute (IRRI) for South Asia+1 种基金Project was completed through the generous cooperation of Hunan Agricultural University, Changsha, Hunan, Chinathe Bangladesh Rice Research Institute (BRRI)
文摘To compare the grain yield and growth behaviors of hybrid rice, field experiments were conducted in a subtropical environment in Changsha, Hunan Province, China, and in two tropical environments in Gazipur and Habiganj in Bangladesh during 2009 to 2011. Three hybrid rice cultivars were grown under three nitrogen （N） management treatments in each experiment. The results showed that grain yield was significantly affected by locations, N treatments and their interaction but not by cultivars. Changsha produced 8-58% higher grain yields than Bangladesh locations. Sink size （spikelet number per unit land area） was responsible for these yield differences. Larger panicle size （spikelet number per panicle） contributed to greater sink size in Changsha. Aboveground total biomass was greater in Changsha than in Bangladesh locations, whereas harvest index was higher in Bangladesh locations than in Changsha. Crop growth rate （CGR） was greater at Changsha than Bangladesh locations during vegetative phase, while the difference was relatively small and not consistent during the later growth phases. Higher leaf area index and leaf area duration were partly responsible for the greater CGR in Changsha. Real-time N management （RTNM） produced lower grain yields than fixed-time N management in more than half of the experiments. Our study suggested that further improvement in rice yield in the tropical environments similar to those of Bangladesh will depend mainly on the ability to increase panicle size as well as CGR during vegetative phase, and the chlorophyll meter threshold value used in RTNM needs to be modified according to environmental conditions and cultivar characteristics to achieve a desirable grain yield.
基金supported by the National Natural Science Foundation of China (Grant Nos. 40871163, 40571107)the Beijing Natural Science Foundation (Grant No. 4083035)+1 种基金the National Basic Research Program of China (Grant No. 2007CB714407)the Program for Key International Science and Tech-nique Cooperation Project of China (Grant No. 2004DFA06300)
文摘Leaf area index (LAI) is an important parameter in monitoring crop growth. One of the methods for retrieving LAI from remotely sensed observations is through inversion of canopy reflectance models. Many model inversion methods fail to account for variable LAI values at different crop growth stages. In this research, we use the crop growth model to describe the LAI changes with crop growth, and consider a priori LAI values at different crop growth stages as constraint information. The key approach of this research is to assimilate multiple canopy reflectance values observed at different growth stages and a priori LAI values into a coupled crop growth and radiative transfer model sequentially using a variational data assimilation algorithm. Adjoint method is used to minimize the cost function. Any other information source can be easily incorporated into the inversion cost function. The validation results show that the time series of MODIS canopy reflectance can greatly reduce the uncertainty of the inverted LAI values. Compared with MODIS LAI product at Changping and Shunyi Counties of Beijing, this method has significantly improved the estimated LAI temporal profile.
