Comparison of satellite-based models for estimating gross primary productivity in agroecosystems

Jiang，Shouzheng1; Zhao，Lu1; Liang，Chuan1; Cui，Ningbo1,2; Gong，Daozhi3; Wang，Yaosheng3; Feng，Yu4; Hu，Xiaotao2; Zou，Qingyao1

2021-02-15

10.1016/j.agrformet.2020.108253

AGRICULTURAL AND FOREST METEOROLOGY   影响因子和分区

0168-1923

1873-2240

Satellite-based gross primary productivity (GPP) models have been widely used for simulating carbon exchanges of terrestrial ecosystems. However, the performances of various GPP models in agroecosystems have been rarely explored. In this study, we calibrated the model parameters and compared the performances of seven light use efficiency (LUE-GPP) models and five vegetation-index (VI-GPP) models for simulating daily GPP of agroecosystems over 106 crop growing seasons, and examined the effects of model structure on model performance. The simulations were carried out based on 19 eddy covariance (EC) sites from the global flux network and vegetation indices obtained from MODIS. The calibrated potential LUE (ε) for C crop (summer maize, 2.59±0.94 g C MJ) was higher than that for C crops (1.42±0.58 g C MJ) in any LUE-GPP models. The performances of models differed across the crops. Generally, all models performed better for C crops than C crops, and for winter crops (winter wheat-Triticum aestivum L, rape-Brassica napus L, and winter barley-Hordeum vulgare L) than summer crops (summer maize-Zea mays L, potato-Solanum tuberosum L, rice-Oryza sativa L. and soybean-Glycine max (L.) Merr.). Cloudiness index-LUE (CI-LUE) model outperformed the other LUE-GPP models, and vegetation index (VEI) model outperformed the other VI-GPP models. LUE-GPP models demonstrated better performance than VI-GPP models due to the inclusion of water stress (W) and temperature stress (T). A comparison of the model structures showed that models only considering the effects of W produced smaller errors than those only considering the effects of T in simulating GPP. W algorithms generated the larger variations in LUE-GPP models compared to those of T, especially during the drought period. All models obtained higher R and smaller errors using the minimum method (Min (T, W)) than using the multiplication method (T × W) to integrate the effects of T and W on GPP, which suggested that the minimum method was better than the multiplication method to integrate T and W on LUE. These results showed that satellite-based models with calibrated crop-specific parameters have the potential to serve as the basis for estimation of agroecosystem GPP, and can provide direction for future model structure optimization.

Agroecosystem Eddy covariance (EC) Gross primary productivity (GPP) models Light use efficiency (LUE) Remote sensing

SCI

英语

其他

National Natural Science Foundation of China[51922072,51779161,51009101] ; Fundamental Research Funds for the Central Universities["2016C DDY-504-SCU","2017CDLZ-N22","2018CDPZH-10"]

Agriculture ; Forestry ; Meteorology & Atmospheric Sciences

Agronomy ; Forestry ; Meteorology & Atmospheric Sciences

WOS:000608676000019

ELSEVIER

AGRICULTURAL SCIENCES

2-s2.0-85097546440

Scopus

1.State Key Laboratory of Hydraulics and Mountain River Engineering & College of Water Resource and Hydropower,Sichuan University,Chengdu,China
2.Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas,Ministry of Education,Northwest A & F University,China
3.State Engineering Laboratory of Efficient Water Use of Crops and Disaster Loss Mitigation,Institute of Environment and Sustainable Development in Agriculture,Chinese Academy of Agriculture Science,China
4.School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,China

Jiang，Shouzheng,Zhao，Lu,Liang，Chuan,et al. Comparison of satellite-based models for estimating gross primary productivity in agroecosystems[J]. AGRICULTURAL AND FOREST METEOROLOGY,2021,297.

Jiang，Shouzheng.,Zhao，Lu.,Liang，Chuan.,Cui，Ningbo.,Gong，Daozhi.,...&Zou，Qingyao.(2021).Comparison of satellite-based models for estimating gross primary productivity in agroecosystems.AGRICULTURAL AND FOREST METEOROLOGY,297.

Jiang，Shouzheng,et al."Comparison of satellite-based models for estimating gross primary productivity in agroecosystems".AGRICULTURAL AND FOREST METEOROLOGY 297(2021).