Assimilation of temporal-spatial leaf area index into the CERES- Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation

• Published in: Journal of Integrative Agriculture Vol. 16; no. 10; pp. 2283 - 2299
• Main Authors: LI, He, JIANG, Zhi-wei, CHEN, Zhong-xin, REN, Jian-qiang, LIU, Bin, Hasituya
• Format: Journal Article
• Language: English
• Published: National Meteorological Information Center, China Meteorological Administration, Beijing 100081, P.R.China 01.10.2017; Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China%Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, P.R.China; KeAi Communications Co., Ltd
• Subjects: Crop Environment Resource Synthesis models; crop model; crop yield; data assimilation; ensemble Kalman filter; growing season; Kalman滤波; leaf area index; uncertainty; uncertainty analysis; wheat; winter wheat yield estimates; 不确定性因素; 产量估计; 冬小麦产量; 叶面积指数; 数据同化; 时空尺度; 集合; crop model; leaf area index; winter wheat yield estimates; data assimilation; uncertainty; ensemble Kalman filter
• ISSN: 2095-3119; 2352-3425
• DOI: 10.1016/S2095-3119(16)61351-5

To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for whe...