1. Assimilating remote sensing-based VPM GPP into the WOFOST model for improving regional winter wheat yield estimation.
- Author
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Zhuo, Wen, Huang, Jianxi, Xiao, Xiangming, Huang, Hai, Bajgain, Rajen, Wu, Xiaocui, Gao, Xinran, Wang, Jie, Li, Xuecao, and Wagle, Pradeep
- Subjects
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EDDY flux , *CROP yields , *CROP growth , *KALMAN filtering , *WINTER wheat , *GRAIN yields - Abstract
Crop growth models are powerful tools for predicting crop growth and yield. Gross primary production (GPP) is a major photosynthetic flux that is directly linked to crop grain yield. To better understand the potential of GPP for regional crop yield estimation, in this study, a novel crop data-model assimilation (CDMA) framework was proposed that assimilates accumulative GPP estimates from the satellite-based vegetation photosynthesis model (VPM) into the WOrld FOod STudies (WOFOST) model using the ensemble Kalman filter (EnKF) algorithm to estimate winter wheat GPP and grain yield. Results showed that the WOFOST simulated GPP agreed with the GPP EC derived from eddy flux tower (R2 = 0.74 and 0.47 in 2015 and 2016, respectively). Assimilating GPP VPM into the WOFOST model improved site-scale GPP estimation (R2 = 0.87 and 0.67 in 2015 and 2016, respectively), and also improved regional-scale winter wheat yield estimates (R2 = 0.36 and 0.29; RMSE= 479 and 572 kg/ha in 2015 and 2016, respectively) compared with the open loop simulations (R2 = 0.14 and 0.10; RMSE= 801 and 788 kg/ha in 2015 and 2016, respectively). Our study demonstrated that assimilation of remotely sensed GPP optimized the results of carbon simulation in the WOFOST model and highlighted the potential of GPP for regional winter wheat yield estimation using a data assimilation framework. • We developed a data-assimilation framework that assimilates remotely sensed GPP data into the WOFOST crop model. • The WOFOST-simulated GPP was strongly related to eddy flux tower simulated GPP. • Assimilating VPM-based GPP into the WOFOST model improved regional-scale winter wheat yield estimation. • A novel ensemble generation method sampled posterior WOFOST parameters to generate WOFOST simulated GPP ensembles. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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