Assimilation of ground measured wheat leaf area index into CERES-wheat model based on Kalman Filter

An approach of assimilating ground measured leaf area index (LAI) into the CERES-Wheat model was developed in this paper. The CERES-Wheat model was used to simulate LAI under the Decision Support System for Agro-Technology Transfer (DSSAT) shell. Interpolation methods were used to solve the matching problem of the time scale between dynamic LAI simulated by the CERES-Wheat model and discrete LAI observed on ground. By comparisons, the interpolated LAIs by using cubic interpolation method based on measured LAI data were better than those of using the nearest neighbor interpolation, linear interpolation and cubic spline interpolation methods, respectively, which were assimilated by using Kalman Filter later. The experimental results showed that combination of the interpolation method and the Kalman Filter algorithm had stable and usable results. Assimilation results of LAI are close to their simulated and measured ones, which are better than the LAI data simulated by the model alone.