Regional yield estimation of summer maize based on assimilation of remotely sensed LAI into EPIC model

In order to acquire more accurate crop yield information, the global optimization algorithm SCE-UA was used to integrate leaf area index derived from remote sensing with crop growth model EPIC to simulate regional summer maize yield and field management information in Huanghuaihai Plain in China. The results showed that the mean relative error of estimated summer maize yield was 4.37% and RMSE was 0.44t/ha. Compared with the actual field observation data, the mean relative error of simulated sowing date, plant density and net nitrogen fertilization application rate was 1.85%, -7.78% and -10.60% respectively. These above simulated results could meet need of accuracy of crop growth simulation and yield estimation at regional scale. It was proved that integrating remotely sensed LAI with EPIC model based on SCE-UA for simulating regional summer maize yield and field management information was feasible and reliable.