Abstract:Biomass and crop water use efficiency (CWUE) are important indicators to reflect plant growth productivity and quality, and their accurate real-time acquisition is the guarantee to achieve accurate agricultural management. To assess the feasibility of unmanned aerial vehicle (UAV) remote sensing platform combined with water use efficiency growth models to estimate crop biomass and CWUE, the silage maize was employed as the research object. The key crop parameter transpiration coefficient (kt) estimated based on the multispectral image of the high-resolution space-time UAV was firstly inputted into two simple water efficiency models to fit the WUE and WP* of the silage maize under different water stress conditions, and then the biomass of silage maize under the same and different water conditions was estimated by the fitted WUE and WP* values. The results showed that the correlation between the biomass and ∑Tc,adj and ∑ktkswkst based on the multispectral UAV platform combined with meteorological and soil water content data reached extremely significant level (P<0.001). Under the different stress conditions, the lowest determinant coefficients of fitted WUE and WP* were 0.92 and 0.93, respectively. Under the same water stress condition, the accuracy of biomass estimation by using the fitted WUE and WP* values was almost the same, which was shown in the following aspects: in the V-R4 growth period of maize, the accuracy of biomass estimation based on the fitted WUE indicating with RMSE was 126g/m2, d was 0.98, the accuracy of biomass estimation based on the fitted WP* indicating with RMSE was 91.7g/m2, d was 0.98, but the accuracy was not high in the R5-R6 growth period. When WUE and WP* values were used to estimate biomass under different water stress conditions, WUE was susceptible to water stress with low accuracy (RMSE was 306g/m2, d was 0.93), while WP* had higher accuracy (RMSE was 195g/m2,d was 0.97). At the same time, the spatial distribution maps of WUE, WP* and biomass on the field scale were obtained based on the multispectral remote sensing image of UAV. Overall, the combination of UAV remote sensing platform and crop growth model can well estimate the field silage maize biomass and water use efficiency.