Understanding drought stress in winter wheat using UAV thermal and multispectral data

This abstract is for SUPPORT APPLICATION.

Drought is the most significant stress that reduces crop yield, hence, agricultural irrigation is the major consumer of freshwater worldwide. There is everlasting need to improve irrigation applications in order to increase water use efficiency and save water. Conventional methods to estimate crop water status and within-field variability are precise, yet, highly demanding for time and manpower. Remote sensing in the reflective and the emissive spectrum with unmanned aerial vehicle (UAV) holds potential to detect drought stress by observing canopy status over a larger area. A common method to detect drought stress using UAV thermal imagery is the Crop Water Stress Index (CWSI), which does needs improvement and parametrization for cereal crops such as winter wheat.
Field experiment with winter wheat was performed in 24 plots (30 m x 30 m) under three different irrigation regimes in 2018 (drought year) and 2019 (normal year) in Denmark. Thermal and multispectral data on UAV scale were collected during the growth period. Plant physiology, i.e., stomatal conductance, leaf water potential and canopy cover was measured, in addition to soil water content. Crop water deficit was estimated through comparison of the variability of canopy temperature and plant physiological changes. The resulting correlation pointed on clear possibility to quantify crop water status using thermal data, which is useful to develop a site-specific application of irrigation. Further work involves parameterization of CWSI and calculation of and comparison with other indices to test for improvements.