Diurnal and Seasonal Mapping of Water Deficit Index and Evapotranspiration by an Unmanned Aerial System: A Case Study for Winter Wheat in Denmark

Precision irrigation is a promising method to mitigate the impacts of drought stress on crop production with optimal use water resources. However, reliable assessment plant status has not been adequately demonstrated, and unmanned aerial systems (UAS) offer great potential for spatiotemporal improvements. This study utilized UAS equipped multispectral thermal sensors detect quantify in winter wheat (Triticum aestivum L.) using Water Deficit Index (WDI). Biennial field experiments were conducted coarse sand soil Denmark analyses performed at both diurnal seasonal timescales. The WDI was significantly correlated leaf stomatal conductance (R2 = 0.61–0.73), correlation weaker 0.39–0.56) topsoil (the highest R2 0.68). A semi-physical model depicting relationship between fraction transpirable (FTSW) root zone derived 0.74. Moreover, estimates improved an energy balance iterative scheme estimate net radiation land surface temperature, as well dual coefficient. variation revealed pattern ratio actual evapotranspiration, being higher morning, decreasing noon hours ‘recovering’ afternoon. Future work should investigate temporal upscaling which may be used develop methods site-specific recommendations.