Integrating Diurnal Physiological and Structural Variations in SIF for Enhanced Daily Drought Detection in Maize

Daily water stress reflects the water stress status of crops on a specific day, which is crucial for studying drought progression and guiding precision irrigation. However, accurately monitoring the daily water stress remains challenging, particularly when eliminating the impact of historical stress and normal growth. Recent studies have demonstrated that the diurnal characteristics of the crop canopy obtained via remote sensing techniques can be used to assess daily water stress levels effectively. Remote sensing observations, such as the solar-induced chlorophyll fluorescence (SIF) and reflectance, offer information on the crop canopy structure, physiology, or their combination. However, the sensitivity of different structural, physiological, or combined remote sensing variables to the daily water stress remains unclear. We investigated this issue via continuous measurements of the active fluorescence, leaf rolling, and canopy spectra of maize under different irrigation conditions. The results indicated that with increasing water stress, vegetation exhibited significant coordinated diurnal variations in both structure and physiology. The influence of water stress was minimal in the morning but peaked at noon. The morning-to-noon ratio (NMR) of the apparent SIF yield (SIFy), in which only the effect of the photosynthetically active radiation (PAR) is eliminated and in which both structural and physiological information is incorporated, exhibited the highest sensitivity to water stress variations. This NMR of the SIFy was followed by the NMR of the normalized difference vegetation index (NDVI) and the NMR of the canopy fluorescence emission efficiency (ΦFcanopy) obtained via the fluorescence correction vegetation index (FCVI) method, which primarily reflect structural and physiological information, respectively. This study highlights the advantages of utilizing diurnal vegetation structural and physiological variations for monitoring daily water stress levels.