Abstract
A variety of spectral vegetation indices (SVIs) have been constructed to monitor crop water stress. However, their abilities to reflect dynamic canopy water content (CWC) and vegetation water content (VWC) during the growing season have not been concurrently examined, and the underlying mechanisms remain unclear, especially in relation to soil drying. In this study, a field experiment was conducted and designed with various irrigation regimes applied during two consecutive growing seasons of maize. The results showed that CWC, VWC, and the SVIs exhibited obvious trends of first increasing and then decreasing within a growing season. In addition, VWC was allometrically related to CWC across the two growing seasons. A linear relationship between the five SVIs and CWC occurred within a certain CWC range (0.01–0.41 kg m−2), while the relationship between these SVIs and VWC was nonlinear. Furthermore, the five SVIs indicated critical values for VWC, and these values were 1.12 and 1.15 kg m−2 for the water index (WI) and normalized difference water index (NDWI), respectively; however, the normalized difference infrared index (NDII), normalized difference vegetation index (NDVI), and optimal soil-adjusted vegetation index (OSAVI) had the same critical value of 0.55 kg m−2. Therefore, in comparison to the NDII, NDVI, and OSAVI, the WI and NDWI better reflected the crop water content based on their sensitives to CWC and VWC. Moreover, CWC was the most important direct biotic driver of the dynamics of SVIs, while leaf area index (LAI) was the most important indirect biotic driver. VWC was a critical indirect regulator of WI, NDWI, NDII, and OSAVI dynamics, whereas vegetation dry mass (VDM) was the critical indirect regulator of NDVI dynamics. These findings may provide additional information for estimating agricultural drought and insights on the impact mechanism of soil water deficits on SVIs.
Highlights
Leaves are an essential component of plant canopy structure, and the water in leaves has a profound effect on photosynthesis, transpiration, and other physiological processes [1].In addition, water storage in the stem provides a buffer between root water uptake and leaf transpiration [2]
The results indicated that, in comparison to the normalized difference vegetation index (NDVI) and optimal soil-adjusted vegetation index (OSAVI), the water index (WI), normalized difference water index (NDWI), and normalized difference infrared index (NDII) were better able to capture canopy water content (CWC) variations during soil drying
Our results showed that CWC was better represented by the WI, NDWI, and NDII than the NDVI and OSAVI (Figure 5)
Summary
Leaves are an essential component of plant canopy structure, and the water in leaves has a profound effect on photosynthesis, transpiration, and other physiological processes [1].In addition, water storage in the stem provides a buffer between root water uptake and leaf transpiration [2]. Leaves are an essential component of plant canopy structure, and the water in leaves has a profound effect on photosynthesis, transpiration, and other physiological processes [1]. Canopy water content (CWC), the total mass of water in all plant leaves per unit of ground area, is commonly applied to monitor plant growth [14,15,16]. Vegetation water content (VWC), the total amount of water in stems and leaves per unit of ground area, is a critical and indirect parameter for retrieving soil moisture from remote sensing data [17,18]. As CWC is sensitive to different water-deficit treatments, it is an optimum indicator for monitoring crop water stress [19]. CWC accounts for only a fraction of the total plant water content, and the largest unknown for predicting
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