Hyperspectral remote sensing for growth-stage-specific water use in wheat

Precise application of irrigation water to crops requires an accurate calculation of daily crop evapotranspiration (ET), which has always remained a challenge to the scientific community. Reflectance-based crop coefficients approach has a strong theoretical base, as both the crop coefficient [ratio of actual crop (ETc) and reference ET (ET0)] and remote sensing of crop follow a similar response curve mediated by crop growth stages and crop health conditions. This paper investigates the feasibility of linking the evolution of basal crop coefficient (Kcb) of wheat to the hyperspectral remote sensing derived vegetation indices, through leaf area index (LAI), the principal plant growth parameter. Two years field experiments were conducted with three cultivars of wheat (Triticum aestivum L.) under adequate (6-cm each irrigation) and limited (4-cm each irrigation) water supply. Ground based observations on profile water balance components, hyperspectral remote sensing, fractional ground coverage, LAI, water potential and relative water content in leaves were monitored periodically. Biomass and yields were recorded at harvest. Limited water application forced the crop to attain its peak crop coefficients and LAI values early (at flowering, 80–95 DAS), compared to at milking stage (90–105 DAS) under adequate water supply. Basal crop coefficients (Kcb), indicative of transpiration in plants were able to generate a better estimate of the stage-specific crop water use. The prospect of its retrieval through hyperspectral remote sensing was demonstrated. A reduction in Kcb could be primarily due to reduction in LAI in wheat, especially when soil moisture was not a limiting factor. Exclusion of residual evaporation and minimizing background effect of soil made the evolution of Kcb similar to LAI and LAI similar to Soil Adjusted Vegetation Index (SAVI). These imply that the transpiration and light absorption profile of the crop increase or decrease with nearly the same rate throughout its growth period. The LAI saturated at a value of 3 in limited and 4 in adequate irrigation treatments suggesting that once the canopy coverage is complete, further increase in LAI might not lead to an increase in single crop coefficient values. Interestingly, SAVI showed a linear response to Kcb, and also did not saturate before the LAI reached to 4.5 (LAI > 4.0 is reported in full developed canopies of wheat). This makes SAVI superior than NDVI (Normalized Difference Vegetation Index), which saturates at LAI > 3.5, for retrieving crop coefficient; and improving the accuracy in predicting crop water use at specific stages. These relations have high potential at an operational scale for irrigation scheduling over extended wheat growing areas like Indo-Gangetic Plains, through use of high resolution earth observation satellite data.

► Basal crop coefficient of wheat is linked to hyperspectral remote sensing data.
► Hyperspectral NDWI at 1241 nm is able to monitor plant water status.
► Soil Adjusted Vegetation Index is better in crop coefficient retrieval.
► Leaf area index–SAVI–Kcb relations can be used for stage-specific irrigation in wheat.