Remote Estimation of Leaf Water Concentration in Winter Wheat under Different Nitrogen Treatments and Plant Growth Stages

Hyperspectral remote sensing can quickly, nondestructively and accurately monitor crop water concentration and provide technical support for winter wheat growth monitoring, drought assessment, and variable irrigation. In this study, canopy spectral reflectance, leaf water concentration (LWC), leaf nitrogen concentration (LNC), leaf area index (LAI), and leaf dry matter (LDM) of four wheat cultivars were measured under different irrigation and nitrogen treatments, and the effects of nitrogen treatment and growth period on spectral reflectance and LWC were analyzed. Canopy spectral reflectance for different growth periods, irrigation, and nitrogen treatments showed significant changes, leading to the phenomena of “nitrogen treatment differentiation” and “growth period differentiation” for the normalized difference spectral index [NDSI (762, 1458, 2301)] and normalized difference infrared index (NDII) monitoring models. To reduce the influence of nitrogen treatment and growth period on the LWC estimation model, a modified normalized difference water index (mNDWI) was constructed by introducing the nitrogen factor (ratio of left and right peak area, RIDA) into the optimized combination of water-sensitive bands [ND (815, 1080), ND (1585, 1740), and ND (2030, 2260)]. Compared with NDSI (762, 1458, 2301), the R 2 of mNDWI was improved by 36.2%–41.1% under different nitrogen levels and 18.6%–22.4% in different growth periods; this effectively reduced the impact of nitrogen status on LWC monitoring and realized the unified modeling and accurate inversion of LWC for the entire growth period. The new index mNDWI, especially mNDWI (815, 1080) and mNDWI (2030, 2260), can effectively monitor the LWC status of wheat under different cultivation conditions, which is important for the real-time diagnosis of plant moisture to guide precision field irrigation applications.