Near-infrared radiance of vegetation is more sensitive than vegetation indices for monitoring NPP of winter wheat under water stress

The quantification of NPP plays a crucial role in ensuring food security. Previous studies have established a noteworthy correlation between the near-infrared radiance of vegetation (NIRv,Rad) and NPP. However, limited research has been conducted to investigate the impact of droughgt on the relationship between NPP and NIRv,Rad. To address this gap, we constructed four distinct water stress gradients (well-watered, mild, moderate, and severe) to assess the effectiveness of NIRv,Rad in monitoring drought-induced variations in NPP for winter wheat. The results indicated that NIRv,Rad exhibited higher sensitivity to water stress compared to traditional vegetation indices (VIs) like the NIR reflectance of vegetation (NIRv,Ref), enhanced vegetation index-2 (EVI2), and normalized difference vegetation index (NDVI), which provided confidence in the capacity of NIRv,Rad as a tool for drought monitoring. NIRv,Rad can accurately estimate NPP at both hourly and daily scales under different water stresses. This advantage was more pronounced at hourly scales compared to NIRv,Ref, EVI2 and NDVI. NIRv,Rad proved to be a superior indicator of NPP compared to VIs under water stresses. Our work introduces a novel approach for accurately and easily estimating NPP under different water stress levels and time scales.