Near-Infrared Radiance of Vegetation is More Sensitive Than Vegetation Indices for Monitoring NPP of Winter Wheat Under Water Stress

The quantification of net primary productivity (NPP) plays a crucial role in ensuring food security. Previous studies have established a noteworthy correlation between the near-infrared radiance of vegetation (NIR
_v,Rad
) and NPP. However, limited research has been conducted to investigate the impact of drought on the relationship between NPP and NIR
_v,Rad
. To address this gap, we constructed four distinct water stress gradients (well-watered, mild, moderate, and severe) to assess the effectiveness of NIR
_v,Rad
in monitoring drought-induced variations in NPP for winter wheat. The results indicated that NIR
_v,Rad
exhibited higher sensitivity to water stress compared to traditional vegetation indices (VIs) like the NIR reflectance of vegetation (NIR
_v,Ref
), enhanced vegetation index-2 (EVI2), and normalized difference vegetation index (NDVI), which provided confidence in the capacity of NIR
_v,Rad
as a tool for drought monitoring. NIR
_v,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 NIR
_v,Ref
, EVI2, and NDVI. NIR
_v,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.