Grasslands cover approximately one-fourth of the land in the world and play a crucial role in the carbon cycle. Therefore, quantifying the gross primary productivity (GPP) of grasslands is crucial to assess the sustainable development of terrestrial ecosystems. Drought is a widespread and damaging natural disaster worldwide, which introduces uncertainties in estimating GPP. Solar-induced chlorophyll fluorescence (SIF) is considered as an effective indicator of vegetation photosynthesis and provides new opportunities for monitoring vegetation growth under drought conditions. In this study, using downscaled GOME-2 SIF satellite products and focusing on the drought event in the Xilingol grasslands in 2009, the ability of SIF to evaluate the variations in GPP due to drought was explored. The results showed that the anomalies of SIF in July–August exhibited spatiotemporal characteristics similar to drought indicators, indicating the capability of SIF in monitoring drought. Moreover, the determination coefficient (R²) between SIF and GPP reached 0.95, indicating that SIF is a good indicator for estimating GPP. Particularly under drought conditions, the relationship between SIF and GPP (R² = 0.90) was significantly higher than NDVI and GPP (R² = 0.62), demonstrating the superior capability of SIF in tracking changes in grassland photosynthesis caused by drought compared to NDVI. Drought reduces the ability of NDVI to monitor GPP but does not affect that of SIF to monitor GPP. Our study provides a new approach for accurately estimating changes in GPP under drought conditions and is of significant importance for assessing the carbon dynamics of ecosystems.

Accurate quantification of net primary productivity (NPP) is key to estimating vegetation productivity and studying the global carbon cycle. However, C3 and C4 plants vary in their living environments and potential productivity due to their different photosynthetic pathways. This study thus explored the potential of the near-infrared radiance of vegetation (NIR_v,Rad) to track hourly and daily changes in C3 and C4 plants and investigate whether their photosynthetic pathways affect the relationship between NPP and NIR_v,Rad. Statistics including long-term spectral data, the growth environment, and physiological indicators were collected using an automatic spectral monitoring system. The vegetation index NIR_v,Rad was extracted from the collected spectral data and NPP was calculated using the collected net photosynthetic rate and leaf area index. The results showed that NIR_v,Rad can effectively respond to NPP changes in C3 and C4 plants on hourly and daily scales. The NPP–NIR_v,Rad relationship on the hourly scale was superior, with R² values for winter wheat and summer maize of 0.81 and 0.70, respectively. Furthermore, when the accumulation of NPP was equal, the NIR_v,Rad of summer maize showed larger changes, indicating that it was more sensitive to NPP change for this species than for winter wheat. Overall, the study demonstrated that NIR_v,Rad can serve as an effective proxy indicator of NPP. In addition, this study provides a theoretical basis and scientific guidance for the construction of new simple models and realizing efficient agriculture, as well as a new method for rapid and accurate quantification of the NPP of C3 and C4 plants at geospatial scales in future research.