## 4 Discussion
### Methods for Monitoring Changes in NPP Dynamics during Drought Events  
Currently, most research on NPP focuses on monitoring annual and monthly changes, and NPP variations at smaller timescales have not been considered. The impact of drought on vegetation is rapid and persistent. Monthly and annual studies cannot reflect the process changes in vegetation during drought events, resulting in an insufficient understanding of the relationship between drought and vegetation productivity. Our research improves time precision by analyzing the ability of SIF to monitor NPP dynamics during drought events on an 8-day time scale to better reveal the impact of drought on NPP and analyze the ability of SIF to monitor NPP dynamics during drought events.  
In current research on the correlation between drought and NPP, several methods have been proposed to discuss the impact of drought on NPP. [PERSON] et al. proposed a method to quantitatively evaluate the effects of different drought levels on grassland productivity using the Biome-BGC process model [57]. [PERSON] et al. used [PERSON]'s trend analysis to examine the changes in vegetation NPP, climate factors, and drought over time series. Based on the Mann-Kendall test for the significance of [PERSON]'s trend, the authors also analyzed the response of vegetation NPP to climate factors and drought in different seasons, as well as their lag relationships. Vegetation dynamics in Central Asia were analyzed from 1982 to 2020 and the response of vegetation to climate factors and drought with a time lag was evaluated. [PERSON] et al. used the Lund-Potsdam-Jena model and NDVI to simulate the spatial distribution pattern and temporal trend in forest NPP in the Yangtze River Basin from 1982 to 2013 and discussed the impact of climate change and human activities on NPP through simple linear regression [55]. Additionally, the spatial efficiency metric (SPAEF) model can also be used to analyze the dynamic changes in NPP during drought events [70]. Our study proposes the use of the SIF/NPP ratio index to monitor the dynamic changes in NPP during drought events. This index is derived from previous research on the linear relationship between SIF and GPP, as well as the ratio between GPP and NPP [42]. In the absence of a clear linear relationship between SIF and NPP, the SIF/NPP ratio can quantify the linear relationship between SIF and NPP, and the dynamic changes in this relationship are intuitively reflected through the variations in the SIF/NPP ratio. In our study, the temporal series of SIF/NPP exhibited pronounced seasonality, consistent with current research on the relationship between SIF and vegetation productivity [49]. The SIF/NPP ratio showed significant fluctuations during spring and summer, which could be attributed to the influence of climatic factors such as precipitation and temperature during the growing season on the linear relationship between SIF and NPP. Additionally, variations in vegetation canopy structure, chlorophyll content, and different vegetation types can also impact the response to climate factors [43; 44; 67]. Therefore, when conducting research on the correlation between SIF and NPP, seasonal changes should be thoroughly considered.