## 4 Discussions
### Pros and Cons of F760 tot for Drought Monitoring  
The first main result lied in that F760 tot and F760 toc were better than the NDVI at early drought monitoring, which is consistent with previous research such as that by [PERSON] et al. [7] and [PERSON] et al. [14]. On this basis, it was further found that both F760 tot and F760 toc had the advantage of early crop drought monitoring, and they exhibited similar responses to the onset of a drought (Figures 4b,c, 10 and 11). SIFtot was downscaled from the canopy to leaf level and outperformed SIFtoc at estimating the GPP [15]. In general, it should be less influenced by canopy structures and more closely related to the plant physiology, which was consistent with the results of Figure 8. The reason for the similar response of these two is that it was incapable of capturing the onset of a drought earlier in time compared with SIFtoc as observed in nadir viewing, because the latter was representative among different observation directions due to its effectiveness in removing the directional effects and reducing the uncertainties induced by varying sun-target-sensor geometries [18]. However, although the response times of F760 tot and F760 toc to droughs were similar, further studies (Figure 6) demonstrated that F760 tot had the potential for detecting moderate droughs because it had more of a decrease than other variables in moderate droughs. Specifically, SIFtot could represent the overall chlorophyll fluorescence emissions, which could reflect more of a decrease of fluorescence emissions under the same level of drought, therefore possibly improving early monitoring for moderate droughs. Another main result was that the NDVI and NIR\({}_{\
u}\) outperformed F760 tot in long-term drought monitoring over the growing season. As depicted in Figures 9-11, the r values between the VIs and SM up to \(\sim\)0.75 were higher than that of F760 tot and F760 toc, regardless of the different time windows or whether the water stress hysteresis effects were considered. Specifically, it was obvious that due to the weakness of F760 tot and F760 toc signals and the influence of many factors, the values of F760 tot and F760 toc fluctuated dramatically during the growing season compared with the VIs in Figure 4 and even showed a slow, regular up and down movement in the time window of 1 week in Figure 11a. The values of the NDVI, in contrast, maintained a smooth, continuous curve in the seasonal scale in Figure 4 and tended to rise during the first 8 days and stabilize in the rest (Figure 11a). Additionally, according to Figures 4 and 5 and previous studies [25], although the relationship of F760 toc with PAR gradually decreased with the increasing severity of the drought, a pronounced day-to-day variation in the SIF pattern was highly correlated with that of PAR, so the daily accumulated values of PAR varied in accordance with the fluctuation of SIF during the growing season, thus leading to the weak correlations between SIF with SM. Here, the drought is defined by the moisture deficits of the root zone. More and more studies have proven that the SIF emissions were sensitive to drought stress, which could be attributed to the decrease in carboxylation capacity and the increase in non-photochemical quenching. For example, compared with VPD, SM is the dominant driver of dryness stress on ecosystem production that is characterized by SIF [43]. Similarly, using SIF as a proxy for GPP, [PERSON] et al. [44] demonstrated that SM plays a more important role, and SIF is very sensitive to aridity gradients in arid and semi-arid ecosystems. The results coincided with our reports. Based on this sensitivity, [PERSON] et al. [45] integrated the relationship of the photosynthesis rate and photosystem II operating efficiency into SUCROS97 and improved the prediction of biomass under a drought. Aside from that, [PERSON] et al.