## 4 Discussion
Under low LAI values, more evaporation from bare soil should enhance nontranspiration flux, which may weaken SIF-IWUE correlations. High LAI values have both positive and negative effects on SIF-IWUE correlations. On the one hand, canopy closure reduces solar radiation received by the ground and thus results in less contribution from soil evaporation, which tends to enhance SIF-IWUE correlations. On the other hand, a dense canopy at high LAI leads to more (re)absorption in red SIF and stronger scattering in near infrared SIF, both of which decouple the link between SIF emission and latent energy measured at top of the canopy. Our results show that the negative effect associated with high LAI is more pronounced when LAI is higher than 4.5. It suggests that a canopy radiationtransfer model [53] may be needed to account for SIF losses due to scattering/absorption processes, especially when SIF is used to estimate IWUE in ecosystems with dense canopy. Previous studies have shown that observation time in the day has a limited impact on both SIF-GPP and SIF-\(T\) correlations [32; 40; 41]. However, SIF-IWUE correlations vary as a function of the observation time during the day and they are strongest in the afternoon. This phenomenon can be explained by variations in evaporation of dew present in the canopy and soil. Specifically, the SIF-IWUE correlation is considerably weakened in the morning, particularly in the early morning [54], when evaporation of dew, a nontranspiration flux, contributes a large fraction of latent flux measured at the top of canopy. Our results suggest that SIF-IWUE correlations derived from remotely sensed SIF data, with an early morning overpass time such as GOME-2, may contain large uncertainties. A model [55], which predicts occurrence and duration of dew events may be needed. When the simulated dew is high, SIF emission may be not suitable for predicting IWUE. The response of the SIF-IWUE correlations to air temperature shows they are affected by confounding factors. Theoretically, both SIF-GPP and SIF-\(T\) correlations [32; 41] degrade under heat stress due to more energy release through heat dissipation. Although higher air temperature in the afternoon may cause lower SIF-GPP and SIF-\(T\) correlations, we find that the benefit, due to less dew evaporation in the afternoon, may largely counteract these negative effects. However, it is important to note that the study site had no strong heat stress in 2014 such that further experiments are needed to evaluate SIF-IWUE correlations in high air temperature. Furthermore, relatively cool air temperature in the morning may enhance both SIF-GPP and SIF-\(T\) correlations [32; 41], while more evaporation of dew tends to weaken the capability of SIF to predict \(T\). Our results show that the intensity of PAR has a limited negative effect on SIF-IWUE correlations. Nonlinear models such as GPR should be used when solar radiation is close to the saturation. Also, the band combinations, especially the one using SIF\({}_{687}\), SIF\({}_{720}\), and SIF\({}_{761}\), provide stable performance under the PAR saturation. We also find that a clear sky condition, which may be used to select good-quality satellite observations, has a marginal impact on SIF-IWUE correlations. It confirms that remotely sensed SIF datasets can be used to derive SIF-IWUE correlations. Data with k\(>\)0.8 are more likely measured under the PAR saturation condition. Our results show that the intensity of PAR has a limited negative effect on the SIF-IWUE correlations such that these correlations tend to have a limited decrease under different sky clearness conditions. The authors are aware of several limitations in this study. Compared to new spectrometers such as QE Pro spectrometer (OceanOptics, Inc, Dunedin, Florida), the signal-to-noise ratio (250:1) of our spectrometer is relatively lower such that measurements of SIF emission may contain more noise, especially in the red SIF emission.