## 4 Discussion  
### Tidal Effects on SIF\({}_{760}\), GPP, and ET Modeling and Underlying Mechanisms  
Although we have conducted meticulous adjustments to the parameters of leaf chlorophyll fluorescence and photosynthesis parameterization within the SCOPE model, using field observation data from _Plragmites australis_ to address the subtle discrepancies between this vegetation and other crops such as cotton, tobacco, and maize that arise when using the default parameterization, the improvements resulting from these adjustments may be relatively minor. Nonetheless, this fine-tuning is of considerable importance for enhancing the accuracy and practicality of the SCOPE model in coastal wetland ecosystems. To further substantially improve the simulation of SIF\({}_{760}\), GPP, and ET in coastal wetland ecosystems, a deeper understanding of tidal influence mechanisms is crucial. During tidal flooding, vegetation tends to have reduced light reaction center opening [51] and stomatal conductance [24]. However, due to the lack of explicit representations of tidal effects, the model is unable to capture the altered physiological status of vegetation during tidal-flooded periods. This may explain why the simulations of SIF\({}_{760}\), GPP, and ET were more poorly performed under tidal-flooded conditions. Moreover, ET encompasses not only transpiration, which is associated with the physiological status of vegetation, but also soil evapotranspiration, both of which are affected by tidal flooding. Regarding SIF\({}_{760}\), tidal flooding affects it not only by altering plant physiology but also by changing its radiative transfer processes. This is likely because, when flooded, the SIF\({}_{760}\) and f\({}_{\rm esc}\) decrease due to the changes in background reflectance and absorption of the emitted fluorescence by the background water [25; 52]. The simulation performance of SIF\({}_{760}\), GPP, and ET in coastal marshes is affected by salinity variations induced by tides. As shown in Figures 6-8, SIF\({}_{760}\), GPP, and ET are best simulated at low salinity levels, probably due to the low concentration-promoting effect of salinity in C4 plants [53]. Similar to previously reported results [54], there was no significant bias between the simulated and observed GPP in low to intermediate salinities, whereas a significant overestimation of GPP occurred at high salinities, which may be caused by the reduction in photosynthetic intensity under salt stress [55]. Additionally, as salinity increases, the osmotic pressure within vegetation cells becomes imbalanced, leading to restrictions in water absorption and transpiration. Consequently, ET is also significantly overestimated under high salinity stress. Furthermore, since the Changjiang River is characterized by relatively low salinity levels (Figure 12) during the flood season (May-September) and high salinity levels during the dry season (November-March), _Plragmites australis_ experiences relatively high salinity at the flowering and ripening growth vegetation stage. At this stage, the simulations of SIF\({}_{760}\), GPP, and ET typically underperform, due to inadequate understanding and parameterizations of the complex physiological variations under the combined stresses of high salinity and low temperatures. Under tidal-flooded conditions, the responses of vegetation to meteorological factors differ. Temperature plays a major role in affecting photosynthesis, respiration, and transpiration of vegetation in coastal wetlands. Photosynthesis and transpiration are expected to show an enhancement trend under warming conditions [56]. However, when vegetation suffers from excessive high and low temperatures, with reductions in photochemical maximum quantum yield, stomatal conductance, and water use efficiency [57], both the photosynthetic rate and transpiration rate will be inhibited, leading to deviations in the simulations of GPP, ET, and SIF from the observations.