## 5 Conclusions  
This study conducted an in-depth exploration of the impacts of major meteorological and tidal factors on GPP, ET, and SIF\({}_{760}\), as well as how these factors influence the correlations between SIF\({}_{760}\) and both GPP and ET, through a comparison of field observations and SCOPE model simulations in the coastal salt marsh wetlands of the Changjiang Estuary in 2019. The results showed that tidal inundation tends to degrade model performance for GPP, ET, and SIF\({}_{760}\), except for scenarios where modeling GPP under tidal inundation shows enhancement when air temperatures are relatively high. This suggests that while tidal inundation affects vegetation photosynthesis and transpiration, it may also have the potential to alleviate high-temperature stress on vegetation. Additionally, high-salinity environments lead to overestimations of SIF\({}_{760}\), GPP, and ET. This study also demonstrates that under tidal inundation conditions, the correlation between SIF\({}_{760}\) and GPP weakens, whereas the correlation with ET strengthens. This does not imply that tidal inundation enhances the relationship between SIF and ET in coastal wetlands; rather, it reflects the interplay between tidal and meteorological factors. These findings offer a new perspective for understanding the impact of tidal environments on vegetation physiological and ecological processes. Based on these discoveries, we emphasize the importance of proposing a parameterization scheme that reflects the influence of tidal inundation on photosynthesis, transpiration, and radiative transfer. Such a scheme would facilitate the development of methods for scientifically estimating GPP and ET based on SIF, providing robust support for the ecological management and protection of coastal salt marsh wetlands. This study not only enhances the understanding of the interactional mechanisms between meteorological and tidal factors in coastal salt marsh wetland ecosystems but also provides a crucial foundation for establishing an SIF-based remote sensing model for estimating GPP and ET for application on coastal blue-carbon ecosystems on a large-scale domain in the future. The following supporting information can be downloaded at [[https://www.mdpi.com/article/10.3390/rs16244636/s1](https://www.mdpi.com/article/10.3390/rs16244636/s1)]([https://www.mdpi.com/article/10.3390/rs16244636/s1](https://www.mdpi.com/article/10.3390/rs16244636/s1)), Table S1. Coefficient of determination (R\({}^{2}\)), root-mean-square error (RMSE), and bias of the relationships between the observed and simulated canopy-level solar-induced chlorophyll fluorescence at 760 nm (SIF\({}_{760}\), W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)), gross primary productivity (GPP, umol m\({}^{-2}\) s\({}^{-1}\)), and evapotranspiration (ET, mm h\({}^{-1}\)) under tidal flooded and non-flooded conditions at the early and rapid stage (rapid, from March to May), peak vegetation stage (peak, from June to August), flowering and ripening stage (ripen, from September to November), and wilt vegetation stage (wilt, from December to February). The significance of the correlation is indicated with \"a\" if the \(p\)-value < 0.01 and \"b\" if the \(p\)-value < 0.05, while \"c\" indicates no significant correlation; Table S2. Coefficient of determination (R\({}^{2}\)), root-mean-square error (RMSE), and bias between the observed and simulated canopy-level solar-induced chlorophyll fluorescence at 760 nm (SIF\({}_{760}\), W m\({}^{-2}\) um\({}^{-1}\) sr\({}^{-1}\)), gross primary productivity (GPP, umol m\({}^{-2}\) s\({}^{-1}\)), and evapotranspiration (ET, mm h\({}^{-1}\)) at different vapor pressure deficits (VPDs, kPa), air temperatures (\"C), and soil temperatures (\"C).