## 3 Results
### Responses of SIF\({}_{760}\), GPP, and ET to Meteorological Factors
The trend of GPP response to temperature remained consistent, but tidal inundation delayed the underestimation range and mitigated deviations. GPP simulations were underestimated at air temperatures of 30\(-\)31 \({}^{\circ}\)C and soil temperatures of 20\(-\)23 \({}^{\circ}\)C under tidal inundation, occurring at a higher temperature range compared to results without tidal effects. Meanwhile, the highest RMSE emerged at air temperatures of 20\(-\)22 \({}^{\circ}\)C and soil temperatures of 28\(-\)29 \({}^{\circ}\)C, both lower than the maximum RMSE without separating tidal effects. Additionally, the results indicated that salinity also induces variations in GPP simulations, with partial GPP underestimation at lower salinity stress levels and progressively increasing bias as salinity levels rise (Figure 8). Therefore, while tidal inundation alleviated the impacts of drought and high-temperature stress on vegetation GPP, subsequent salinity stress exerted an inhibitory effect. Figure 6: Relationships between the observation and simulation (with the subscript ‘sim’) of gross primary productivity (GPP) (**a1–a3**), evapotranspiration (ET) (**b1–b3**), and solar-induced chlorophyll fluorescence at 760 nm (\(\text{SIF}_{760}\)) (**c1–c3**) at different VPDs (**a1,b1,c1**), air temperatures (**a2,b2,c2**), and soil temperatures (**a3,b3,c3**). The coefficient of determination (R\({}^{2}\)) (blue bars) and bias (red lines) across various groups are displayed in the inset at the bottom right. The more details of R\({}^{2}\), bias, and root-mean-square error (RMSE) can be found in Tables S2 and S3. Tidal inundation did not affect the response of ET to VPD variations but influenced its response to temperature. ET simulation deviation peaked at a lower air temperature (peaked at 33 \({}^{\circ}\)C) under tidal inundation and at a lower soil temperature (peaked at 26 \({}^{\circ}\)C) (Figure 8). The bias initially decreased and then increased with rising soil temperature (dipped below 20-24 \({}^{\circ}\)C), similar to water temperature (dipped below 19-25 \({}^{\circ}\)C). Additionally, salinity induced variations in ET simulations, with increasing bias as salinity rose. Overall, tidal inundation did not alleviate the impact of drought on ET but mitigated high-temperatures stress within a certain temperature range. However, concomitant salinity stress inhibited ET. Under tidal inundation, the response of \(\text{SIF}_{760}\) to moisture, salinity, and temperature variations was influenced. As VPD increased, \(\text{SIF}_{760}\) simulations bias exhibited a decreasing-then-increasing trend, reaching a minimum 1.2-1.4 kPa VPD. Bias and RMSE increased with rising air temperature, while soil and water temperature increases led to an initial decrease followed by an increase in bias, with a minimum consistently observed at 20-23 \({}^{\circ}\)C (Figures 7 and 8). Additionally, \(\text{SIF}_{760}\) simulations were better at lower salinity levels but worsened as salinity increased (Figure 8). In summary, tidal inundation reduced \(\text{SIF}_{760}\) production under water-salt stress and temperature stress. Figure 7: Relationships between the observed (with the subscript ‘\({}_{\text{obs}}\)’) and simulated (with the subscript ‘\({}_{\text{sim}}\)’) (**a1**–**a3**) gross primary productivity (GPP), (**b1**–**b3**) evapotranspiration (ET), (**c1**–**c3**) solar-induced chlorophyll fluorescence (\(\text{SIF}_{760}\)) at different (**a1**,**b1**,**c1**) VPDs, (**a2**,**b2**,**c2**) air temperatures, and (**a3**,**b3**,**c3**) soil temperatures under tidal flooding. The coefficient of determination (R\({}^{2}\)) (blue bars) and bias (red lines) across various groups are displayed in the inset at the bottom right. More details on R\({}^{2}\), bias, and root-mean-square error (RMSE) can be found in Tables S2 and S3.