## 3 Results
### Simulation and Evaluation of Vegetation Photosynthesis Model  
We run the VPM model based on the observation of Ta, PAR, and MODIS VIs (EVI and LSWI), and examined the seasonal variation of the modeled GPP (GPP\({}_{\text{VPM}}\)) for the tested coastal wetland during 2009-2010 (Figure 7). GPP\({}_{\text{VPM}}\) was close to zero from November to early March, then began to increase rapidly in mid-March, and achieved a peak in early-August and mid-July in 2009 and 2010,  
Figure 5: Linear relationships between (**a**,**d**) Normalized Difference Vegetation Index (NDVI); (**b**,**e**) Enhanced Vegetation Index (EVI); (**c**,**f**) Land Surface Water Index (LSWI) and estimated gross primary production (GPP) from EC tower data (GPP\({}_{\text{EC}}\)) during 2009–2010. Dashed lines are the linear trends of NDVI, EVI, LSWI, and GPP\({}_{\text{EC}}\), respectively. Figure 6: Linear relationships between (**a**) Normalized Difference Vegetation Index (NDVI); (**b**) Enhanced Vegetation Index (EVI); (**c**) Land Surface Water Index (LSWI); and (**d**) estimated GPP from EC tower data (GPP\({}_{\text{EC}}\)) and air temperature (Ta) during 2009–2010. NDVI = 0.00019\(\cdot\)Ta\({}^{2}\) + 0.004\(\cdot\)Ta + 0.01 (\(R^{2}\) = 0.55, \(p\) < 0.0001, \(N\) = 92); EVI = 0.0002\(\cdot\)Ta\({}^{2}\) – 0.0002\(\cdot\)Ta + 0.01 (\(R^{2}\) = 0.62, \(p\) < 0.0001, \(N\) = 92); LSWI = 0.00048\(\cdot\)Ta\({}^{2}\) – 0.0092\(\cdot\)Ta + 0.034 (\(R^{2}\) = 0.28, \(p\) < 0.0001, \(N\) = 92); GPP\({}_{\text{EC}}\) = 0.009\(\cdot\)Ta\({}^{2}\) + 0.053\(\cdot\)Ta \(-\) 0.76 (\(R^{2}\) = 0.78, \(p\) < 0.0001, \(N\) = 53). respectively. GPP\({}_{\text{VPM}}\) declined gradually after reaching peak it and dropped below 1 g C m\({}^{-2}\) day\({}^{-1}\) by early-November. Comparisons between GPP\({}_{\text{VPM}}\) and GPP\({}_{\text{EC}}\) fluxes at eight-day time intervals show that the simulated eight-day GPP\({}_{\text{VPM}}\) fluxes were in good agreement with GPP\({}_{\text{EC}}\) fluxes regarding to the patterns and magnitudes. VPM fairly reappeared the U-shaped growth pattern, which driveled by the variation in Ta and PAR, and accurately simulated the seasonal dynamics of GPP\({}_{\text{EC}}\) fluxes for the simulated two years. However, eight-day GPP\({}_{\text{VPM}}\) peak values were slightly higher than GPP\({}_{\text{EC}}\) in both 2009 and 2010 (Figure 7). To further evaluate the accuracy of model simulation, a linear regression analysis between GPP\({}_{\text{VPM}}\) and GPP\({}_{\text{EC}}\) was conducted (Figure 8). For both years, the linear regression of GPP\({}_{\text{VPM}}\) against GPP\({}_{\text{EC}}\) shows a good correlation (\(R^{2}\geq 0.72\), \(p<0.0001\); Figure 8; Table 1). The RMD and RMSE values were \(-1.01\%\) and \(25.29\%\) during 2009-2010, respectively. The simulated annual GPP\({}_{\text{VPM}}\) were 1057.64 and 1091.76 g C m\({}^{-2}\) yr\({}^{-1}\) for 2009 and 2010, respectively, which is slightly lower than the estimated annual GPP\({}_{\text{EC}}\) (1068.51 and 1102.84 g C m\({}^{-2}\) yr\({}^{-1}\) for 2009 and 2010, respectively), both with relative error (RE) values of \(-1\%\) (Table 1). Moreover, cumulative GPP fluxes simulated over the two years were in good agreement with the estimated values, with \(-1\%\) RE (Table 1).