## 6 Conclusions  
Estimating GPP and ET in a water-carbon coupling way is important to correctly assess the water use efficiency of crops. In this paper, the usage of the PML-V2 water-carbon coupling model was evaluated in the lower reaches of the Poyang Lake plain. As a diagnostic model, the PML-V2 model does not require detailed crop management information; however, the model performed reasonably well in simulating both the GPP and ET and therefore the WUE because the key parameters of the model exhibited predictable seasonal variations, and the NDVI is capable of indicating crop growth status. Our study shows that the PML-V2 model is feasible in regional estimates of rice GPP and ET in the sub-tropical climate. The vegetation information (e.g., NDVI) is the most important input for regional application because of its fine spatial resolution. However, the uncertainty of vegetation information will propagate into the estimation of GPP, canopy conductance, and therefore \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Regression Equation** & \(\mathbf{R^{2}}\) & **RMSE** \\ \hline \multirow{4}{*}{Early rice} & GPP & 14.14 NDVI + 0.08 & 0.93 & 0.41 \\ \cline{2-4}  & ET & 1.424 NDVI + 0.016R\({}_{\text{s}}\)\(\downarrow\) + 0.16T\({}_{\text{a}}\) – 47.0 & 0.90 & 0.12 \\ \cline{2-4}  & T/ET & 1.068 NDVI + 0.006u + 0.134 & 0.98 & 0.02 \\ \cline{2-4}  & WUE & 2.822 NDVI + 0.165 & 0.82 & 0.14 \\ \hline \multirow{4}{*}{Late rice} & GPP & 14.11 NDVI \(-\) 0.005T\({}_{\text{a}}\) & 0.94 & 0.43 \\ \cline{2-4}  & ET & 2.177 NDVI + 0.026 R\({}_{\text{s}}\)\(\downarrow\) + 0.438u \(-\) 2.1 & 0.91 & 0.11 \\ \cline{2-4}  & T/ET & 0.933 NDVI + 0.0006T\({}_{\text{a}}\) + 0.03 & 0.97 & 0.02 \\ \cline{2-4}  & WUE & 2.418 NDVI \(-\) 0.0003T\({}_{\text{a}}\) & 0.87 & 0.11 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Stepwise linear regression analysis for multi-year daily values of all gridded GPP (gC/m\({}^{2}\)/d), ET (mm/d), T/ET (–), and WUE (gC/kgH\({}_{2}\)O) for the early rice and late rice in the study area. canopy transpiration. The calibrated parameters are prone to NDVI uncertainty. In addition, due to the limited temporal resolution of the MODIS NDVI product (16 days), it is difficult to retrieve the start and end dates of the growth stages of the rice. In conclusion, vegetation information at finer spatial and temporal resolution is the key to the application of the PML-V2 model. The following are available at [[https://www.mdpi.com/article/10.3390/rs13173470/s1](https://www.mdpi.com/article/10.3390/rs13173470/s1)]([https://www.mdpi.com/article/10.3390/rs13173470/s1](https://www.mdpi.com/article/10.3390/rs13173470/s1)), Figure S1: Regional distribution of annual averages of meteorological variables and NDVI in 2000, Figure S2: Regional distribution of annual averages of meteorological variables and NDVI in 2005, and Figure S3: Regional distribution of annual averages of meteorological variables and NDVI in 2015. Conceptualization, G.G. ; methodology, G.G. and X.Z. ; formal analysis, G.G. ; resources, Y.L., H.X., W.J. ; data curation, X.F., H.Z. and Y.C. ; writing--original draft preparation, G.G. and X.Z. ; writing--review and editing, Y.L. ; visualization, G.G. ; supervision, Y.L. ; project administration, Y.L. All authors have read and agreed to the published version of the manuscript. Our research is jointly funded by the National Natural Science Foundation of China (42071054, 41971374, 51879255) and the Open Fund of State Key Laboratory of Remote Sensing Science (OFSLRSS202020). The study was conducted according to the guidelines of the Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, and approved by the Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences. Not applicable. The data presented in this study are available on request from the corresponding author.