## 4 Discussion
[55] also found that ecosystem WUE in continental boreal forest had an apparent reduction from 2.41 g kg\({}^{-1}\) to 1.32 g kg\({}^{-1}\) during an extreme drought year. Nevertheless, a contrasting response of WUE to drought between arid (WUE increased with drought) and semi-arid/sub-humid ecosystems (WUE decreased with drought), which was attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions [56]. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). In this study, owing to limited flux measurements under normal years, we can only reveal the positive relationship between ecosystem WUE and natural precipitation. Large biases in the MODIS WUE estimates (Figure 4) essentially reflected great uncertainties in coupling the fluxes of carbon and water including MODIS GPP and ET products such as the algorithm structure, various upstream inputs and the biome-specific parameters in the fixed look-up tables [57; 58]. Therefore, further analysis is required to explore whether the MODIS GPP or ET product caused the large discrepancies in seasonal dynamics of WUE\({}_{\text{MOD}}\). Figures 6 and 7 compared the seasonal variations in GPP and ET from flux measurements and the corresponding MODIS estimates. During the two-year periods, GPP\({}_{\text{MOD}}\) at the Arou grassland site matched reasonably well to the EC-based observations with \(R^{2}\) and RMSE of 0.97 and 0.73 g m\({}^{-2}\) d\({}^{-1}\), respectively, whereas ET\({}_{\text{MOD}}\) exhibited a large overestimation in the dormant season and persistent underestimations during the growth period in spite of a small deviation of annual mean ET\({}_{\text{MOD}}\) and ET\({}_{\text{EC}}\) with about 9.1%. However, large biases existed in MODIS GPP and ET products at the Daman cropland site. Both were severely underestimated across the growing season. Although GPP\({}_{\text{MOD}}\) and GPP\({}_{\text{EC}}\) at Daman were strongly and linearly correlated with \(R^{2}\) of 0.93, the RMSE value reached up to 3.77 g m\({}^{-2}\) d\({}^{-1}\), about five times of that at the Arou site. Overall, annual mean GPP\({}_{\text{EC}}\) was underestimated by about 54.9%. Similar to the biases in GPP variability, most eight-day periods of ET\({}_{\text{EC}}\) were overly underestimated by ET\({}_{\text{MOD}}\) with steady changes. \(R^{2}\) and RMSE at the Daman site between ET\({}_{\text{EC}}\) and ET\({}_{\text{MOD}}\) were 0.43 and 1.83 mm d\({}^{-1}\), respectively. The percentage deviation was up to 61.9%. Thus, the accuracies of the MODIS GPP and ET products constrained its performance on modeling the WUE variability of maize ecosystem in the arid and semi-arid regions. Nevertheless, [PERSON] et al. [47] found that the MODIS ET product at an Americaflux site located in the humid area was quite consistent to the measured ET for both maize and soybean ecosystems with the percentage deviation of multi-year mean annual ET\({}_{\text{EC}}\) and ET\({}_{\text{MOD}}\) of less than 5%. The large bias of ET in this study can be ascribed to the necessary irrigation for maintaining crop growth in the dry regions while the MODIS ET algorithm neglected this part of the water supply. As shown in Figure 6, the peak of ET\({}_{\text{EC}}\) during about WOY 12 before sowing crops just experienced conventional irrigation. Annual rainfall at the Daman site was only 144.6 mm, whereas the amount of ET was 762.5 mm. Meanwhile, owing to a lack of effective distinction of C\({}_{3}\) and C\({}_{4}\) species, the MODIS GPP product contained large uncertainties in C\({}_{4}\) crops, such as maize, thereby propagating to WUE estimation. [PERSON] et al. [59] indicated that the bias of MODIS-based WUE was partly derived from the uncertainties in eddy flux  
data because of gap-filling processes and an unbalanced surface energy issue.