## 4 Conclusions  
To solve the problem of the overestimation of ET for vegetation in water stress conditions, this study proposed an approach to improve the accuracy of ET estimates through integrating MPDI as an indicator of soil moisture into the SEBS model through a modified definition of kB\({}^{-1}\). The new approach was tested by comparing it with observations from the EC tower. The results indicated a clear improvement of H with 42.5 W m\({}^{-2}\) for the case of sparse vegetation with low soil moisture. Regarding the agricultural crops with relatively high soil moisture, there was a moderate improvement with 22.5 W m\({}^{-2}\). Accordingly, the MPDI-integrated SEBS approach significantly remedied the shortcoming of overestimating evapotranspiration under water-limited conditions. The daily ET map generated by the MPDI-integrated SEBS had a higher spatial variability compared to the original SEBS and was able to better distinguish between the irrigated fields and the neighboring dry areas in arid and semi-arid regions. The authors carried out crop evapotranspiration estimation at the field scale in the Ganzhou irrigation districts in 2015 using the MPDI-integrated SEBS model and HJ-1 images. The results showed that the spatial resolution of HJ-1 provided valuable information regarding the spatial variability of ET within fields. Furthermore, the relatively short revisit period permitted the capture of the dynamic change of crop daily ET, especially of a few peak values after rainfall or irrigation events. Based on the day-by-day dynamics of ET, the temporal variation of crop ET changed with clear seasonality, which was closely related to the crops' phenophase. The field to field and crop to crop variability in evapotranspiration provide substantial information about crop consumption via ET for agricultural water management in arid and semi-arid regions. The authors were able to successfully leverage the capacity of HJ-1 satellite images in a way that can provide both integrative and quantitative visual and analytical components for the study of water use and availability. The MPDI-integrated SEBS model only requires HJ-1 data and meteorological data as inputs, providing an effective way to obtain high spatial resolution soil moisture information for the SEBS model under water-limited conditions, especially for sparsely vegetated surfaces. The scheme effectively resolves the overestimation of ET in areas with sparsely vegetated surfaces under water stress conditions. However, the estimation of ET in dense vegetation areas still need to be improved. Figure 11: Variation of daily ET over different land-cover types in the Ganzhou irrigation districts during the growing season of 2015. On the one hand, there are uncertainties in the parameterization schemes of the land surface parameters and daily net radiation, which are usually related to the study region and the selected sensors. On the other hand, MPDI is not sensitive to soil moisture variation for dense vegetation. When the leaf area index is more than 5 (see Figure 5a), the function of MPDI in regulating kB\({}^{-1}\) will be reduced as the canopy density increases. In fact, MPDI present a strong correlation with the normalized difference vegetation index (NDVI) related to canopy density [55]. Future study will consider the removal of this correlation in order to capture the vegetation stress. [PERSON], [PERSON], and [PERSON] conceived and designed research; [PERSON], [PERSON], [PERSON], and [PERSON] performed the satellite data analysis; [PERSON] analyzed the results; [PERSON] wrote the paper; and [PERSON], [PERSON], and [PERSON] contributed to analysis and discussion.