## 4 Conclusions  
Based on two fundamental ecophysiological indicators, ET and GPP, this study utilized the DLM-Ecohydro model to simulate the exchanges between energy, water and carbon assimilation in the Upper Heihe watershed with a tightly coupled manner. The combination of in situ measurements and remotely sensed datasets provided detailed environmental disturbances from both nature and human beings, contributing a regionally accurate and spatially explicit simulation. The land surface model fully took topographical influence into consideration, modeling the lateral hydrological processes by solving a water balance equation. In order to accurately represent the ecophysiological processes in the watershed, the model separately simulated sunlit and shaded leaves and flexibly derived soil profiles as multiple layers according to the moisture regimes.  
The simulation suggested that in spatial and temporal patterns, ET and GPP have significantly synchronous variations in the Upper Heihe watershed. Although the precipitation was mainly concentrated during May and September in the watershed, soil water content was still a major limiting factor for vegetation transpiration and photosynthesis efficiency in mid-summer. The spatial distribution of ET highly depends on soil texture. Silt loam and clay had the maximum and minimum annual ET loss, respectively, mainly because of their different abilities of hydraulic conductance. Vegetation transpiration accounted for the most part of ecosystem ET losses in the two study years. Photosynthesis was more sensitive to plant functional types: Deciduous forests had the highest annual carbon assimilation rate owing to it having a higher stomatal conductance and leaf nitrogen content and a lower canopy clumping index. LAI and topography, however, made a strong contribution for both ecophysiological processes simultaneously.  
There are also some limitations of this study. Because the model did not consider the dynamics of frozen soil and the melting runoff from glaciers in the alpine regions, it would cause an unreality estimation of soil moisture regimes during the frozen and major melting seasons. While overall, the model showed a fair performance for the simulation of hydro-ecological processes, especially during vegetation growing seasons.  
Conceptualization, B.C.; data curation, H.J., S.S. and X.L.; formal analysis, H.J., S.S., S.M., X.L. and L.G.; funding acquisition, B.C.; investigation, H.J., S.S.; methodology, B.C., H.J., S.S., H.Z. and S.M.; project administration, B.C.; resources, B.C.; software, H.J., S.S. and H.Z.; supervision, B.C.; validation, H.J., S.S. and L.G.; visualization, H.J., S.S. and L.G.; writing - original draft, H.J.; and writing - review and editing, B.C. and S.S.  
This research was funded by the National Key R&D Program of China (2018 YFA0606001, 2017 YFA0604301, 2017 YFA0604302, 2017 YFC0503904), an international partnership program of Chinese Academy of Sciences (Grant #131A11 KYSB20170025), a research project funded by the State Key Laboratory of Resources and Environmental Information System (O88 RA901 YA, O8R8A085 YA) and a project funded by the National Natural Science Foundation of China (41771114).  
We thank the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) program for providing the ecophysiological validation of datasets of the Arou station in the Upper Heihe watershed.  
Figure 11: The relationship between simulated ET and GPP in two study years.  
**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.