Evapotranspiration (ET) is an important component of the water cycle in terrestrial ecosystems. Understanding the ways in which ET changes with meteorological factors is central to a better understanding of ecological and hydrological processes. In this study, we used eddy covariance measurements of ET from a typical alpine shrubland meadow ecosystem in China to investigate the hysteresis response of ET to environmental variables including air temperature (T_a), vapor pressure deficit (VPD) and net radiation (R_n) at a diel timescale. Meanwhile, the simulated ET by Priestly-Taylor equation was used to interpret the measured ET under well-watered conditions. Pronounced hysteresis was observed in both T_a and VPD response curves of ET. At a similar T_a and VPD, ET was always significantly depressed in the afternoon compared with the morning. But the hysteresis response of ET to R_n was not evident. Similar hysteresis patterns were also observed in the T_a/VPD response curves of simulated ET. The magnitudes of the measured and simulated hysteresis loops showed similar seasonal variation, with relatively smaller values occurring from May to September, which agreed well with the lifetime of plants and the period of rainy season at this site. About 62% and 23% of changes in the strength of measured ET-T_a and ET-VPD loops could be explained by the changes in the strength of simulated loops, respectively. Thus, the time lag between R_n and T_a/VPD is the most important factor generating and modulating the ET-T_a/VPD hysteresis, but plants and water status also contribute to the hysteresis response of ET. Our research confirmed the different hysteresis in the responses of ET to meteorological factors and proved the vital role of R_n in driving the diel course of ET.

The modeling and partitioning of regional evapotranspiration (ET) are key issues in global hydrological and ecological research. We incorporated a stomatal conductance model and a light-use efficiency-based gross primary productivity (GPP) model into the Shuttleworth–Wallace model to develop a simplified carbon-water coupling model, SWH, for estimating ET using meteorological and remote sensing data. To enable regional application of the SWH model, we optimized key parameters with measurements from global eddy covariance (EC) tower sites. In addition, we estimated soil water content with the principle of the bucket system. The model prediction of ET agreed well with the estimates obtained with the EC measurements, with an average R² of 0.77 and a root mean square error of 0.72 mm·day⁻¹. The model performance was generally better for woody ecosystems than herbaceous ecosystems. Finally, the spatial patterns of ET and relevant model outputs (i.e., GPP, water-use efficiency and the ratio of soil water evaporation to ET) in China with the model simulations were assessed.

Understanding the spatial variation in annual actual evapotranspiration (AET) and its influencing factors is crucial for a better understanding of hydrological processes and water resources management. By synthesizing ecosystem-level observations of eddy-covariance flux sites in China (a total of 61 sites), we constructed the most complete AET dataset in China up to now. Based on this dataset, we quantified the statistic characteristics of AET and water budgets (defined as the ratio of AET to annual mean precipitation (MAP), AET/MAP) of terrestrial ecosystems in China. Results showed that AET differed significantly among both different vegetation types and climate types in China, with overall mean AET of 534.7±232.8 mm yr^-1. AET/MAP also differed significantly among different climate types, but there were no distinct differences in AET/MAP values across vegetation types, with mean AET/MAP of 0.82±0.28 for non-irrigated ecosystems. We further investigated how the main climatic factors and vegetation attributes control the spatial variation in AET. Our findings revealed that the spatial variation of AET in China was closely correlated with the geographical patterns of climate and vegetation, in which the effects of total annual net radiation (R _n), MAP and mean annual air temperature (MAT) were dominant. Thus, we proposed an empirical equation to describe the spatial patterns of AET in China, which could explain about 84% of the spatial variation in AET of terrestrial ecosystems in China. Based on the constructed dataset, we also evaluated the uncertainties of five published global evapotranspiration products in simulating site-specific AET in China. Results showed that large biases in site-specific AET values existed for all five global evapotranspiration products, which indicated that it is necessary to involve more observation data of China in their parameterization or validation, while our AET dataset would provide a data source for it.