Partitioning of evapotranspiration and its controls in four grassland ecosystems: Application of a two-source model

Quantifying the partitioning of evapotranspiration (ET) and its controls are particularly important for accurate prediction of the climatic response of ecosystem carbon, water, and energy budgets. In this study, we employed the Shuttleworth–Wallace model to partition ET into soil water evaporation (E) and vegetation transpiration (T) at four grassland ecosystems in China. Two to three years (2003–2005) of continuous measurements of ET with the eddy covariance technique were used to test the long-term performance of the model. Monte Carlo simulations were performed to estimate the key parameters in the model and to evaluate the accuracy in model partitioning (i.e. E/ET). Results indicated that the simulated ET at the four ecosystems was in good agreement with the measurements at both the diurnal and seasonal timescales, but the model tended to underestimate ET by 3–11% on rainy days, probably due to the lack of model representation of rainfall interception. In general, E accounted for a large proportion of ET at these grasslands. The monthly E/ET ranged from 12% to 56% in the peak growing seasons and the annual E/ET ranged from 51% to 67% across the four ecosystems. Canopy stomatal conductance controlled E/ET at the diurnal timescale, and the variations and magnitude of leaf area index (LAI) explained most of the seasonal, annual, and site-to-site variations in E/ET. A simple linear relationship between growing season LAI and E/ET explained ca. 80% of the variation observed at the four sites for the 10 modeled site-years. Our work indicated that the daily E/ET decreased to a minimum value of ca. 10% for values of LAI greater than 3 m2 m−2 at the ecosystem with a dense canopy. The sensitivities of E/ET to changes in LAI increased with the decline in water and vegetation conditions at both the seasonal and the annual time scales, i.e., the variations in LAI could cause stronger effects on E/ET in the sparse-canopy ecosystems than in the dense-canopy ecosystems. It implies that the hydrological processes and vegetation productivity for ecosystems in arid environments might be more vulnerable to projected climate change than those in humid environments.