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

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Abstract

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.

Introduction

Evapotranspiration (ET) is an important process for ecosystem water budgets and energy balance, and is closely linked to ecosystem productivity (Law et al., 2002, Scott et al., 2006). Vegetation transpiration (T) and soil water evaporation (E), controlled by different biotic and physical processes, are the two major components of ET. To accurately predict the climatic response of ecosystem functions and processes, quantifying the partitioning of ET and its controls are critical (Williams et al., 2004, Lauenroth and Bradford, 2006). The common approaches used to partition ET currently are measurements using lysimeter, sap flow, infrared thermometers and isotopes (Evett et al., 1994, Williams et al., 2004, Scott et al., 2006, Moran et al., 2009) and modeling (Shuttleworth and Wallace, 1985, Kustas, 1990, Brenner and Incoll, 1997, Kemp et al., 1997, Reynolds et al., 2000). Among these methods, modeling is becoming more and more popular because of its exclusive advantage in addressing ecosystem processes over a spectrum of timescales (Shugart, 2000). The Shuttleworth–Wallace model (S–W model) has been widely used for its simple and accurate consideration of hydrological processes, and good performance (Sene, 1994, Tourula and Heikinheimo, 1998, Brisson et al., 1998, Iritz et al., 1999, Anadranistakis et al., 2000, Kato et al., 2004).

Nevertheless, there are still some insufficiencies in the application of the S–W model. First, most of its applications were undertaken on croplands, with far fewer reports on its use on grasslands (Lafleur and Rouse, 1990, Nichols, 1992, Stannard, 1993). Grasslands occupy nearly 40% of global land surface and play a very important role in global energy balance and carbon budgets (White et al., 2000). In China, also about 40% of the country is covered by grasslands (Fan et al., 2008). Studies have indicated that the grassland regions in China are highly sensitive to global climate change (Ding et al., 2006). Until now very few reports have addressed the partitioning of ET in Chinese grasslands using the S–W model or other methods. The second problem is that the S–W model has mostly been used with short time periods (less than one growing season). Its long-term performance, when more processes are involved, has not been fully tested. Furthermore, due to the lack of investigating the model long-term performance, our knowledge of the partitioning of ET and its controls is critically limited. This limitation complicates our ability to predict the climatic responses of ecosystem carbon and water processes (Williams et al., 2004, Lauenroth and Bradford, 2006, Scott et al., 2006).

Many studies have indicated that E/ET, the indicator of ET partitioning, was controlled by canopy conductance at the diurnal timescale and by leaf area index (LAI) at the seasonal timescale (Sakuratani, 1987, Liu et al., 2002, Kato et al., 2004, Scott et al., 2006, Sauer et al., 2007). However, a question persists: what factor is dominantly responsible for the year-to-year and site-to-site variations? Further, due to the dearth of research on inter-site comparisons, how the effects of canopy stomatal conductance and LAI on E/ET would change across an environmental gradient remains unclear.

Using multi-year measurements of carbon and water vapor fluxes with the eddy covariance technique for four grassland ecosystems in China, we sought to address the following questions: (1) is the S–W model applicable to Chinese grasslands over long-term periods of time? (2) What is the importance of the soil water evaporation for whole ecosystem water vapor fluxes in Chinese grasslands? (3) How do the canopy stomatal conductance and LAI affect E/ET at different spatiotemporal scales? (4) How do the responses of E/ET to changes in canopy stomatal conductance and LAI vary across an environmental gradient? The ecosystems in this study belong to the main Chinese grassland types, and they illustrate an obvious water availability gradient (Fan et al., 2008), which enables us to investigate the effects of the environment over diverse spatial scales. There are obvious seasonal and inter-annual variations in ET in each ecosystem. This provides us a good opportunity to test the applicability of the S–W model.

Section snippets

Study sites

Four ecosystems with distinct water availability conditions and vegetation types were selected from ChinaFLUX eddy covariance (EC) tower stations (Yu et al., 2006a, Yu et al., 2006b). Shidi alpine swamp meadow (SD) is located at the Haibei alpine grassland station on the Qinghai-Tibet Plateau (37°37′N, 101°20′E; 3160 m a.s.l.). The climate at this site is characterized by strong solar radiation, with long cold winters and short cool summers. Annual mean air temperature is −1.7 °C. Annual mean

Performance of S–W model at the half-hour time scale

We ran the S–W model with the best parameter set which was the mean of the 20 most successful parameter sets (Table 2). In general, the model successfully simulated ET at the four ecosystems with the R2 between measured and modeled ET above 0.8 (Fig. 2). According to the slope k, the model generally overestimated ET by 8–15% at all the sites except DX. We also examined diurnal simulation in three distinct phases: pre-growing season (April), peak growing season (August) and late growing season

Model performance and uncertainties

The accurate estimate of ET at the diurnal and seasonal time scales in this study confirmed the ability of the S–W model to make accurate predictions for Chinese grasslands. The good performance of the S–W model was also confirmed in many other ecosystems (Tourula and Heikinheimo, 1998, Sene, 1994, Iritz et al., 1999, Kato et al., 2004). Compared with previous studies, the performance of the S–W in this study was generally better. The following three reasons may be responsible for the

Conclusion

With multi-year measurements of ecosystem evapotranspiration with eddy covariance systems, this study confirmed the good long-term performance of the S–W model at the four grassland ecosystems in China. Our study indicates that taking into account canopy rainfall interception and using varied parameter sets in different years may improve the model performance. The results of this study highlight the importance of soil water evaporation in water vapor fluxes for Chinese grasslands, and future

Acknowledgements

This research was jointly funded by National Natural Science Foundation of China (Grant Nos. 30590381, 30800151 and 30700110), the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KZCX2-YW-432), the National Key Research and Development Program (Grant No. G2002CB412501), and the “Hundred Talents” Program of the Chinese Academy of Sciences. We thank two anonymous reviewers for their valuable comments to improve this manuscript. Special thanks to Mr. David C. Brill at

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