Abstract
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.
Highlights
Evapotranspiration (ET) is a key process of the ecosystem water cycle and energy balance and is closely linked to ecosystem productivity [1,2]
Five resistances are necessary to estimate ET with the SWH model (Figure 1, Appendix A), i.e., soil surface resistance, canopy stomatal resistance, the aerodynamic resistances encountered by the water flux leaving leaf lamina or soil surface before being incorporated into the mean canopy flow and the transfer resistance between the hypothetical mean canopy flow and the reference height. rss and rsc are the most critical for model performance among the five resistances. rss was estimated as a function of soil water content [23,24]: rss = b1 (
With the calculated biome-specific parameters and soil water content being estimated with the bucket scheme, we evaluated the model with two independent datasets of ET and gross primary productivity (GPP)
Summary
Evapotranspiration (ET) is a key process of the ecosystem water cycle and energy balance and is closely linked to ecosystem productivity [1,2]. Detailed and precise knowledge of regional ET is important to obtain a better understanding of the global carbon and water cycles [2,3,4]. A comparison of 15 model simulations from the Global Soil Wetness Project-2. (GSWP-2) revealed that the annual mean global land surface ET ranged from 272 to 441 mm·year−1 , indicating large discrepancies among the models [7]. A comparison by Chen et al [6] of eight ET models revealed a range of annual mean ET values from 535 to 852 mm in China, confirming large model-to-model differences. Further improvements in regional ET simulation and partitioning are needed
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