Spatiotemporal variations in the ratio of transpiration to evapotranspiration and its controlling factors across terrestrial biomes

Quantifying the ratio of transpiration (T) to evapotranspiration (ET), T/ET, is crucial for understanding and predicting the water cycle and energy balance between the land and atmosphere. Here, we used three well-validated ET partitioning models to estimate T/ET at global fluxnet sites. The models are the Shuttleworth-Wallace-Hu (SWH) model, the Priestley-Taylor Jet Propulsion Lab (PT-JPL) model, and the underlying water use efficiency (uWUE) method. SWH illustrated the most reliable estimate in both the magnitude and the across-site variability of T/ET among three models. Mean annual T/ET derived from SWH, PT-JPL, and uWUE were 0.61 +/- 0.14, 0.52 +/- 0.12 and 0.59 +/- 0.07, respectively. Leaf area index (LAI) was the key driver of spatial variations in T/ET across sites, as well as seasonal variations in T/ET in ecosystems in most climatic zones except for the tropical and arid regions. However, there were discrepancies in factors controlling inter-annual variations in T/ET among the models. SWH and PT-JPL showed that the inter-annual variation in T/ET was more related to LAI than climatic factors but an opposite result was found by uWUE due to the simple structure and less forcing data of uWUE. The findings of our research highlight the importance of capturing the controls of LAI on ET partitioning for predicting future water cycle with land models. We appeal for direct measurements of ET components at the flux tower sites for validating the models and reduce model uncertainties.

Automated summary

Quantifying the ratio of transpiration to evapotranspiration (T/ET) is crucial for understanding and predicting the water cycle and energy balance. Three well-validated ET partitioning models were used to estimate T/ET at global fluxnet sites. Leaf area index was found to be the key driver of spatial variations in T/ET across sites, and there were discrepancies in factors controlling inter-annual variations in T/ET among the models.