Preprints
https://doi.org/10.5194/egusphere-2025-4325
https://doi.org/10.5194/egusphere-2025-4325
21 Oct 2025
 | 21 Oct 2025
Status: this preprint is open for discussion and under review for Biogeosciences (BG).

Evaluation of evapotranspiration partitioning models in the Amazon forest

Long-Xiao Luo, Jun Lei, and Zheng-Hong Tan

Abstract. Although models that simulate actual ET have been widely used globally, their performance in tropical forests is unsatisfactory. The distribution of ET components is one of the key reasons. In this study, we evaluated the ability of three ET models (Forest-CEW, PML-V2, and PT-JPL) in a complex forest by analyzing their components. The data comes from seven ground-based eddy covariance flux towers in Brazil, which are part of the "Large Scale Biosphere- Atmosphere Experiment in Amazonia" (LBA) project. Our study found that the R2 of Forest-CEW was 0.64, that of PT-JPL was 0.43, and that of PML-V2 was only 0.29. The average results of the model show that T/ET=63.2 %±16 %, Ei/ET=32.3 %±16 %, and Es/ET=6 %±5 %. The model simulates better results in Savanna (RMSE=10.4 mm/month) than in the rainforest (RMSE=17.6 mm/month). Rn is the main driving variable of the model ET and T, with a sensitivity of 20 %, temperature is the main driver of Ei, accounting for 17 %, and LAI is the main driver of Es, but it produces a negative effect (-22.5 %). Our analysis emphasizes the differences in the ability of existing models to simulate ET dynamics in complex forests. Improving the formulation of ET components, particularly the canopy interception part, holds significant potential for substantially enhancing the accuracy and reliability of these ET models.

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Long-Xiao Luo, Jun Lei, and Zheng-Hong Tan

Status: open (until 02 Dec 2025)

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Long-Xiao Luo, Jun Lei, and Zheng-Hong Tan
Long-Xiao Luo, Jun Lei, and Zheng-Hong Tan

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Short summary
The purpose of this study is to evaluate the performance of the Evapotranspiration (ET) model in tropical forests. Compared to previous studies, this evaluation focuses more on the components of the model, which are also components of ET. Furthermore, one of the models being evaluated is still under development. This study can provide unique insights into the ET model.
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