| 21 Oct 2025
Evaluation of evapotranspiration partitioning models in the Amazon forest
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.
The manuscript presents a model intercomparison study involving three approaches for estimating total evapotranspiration (ET) and partitioning it into transpiration (T), canopy-interception evaporation (Ei), and soil evaporation (Es) across seven sites located in and around the Amazon region. The models evaluated include a Penman–Monteith–based formulation (PML-V2), a Priestley–Taylor–based model (PT-JPL), and a new model developed by the authors (Forest-CEW). The study sites span diverse ecosystems—four tropical rainforests, one tropical wet-and-dry forest, one seasonally flooded forest–savanna ecotone, and one savanna—each equipped with eddy-covariance flux towers providing observed ET and key micrometeorological variables.
The topic is interesting and highly relevant, especially given the potentially large contribution of canopy-interception evaporation in dense tropical forests. Because Ei responds to meteorological drivers and canopy characteristics in ways very different from transpiration or soil evaporation, improving its representation remains an important challenge for land-surface and ecohydrological models.
Before evaluating model performance, the authors optimized key parameters for all three models using flux-tower data. Model skill was then assessed against observed ET across the seven sites. While all models captured general seasonal patterns, they performed poorly in reproducing ET magnitudes—particularly during the wet season, when Ei should be most prominent. This systematic bias suggests that interception processes are not adequately represented in any of the models. This is a major limitation of the study, aggravated by the absence of observational constraints for T, Ei, and Es, which restricts the ability to validate the partitioning schemes or identify which process assumptions are responsible for the errors.
Nonetheless, the study offers meaningful scientific insights. By contrasting structurally different models, the authors highlight persistent model biases, expose weaknesses in the treatment of interception losses, and point to model components that require improvement to better capture the ecohydrological dynamics of tropical forest ecosystems. With clearer exposition, careful treatment of uncertainties, and a more explicit discussion of limitations, this work could contribute valuably to the ongoing effort to improve ET partitioning in complex forest environments.
Specific comments (in order of appearance)
The manuscript requires a thorough language and clarity revision. Below are specific comments, organized by line number, to assist the authors in improving precision and readability.
Line 48: Replace “high” by “higher”.
Line 85: The reported LAI value of 6 m²/m² seems inconsistent with Figure 1, where maximum values are around 3. Verify and clarify.
Line 92: Clarify how monthly averages in Figure 1 were computed. Are they based on a single year or multiple years? How were daily variations in temperature and VPD handled?
Line 108–111: The reduction in Rn during the dry season may be related to the site’s (negative) latitude, which increases the solar-incidence angle. Consider revising the explanation accordingly.
Line 130: Specify which models have been “well applied” and clarify what is meant by “well applied”.
Line 151: Define qs and qp in Equation (2).
Line 152: Units of gv and gs appear inconsistent; they should not be directly added if units differ. Please verify.
Line 167: The text states that equations for Ei and Wwet are presented, but only the Ei equation appears. Include the missing equation or adjust the text.
Line 168: Clarify the time step of model simulations (hourly, daily, monthly).
Line 208: The Gash model is referenced but not presented. Provide details or remove the reference.
Line 214: Define G in Equation (15).
Line 242: The fact that K34 data are used for calibration should be mentioned earlier in the Methods.
Line 245: The models appear to overestimate ET rather than underestimate it. Re-evaluate this statement.
Line 251: In Figure 3, are the plotted points hourly ET values? Clarify in the caption and text.
Line 256: The meaning of “easier” is unclear; provide a more precise explanation.
Line 259: Replace “provids” with “provides”.
Line 264: Should be 500 m, not 500 km.
Line 305: In Figure 6, the trend lines do not seem to offer meaningful information; the slopes lack physical interpretation.
Line 323–329: This discussion seems uninformative. Averaging across sites with fundamentally different ecohydrological dynamics (e.g., rainforests vs. savanna) may be misleading.
Line 364–366: Is this statement supported by model results or observational data? Clarify the basis.
Line 409: Specify which of the three models this statement refers to.
Line 448–450: Without measurements of the ET components, it is difficult to state that the results are “incorrect”. A more appropriate term might be “inconsistent”.
Line 463: Clarify which model this refers to. The limitation may apply to all models, as none account for topographical effects.