Yi Wang

Evapotranspiration (ET) is the dominant hydrologic flux in wetlands, and partitioning into transpiration (T) and evaporation (E) is essential for understanding water and carbon dynamics, guiding sustainable water management practices, and predicting responses to climate change in these systems. However, the presence of moss layers and the dynamic hydrological condition in many wetlands challenges the assumptions of commonly used partitioning methods. This study evaluates ten eddy covariance (EC)-based ET partitioning approaches representing three methodological groups, namely high-frequency EC-based, ecosystem carbon-water coupling, and machine learning approaches, across four moss-covered wetlands in the boreal region and the Canadian Rocky Mountains. Evapotranspiration partitioning estimates were evaluated against independent measurement-based T : ET estimates derived from flux chambers, micro-lysimeters, sap flow sensors, and EC measurements, and against the ensemble mean of all ET partitioning approaches. Results showed that none of the evaluated approaches consistently outperformed the others across sites or under both flooded and non-flooded conditions, and no methodological group demonstrated a clear overall advantage. Evapotranspiration partitioning performance is likely influenced by the combined effects of multiple environmental and methodological factors, including moss cover, flooding conditions, canopy structure, ecosystem heterogeneity, EC measurement configuration and data quality, and the assumptions underlying each approach. In addition, the evaluation results are also influenced by the choice of reference dataset, which highlights the uncertainty associated with benchmarking ET partitioning methods. These findings suggest that applying multiple ET partitioning approaches concurrently, whenever possible, can help identify sources of uncertainty and potential errors. The study also highlights the need to develop wetland-specific ET partitioning approaches that better represent moss-mediated carbon uptake, dynamic carbon-water coupling, and transitions between unsaturated and flooded conditions.

Accurate estimation of surface energy fluxes is essential for understanding land–atmosphere interactions, yet many existing models requires numerous parameters that are often difficult to measure or calibrate. Models based on equilibrium concepts, such as the Relative Humidity at Equilibrium approach and the Surface Flux Equilibrium method, together with the model based on the maximum entropy production principle, have been shown to effectively estimate surface energy fluxes with reduced reliance on parameterization and calibration data. A previous study demonstrated the connection of these approaches in estimating evapotranspiration and proposed a unified formulation. However, the performance and physical soundness of this formulation have not yet been fully established. In particular, the dissipation function in the maximum entropy production model is conceptualized based on heat conduction, whereas heat transfer in the atmospheric surface layer is governed by turbulent transport. This difference needs to be reconciled to ensure physical consistency. This study addresses this issue by reparametrizing the dissipation function within a bulk resistance scheme, which allows equilibrium concepts and the maximum entropy production principle to be integrated to estimate surface energy fluxes. This framework is evaluated across different ecosystems using only air temperature, humidity, pressure, net radiation and wind speed. Results show that it provides reliable half-hourly estimates of sensible and latent heat fluxes and improves performance relative to the original maximum entropy production model. Overall, the proposed framework provides a low-input, physically grounded approach for estimating surface energy fluxes and offers a new perspective for representing land–atmosphere coupling.

Evapotranspiration (ET) is the dominant hydrologic flux in wetlands, and partitioning into transpiration (T) and evaporation (E) is essential for understanding water and carbon dynamics, guiding sustainable water management practices, and predicting responses to climate change in these systems. However, the presence of moss layers in many wetlands challenges the assumptions of commonly used partitioning methods. This study evaluates the performance of nine eddy covariance (EC)-based ET partitioning approaches across multiple moss-covered wetland sites located in boreal and the Canadian Rocky Mountains. The partitioning results from each approach were compared against independent measurement-based estimates, which were obtained using flux chamber, micro-lysimeters, sap flow sensors, and EC systems. Results showed that none of the evaluated methods provided both accurate and precise estimates of ET partitioning (T:ET), and no single method emerged as the most suitable for studied ecosystems. Despite this, the general agreement between modelled and measured T:ET values indicates that many of these approaches still provide valuable insights. Applying multiple methods concurrently is recommended, where possible, to enhance confidence in partitioning results. For researchers with access to high-frequency EC data, priority should be given to high-frequency EC-based methods due to their more consistent performance across sites. The findings also highlight the limitations of current partitioning approaches under evaporation-dominated conditions, and underscore the need to examine the mechanistic role of mosses, as well as to improve how optimal stomatal conductance theory is conceptualized and implemented in model formulations.

Evapotranspiration (ET) is the dominant hydrologic flux in wetlands, and partitioning into transpiration (T) and evaporation (E) is essential for understanding water and carbon dynamics, guiding sustainable water management practices, and predicting responses to climate change in these systems. However, the presence of moss layers in many wetlands challenges the assumptions of commonly used partitioning methods. This study evaluates the performance of nine eddy covariance (EC)-based ET partitioning approaches across multiple moss-covered wetland sites located in boreal and the Canadian Rocky Mountains. The partitioning results from each approach were compared against independent measurement-based estimates, which were obtained using flux chamber, micro-lysimeters, sap flow sensors, and EC systems. Results showed that none of the evaluated methods provided both accurate and precise estimates of ET partitioning (T:ET), and no single method emerged as the most suitable for studied ecosystems. Despite this, the general agreement between modelled and measured T:ET values indicates that many of these approaches still provide valuable insights. Applying multiple methods concurrently is recommended, where possible, to enhance confidence in partitioning results. For researchers with access to high-frequency EC data, priority should be given to high-frequency EC-based methods due to their more consistent performance across sites. The findings also highlight the limitations of current partitioning approaches under evaporation-dominated conditions, and underscore the need to examine the mechanistic role of mosses, as well as to improve how optimal stomatal conductance theory is conceptualized and implemented in model formulations.

Evapotranspiration (ET) is the dominant hydrologic flux in wetlands, and partitioning into transpiration (T) and evaporation (E) is essential for understanding water and carbon dynamics, guiding sustainable water management practices, and predicting responses to climate change in these systems. However, the presence of moss layers in many wetlands challenges the assumptions of commonly used partitioning methods. This study evaluates the performance of nine eddy covariance (EC)-based ET partitioning approaches across multiple moss-covered wetland sites located in boreal and the Canadian Rocky Mountains. The partitioning results from each approach were compared against independent measurement-based estimates, which were obtained using flux chamber, micro-lysimeters, sap flow sensors, and EC systems. Results showed that none of the evaluated methods provided both accurate and precise estimates of ET partitioning (T:ET), and no single method emerged as the most suitable for studied ecosystems. Despite this, the general agreement between modelled and measured T:ET values indicates that many of these approaches still provide valuable insights. Applying multiple methods concurrently is recommended, where possible, to enhance confidence in partitioning results. For researchers with access to high-frequency EC data, priority should be given to high-frequency EC-based methods due to their more consistent performance across sites. The findings also highlight the limitations of current partitioning approaches under evaporation-dominated conditions, and underscore the need to examine the mechanistic role of mosses, as well as to improve how optimal stomatal conductance theory is conceptualized and implemented in model formulations.

Evapotranspiration (ET) is the dominant hydrologic flux in wetlands, and partitioning into transpiration (T) and evaporation (E) is essential for understanding water and carbon dynamics, guiding sustainable water management practices, and predicting responses to climate change in these systems. However, the presence of moss layers in many wetlands challenges the assumptions of commonly used partitioning methods. This study evaluates the performance of nine eddy covariance (EC)-based ET partitioning approaches across multiple moss-covered wetland sites located in boreal and the Canadian Rocky Mountains. The partitioning results from each approach were compared against independent measurement-based estimates, which were obtained using flux chamber, micro-lysimeters, sap flow sensors, and EC systems. Results showed that none of the evaluated methods provided both accurate and precise estimates of ET partitioning (T:ET), and no single method emerged as the most suitable for studied ecosystems. Despite this, the general agreement between modelled and measured T:ET values indicates that many of these approaches still provide valuable insights. Applying multiple methods concurrently is recommended, where possible, to enhance confidence in partitioning results. For researchers with access to high-frequency EC data, priority should be given to high-frequency EC-based methods due to their more consistent performance across sites. The findings also highlight the limitations of current partitioning approaches under evaporation-dominated conditions, and underscore the need to examine the mechanistic role of mosses, as well as to improve how optimal stomatal conductance theory is conceptualized and implemented in model formulations.

The maximum information entropy production model (MaxEnt), the relative humidity at equilibrium approach (ETRHEQ), and the Surface Flux Equilibrium model (SFE) are three recently developed models to estimate evapotranspiration. Although the connection between ETRHEQ and SFE is evident, no attempts have been made to investigate the congruence, distinctions, or potential complementarity between the two models and MaxEnt. Our mathematical analysis demonstrates that minimizing the vertical variance of RH in ETRHEQ is equivalent to minimizing the dissipation function of energy fluxes in MaxEnt, under the assumption of the same eddy diffusivity of heat and water vapor and with a specific expression for the ratio between the thermal inertia terms for H and LE. The connection between ETRHEQ, SFE, and MaxEnt is independent of Monin‐Obukhov similarity theory (MOST)’s extremum solution, and MOST's extreme solution can be viewed as equivalent to introducing a constant correction factor to account for atmospheric stability. While ETRHEQ and MaxEnt can be united within a single hydrometeorological framework, they diverge in their approaches to modeling evapotranspiration, particularly in how they address the roles of vegetation and land surface heterogeneity. More importantly, the unified framework suggests that turbulence fluxes within the atmospheric boundary layer adhere to the principles of maximum information entropy production. The way in which dissipation, along with its associated entropy production, is established using information entropy theory deviates from traditional thermodynamic entropy formulations. Exploring the connection between thermodynamic and information entropy and developing proper formulations of dissipation for energy fluxes presents an appealing avenue for prospective research.

The maximum information entropy production model (MaxEnt), the relative humidity at equilibrium approach (ETRHEQ), and the Surface Flux Equilibrium model (SFE) are the three effective parsimonious models to estimate evapotranspiration. No attempts have been made to investigate their congruence, distinctions, or potential complementarity. Our mathematical analysis demonstrates that minimizing the dissipation function of energy fluxes in MaxEnt is equivalent to minimizing the vertical variance of RH in ETRHEQ. The effectiveness of both MaxEnt and ETRHEQ lies in the fact that far-from-equilibrium ecosystems progress toward a steady state (the SFE state) by minimizing dissipation. This tendency is manifested through the vertical variance of RH. The connection between MaxEnt, ETRHEQ, and SFE is independent of Monin-Obukhov similarity theory (MOST)’s extremum solution, and MOST’s extreme solution can be viewed as equivalent to introducing a constant correction factor to account for atmospheric stability. While MaxEnt and ETRHEQ share a common physical foundation, they diverge in their approaches to modeling evapotranspiration, particularly in how they address the roles of vegetation and land surface heterogeneity. More importantly, the unified hydrometeorological framework suggests that turbulence fluxes within the atmospheric boundary layer adhere to the principles of maximum information entropy production. The way in which dissipation, along with its associated entropy production, is established using information entropy theory deviates from traditional thermodynamic entropy formulations. Delving into the precise computation of dissipation and entropy production for energy fluxes at different temporal and spatial scales presents an appealing avenue for prospective research.

Bare soil evaporation has been studied extensively, but less is certain regarding how site‐specific features, especially the overstory tree canopy and ground covers, mediate evaporation processes. Inspired by recent advances on modelling bare soil evaporative efficiency (SEE), this study explored SEE over a range of soil substrates and ground cover types, with and without the presence of an overstory canopy in three mesic ecosystems in Canadian Rocky Mountains. A significant relationship was found between the critical soil water content and ground cover mass fractions across various ground cover types, both with and without the presence of an overstory canopy. This relationship is expected to be prevalent across various ecosystems. Moreover, a simple approach for modelling SEE of vegetated surfaces and a correction method to account for below‐canopy SEE is also proposed. The model yields satisfactory simulations, and the approach is expected to be widely applicable, given the strength that its parameters are easily acquired, and its formulations are simple and straightforward. While the model may be particularly suited to mesic ecosystems, the underlying mechanism of SEE suggests that this model can also be applied in dryer conditions. This approach will greatly improve ET parameterization in land‐surface models (LSMs) and increase our knowledge of the global water cycle and ecosystem responses under climate change impacts.