Stomatal Conductance Modeling from the Perspectives of Land Surface Models
Abstract
To gain a deep understanding of the soil-plant-atmosphere continuum, important plants related processes have been identified and introduced into various stomatal conductance models. This leads to the increase in completeness in stomatal conductance models, so is the increase in the model complexity and the number of model parameters involved for estimation. Employing optimality principles is an effective way of reducing the number of model parameters related to plants, especially for situations with limited available observations. Studies have shown that various models, even those based on optimality principle, yield diverge results. This implies the current knowledge gap. In this study, we investigate the capabilities and potential limitations of individual optimality rules. Specifically, we employ the expressions of the least-cost optimality theory from the original formulation of Prentice et al. (2014), after extending it to include water-limited conditions, the updated semi-empirical Ball-Berry-Leuning formulation (Tuzet et al., 2003), the Anderegg, Dewar, and Sperry schemes, respectively, and investigate them from the land surface model perspectives. All of these five schemes are implemented into the VIC+ land surface model. This comparative study is focused on the differences in model's behaviors, the uncertainties of the model simulated variables of carbon assimilation, latent heat flux, stomatal conductance, leaf water potential, CO2 concentration in leaf, and soil moisture. The relevant parameters are analyzed using hourly time series of multiple years with data from two sites in the U.S. The interpretation of the results, specifically regarding the reasonableness of the variable combinations of solutions, is discussed and their implications are explored.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.B11A..02L