Estimating stomatal conductance under drought: Parameterizing a phenomenological model and evaluating roles of the energy balance equation

Qian Liu, Fangmin Zhang and Xinyou Yin

Ecological Modelling, 2025, vol. 505, issue C

Abstract: Accurate estimation of stomatal conductance (gs) is fundamental for modeling coupled photosynthesis-transpiration responses to climate change, yet current approaches face limitations under drought conditions. To predict gs under drought, the widely-used Ball-Woodrow-Berry (BWB) model relies on empirical soil moisture functions (fw) with uncertain validity. As a physically-based alternative, inverted Penman-Monteith (PM) equation derived from leaf energy balance principles offers a mechanistic solution. To evaluate the implicit assumption that BWB model parameters (excluding fw) remain not altered by drought and the predictive capability of the PM-based energy balance approach, a two-year field experiment in the nationally-planted oil crops—soybean (Glycine max L.) and oilseed rape (Brassica napus L.) was conducted. Our results revealed that crop-specific responses in BWB parameter variations during water stress, with significant predictive errors occurring if responses of gs to vapor pressure deficit were not considered. While the PM-based energy balance approach performed well for gs of oilseed rape, it required modification for soybean to account for greater leaf temperature fluctuations (ΔTleaf) under water-deficit relative to well-watered conditions caused by more variable water deficits. Our study demonstrated that integrating an inversed PM equation for gs with the CO2-diffusion law and a biochemical photosynthesis model accounting for ΔTleaf is an effective approach to predict both photosynthetic rate and gs under water stress without introducing empirical functions.

Keywords: Stomatal conductance; Ball-Woodrow-Berry (BWB) model; Penman-monteith equation; Water stress; Leaf temperature (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:505:y:2025:i:c:s0304380025001188

DOI: 10.1016/j.ecolmodel.2025.111133

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