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

Accurate estimation of stomatal conductance (g_s) is fundamental for modeling coupled photosynthesis-transpiration responses to climate change, yet current approaches face limitations under drought conditions. To predict g_s under drought, the widely-used Ball-Woodrow-Berry (BWB) model relies on empirical soil moisture functions (f_w) 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 f_w) 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 g_s to vapor pressure deficit were not considered. While the PM-based energy balance approach performed well for g_s of oilseed rape, it required modification for soybean to account for greater leaf temperature fluctuations (ΔT_leaf) under water-deficit relative to well-watered conditions caused by more variable water deficits. Our study demonstrated that integrating an inversed PM equation for g_s with the CO₂-diffusion law and a biochemical photosynthesis model accounting for ΔT_leaf is an effective approach to predict both photosynthetic rate and g_s under water stress without introducing empirical functions.