Predicting Forest Evapotranspiration by Coupling Carbon and Water Cycling Based on a Critical Stomatal Conductance Model

Quantifying forest evapotranspiration (ET) is essential for understanding of climatic response of forest carbon and water cycling. However, there are still large uncertainties in forest ET predictions, especially in plant transpiration (PT). The poor estimations of forest ET and PT are largely attributed to the neglect of wet canopy evaporation and uncertainties in the stomatal conductance. Thus, by coupling a revised Ball-Woodrow-Berry (BWB) model, a precipitation intercepted algorithm and the gross primary production (GPP) model to Shuttleworth-Wallace (SW) model, this study introduced a modified SW (SWm ) model. The performances of this model were subsequently tested in three different forest sites with long-term observed records. Compared with previous models, SWm had a canopy stomatal scheme with stronger ecological significance and simpler GPP estimation scheme. Our analyses reveal the following. 1) SW
_m
evidently improves the agreements between estimated and measured ET compared to original SW (R
²
increasing by 0.19-0.68). SWm could more accurately partition PT and evaporation, when compared with an earlier BWB-based SW (R2 increasing by ~0.03). This finding also supports the use of Lohammer function in semiempirical model of stomatal conductance. 2) Accurate predictions of GPP are helpfulforimprovingETestimationsinSW
_m
(r = 0.73,p <; 0.01), suggesting that carbon and water fluxes are inherently linked. 3) In addition to GPP, leaf area index evidently affects the performances of estimated ET in SWm. These results suggest that critically coupling carbon and water cycling are very important for improving forest ET prediction.