Plant Hydraulics Improves Predictions of ET and GPP Responses to Drought

Abstract Land surface models typically ignore plant hydraulic processes and use empirical soil moisture stress functions to limit transpiration and photosynthesis. How plant hydraulics impacts the predictions of carbon and water fluxes and their responses to drought remains unclear. Here, we developed an analytical plant hydraulic scheme wherein hydraulic capacitances at the leaf level and stem level were considered, and incorporated it into the vegetation interface processes model (hereafter, VIP‐PHS). Then, we calibrated the VIP‐PHS parameters using a Markov Chain Monte Carlo (MCMC) method and conducted an ecosystem‐scale evaluation of the VIP‐PHS at 30 FLUXNET sites. The results showed that VIP‐PHS improved evapotranspiration (ET) and gross primary production (GPP) simulations across the studied sites, reducing the root mean square error (RMSE) by 0.02–0.27 mm day −1 and 0.04–0.52 g C m −2 day −1 in relation to the empirical soil hydraulic scheme (hereafter, VIP‐SHS). VIP‐PHS decreased the RMSE in ET and GPP by up to 45% and 55% in evergreen needleleaf forests. Compared to VIP‐SHS, VIP‐PHS decreased the sensitivities of ET and GPP to soil moisture stress, and significantly improved ET and GPP predictions under low soil moisture conditions. The sensitivity analysis showed that larger stem hydraulic capacitance better relieved xylem water stress, resulting in greater transpiration and GPP and less‐negative daily minimum stem water potential. These findings highlight the need to incorporate plant hydraulics into the next generation of Earth system models under future drought conditions.