November 23, 2019
Modeling Tree Stem-water Dynamics over an Amazonian Rainforest
Incorporating tree stem-water dynamics improves land model capability to simulate water and energy fluxes in tropical forests.
Scientists at Oak Ridge National Laboratory incorporated a tree stem-water component into the version 4 of Community Land Model (CLM4) to characterize the dynamic stem-water storage and its impacts on the daily transpiration rate. The updated model was evaluated at an Amazonian rainforest site to assess model capability to simulate diurnal and monthly dynamics in water and energy fluxes
The study demonstrated that the inclusion of stem capacitance in CLM4 can significantly improve the model’s capability to simulate the response of water and heat fluxes of tropical rainforests to drought conditions.
A novel tree stem-water model was developed to capture the dynamics of stem- water storage and its contribution to daily transpiration. The module was incorporated into the Community Land Model (CLM), where it was used to test model sensitivity to stem-water content for an NGEE-Tropics evergreen rainforest site in Amazonia, that is, the BR-Sa3 eddy covariance site. With the inclusion of the stem-water storage, CLM produced greater dry-season latent heat flux that was closer to observations, facilitated by easier canopy access to a nearby stem-water source rather than being solely dependent on soil water. The simulated stem-water content also showed seasonal variations in magnitude corresponding with seasonal variations in sap flow rate. Stored stem-water of a single mature tree was estimated to contribute 20–80 kg/day of water to transpiration during the wet season and 90–110 kg/day during the dry season, thereby partially replacing soil water and maintaining plant transpiration during the dry season. Diurnally, stem-water content declined as water was extracted for transpiration in the morning and then was refilled from soil water beginning in the afternoon and through the night. The dynamic discharge and recharge of stem storage was also shown to be regulated by multiple environmental drivers. Our study indicates that the inclusion of stem capacitance in CLM significantly improves model simulations of dry-season water and heat fluxes, in terms of both magnitude and timing.
Oak Ridge National Laboratory
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
Jiafu Mao, Peter E. Thornton, Xiaoying Shi, Daniel M. Ricciuto, Jeffrey M. Warren, and Forrest M. Hoffman are supported by DOE Office of Science, Biological and Environmental Research, including support from NGEE-Tropics and the ORNL Terrestrial Ecosystem Science SFA.
Binyan Y., J. Mao, E. E. Dickinson, and P. E. Thornton, et al. "Modelling tree stem-water dynamics over an Amazonian rainforest site". Ecohydrology 13 (1), e2180 (2020). https://doi.org/10.1002/eco.2180.