BibTex format

author = {Tan, S and Wang, H and Prentice, IC and Yang, K and Nóbrega, RLB and Liu, X and Wang, Y and Yang, Y},
doi = {10.1016/j.agrformet.2023.109478},
journal = {Agricultural and Forest Meteorology},
pages = {1--11},
title = {Towards a universal evapotranspiration model based on optimality principles},
url = {},
volume = {336},
year = {2023}

RIS format (EndNote, RefMan)

AB - Natural resource management requires knowledge of terrestrial evapotranspiration (ET). Most existing numeric models for ET include multiple plant- or ecosystem-type specific parameters that require calibration. This is a significant source of uncertainty under changing environmental conditions. A novel ET model with no type−specific parameters was developed recently. Based on the coupling the diffusion (via stomata) of water and carbon dioxide (CO2), this model predicts canopy conductance based on environmental conditions using eco-evolutionary optimality principles that apply to all plant types. Transpiration (T) and ET are calculated from canopy conductance using the Penman-Monteith equation for T and a universal empirical function for the T:ET ratio. Here, the model is systematically evaluated at globally distributed eddy-covariance sites and river basins. Site-scale modelled ET agrees well with flux data (r = 0.81, root mean square error = 0.73 mm day–1 in 23,623 records) and modelled ET in 39 river basins agrees well with the ET estimated by monthly water budget using two runoff datasets (r = 0.62 and 0.66, respectively). Modelled global patterns of ET are consistent with existing global ET products. The model's universality, parsimony and accuracy combine to indicate a broad potential field of application in resource management and global change science.
AU - Tan,S
AU - Wang,H
AU - Prentice,IC
AU - Yang,K
AU - Nóbrega,RLB
AU - Liu,X
AU - Wang,Y
AU - Yang,Y
DO - 10.1016/j.agrformet.2023.109478
EP - 11
PY - 2023///
SN - 0168-1923
SP - 1
TI - Towards a universal evapotranspiration model based on optimality principles
T2 - Agricultural and Forest Meteorology
UR -
UR -
UR -
VL - 336
ER -