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Towards a universal evapotranspiration model based on optimality principles

Title: Towards a universal evapotranspiration model based on optimality principles
Authors: Tan, S; Wang, H; Prentice, IC; Yang, K; Nóbrega, RLB; Liu, X; Wang, Y; Yang, Y
Source: 11 ; 1
Publisher Information: Elsevier B.V.
Publication Year: 2023
Collection: Imperial College London: Spiral
Description: 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.
Document Type: article in journal/newspaper
Language: English
Relation: Agricultural and Forest Meteorology; http://hdl.handle.net/10044/1/104192
DOI: 10.1016/j.agrformet.2023.109478
Availability: http://hdl.handle.net/10044/1/104192; https://doi.org/10.1016/j.agrformet.2023.109478
Rights: © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ; https://creativecommons.org/licenses/by-nc-nd/4.0/
Accession Number: edsbas.37946FCE
Database: BASE