Towards a universal evapotranspiration model based on optimality principles

Shen Tan; Han Wang; Iain Colin Prentice; Kun Yang; Rodolfo L.B. Nóbrega; Xiaomang Liu; Yong Wang; Yuting Yang

doi:10.1016/j.agrformet.2023.109478

Towards a universal evapotranspiration model based on optimality principles

Shen Tan, Han Wang^*, Iain Colin Prentice, Kun Yang, Rodolfo L.B. Nóbrega, Xiaomang Liu, Yong Wang, Yuting Yang

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

7 Citations (Scopus)

Abstract

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.

Original language	English
Article number	109478
Journal	Agricultural and Forest Meteorology
Volume	336
Early online date	2 May 2023
DOIs	https://doi.org/10.1016/j.agrformet.2023.109478
Publication status	Published - 1 Jun 2023

Bibliographical note

Funding Information:
This research was supported by the National Natural Science Foundation of China (no. 31971495 , 42001356 , 32022052 ). ICP and RLBN acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No: 787203 REALM) and the High-End Foreign Expert program of the China State Administration of Foreign Expert Affairs at Tsinghua University (No: G202210301 ). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme. We thank the FLUXNET community for providing tower-based flux observation. We also like to thank the Google Earth Engine team for providing calculation resource and distribution platform.

Funding Information:
This research was supported by the National Natural Science Foundation of China (no. 31971495, 42001356, 32022052). ICP and RLBN acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No: 787203 REALM) and the High-End Foreign Expert program of the China State Administration of Foreign Expert Affairs at Tsinghua University (No: G202210301). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme. We thank the FLUXNET community for providing tower-based flux observation. We also like to thank the Google Earth Engine team for providing calculation resource and distribution platform.

Publisher Copyright:
© 2023

Keywords

Canopy conductance
Eco-evolutionary optimality
Evapotranspiration
Remote sensing
Transpiration
Water balance

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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title = "Towards a universal evapotranspiration model based on optimality principles",

abstract = "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.",

keywords = "Canopy conductance, Eco-evolutionary optimality, Evapotranspiration, Remote sensing, Transpiration, Water balance",

author = "Shen Tan and Han Wang and Prentice, {Iain Colin} and Kun Yang and N{\'o}brega, {Rodolfo L.B.} and Xiaomang Liu and Yong Wang and Yuting Yang",

note = "Funding Information: This research was supported by the National Natural Science Foundation of China (no. 31971495 , 42001356 , 32022052 ). ICP and RLBN acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No: 787203 REALM) and the High-End Foreign Expert program of the China State Administration of Foreign Expert Affairs at Tsinghua University (No: G202210301 ). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme. We thank the FLUXNET community for providing tower-based flux observation. We also like to thank the Google Earth Engine team for providing calculation resource and distribution platform. Funding Information: This research was supported by the National Natural Science Foundation of China (no. 31971495, 42001356, 32022052). ICP and RLBN acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No: 787203 REALM) and the High-End Foreign Expert program of the China State Administration of Foreign Expert Affairs at Tsinghua University (No: G202210301). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme. We thank the FLUXNET community for providing tower-based flux observation. We also like to thank the Google Earth Engine team for providing calculation resource and distribution platform. Publisher Copyright: {\textcopyright} 2023",

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AU - Nóbrega, Rodolfo L.B.

AU - Liu, Xiaomang

AU - Wang, Yong

AU - Yang, Yuting

N1 - Funding Information: This research was supported by the National Natural Science Foundation of China (no. 31971495 , 42001356 , 32022052 ). ICP and RLBN acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No: 787203 REALM) and the High-End Foreign Expert program of the China State Administration of Foreign Expert Affairs at Tsinghua University (No: G202210301 ). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme. We thank the FLUXNET community for providing tower-based flux observation. We also like to thank the Google Earth Engine team for providing calculation resource and distribution platform. Funding Information: This research was supported by the National Natural Science Foundation of China (no. 31971495, 42001356, 32022052). ICP and RLBN acknowledges support from the European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No: 787203 REALM) and the High-End Foreign Expert program of the China State Administration of Foreign Expert Affairs at Tsinghua University (No: G202210301). This work is a contribution to the LEMONTREE (Land Ecosystem Models based On New Theory, obseRvations and ExperimEnts) project, funded through the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures programme. We thank the FLUXNET community for providing tower-based flux observation. We also like to thank the Google Earth Engine team for providing calculation resource and distribution platform. Publisher Copyright: © 2023

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N2 - 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.

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.

KW - Canopy conductance

KW - Eco-evolutionary optimality

KW - Evapotranspiration

KW - Remote sensing

KW - Transpiration

KW - Water balance

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M3 - Article (Academic Journal)

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JO - Agricultural and Forest Meteorology

JF - Agricultural and Forest Meteorology

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ER -

Towards a universal evapotranspiration model based on optimality principles

Abstract

Bibliographical note

Keywords

UN SDGs

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