Publication

An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates

Li, J., Ju, W., He, W., Wang, H., Zhou, Y. & Xu, M., Apr-2019, In : Journal of geophysical research-Biogeosciences. 124, 4, p. 807-824 18 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Li, J., Ju, W., He, W., Wang, H., Zhou, Y., & Xu, M. (2019). An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates. Journal of geophysical research-Biogeosciences, 124(4), 807-824. https://doi.org/10.1029/2018JG004675

Author

Li, Jing ; Ju, Weimin ; He, Wei ; Wang, Hengmao ; Zhou, Yanlian ; Xu, Mingzhu. / An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates. In: Journal of geophysical research-Biogeosciences. 2019 ; Vol. 124, No. 4. pp. 807-824.

Harvard

Li, J, Ju, W, He, W, Wang, H, Zhou, Y & Xu, M 2019, 'An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates', Journal of geophysical research-Biogeosciences, vol. 124, no. 4, pp. 807-824. https://doi.org/10.1029/2018JG004675

Standard

An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates. / Li, Jing; Ju, Weimin; He, Wei; Wang, Hengmao; Zhou, Yanlian; Xu, Mingzhu.

In: Journal of geophysical research-Biogeosciences, Vol. 124, No. 4, 04.2019, p. 807-824.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Li J, Ju W, He W, Wang H, Zhou Y, Xu M. An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates. Journal of geophysical research-Biogeosciences. 2019 Apr;124(4):807-824. https://doi.org/10.1029/2018JG004675


BibTeX

@article{72cd93318f9f46dd8cd90ee586eb7b19,
title = "An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates",
abstract = "Surface conductance (G(s)) is a key parameter in estimating land surface evapotranspiration (ET) and difficult to determine. Here we proposed an approach for determining G(s) according to the stomatal conductance of sunlit and shaded leaves that is estimated from their respective gross primary production (GPP) with the Ball-Berry model. Central to this approach, GPP is separately simulated for sunlit and shaded leaves with a revised two-leaf light use efficiency model. We tested the approach at 17 FLUXNET sites with seven different vegetation types. The revised two-leaf light use efficiency model outperforms its predecessor in estimating GPP at most sites. As to G(s) estimation, although our proposed algorithm has higher Akaike information criterion values than has the model estimating G(s) using vegetation indices, it was able to capture G(s) variations at all sites, while models estimating G(s) using leaf area index and vegetation indices performed poor at some sites. The proposed algorithm also improves ET estimation, indicated by lower Akaike information criterion, higher determination coefficient (R-2), and lower root mean square error of simulated daily ET for both calibration and validation data sets. This study demonstrates the usefulness of differentiating sunlit and shaded leaves in improving canopy conductance and ET estimates.",
keywords = "GROSS PRIMARY PRODUCTION, CARBON-DIOXIDE EXCHANGE, USE EFFICIENCY MODEL, STOMATAL CONDUCTANCE, SENSITIVITY-ANALYSIS, DECIDUOUS FOREST, WATER FLUXES, NARROW-BAND, SCALING-UP, EVAPOTRANSPIRATION",
author = "Jing Li and Weimin Ju and Wei He and Hengmao Wang and Yanlian Zhou and Mingzhu Xu",
year = "2019",
month = "4",
doi = "10.1029/2018JG004675",
language = "English",
volume = "124",
pages = "807--824",
journal = "Journal of Geophysical Research",
issn = "0148-0227",
publisher = "AMER GEOPHYSICAL UNION",
number = "4",

}

RIS

TY - JOUR

T1 - An Algorithm Differentiating Sunlit and Shaded Leaves for Improving Canopy Conductance and Vapotranspiration Estimates

AU - Li, Jing

AU - Ju, Weimin

AU - He, Wei

AU - Wang, Hengmao

AU - Zhou, Yanlian

AU - Xu, Mingzhu

PY - 2019/4

Y1 - 2019/4

N2 - Surface conductance (G(s)) is a key parameter in estimating land surface evapotranspiration (ET) and difficult to determine. Here we proposed an approach for determining G(s) according to the stomatal conductance of sunlit and shaded leaves that is estimated from their respective gross primary production (GPP) with the Ball-Berry model. Central to this approach, GPP is separately simulated for sunlit and shaded leaves with a revised two-leaf light use efficiency model. We tested the approach at 17 FLUXNET sites with seven different vegetation types. The revised two-leaf light use efficiency model outperforms its predecessor in estimating GPP at most sites. As to G(s) estimation, although our proposed algorithm has higher Akaike information criterion values than has the model estimating G(s) using vegetation indices, it was able to capture G(s) variations at all sites, while models estimating G(s) using leaf area index and vegetation indices performed poor at some sites. The proposed algorithm also improves ET estimation, indicated by lower Akaike information criterion, higher determination coefficient (R-2), and lower root mean square error of simulated daily ET for both calibration and validation data sets. This study demonstrates the usefulness of differentiating sunlit and shaded leaves in improving canopy conductance and ET estimates.

AB - Surface conductance (G(s)) is a key parameter in estimating land surface evapotranspiration (ET) and difficult to determine. Here we proposed an approach for determining G(s) according to the stomatal conductance of sunlit and shaded leaves that is estimated from their respective gross primary production (GPP) with the Ball-Berry model. Central to this approach, GPP is separately simulated for sunlit and shaded leaves with a revised two-leaf light use efficiency model. We tested the approach at 17 FLUXNET sites with seven different vegetation types. The revised two-leaf light use efficiency model outperforms its predecessor in estimating GPP at most sites. As to G(s) estimation, although our proposed algorithm has higher Akaike information criterion values than has the model estimating G(s) using vegetation indices, it was able to capture G(s) variations at all sites, while models estimating G(s) using leaf area index and vegetation indices performed poor at some sites. The proposed algorithm also improves ET estimation, indicated by lower Akaike information criterion, higher determination coefficient (R-2), and lower root mean square error of simulated daily ET for both calibration and validation data sets. This study demonstrates the usefulness of differentiating sunlit and shaded leaves in improving canopy conductance and ET estimates.

KW - GROSS PRIMARY PRODUCTION

KW - CARBON-DIOXIDE EXCHANGE

KW - USE EFFICIENCY MODEL

KW - STOMATAL CONDUCTANCE

KW - SENSITIVITY-ANALYSIS

KW - DECIDUOUS FOREST

KW - WATER FLUXES

KW - NARROW-BAND

KW - SCALING-UP

KW - EVAPOTRANSPIRATION

U2 - 10.1029/2018JG004675

DO - 10.1029/2018JG004675

M3 - Article

VL - 124

SP - 807

EP - 824

JO - Journal of Geophysical Research

JF - Journal of Geophysical Research

SN - 0148-0227

IS - 4

ER -

ID: 118596108