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.

Improvement of transpiration estimation based on a two-leaf conductance-photosynthesis model with seasonal parameters for temperate deciduous forests

“…However, the parametrized schemes remain less robust. Generally, the key parameters in the g s -A models are temporal constant ( Miner et al., 2017 ), especially the model with the two-leaf scheme ( Lawrence et al., 2011 ; Li et al., 2019 ). Previous studies have reported that hydraulic and photosynthetic parameters varied with time, showing a higher value in mature leaves relative to young and old leaves ( Wilson et al., 2001 ; Albert et al., 2018 ; Chavana-Bryant et al., 2019 ).…”

“…Considering the seasonality of the physiological variables, this study aimed to investigate performances of the TL-based g s -A models with different parametrization schemes (i.e., the fixed vs. dynamic parametrization schemes). Towards this aim, the TL-LUE ( He et al., 2013 ) and TL B-B model ( Li et al., 2019 ) were adopted, as well as flux- and satellite-based observations at three temperate deciduous broadleaf forests (DBF) FLUXNET sites. Two specific questions are answered in this study: (1) Do the key parameters of photosynthesis and stomatal conductance modeling vary with season?…”

A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies from 1992 to 2020

“…The revised TL-LUE model adds the atmospheric CO 2 concentration regulation scalar and modifies air temperature regulation scalar. GPP is divided into GPP shade and GPP sun 52 . It is described as Eqs.…”

“…The regulation scalars of temperature (T s ) 52 , water stress (W s ) 48 , and atmospheric CO 2 concentration (C s ) 54 are calculated as follows: where the maximum (T max ) and minimum temperatures for vegetation photosynthesis (T min ) were set to 313.15 K and 273.15 K, respectively 49 . The optimum temperature for vegetation photosynthesis (T opt ) is set as the average of different types in Huang et al .…”

A dynamic-leaf light use efficiency model for improving gross primary production estimation

“…For example, a 5% uncertainty of SW can lead to a 5% uncertainty of CI (CI = SW/1367cosθ). Finally, several efficient environmental constraints (Li et al 2019, Zheng et al 2020 and the spatial and temporal variations in the mean leaf-sun angle (Liu et al 2019, Li et al 2023 and clumping index (He et al 2012, Fang et al 2019 were not considered in this study, since it mainly focused on the comparative performances of the three LUE models rather than the absolute accuracy of the DL-LUE model. More future attempts should be implemented to address these issues.…”