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Cited by 68Plant Water Relations and Carbon DynamicsSoil Moisture and Remote SensingHydrology and Drought Analysis

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The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models

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Trebs, Ivonne, Mallick, Kaniska, Bhattarai, Nishan, Sulis, Mauro, Cleverly, Jamie, Woodgate, William, Silberstein, Richard, Hinko-Najera, Nina, Beringer, Jason, Meyer, Wayne S., Su, Zhongbo, Boulet, Gilles·2021·Remote Sensing of Environment
DOI 10.1016/j.rse.2021.112602
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Abstract

Aerodynamic resistance (hereafter ra) is a preeminent variable in evapotranspiration (ET) modelling. The accurate quantification of ra plays a pivotal role in determining the performance and consistency of thermal remote sensing-based surface energy balance (SEB) models for estimating ET at local to regional scales. Atmospheric stability links ra with land surface temperature (LST) and the representation of their interactions in the SEB models determines the accuracy of ET estimates. The present study investigates the influence of ra and its relation to LST uncertainties on the performance of three structurally different SEB models. It used data from nine Australian OzFlux eddy covariance sites of contrasting aridity in conjunction with MODIS Terra and Aqua LST and leaf area index (LAI) products. Simulations of the sensible heat flux (H) and the latent heat flux (LE, the energy equivalent of ET in W/m2) from the SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration), SEBS (Surface Energy Balance System) and STIC (Surface Temperature Initiated Closure) models forced with MODIS LST, LAI, and in-situ meteorological datasets were evaluated against flux observations in water-limited (arid and semi-arid) and energy-limited (mesic) ecosystems from 2011 to 2019. Our results revealed an overestimation tendency of instantaneous LE by all three models in the water-limited shrubland, woodland and grassland ecosystems by up to 50% on average, which was caused by an underesti…

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Authors
Trebs, I., Mallick, K., Bhattarai, N., Sulis, M., Cleverly, J., Woodgate, W., Silberstein, R., Hinko-Najera, N., Beringer, J., Meyer, W. S., Su, Z., & Boulet, G.
Affiliations
  • Luxembourg Institute of Science and Technology (LU)
  • University of Michigan (US)
  • Commonwealth Scientific and Industrial Research Organisation (AU)
  • Edith Cowan University (AU)
  • The University of Western Australia (AU)
  • The University of Adelaide (AU)
  • International Institute for Geo-Information Science and Earth Observation (NL)
  • Centre National de la Recherche Scientifique (FR)
Corresponding author
  • Trebs, Ivonne
  • Mallick, Kaniska
ORCID
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2021-10
Volume
264
Pages
112602
ISSN
0034-4257 (ISSN-L)
DOI
10.1016/j.rse.2021.112602
OpenAlex
W3193585998
Cited by
68
References
1
Citations by year
2026: 16 · 2025: 17 · 2024: 13 · 2023: 12 · 2022: 9 · 2021: 1
FWCI
3.46
Type
journal article
Language
en
Open access
Licence
Locations
  • Remote Sensing of Environment (publishedVersion, cc-by-nc-nd)
  • UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by-nc-nd)
  • Australasian Journal of Paramedicine (submittedVersion, cc-by-nc-nd)
  • HAL (submittedVersion, cc-by-nc-nd)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by-nc-nd)
  • University of Twente Research Information (submittedVersion, cc-by-nc-nd)
Funders
  • Australian Research Council (00002308)
  • Luxembourg Institute of Science and Technology (00002308)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Plant Water Relations and Carbon Dynamics
  • Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
  • Physical Sciences › Environmental Science › Global and Planetary Change › Hydrology and Drought Analysis
Keywords
aerodynamic resistance, evapotranspiration modeling, surface energy balance model, sensible heat flux, latent heat flux, atmospheric stability, MODIS land surface temperature, sparse models, SEBS model, arid and semi-arid ecosystems, roughness length, buoyancy-driven turbulence

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