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Early forest water stress detection using thermal infrared energy balance modeling during flash drought
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  • Published: 02 June 2026

Early forest water stress detection using thermal infrared energy balance modeling during flash drought

  • Lisheng Song1 na1,
  • Zhiwen Guan1 na1,
  • Michael Liddell2,
  • Bin He  ORCID: orcid.org/0000-0002-9088-262X3,
  • Jingfeng Xiao  ORCID: orcid.org/0000-0002-0622-69034,
  • Yan Li5,
  • Aoxiang Guo1,
  • Jianbo Qi  ORCID: orcid.org/0000-0001-6601-78826,
  • Peipei Xu1,
  • Fengman Fang1,
  • Kaifang Shi1,
  • Dong Chu1,
  • Xuguang Tang7 &
  • …
  • Shaomin Liu5 

Communications Earth & Environment (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Forest ecology
  • Natural hazards

Abstract

Rapid-onset flash droughts may cause devastating impacts on both ecosystems and human communities. We found that widely used multispectral satellite methods typically failed to capture the initial physiological response of forests to flash drought. Using a 3D radiative transfer model, we showed that canopy reflectance remained largely unchanged in the early stages of flash drought, even when upper-canopy leaves were wilting. We developed a new method based on a two-source energy balance model (TSEB-SM) driven by satellite infrared and soil moisture observations to capture water-flux dynamics in forests affected by flash drought. TSEB-SM tracked early-stage flash drought dynamics in China, where 8-daily transpiration declined by mean values of 14% (summer) and 6% (autumn) during the first two weeks of flash drought. Our results demonstrate that satellite-driven energy balance models can accurately track the temporal response of forests to flash drought, providing new tools for forest management in a warming climate.

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Acknowledgements

The ground observations of water and carbon flux data were collected and made freely available from FLUXNET 2015 dataset. We would like to thank all the scientists, engineers, and students who participated in the observations.

Funding

L.S.S. acknowledges National Natural Science Foundation of China (Grant No. 42071298) and Open Cooperation Foundation of Zhejiang Key Laboratory of Digital Intelligence Monitoring and Restoration of Watershed Environment (No. KF-202511). S.M.L. acknowledges National Key Research and Development Program of China (Grant No. 20237FF1303503).

Author information

Author notes
  1. These authors contributed equally: Lisheng Song, Zhiwen Guan.

Authors and Affiliations

  1. Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, Anhui Province, School of Geography and Tourism, Anhui Normal University; Zhejiang Key Laboratory of Digital Intelligence Monitoring and Restoration of Watershed Environment, Zhejiang Normal University, Jinhua, Zhejiang, China

    Lisheng Song, Zhiwen Guan, Aoxiang Guo, Peipei Xu, Fengman Fang, Kaifang Shi & Dong Chu

  2. College of Science and Engineering, James Cook University, Cairns, Queensland, Australia

    Michael Liddell

  3. Department of Earth System Science, Tsinghua University, Beijing, China

    Bin He

  4. Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NIH, USA

    Jingfeng Xiao

  5. State Key Laboratory of Earth Surface Processes and Disater Risk Reduction, Faculty of Geographical Sciences, Beijing Normal University, Beijing, China

    Yan Li & Shaomin Liu

  6. Faculty of Geographical Sciences, Beijing Normal University, Beijing, China

    Jianbo Qi

  7. Institute of Remote Sensing and Geosciences, Hangzhou Normal University, Hangzhou, China

    Xuguang Tang

Authors
  1. Lisheng Song
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  2. Zhiwen Guan
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  3. Michael Liddell
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  4. Bin He
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  5. Jingfeng Xiao
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  6. Yan Li
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  7. Aoxiang Guo
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  8. Jianbo Qi
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  9. Peipei Xu
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  10. Fengman Fang
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  11. Kaifang Shi
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  12. Dong Chu
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  13. Xuguang Tang
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  14. Shaomin Liu
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Corresponding authors

Correspondence to Lisheng Song or Shaomin Liu.

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The authors declare no competing interests.

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article

Song, L., Guan, Z., Liddell, M. et al. Early forest water stress detection using thermal infrared energy balance modeling during flash drought. Commun Earth Environ (2026). https://doi.org/10.1038/s43247-026-03638-1

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  • Received: 02 July 2025

  • Accepted: 08 May 2026

  • Published: 02 June 2026

  • DOI: https://doi.org/10.1038/s43247-026-03638-1

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