Tracking Water Dynamics of a Temperate Forest Under Drought and Non‐Drought Conditions Using Active and Passive Microwave and Optical Remote Sensing

Abstract Water status, water dynamics, and ecohydrological resilience of a protected German beech forest during the 2018–2020 multi‐year drought are assessed using over six years of multi‐frequency remote sensing data, integrating active, passive, and optical sensors with varying canopy penetration depths, highlighting the importance of monitoring forests under extreme conditions. In this study, we investigate Sentinel‐1 C‐band backscatter (S‐1 γ 0 ) and the relative water content estimated from vegetation optical depth (RWC VOD ) of AMSR2 (X‐ and C‐bands) and SMAP (L‐band) within the soil‐plant‐atmosphere system (SPAS). In addition, time series are intercompared and examined through correlation and sensitivity analyses applying tailored environmental and newly developed hydrological selection strategies. Our results show that S‐1 γ VH is most influenced by leaf area index and thus leaf biomass when sensed during dense vegetation (leaf‐on), no‐frost, and very wet conditions ( r = −0.94). In contrast, during sparse vegetation (leaf‐off), no‐frost, stable dry‐down, and extremely dry conditions, S‐1 γ VH is very sensitive to topsoil moisture ( r = 0.91). Due to increased microwave attenuation, resulting in reduced S‐1 γ VH backscatter, an anti‐cyclical behavior (negative correlations) is observed between almost all SPAS‐based variables/proxies and S‐1 γ VH during leaf‐on conditions. Conversely, this reverses to a cyclical behavior (positive correlations) during leaf‐off conditions. Our results reveal that X‐ and C‐band RWC VOD effectively detect drought onset by capturing fast water content changes in leaves and twigs of the top canopy due to shallow sensing depth, while L‐band RWC VOD captures legacy effects after repetitive droughts through slower water content changes in branches and trunks of lower tree compartments.

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Publication Details

Journal
Journal of Geophysical Research Biogeosciences
Published
2026-04-30
DOI
https://doi.org/10.1029/2025jg009240
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00

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article

Tracking Water Dynamics of a Temperate Forest Under Drought and Non‐Drought Conditions Using Active and Passive Microwave and Optical Remote Sensing

Florian M. Hellwig, Anke Fluhrer, Thomas Jagdhuber, Markus Zehner et al.
Journal of Geophysical Research Biogeosciences
Soil Moisture and Remote Sensing
article

Tracking Water Dynamics of a Temperate Forest Under Drought and Non‐Drought Conditions Using Active and Passive Microwave and Optical Remote Sensing

Florian M. Hellwig, Anke Fluhrer, Thomas Jagdhuber, Markus Zehner, Konstantin Schellenberg, María Piles, David Chaparro, Harald Kunstmann, Clémence Dubois, Christiane Schmullius, Anne Klosterhalfen
article en

Abstract

Abstract Water status, water dynamics, and ecohydrological resilience of a protected German beech forest during the 2018–2020 multi‐year drought are assessed using over six years of multi‐frequency remote sensing data, integrating active, passive, and optical sensors with varying canopy penetration depths, highlighting the importance of monitoring forests under extreme conditions. In this study, we investigate Sentinel‐1 C‐band backscatter (S‐1 γ 0 ) and the relative water content estimated from vegetation optical depth (RWC VOD ) of AMSR2 (X‐ and C‐bands) and SMAP (L‐band) within the soil‐plant‐atmosphere system (SPAS). In addition, time series are intercompared and examined through correlation and sensitivity analyses applying tailored environmental and newly developed hydrological selection strategies. Our results show that S‐1 γ VH is most influenced by leaf area index and thus leaf biomass when sensed during dense vegetation (leaf‐on), no‐frost, and very wet conditions ( r = −0.94). In contrast, during sparse vegetation (leaf‐off), no‐frost, stable dry‐down, and extremely dry conditions, S‐1 γ VH is very sensitive to topsoil moisture ( r = 0.91). Due to increased microwave attenuation, resulting in reduced S‐1 γ VH backscatter, an anti‐cyclical behavior (negative correlations) is observed between almost all SPAS‐based variables/proxies and S‐1 γ VH during leaf‐on conditions. Conversely, this reverses to a cyclical behavior (positive correlations) during leaf‐off conditions. Our results reveal that X‐ and C‐band RWC VOD effectively detect drought onset by capturing fast water content changes in leaves and twigs of the top canopy due to shallow sensing depth, while L‐band RWC VOD captures legacy effects after repetitive droughts through slower water content changes in branches and trunks of lower tree compartments.

Journal of Geophysical Research BiogeosciencesVol. 131(5)
Karlsruhe Institute of Technology (DE), Technische Hochschule Augsburg (DE), Universitat de València (ES), University of Augsburg (DE), Parc Científic de la Universitat de València (ES), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Centre for Research on Ecology and Forestry Applications (ES), Max Planck Institute for Biogeochemistry (DE), University of Göttingen (DE), Friedrich Schiller University Jena (DE)
“la Caixa” Foundation, Deutsche Forschungsgemeinschaft
Clean water and sanitation
Openalex Percentile: Top 10%
Soil Moisture and Remote Sensing
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