This session welcomes both methodological advances, applications and validations. We emphasise developments in passive and active microwave (radiometry, radar) retrievals, GNSS-based approaches (transmissometry, reflectometry), and optical/thermal methods, alongside in situ measurements (e.g., leaf/stem water potential, dielectric probes, dendrometry) and model-data integration.
We invite contributions that: (i) improve retrieval algorithms, including cross-frequency synergies; (ii) fuse microwave/optical/LiDAR with in situ data to bridge scales; (iii) quantify uncertainties and disentangle confounding factors; (iv) integrate observations into ecohydrological and land-surface models via data assimilation and machine learning, and advance model representation of plant hydraulics, improve the coupling between the water and carbon cycles, and make use of emerging observations; and (v) use hydraulic observations and products, including VWC and related metrics, to resilience and disturbance/recovery assessment, drought monitoring and early warning, phenology, and agricultural/forestry management.
Case studies, global syntheses, and contributions providing open datasets, intercomparisons and community benchmarks are encouraged. The session aims to foster discussion between attendees from various scientific communities approaching plant hydraulics from different perspectives.
The aim of this presentation is to highlight the confluence of developments in plant physiology, biogeosciences and microwave remote sensing and a potential route to a global perspective on plant hydraulics. The context is the continued development of a satellite mission concept based on a Low Earth Orbit (LEO) constellation of Synthetic Aperture Radars (SAR) that would provide sub-daily observations including vegetation water content and vegetation wet/dry state (Steele-Dunne et al., 2023, Matar et al., 2023). A recurring challenge in mission concept development has been the scarcity sub-daily microwave data, specifically radar data. These are critical to consolidate measurement and observation requirements, and to demonstrate the science case.
Here, we will highlight research activities centred on our installation of a network of GNSS transmissivity (GNSS-T) sensors at existing forest monitoring sites across Europe. GNSS-T is an emerging measurement technique that provide crucial insight into sub-daily changes in the vegetation as a dielectric medium. Because GNSS-T is relatively inexpensive, it enables data collection across a wide range of biomes, complementing sparser tower-based sensors and providing critical observations to support mission development.
We will outline how we are using GNSS-T observations with radiative transfer modeling to consolidate observation and measurement requirements. We will illustrate how we using GNSS-T observations to investigate the link between microwave observations and biogeophysical variables at the heart of plant water relations and the surface water and energy balances. We will also discuss how the exploitation of GNSS-T for these purposes is not trivial, highlighting some of the theoretical considerations we have encountered and our attempts to handle them.
Finally, we will put our activities in the wider context of developments in plant physiology and biogeosciences to discuss opportunities to bring these fields closer together. This is essential to reach the global perspective needed to address urgent scientific and societal challenges.
How to cite: Steele-Dunne, S., van der Borght, N., Neyer, A., Tronquo, E., Swiatek, P., Frantzen, P., and Villaroya Carpio, A.: Towards a global perspective on plant hydraulics: Challenges and opportunities extending microwave remote sensing to sub-daily scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18484, https://doi.org/10.5194/egusphere-egu26-18484, 2026.
Vegetation Optical Depth (VOD) has become an increasingly important biogeophysical variable, and has been used to estimate aboveground biomass (AGB) or vegetation water content (VWC). In recent years, GNSS transmissometry (GNSS-T) has been developed as a tool to estimate VOD continuously on plot-level (e.g. Humphrey & Frankenberg (2023)). Currently, observations of GNSS-VOD throughout the globe are being brought together within VODnet, aiming to, amongst others, serve the calibration/validation of satellite VOD products. (Brede et al. (2025)).
At the same time, we lack fundamental understanding of the drivers of temporal GNSS-VOD variability and their relative roles under different conditions, as well as the comparability with radiometry-based VOD. Here, we present (1) a detailed analysis of a 2.5-year record of low-cost (u-blox) GNSS-VOD observations from a dense Douglas fir forest in the Netherlands, including quantifying the biophysical drivers of temporal VOD dynamics (i.e. VWC, AGB, interception/dew, and temperature) and their relative importance, and (2) a cross-comparison of GNSS-VOD and L-band, upward-looking radiometer-based VOD measurements from a Scots pine forest in Switzerland.
References:
Humphrey, V. and Frankenberg, C.: Continuous ground monitoring of vegetation optical depth and water content with GPS signals, Biogeosciences, 20, 1789–1811, 2023.
Brede, B., Schellenberg, K., Camps, A., Chaparro Danon, D., Damm, A., Forkel, M., Frankenberg, C., Ghosh, A., Hartmann, H., Herold, M., Humphrey, V., Jagdhuber, T., Konings, A., Kurum, M., Niederberger, M., Schmullius, C., Stassin, T., Steele-Dunne, S., Van der Borght, N., Strube, M., Vermunt, P., Yao, Y., Monteith, A., Richards, E., Persson, H., Lecart, B., and Jonard, F.: VODnet: a virtual GNSS-T VOD network for monitoring of forest water budget and structure, Living Planet Symposium '25, Vienna, https://doi.org/10.13140/RG.2.2.17146.35522, 2025.
How to cite: Vermunt, P., Zhou, Y., Rietbroek, R., Guglielmi, B., Gisler, J., Schwank, M., Gessler, A., and Drusch, M.: GNSS-VOD in conifer forests: Biogeophysical Drivers and Comparison with L-Band Radiometry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3615, https://doi.org/10.5194/egusphere-egu26-3615, 2026.
The resilience of terrestrial ecosystems to drought and heat stress is a key control on the future terrestrial carbon sink. Plant hydraulic traits such as conductivity and capacitance provide useful indicators of this resilience. These traits can be inferred from sub-daily vegetation water dynamics, yet rapid changes in vegetation water content remain poorly observed and are therefore weakly represented in land-surface models due to the lack of suitable measurements at temporal and spatial scales.
Microwave remote sensing is a promising tool to monitor diurnal variations in vegetation water content at scale, but no existing or planned satellite missions can currently resolve these dynamics at the sub-daily resolution. To address this critical observation and knowledge gap, SLAINTE has been proposed as an ESA New Earth Observation Mission Idea, comprising a constellation of identical, decametric, monostatic SAR instruments designed to capture sub-daily variations in vegetation water storage, plant water potential, and surface soil moisture (Steele-Dunne et al., 2024; Matar et al., 2024).
One of the challenges in mission development is the lack of sub-daily microwave data across ecosystems. To answer this need of characterizing variability, a GNSS transmissometry (GNSS-T) network has been set up across Europe. GNSS-T compares the signal to noise ratio (SNR) at two GNSS receivers, one above and one below the vegetation canopy, to estimate L-band attenuation, also known as vegetation optical depth (VOD) (Humphrey et al., 2023).
This GNSS-T network, consisting of 21 GNSS receivers across 9 different forest research sites in Europe, has been installed between 05/2025 and 09/2025, building on a pilot installation set up at our Dutch site one year earlier. Data are collected automatically, processed in near real-time, and prepared for dissemination through a central data server, which enables continuous monitoring for data gaps and basic quality checks.
We will discuss lessons learned and methodological advances from installation and operation of the network in sites with variable conditions. The insights gained from constructing an hourly VOD timeseries from high-frequency SNR signals will be presented. Building on the original methodology by Humphrey et al. (2023), we explore sensitivity to GNSS-related artefacts in order to yield robust diurnal signals across sites. These first results demonstrate the feasibility of GNSS-T for monitoring sub-daily vegetation water dynamics.
The established processing workflow, together with the extensive network, paves the way to linking GNSS-derived vegetation water content with plant hydraulic models to infer ecosystem-scale hydraulic traits from a microwave observable.
References:
Humphrey, V., & Frankenberg, C. (2023). Continuous ground monitoring of vegetation optical depth and water content with GPS signals. Biogeosciences, 20(1), 1789–1811. https://doi.org/10.5194/bg-20-1789-2023
Matar, J., Sanjuan-Ferrer, M. J., Rodriguez-Cassola M., Steele-Dunne, S. & De Zan, F. (2024). A Concept for an Interferometric SAR Mission with Sub-daily Revisit. EUSAR 2024; 15th European Conference on Synthetic Aperture Radar, pp. 18-22. IEEE, 2024.
Steele-Dunne, S., Basto, A., De Zan, F., Dorigo, W., Lhermitte, S., Massari, C., Matar J. et al. (2024) SLAINTE: A SAR mission concept for sub-daily microwave remote sensing of vegetation. EUSAR 2024; 15th European Conference on Synthetic Aperture Radar, pp. 870-872. VDE, 2024.
How to cite: Van der Borght, N., Steele-Dunne, S., Tronquo, E., Neyer, A. S., Mackenzie, R., van der Marel, H., and Frantzen, P.: First insights from a Europe-wide GNSS transmissometry network: improved retrieval of sub-daily canopy water status, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12846, https://doi.org/10.5194/egusphere-egu26-12846, 2026.
Monitoring plant water stress requires plant hydraulic measurements, such as measurements of water potential. However, such measurements are challenging to make at scales beyond single plants and over extended time periods. Observing plant water conditions across broad spatiotemporal scales is now enabled by passive microwave remote sensing. Specifically, vegetation optical depth (VOD) retrieved from satellite radiometers (SMAP, AMSR) provides a measure of vegetation water volume in the canopy at tens of kilometers. While satellite-based VOD has been used for a range of applications, rigorous validations of satellite VOD have not been carried out due to a need for labor intensive, widespread in-situ biomass and plant water potential measurements. A new method has enabled direct measurements of in-situ VOD, from Global Navigation Satellite Systems (GNSS). However, they have been less commonly used to evaluate shorter statured vegetation, which dominates most ecosystems. Here, we explore how satellite-based VOD from SMAP and AMSR-2 compare with field-based microwave observations from 272 GNSS-based interferometric reflectometry (GNSS-IR) sites located throughout the Western U.S as a part of the Plate Boundary Observatory (PBO) H20 network. These sensors use GNSS signals to estimate a normalized microwave reflectance index (NMRI), a proxy for VOD at a scale of tens of meters. We find that satellite VOD generally positively correlates with GNSS NMRI with correlations between 0.2 to 0.6 across sites, which is encouraging considering the vast differences in spatial scale (10s of meters for field sensors versus 10s of kilometers for the satellites). These correlations increase to 0.3 to 0.7 when evaluating sites in regions with low spatial vegetation type heterogeneity, low tree cover, and large seasonal vegetation dynamics. The correlations are higher for X-band VOD, likely related to our finding that both X-band VOD and NMRI are both more sensitive to seasonal vegetation variations relative to daily-scale responses than C-band and L-band VOD products are. These findings suggest that satellite VOD is capturing field-based GNSS signals, and therefore that these sensors are a critical (and arguably the only feasible) resource for calibrating and validating satellite VOD across spatial scales.
How to cite: Feldman, A., Smith, W., Konings, A., and Serbin, S.: Water dynamics of short-statured vegetation inferred from field versus satellite-scale microwave remote sensing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2200, https://doi.org/10.5194/egusphere-egu26-2200, 2026.
Vegetation phenology and productivity in water-limited ecosystems are tightly coupled to plant hydraulic functioning, particularly the capacity to access and store water across seasonal dry periods. Across the African dry tropics, many woodland ecosystems initiate leaf green-up prior to the onset of seasonal rainfall, suggesting complex water-use mechanisms that are not directly observable through precipitation or surface soil moisture data alone. Understanding the hydraulic basis of these phenological strategies is critical for interpreting remotely sensed vegetation water signals and for predicting ecosystem responses to shifting rainfall regimes.
Here, we integrate satellite observations and reanalysis data to investigate how vegetation phenology and ecosystem productivity are mediated by plant water status across Africa. We identify three water-stress regimes based on the sensitivity of gross primary productivity (GPP) to rainfall frequency, intensity, and rainy season length, and assess the extent to which these regimes explain the widespread decoupling between rainfall onset and vegetation green-up across dry tropical woodlands. Furthermore, using observations of vegetation optical depth (VOD) as an integrative proxy for vegetation water content, we evaluate the role of plant-stored water in facilitating pre-rain leaf-out. We find that 64% of Africa's terrestrial ecosystems are subject to chronic water stress, and another 22% experience acute water stress. These acutely water-stressed regions initiate green-up when soil moisture is lower relative to chronically water-stressed regions, indicating decoupling between onset of rainfall and leaf-out. Notably, seasonal trajectories of LAI and VOD are asynchronous in regions with pre-rain green-up, consistent with the mobilization of plant-stored water to support early leaf-out.
Our results demonstrate how satellite-derived vegetation water content metrics can reveal hydraulic strategies that decouple vegetation dynamics from surface moisture forcing. This work highlights the value of microwave-based observations for diagnosing plant hydraulic functioning at ecosystem scales and underscores vulnerabilities of water-limited ecosystems to shifts in rainfall timing and seasonality under climate change.
How to cite: Morgan, B. and Entekhabi, D.: Vegetation water content mediates decoupling between leaf-out and rainfall onset in the African dry tropics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14952, https://doi.org/10.5194/egusphere-egu26-14952, 2026.
Decreasing water availability due to climate change reduces the vegetation water pool. This affects the capacity of vegetation to mediate land-atmosphere feedbacks through photosynthesis and transpiration and impacts vegetation health worldwide [1]. Thus, it is paramount to model vegetation water storage (VWS; the mass of water per ground area) in order to monitor vegetation function. Passive microwave sensors on satellites like the Soil Moisture Active-Passive (SMAP) quantify the attenuation that vegetation exerts over land microwave emissions expressed as the vegetation optical depth (VOD). The VOD is linearly related to VWS via the b factor (VOD = b·VWS) and is a good proxy of VWS. Still, satellite-based VWS estimates have been scarcely validated and, importantly, values of b are purely empirical and are time-invariant, omitting relevant phenological changes in VWS [2]. The lack of accurate estimation of b values limits our capacity to better understand the VOD-VWS relationship, to accurately model VWS, or to further explore the transit time of water in vegetation [3]. Here, we bridge this gap by using newly generated, quasi-global benchmark maps of VWS for leaves (VWSleaf), wood (VWSwood) and their summation (VWStotal). These maps are based on ground information of plant traits (specific leaf area and wood density) from the TRY database [4] and their relationship with leaf and wood water storage [5]. Here, we first find that the linear relationship between SMAP L-band VOD and VWS holds when VWStotal is used. We extend this analysis to AMSR2 X- and Ku-VOD data and find linear relationships with VWSleaf (we test against leaves due to the shallow sensing depth of X- and Ku-VOD). Second, we assess the SMAP VWS datasets against VWStotal and find that spatial differences in VWS are biome-dependent. Third, we divide global maps of annual averages of VOD by VWStotal (for L-VOD) and by VWSleaf (for X- and Ku-VOD) to derive global, multi-frequency maps of b and to study its spatiotemporal variation. Results provide new insights on the accuracy of VOD-derived VWS estimates and open a new path towards estimating VWS for different canopy layers, which has wide implications for the remote sensing and the plant ecology research communities.
[1] Grossiord, C., et al. (2020). Plant responses to rising vapor pressure deficit. New Phytologist, 226, 1550–1566.
[2] Togliatti, K., et al. (2019). Satellite L-band vegetation optical depth is directly proportional to crop water in the US Corn Belt. Remote Sensing of Environment, 233, 111378.
[3] Felton, A. J., et al. (2025). Global estimates of the storage and transit time of water through vegetation. Nature Water, 3(1), 59-69.
[4] Kattge, J., et al. (2020). TRY plant trait database–enhanced coverage and open access. Global Change Biology, 26, 119-188.
[5] Stewart, L., et al. (submitted). Wood You Be-Leaf It? The First Trait-Based Map of Global Vegetation Water Storage. To be presented at EGU 2026.
How to cite: Chaparro, D., Stewart, L., Mencuccini, M., Jagdhuber, T., and Binks, O.: Global assessment of SMAP-derived vegetation water storage and estimation of the b-parameter using a trait-based VWS map, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13532, https://doi.org/10.5194/egusphere-egu26-13532, 2026.
Microwave radiometers have been used to monitor the Earth’s land and oceans since the late 1970s, beginning with sensors such as the Scanning Multichannel Microwave Radiometer (SMMR). Due to the physical properties of the atmosphere, specifically the high transmissivity of atmospheric windows in much of the microwave spectrum, microwave radiation propagates with minimal attenuation, enabling observations through clouds and light precipitation. Depending on the frequency of observation, these sensors are largely unaffected by atmospheric and illumination conditions and can acquire measurements both day and night. Therefore, missions such as NASA’s Advanced Microwave Scanning Radiometer 2 (AMSR2) and Soil Moisture Active Passive (SMAP) provide frequent global mapping (typically every 2–3 days), however, retrievals are not always consistent, as other factors such as frozen soils and radio‑frequency interference can influence the measurements. A fundamental measurement collected by passive microwave sensors (radiometers) is brightness temperature, which serves as the primary input for retrieving parameters related to soil and vegetation water content, yielding products such as soil moisture and Vegetation Optical Depth (VOD). Passive sensors rely on naturally emitted microwave radiation from the Earth system and do not illuminate the surface, in contrast to active sensors (radars). VOD is not a directly measurable physical property, but a model-based parameter primarily estimated using remotely sensed data. By quantifying canopy opacity, VOD offers a critical proxy for Vegetation Water Content (VWC) and above-ground biomass. While high-frequency bands (e.g., C-, X-, and Ku-bands) interact primarily with leaves and small branches to reflect upper canopy VWC, longer wavelengths (e.g., L-band) penetrate deeper to interact with trunks and woody structure. This multi-band capability allows for a comprehensive assessment of ecosystem hydraulic status, drought impact, and given sufficient spatio-temporal coverage ecosystem resilience. However, while soil moisture is an established Essential Climate Variable with defined GCOS measurement uncertainty target for surface soil moisture (<0.08 m3m-3, k=2) VOD lacks standardised guidance on uncertainty targets. This absence represents a critical gap in both product specifications and the scientific literature, limiting confidence in VOD interpretations and constraining its reliability as an indicator of vegetation water content in long‑term climate studies. Addressing this gap is therefore central to advancing the use of VOD in climate monitoring frameworks. This study explores the uncertainties associated with VOD retrievals within the Land Parameter Retrieval Model (LPRM), a widely used forward radiative transfer model. Utilising dual-polarised brightness temperature data from AMSR2 and performing Monte Carlo sensitivity analysis, we characterise how uncertainties in the model input parameters propagate through the VOD retrieval process. The research outlines a preliminary traceability diagram, identifying the sensitivity of the LPRM algorithm across different frequency bands and land cover types. By estimating uncertainty magnitudes under various scenarios, this work provides a framework for improving the reliability of VOD and VWC estimates, facilitating their integration into eco-hydrological models and early warning systems for vegetation stress.
How to cite: Ormane, R., Morris, H., Mota, B., Zotta, R., and Bader, N.: Characterising Uncertainty in Vegetation Optical Depth Retrievals Using the Land Parameter Retrieval Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5061, https://doi.org/10.5194/egusphere-egu26-5061, 2026.
Plant water content is the primary contributor to the Vegetation Optical Depth (VOD), a remote sensing parameter that describes signal attenuation by vegetation in the microwave domain. Short-term variations in VOD contain information about changes in canopy water content, while long-term changes reflect phenological dynamics and overall vegetation development. VOD is also used in several models to estimate biomass and vegetation water content.
Unfortunately, the validation of VOD remains challenging due to the lack of direct ground-truth data, making it common practice to evaluate its performance through spatiotemporal comparisons with relevant vegetation proxy variables. Corner reflectors are passive reflective surfaces that allow accurate characterisation of reflected microwave radiation. By placing them within forest vegetation, we can directly measure the attenuation of their signal caused by the canopy. This makes them a potentially practical tool for direct VOD measurements as well as water balance.
In our project, we developed an innovative corner reflector design specifically for forest microwave satellite observations. We verified the geometry using theoretical reflection simulations at several frequencies for future applications with the Sentinel-1 (5.405 GHz), TanDEM-X (9.65 GHz), and NISAR (L-band: 1.257 GHz / 3.2 GHz) missions. Based on these theoretical assumptions, we subsequently constructed four prototypes and deployed them in mature forest stands in Germany and the Czech Republic. To evaluate the maximum forest canopy density that can still be measured using our corner reflectors, we also conducted an artificial shading experiment. The results demonstrate the capability of corner reflectors to measure VOD, as well as the limitations of current prototypes and recommendations for future applications.
How to cite: Moravec, D. and Forkel, M.: Corner Reflectors for Direct Measurement of Forest Vegetation Optical Depth, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12248, https://doi.org/10.5194/egusphere-egu26-12248, 2026.
Forest water dynamics can be assessed on large spatio-temporal scales using satellite-based remote sensing. Vegetation optical depth (VOD), which indicates the vegetation's attenuation of microwaves, contains mainly information on the dry biomass, structure, and water content of the vegetation. Water dynamics can be reflected in short-term variations in VOD. Currently, VOD is operationally retrieved using passive microwave sensors, such as AMSR-2, SMAP, and SMOS, or radar-based sensors, such as ASCAT, with a coarse spatial resolution (tens of kilometers), which hinders the understanding of complex landscapes and is a major obstacle for VOD validation using ground sensors. To overcome this shortcoming of spatial resolution, we utilize synthetic aperture radar (SAR) sensors, such as Copernicus Sentinel-1 (S1) C-band (5.504 GHz), which enables a much higher spatial resolution (tens of meters).
This study aims to estimate spatially high-resolution SAR-based VOD across different forest ecosystems, using both VH and VV polarizations, and ultimately assess forest water dynamics. We employ soil and vegetation physical scattering models (De Roo et al., 2001; Ulaby & Long, 2014) and constrain the effective scattering albedo (ω), which indicates the ratio of scattering to absorption of vegetation. In our dual-channel approach, we utilize in situ soil moisture from forest ecological observatories and co-polarized S1 backscatter as direct model inputs, and characterize the vegetation structure (ω) using cross-polarized S1 backscatter to estimate SAR-based VOD. We test our approach across two deciduous broadleaf and three evergreen needleleaf forest ecosystems in Central Europe for up to three years (2023-2025). In addition, we compare our SAR-based VOD with VOD estimates from Global Navigation Satellite System-Transmissometry (GNSS-T), derived from a pair of in situ receivers: one located at the top of the canopy and one on the ground for each test site (Brede et al., 2025). We validate our approach using in situ plant gravimetric moisture content (mg; [kgwater/kgwet biomass]) measurements of the tree canopy and remote sensing-based leaf area index. We will also transfer our dual-channel approach to the agricultural site of the Land-Atmosphere Feedback Initiative (LAFI) and other ecosystems in a later step. In the end, spatially high-resolution satellite-based SAR-based VOD enables not only analyses of forest water dynamics but also small-scale up to stand-based assessments of plant hydraulics.
References
Brede, B., Schellenberg, K., Camps, A., Chaparro, D., Damm, A., Forkel, M., Frankenberg, C., Ghosh, A., Hartmann, H., Herold, M., Humphrey, V., Jagdhuber, T., Konings, A., Kurum, M., Niederberger, M., Schmullius, C., Stassin, T., Steele-Dunne, S., Borght, N., …, Jonard, F. (2025). VODnet: a virtual GNSS-T VOD network for monitoring of forest water budget and structure. https://doi.org/10.13140/RG.2.2.17146.35522.
De Roo, R. D., Du, Y., Ulaby, F. T., Dobson, M. C. (2001). A semi-empirical backscattering model at L-band and C-band for a soybean canopy with soil moisture inversion. IEEE Transactions on Geoscience and Remote Sensing, 39(4), 864–872. https://doi.org/10.1109/36.917912.
Ulaby, F. T., Long, D. G. (2014). Microwave radar and radiometric remote sensing. University of Michigan Press.
How to cite: Hellwig, F. M., Fluhrer, A., Schellenberg, K., Vermunt, P., Lecart, B., Jonard, F., Zehner, M., Weiß, T., Chaparro, D., Dubois, C., Link, M., Bliefernicht, J., Kunstmann, H., and Jagdhuber, T.: Assessing dual-channel multi-year active microwave-based vegetation optical depth in temperate forest ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14360, https://doi.org/10.5194/egusphere-egu26-14360, 2026.
Current modeling of plant hydraulics under water stress often relies on complex, high-order differential equations that describe the catastrophic failure of the xylem. While these models capture the physics of cavitation, they frequently struggle with numerical stability and upscaling in coupled soil-vegetation-atmosphere simulations, and their high parameterization demands complicate data assimilation from emerging hydraulic observations.
In this study, we propose that plant stomatal regulation effectively acts as a "system damper" that trades a linear loss in transpiration flux for the avoidance of exponential hydraulic collapse. This regulatory strategy can be captured with simplified models that are more amenable to integration with diverse hydraulic observations, from in situ water potential measurements to satellite-derived vegetation water content (VWC).
We investigate the transition from a plant-limited hydraulic regime to a soil-limited one, demonstrating that the "Hydraulic Cliff", the point where the loss of soil and xylem conductivity (K) outpaces the pressure gradient, is not a static property but a dynamic bottleneck that shifts as the soil dries. By applying elementary mathematics to the energy and mass balance, we show that stomatal closure follows a regulatory logic that prevents the leaf water potential (Ψl) from entering the "runaway" zone where demand exponentially exceeds supply.
Our "Dynamic Hydraulic Cliff" framework reveals that the plant's strategy is to decouple the leaf's energy budget (and its associated exponential temperature-driven demand) from the supply decay of the rhizosphere. This approach maintains system stability while being directly linkable to observable quantities: stomatal conductance controls transpiration linearly, while Ψl remains within measurable bounds that can be monitored via sap flow, pressure chambers, or inferred from microwave-based VWC retrievals.
We demonstrate that this parsimonious formulation provides a robust pathway for assimilating multi-scale hydraulic observations into land surface and ecohydrological models without the computational burden and parameter uncertainty of solving complex hydraulic PDEs. The framework enables improved representation of plant responses to drought while facilitating the integration of emerging observational products (VWC, water potential proxies) into operational monitoring systems.
We conclude that "linear" stomatal regulation is an evolutionarily optimal response to the multi-exponential risks inherent in the soil-plant-atmosphere continuum, and that recognizing this principle can bridge the gap between detailed hydraulic theory and practical large-scale prediction of transpiration under future climate extremes.
How to cite: D'Amato, C. and Rigon, R.: Stomata close to maximize transpiration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14608, https://doi.org/10.5194/egusphere-egu26-14608, 2026.
Vegetation Optical Depth (VOD) characterizes the attenuation of soil-emitted microwave radiation as it propagates through the vegetation layer. VOD is retrieved in the microwave domain, making it less susceptible to saturation effects and atmospheric conditions. Hence, VOD is used in a wide range of applications, including drought monitoring, fire risk analyses, carbon-flux modelling, or studies on ecosystem resilience and tipping dynamics.
The Land Parameter Retrieval Model (LPRM) is based on a tau-omega radiative transfer model, which simultaneously retrieves soil moisture and VOD via a sequential, refining search, maximizing the agreement between modeled and observed brightness temperatures. The single scattering albedo ω expresses the fraction between scattered and absorbed radiation intercepted by vegetation and is treated in LPRM conventionally as a global (time-invariant) parameter. Recent studies, however, have shown that ω exhibits systematic temporal variability, suggesting that the assumption of global constancy may not be adequate in LPRM.
This study proposes an extension of LPRM in which C-band brightness temperature observations from the Advanced Microwave Scanning Radiometer 2 (AMSR2) mission are optimized in a two-level procedure for boreal deciduous forests (BDF). Local and global model parameters are solved separately by fixing corresponding parameters through large weights. In a first step, all global model parameters are optimized for the full time series while keeping the local parameter ω fixed. In a second stage, the time series is stratified into temporal windows, within each ωj is solved independently, keeping global parameters fixed, and allowing for seasonal alignment of ω.
This leads to the following hypothesis: Allowing the single-scattering albedo ω to vary temporally, via a stratified two-step optimization procedure, improves C-band VOD retrievals, specifically in terms of (a) correlations between LAI and C-band VOD; and (b) agreement between modeled and observed brightness temperatures, when being compared against retrieval scenarios in which ω is treated constant.
The findings of this study aim to provide insights into the seasonality of ω, and to assess whether the conventional assumption of constant ω is sufficient or if future studies should treat it as time-variant model parameter.
How to cite: Voß, N., Zotta, R.-M., Bader, N., and Dorigo, W.: Improving LPRM C-Band VOD Retrievals Using Stratified Temporal Optimization of the Single-Scattering Albedo, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7255, https://doi.org/10.5194/egusphere-egu26-7255, 2026.
Vegetation annotates the radiation emitted by the Earth’s surface. The degree of annotation can be quantified by space-
born passive microwave radiometers and is commonly known as Vegetation Optical Depth (VOD). VOD is directly connected
to and influenced by several factors, such as the water content, vegetation density, the wavelength used for observation and
the land cover type. One widley used algoritm is the Land Parameter Retrieval Model (LPRM). LPRM is a model that re-
trieves both soil moisture and VOD simultaneously from V and H polarized microwave observations. Nighttime LPRM VOD
has been extensively validated and used in many applications (e.g. Moesinger et al. [1], Zotta et al. [2]). LPRM assumes
nightime equilibrium of canopy and soil temperature [3]. This does hold for daytime observations which we aim at doing
here.
Here, we introduce an approach that separates the canopy and soil temperature using reanalysis data. We use it to
retrieve AMSR2 VOD at X-band. First, existing VOD retrievals, retrieved for daytime and nighttime observations under the
thermal equilibrium assumption, are compared to each other and to independent vegetation parameters such as the Leaf
Area Index (LAI) and the Fraction of Absorbed Photosynthetic Active Radiation (fAPAR). We also took Land cover classes
(CCI Land Cover) into account to see in which biomes daytime VOD and nighttime VOD already agree with each other and
analysed why. In a second step, we plug in the soil and vegetation temperature from reanalysis separately into the LPRM to
see how it affects daytime VOD. We evaluate where and by how much it improves, especially in biomes where nighttime and
daytime retrievals are assumed to differ significantly. Furthermore, we will transfer the approach to Ku-band observations.
First results indicate that our approach works best in dense vegetation (e.g. 60-Tree cover, broadleaved, deciduous,
closed to open (>15%)), except for tropical rainforest. This class shows the largest discrepancy between daytime and
nighttime retrievals due to an underestimation of daytime VOD caused by strong transpiration and large day-night temper-
ature contrast.
References
[1] L. Moesinger, W. Dorigo, R. de Jeu, et al. The global long-term microwave Vegetation Optical Depth Climate Archive
(VODCA). Earth System Science Data 12, 177–196 (2020).
[2] R.-M. Zotta, L. Moesinger, R. van der Schalie, et al. VODCA v2: multi-sensor, multi-frequency vegetation optical depth
data for long-term canopy dynamics and biomass monitoring. Earth System Science Data 16, 4573–4617 (2024).
[3] Manfred Owe, Richard de Jeu, and Thomas Holmes. Multisensor historical climatology of satellite-derived global
land surface moisture. Journal of Geophysical Research: Earth Surface 113 (2008). eprint: https : / / agupubs .
onlinelibrary.wiley.com/doi/pdf/10.1029/2007JF000769.
How to cite: Meixner, F., Zotta, R.-M., Bader, N., and Dorigo, W.: Assessing daytime vegetation water content estimates derived through the land parameter retrieval model from AMSR2 X-band observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7306, https://doi.org/10.5194/egusphere-egu26-7306, 2026.
Plants modify their functional traits in response to changing environmental conditions under climate change. However, it remains unclear whether tree planting alters patterns and acclimation of hydraulic traits across spatial scales. Here, we compiled a site-level dataset of hydraulic traits in natural (NF) and planted forests (PF) to examine trait patterns and relationships, quantified environmental and ecological drivers on ecosystem-scale hydraulic traits of PF and NF across China, and computationally projected future trait acclimation using the space-for-time approach. We identified distinct differences in hydraulic traits between NF and PF, with PF exhibiting higher hydraulic safety but lower hydraulic efficiency than NF at the species level. NF demonstrated a negative trade-off between hydraulic efficiency and safety, whereas PF exhibited a contrasting positive correlation between these traits. We confirmed that both environmental and ecological factors influence ecosystem-scale hydraulic traits in NF and PF, although dominant drivers vary among specific traits. Projections under future climate scenarios suggest that, despite persistent differences in trait acclimation between NF and PF, both forest types tend to exhibit increased water-use efficiency and enhanced drought resistance in response to rising precipitation and air dryness. These findings provide a valuable benchmark for estimating potential changes in hydraulic traits under climate change, supporting improved simulations of carbon and water fluxes in response to climate and anthropogenic influences.
How to cite: Bai, Y. and Hu, Y.: Climate-Driven Hydraulic Traits Shift in Natural and Planted Forests: Patterns, Drivers, and Future Acclimation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2664, https://doi.org/10.5194/egusphere-egu26-2664, 2026.
Monitoring vegetation water status is key to understanding forest canopy hydraulics, stomatal regulation, and ultimately the biosphere's drought response under a changing climate. Yet direct, in situ measurements of hydraulic state are labor-intensive and rarely sustained long enough to produce the multi-year time series needed for model development and drought-impact forecasting. Continuous proxies such as sap flow or stem water potential provide vital information about fluxes, but their representativeness for entire trees and stand-scale canopy water status remains very limited.
Here, we highlight the potential of Global Navigation Satellite Systems Transmissometry (GNSS-T) to bridge this observation gap. GNSS-T retrieves vegetation optical depth (VOD), the effective canopy opacity at L-band (1-2 GHz), by measuring one-way attenuation of GNSS microwave signals along their path from the transmitting satellite to a receiver located below the canopy. GNSS-T VOD integrates information on canopy biomass and water content of the canopy (plant and interception storage) and has demonstrated sensitivity to stand-scale vegetation water dynamics. However, its sensitivity to changes in vegetation water dynamics is expected to vary with stand biomass and canopy cover, species hydraulic strategies, and climatic conditions. These dependencies remain poorly quantified. To date, progress has been limited due to the novelty of this emerging technique as existing GNSS-T records are rather short in time and largely confined to individual sites.
In this contribution, we present the first data from VODnet, a community-driven network that builds, maintains, and advances GNSS-T for ecological research. The emerging dataset spans 10 forest stations across diverse biomes, including temperate, Mediterranean, savanna, and tropical ecosystems in South America, and Southern and Central Europe, enabling cross-site analyses of GNSS-T VOD sensitivity under contrasting climate conditions and vegetation properties.
The goal of this study is to understand the sensitivity of GNSS-T VOD to changes in vegetation water status across climate gradients, plant traits, and forest structural conditions. We do this by calculating partial correlations of VOD with hydrological drivers such as soil moisture deficit, sap flow and water potential anomalies while accounting for structural properties such as LAI, total biomass and canopy cover, and measure the degree to which site factors drive this correlation. Beyond in situ applications, VODnet provides a unique opportunity to study uncertainty in widely used spaceborne VOD data sets (e.g., SMAP, AMSR-2) through validation across forest ecosystems. Based on our results, we can now provide a first assessment of whether GNSS-T can serve as a validation reference for satellite-derived VOD.
How to cite: Schellenberg, K., Chaparro, D., Brede, B., Stanley, V., Feldman, A., Konings, A. G., Duveiller, G., Paulus, S. J., Stassin, T., Hartmann, H., Schmullius, C., and Jagdhuber, T.: Tracking Water Status and Drought Response with GNSS-T VOD Across Tropical to Temperate Forest Ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14924, https://doi.org/10.5194/egusphere-egu26-14924, 2026.
Global Navigation Satellite System (GNSS) signal attenuation offers a novel approach to estimate Vegetation Optical Depth (VOD) and thereby monitor vegetation structure and vegetation water status at high temporal resolution. At the FAIR site in Mieming (Austria), a GNSS receiver system has recently been installed, opening new opportunities to explore the applicability and added value of GNSS-based VOD in a well-instrumented forest ecosystem. The exceptional strength of FAIR lies in its dense and diverse sensor infrastructure, including eddy covariance measurements above and below the canopy, dendrometer observations, stem water potential measurements, sapflow systems, cosmic-ray neutron sensing (CRNS), soil water content and soil water potential profiles, detailed observations of precipitation and throughfall, as well as periodic, manual measurements of leaf water content.
The co-location of these measurements enables a unique framework to investigate how GNSS-derived VOD relates to plant water status, biomass dynamics, and ecosystem-scale fluxes. Key research questions include the sensitivity of GNSS-VOD to short-term vegetation water dynamics, its coupling with transpiration and carbon exchange at ecosystem levels, and its response to soil moisture variability and atmospheric demand. The FAIR site thus provides an ideal testbed to assess the potential of GNSS-based VOD as an integrative indicator of vegetation–soil–atmosphere interactions and to evaluate its role in multi-sensor ecohydrological monitoring.
In addition, we present first GNSS-VOD time series from the newly installed system and present a first draft of a data processing routine, providing a basis for future analyses and for the integration of GNSS-derived VOD into the existing multi-sensor framework at FAIR.
How to cite: Hammerle, A., Bader, N. F., and Wohlfahrt, G.: Tracking Canopy Water Content with GNSS-Derived VOD in a Highly Instrumented Multi-Sensor Forest Field Infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9965, https://doi.org/10.5194/egusphere-egu26-9965, 2026.
European beech (Fagus sylvatica L.) is one of the most widespread and ecologically significant broadleaf tree species in Central Europe and is highly sensitive to drought and climatic extremes. Monitoring canopy water status is therefore critical for understanding plant hydraulic functioning, ecosystem resilience, and responses to environmental stress. Satellite-derived Vegetation Optical Depth (VOD) quantifies microwave signal attenuation by vegetation, serves as a proxy for vegetation water content, and provides valuable large-scale information for global vegetation monitoring and climate studies. However, well-characterized ground-based observations are required to resolve canopy-scale processes and hydraulic dynamics and to validate and improve satellite VOD retrievals.
To address this need, we employ Global Navigation Satellite System Transmissometry (GNSS-T) as an in situ remote sensing approach to observe canopy water content dynamics in a mature European beech forest in eastern Austria. GNSS-T exploits signals of opportunity from navigation satellites operating at L-band frequencies comparable to microwave radiometers by comparing simultaneous signal reception at paired open-sky reference and below-canopy receivers, with differences in received signal power attributable to vegetation. Using a stationary, multi-frequency, multi-constellation GNSS-T setup operated continuously for one and a half years, VOD was retrieved using a simplified tau–omega radiative transfer model as a function of GNSS system, frequency band, and ranging code type.
Retrieved VOD magnitudes are generally consistent across systems and frequency bands. GNSS-T-derived VOD resolves spatial canopy structure as well as pronounced diel and seasonal dynamics and shows sensitivity to meteorological drivers. Comparisons with camera-based vegetation proxies (in situ LAI- and NDVI-proxies) and satellite-derived vegetation indicators (AMSR2 X- and Ku-band VOD, MODIS LAI, Sentinel-1 cross-polarization ratio) support the physical interpretability of these observations. A systematic, azimuth-independent decrease of VOD toward the horizon might point to limitations of the implemented radiative transfer framework.
Overall, the results demonstrate the potential of GNSS-T to provide continuous, non-destructive in situ observations of canopy-scale hydraulic dynamics.
How to cite: Bader, N., Zotta, R.-M., Diaz-Pines, E., Möller, G., Loderer, W., Kager, T., and Dorigo, W.: GNSS-T Monitoring of Canopy Water Dynamics in a European Beech Forest: Potentials and Caveats Across Diel to Seasonal Scales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9976, https://doi.org/10.5194/egusphere-egu26-9976, 2026.
Long-term monitoring of gross primary production (GPP) is essential for quantifying terrestrial carbon uptake, understanding ecosystem responses to climate variability and extremes, and evaluating Earth system models. Yet, long-term global GPP estimates derived from optical remote sensing, eddy covariance upscaling, and process-based models still diverge in magnitude and trends, motivating the development of complementary products based on independent observations. Passive microwave vegetation optical depth (VOD) provides an all-weather, largely illumination-independent signal linked to vegetation water content and biomass and is used in the microwave-driven VODCA2GPP product. However, the current VODCA2GPP implementation uses reanalysis 2 m air temperature (T2M) and shows reduced performance in water-limited regions.
Here, we assess a microwave-driven, model-independent GPP framework using random forest models trained on FLUXNET GPP and subsets of primarily microwave predictors. We replace T2M with daytime land-surface temperature (LSTday) retrieved from Ka-band brightness temperatures (AMSR-E, AMSR2, SSM/I). To better represent hydraulic and structural constraints, we additionally test land cover (LC), an L-band VOD biomass composite (LVOD), and surface and root-zone soil moisture (RZSM), alongside VOD (VODCA v2).
Replacing T2M with LSTday preserves or slightly improves skill at FLUXNET sites and against independent GPP references, while producing near-identical global trend patterns, supporting LSTday as an observation-based thermal constraint consistent with large-scale controls on photosynthesis. Adding physiologically plausible predictors yields robust gains, with the most significant improvement from LC, which reduces cross-biome mixing and curbs unrealistically high GPP in open vegetation. The best performance is achieved when using VOD, LSTday, LC, LVOD, and RZSM together as predictors, highlighting the complementary constraints from plant-available water and biomass/long-term vegetation state. These results motivate an updated VODCA2GPP release, using LSTday instead of T2M and incorporating LC, LVOD, and RZSM, to better capture the structural and hydrologic limitations on carbon uptake.
How to cite: Zotta, R., Müller, M. C., Lazameta, R., Walther, S., Forkel, M., and Dorigo, W.: An improved machine learning approach to estimate GPP using vegetation optical depth and other microwave remote sensing observations , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7818, https://doi.org/10.5194/egusphere-egu26-7818, 2026.
Through the water-uptake at their roots, and the transpiration at their leaves, vegetation plays a key role in the movement of water from the soil to the atmosphere. To improve our understanding of processes dictating the uptake and transpiration of water by vegetation at large scales, dynamics of vegetation water content are an important source of information. Active microwave instruments have been used for decades to estimate vegetation water content, owing to their high sensitivity to water at earth’s surface. Recent developments in the retrieval of normalised C-band backscatter and the associated backscatter-incidence angle relation from the ASCAT scatterometer onboard the series of Metop satellites have enabled the use of the dynamic backscatter-incidence angle relation for monitoring of vegetation water content from sub-seasonal to multi-year time scale. The result is a global data record of daily estimates of the backscatter-incidence angle relation spanning 2007 to 2025. Additionaly, measurements from the scatterometer onboard the ERS and the future Metop-SG B satellite series, respectfully preceding and succeeding ASCAT, can be included to create a record spanning multiple decades. In this contribution, the spatial and temporal variation of the ASCAT backscatter-incidence angle relation are linked to dynamics of vegetation water content and biomass in different settings to demonstrate the potential of the dynamic C-band backscatter-incidence angle relation for monitoring of vegetation water dynamics.
How to cite: Frantzen, P., Steele-Dunne, S., Vreugdenhil, M., Hahn, S., and Wagner, W.: Linking the Dynamic ASCAT Backscatter-Incidence Angle Relation to Vegetation Water Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11695, https://doi.org/10.5194/egusphere-egu26-11695, 2026.
Synthetic Aperture Radar (SAR) satellites provide all-weather, day-night global Earth surface coverage, enabling continuous monitoring of ecosystems across multiple microwave bands. Over forested areas, SAR backscatter carries information on canopy water content, vegetation structure, and soil moisture. Microwave signals with shorter wavelengths interact with leaves and upper canopy layers, while longer wavelengths penetrate deeper and investigate branches, trunks, and soil. This makes SAR backscatter a proxy for retrieving ecosystem variables related to water and carbon cycles, such as soil moisture and biomass, which are critical inputs in data assimilation schemes for Earth system models.
However, SAR applications over forests are limited by backscatter saturation over dense canopies and by the limited penetration depth of shorter wavelengths through vegetation. Understanding how these constraints vary across different microwave bands, SAR variables, and forest types is thus essential before implementing data assimilation experiments.
This study explores the sensitivity of Sentinel-1 C-band (5.405 GHz, l ~ 5.55 cm) and SAOCOM L-band (1.275 GHz, l ~ 23.5 cm) SAR observations to soil moisture (SM), evaporation (ET), gross primary productivity (GPP), and Leaf Area Index (LAI), over Mediterranean forest sites. We analyze the sigma nought (σ0) backscattering coefficient in different polarizations (dual-pol for Sentinel-1, quad-pol for SAOCOM), along with its cross-ratio (σ0VH/ σ0VV), backscatter-incidence angle slope, and polarimetric decomposition parameters. We calculate the sensitivity of each parameter by computing linear regression against in-situ measurements of ecosystem variables. We also assess sensitivity changes across different acquisition geometries and timing (morning and evening overpasses), seasonality, and forest types.
We consider three study sites in central and northern Italy, namely IT-BFt, IT-Cp2, and IT-SR2, which belong to the ICOS/FLUXNET network and are equipped with soil moisture probes and eddy covariance towers for water and carbon fluxes measurements. The three sites comprise both deciduous (Carpinus betulus, Quercus robur) and evergreen (Pinus pinea l., Quercus ilex) forests with diverse structural characteristics.
C-band backscatter from Sentinel-1 exhibits saturation at two out of three study sites, particularly where canopies are the densest. Conversely, L-band backscatter shows higher sensitivity to soil moisture and vegetation growth. By characterizing the sensitivity of SAR parameters to geophysical variables, this study contributes to a better understanding of the potential of SAR retrievals in data assimilation experiments to improve predictions of hydrological and carbon fluxes over forested regions.
How to cite: Natali, M., De Lannoy, G., Flammini, A., Steele-Dunne, S., and Massari, C.: Sensitivity of C- and L-band SAR observations to water and carbon cycle variables in Mediterranean forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21068, https://doi.org/10.5194/egusphere-egu26-21068, 2026.
