EGUsphere EGUsphere EGUsphere EGUsphere Copernicus Publications Göttingen, Germany 10.5194/egusphere-2026-1759 Assessment of vegetation water dynamics by comparing microwave remote sensing signals from satellites and field-based GNSS reflectometry Feldman Andrew F. https://orcid.org/0000-0003-1547-6995 1 2 Smith William K. 3 Konings Alexandra G. https://orcid.org/0000-0002-2810-1722 4 Baur Martin J. https://orcid.org/0000-0002-1516-8602 5 Browne Marvin 4 Chaparro David 6 Devine Charles https://orcid.org/0000-0003-1651-7613 3 Diehl Jennifer L. https://orcid.org/0000-0003-3070-6621 1 2 Endsley Arthur https://orcid.org/0000-0001-9722-8092 7 Jagdhuber Thomas 8 9 Larson Kristine M. https://orcid.org/0000-0003-4666-8885 10 del Mar Valle-Rodriguez Coral 11 Schellenberg Konstantin https://orcid.org/0000-0002-2563-9017 12 13 Zotta Ruxandra-Maria https://orcid.org/0000-0001-8649-3421 14 Serbin Shawn P. 1 Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA School of Natural Resources and the Environment, University of Arizona, Tucson, Arizona, USA Department of Earth System Science, Stanford University, Stanford, California, USA Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland CREAF, Cerdanyola del Valles, 08193 Barcelona, Spain Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT, USA Microwaves and Radar Institute, German Aerospace Center (DLR), Oberpfaffenhofen, Germany Institute of Geography, University of Augsburg, Augsburg, Germany Department of Aerospace Engineering Sciences, University of Colorado, Boulder, CO, USA Department of Ecology and Evolutionary Biology, Cornell University, Ithaca NY, USA Department Biogeochemical Processes, Max Planck Institute for Biogeochemistry, Jena, Germany Department of Earth Observation, Friedrich Schiller University Jena, Jena, Germany Department for Geodesy and Geoinformation, TU Wien, Vienna, Austria 09 04 2026 2026 1 38 Copyright: © 2026 Andrew F. Feldman et al. 2026 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1759/ The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1759/egusphere-2026-1759.pdf

Monitoring plant water stress and biomass is limited by labor intensive measurements techniques. Observing plant water conditions more broadly is now enabled by microwave remote sensing. Specifically, satellite-based vegetation optical depth (VOD) provides daily observations of vegetation water volume at tens of kilometers. While satellite VOD has been used for many applications, VOD validations have rarely been carried out. A new method has enabled direct measurements of in-situ VOD, from Global Navigation Satellite Systems (GNSS). However, GNSS measurements have yet to be applied to more globally dominant grasslands and shrublands. Here, we explore how satellite-based VOD from SMAP and AMSR-2 compares with field-based microwave observations from 272 GNSS-based interferometric reflectometry (GNSS-IR) sites across the Western U.S as a part of the Plate Boundary Observatory (PBO) H20 network. These sensors measure a proxy for VOD at a scale of tens of meters, the normalized microwave reflectance index (NMRI). We find that satellite VOD generally positively correlates with GNSS NMRI with correlations between 0.2 to 0.6 across sites. 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 than C-band and L-band VOD products. These findings suggest that satellite VOD is capturing field-based GNSS signals in dryland ecosystems, and therefore that these sensors are a critical resource for validating satellite VOD at scale.

 National Aeronautics and Space Administration 80NSSC25K0156