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Peer-reviewedCC BYWater Resources Research

Evaluating SWOT Satellite Data With Gage Information in the United States and Canada

  • M. E. Harlan1
  • D. M. Bjerklie2
  • J. Eggleston3
  • D. Feng4
  • R. Riggs5
  • F. B. Bennitt6
  • C. Cazals7
  • R. W. Dudley8
  • M. Durand9
  • E. Friedmann6
  • C. J. Gleason6
  • J. T. Minear10
4 more authors
  • H. Oubanas11
  • T. Pavelsky12
  • C. Stuurman13
  • J. Zwart14
14 affiliations
  1. 1U.S. Geological Survey Hydrologic Remote Sensing Branch Lakewood CO USA
  2. 2New England Water Science Center U.S. Geological Survey East Hartford CT USA
  3. 3U.S. Geological Survey Hydrologic Remote Sensing Branch Leetown WV USA
  4. 4Department of Chemical and Environmental Engineering University of Cincinnati Cincinnati OH USA
  5. 5Integrated Modeling and Prediction Division U.S. Geological Survey Conroe TX USA
  6. 6Department of Civil and Environmental Engineering University of Massachusetts Amherst Amherst MA USA
  7. 7CS GROUP FRANCE Toulouse France
  8. 8New England Water Science Center U.S. Geological Survey Pembroke NH USA
  9. 9The School of Earth Sciences, and Byrd Polar and Climate Research Center The Ohio State University Columbus OH USA
  10. 10Cooperative Institute for Research in Environmental Sciences University of Colorado, Boulder Boulder CO USA
  11. 11G‐EAU University Montpellier AgroParisTech BRGM CIRAD INRAE Institut Agro IRD Montpellier France
  12. 12Department of Geological Sciences University of North Carolina Chapel Hill NC USA
  13. 13Jet Propulsion Laboratory California Institute of Technology Flintridge CA USA
  14. 14Data Science Branch U.S. Geological Survey Moffet Field CA USA
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Abstract

The Surface Water and Ocean Topography (SWOT) satellite mission represents a transformative approach to water resources management, offering high‐resolution data on water‐surface elevations (WSE) and extents. This study evaluates SWOT WSE accuracy in the United States and Canada with in situ streamgage and lake and reservoir gage data. We compare SWOT Level 2 Hydrology data products (Version D) to in situ timeseries of WSE on 335,531 paired observations across 2,629 gages. SWOT data accuracy and temporal coverage are explored as functions of various SWOT quality filters. After applying a standard set of defined filters and thresholds to compare paired measurements of SWOT and in situ observations (both referenced to the Earth Gravitational Model 2008), we find 1‐σ (68th percentile) absolute differences of 20 and 11 cm, and median biases of 2.8 and 0.1 cm, for filtered river node and lake data, respectively. River reach and lake comparisons may be biased due to scale mismatches between in situ point‐based data and spatially averaged SWOT data. Applying SWOT data quality filters improved median paired elevation R2 between unfiltered and filtered data from 0.12 to 0.92 across all reach, node, and lake observations. Overall, we find that 60.0% and 73.8% of all paired SWOT node and lake WSE observations that satisfy SWOT‐observable criteria (ice‐free observations from sufficiently large waterbodies within the SWOT cross track range) have elevations within 25 cm of reported gage observations. These comparisons also provide a baseline benchmark that can help inform continued SWOT algorithm refinement.

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Cite

BibTeXRIS
BibTeX
@article{harlan2026evaluating,
  title = {{Evaluating SWOT Satellite Data With Gage Information in the United States and Canada}},
  author = {M. E. Harlan and D. M. Bjerklie and J. Eggleston and D. Feng and R. Riggs and F. B. Bennitt and C. Cazals and R. W. Dudley and M. Durand and E. Friedmann and C. J. Gleason and J. T. Minear and H. Oubanas and T. Pavelsky and C. Stuurman and J. Zwart},
  journal = {Water Resources Research},
  year = {2026},
  month = oct,
  doi = {10.1029/2025wr041915},
  url = {https://doi.org/10.1029/2025wr041915},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Evaluating SWOT Satellite Data With Gage Information in the United States and Canada
AU  - M. E. Harlan
AU  - D. M. Bjerklie
AU  - J. Eggleston
AU  - D. Feng
AU  - R. Riggs
AU  - F. B. Bennitt
AU  - C. Cazals
AU  - R. W. Dudley
AU  - M. Durand
AU  - E. Friedmann
AU  - C. J. Gleason
AU  - J. T. Minear
AU  - H. Oubanas
AU  - T. Pavelsky
AU  - C. Stuurman
AU  - J. Zwart
PY  - 2026
DA  - 2026/10/26
JO  - Water Resources Research
DO  - 10.1029/2025wr041915
UR  - https://doi.org/10.1029/2025wr041915
AB  - The Surface Water and Ocean Topography (SWOT) satellite mission represents a transformative approach to water resources management, offering high‐resolution data on water‐surface elevations (WSE) and extents. This study evaluates SWOT WSE accuracy in the United States and Canada with in situ streamgage and lake and reservoir gage data. We compare SWOT Level 2 Hydrology data products (Version D) to in situ timeseries of WSE on 335,531 paired observations across 2,629 gages. SWOT data accuracy and temporal coverage are explored as functions of various SWOT quality filters. After applying a standard set of defined filters and thresholds to compare paired measurements of SWOT and in situ observations (both referenced to the Earth Gravitational Model 2008), we find 1‐σ (68th percentile) absolute differences of 20 and 11 cm, and median biases of 2.8 and 0.1 cm, for filtered river node and lake data, respectively. River reach and lake comparisons may be biased due to scale mismatches between in situ point‐based data and spatially averaged SWOT data. Applying SWOT data quality filters improved median paired elevation R2 between unfiltered and filtered data from 0.12 to 0.92 across all reach, node, and lake observations. Overall, we find that 60.0% and 73.8% of all paired SWOT node and lake WSE observations that satisfy SWOT‐observable criteria (ice‐free observations from sufficiently large waterbodies within the SWOT cross track range) have elevations within 25 cm of reported gage observations. These comparisons also provide a baseline benchmark that can help inform continued SWOT algorithm refinement.
SN  - 1944-7973
SN  - 0043-1397
ER  -