{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "U.S. Geological Survey Hydrologic Remote Sensing Branch Lakewood CO USA",
    "New England Water Science Center U.S. Geological Survey East Hartford CT USA",
    "U.S. Geological Survey Hydrologic Remote Sensing Branch Leetown WV USA",
    "Department of Chemical and Environmental Engineering University of Cincinnati Cincinnati OH USA",
    "Integrated Modeling and Prediction Division U.S. Geological Survey Conroe TX USA",
    "Department of Civil and Environmental Engineering University of Massachusetts Amherst Amherst MA USA",
    "CS GROUP FRANCE Toulouse France",
    "New England Water Science Center U.S. Geological Survey Pembroke NH USA",
    "The School of Earth Sciences, and Byrd Polar and Climate Research Center The Ohio State University Columbus OH USA",
    "Cooperative Institute for Research in Environmental Sciences University of Colorado, Boulder Boulder CO USA",
    "G‐EAU University Montpellier AgroParisTech BRGM CIRAD INRAE Institut Agro IRD Montpellier France",
    "Department of Geological Sciences University of North Carolina Chapel Hill NC USA",
    "Jet Propulsion Laboratory California Institute of Technology Flintridge CA USA",
    "Data Science Branch U.S. Geological Survey Moffet Field CA USA"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 16,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "M. E. Harlan"
    },
    {
      "affs": [
        1
      ],
      "name": "D. M. Bjerklie"
    },
    {
      "affs": [
        2
      ],
      "name": "J. Eggleston"
    },
    {
      "affs": [
        3
      ],
      "name": "D. Feng"
    },
    {
      "affs": [
        4
      ],
      "name": "R. Riggs"
    },
    {
      "affs": [
        5
      ],
      "name": "F. B. Bennitt"
    },
    {
      "affs": [
        6
      ],
      "name": "C. Cazals"
    },
    {
      "affs": [
        7
      ],
      "name": "R. W. Dudley"
    },
    {
      "affs": [
        8
      ],
      "name": "M. Durand"
    },
    {
      "affs": [
        5
      ],
      "name": "E. Friedmann"
    },
    {
      "affs": [
        5
      ],
      "name": "C. J. Gleason"
    },
    {
      "affs": [
        9
      ],
      "name": "J. T. Minear"
    },
    {
      "affs": [
        10
      ],
      "name": "H. Oubanas"
    },
    {
      "affs": [
        11
      ],
      "name": "T. Pavelsky"
    },
    {
      "affs": [
        12
      ],
      "name": "C. Stuurman"
    },
    {
      "affs": [
        13
      ],
      "name": "J. Zwart"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0ymmte9xkwzz9.bib",
  "cited_by": 0,
  "doi": "10.1029/2025wr041915",
  "fulltext_url": "https://doi.org/10.1029/2025WR041915",
  "id": "0ymmte9xkwzz9",
  "issns": [
    "1944-7973",
    "0043-1397"
  ],
  "landing_url": "https://doi.org/10.1029/2025wr041915",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "GE1-350"
    ],
    [
      "openalex",
      "2312|Hydrology and Watershed Management Studies"
    ]
  ],
  "openalex": "W7223701936",
  "pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1029/2025WR041915",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-26",
  "publisher": "Wiley",
  "ris": "https://research.draconitic.com/paper/0ymmte9xkwzz9.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:47:29Z",
      "native_id": "5a1b3b434fe944c6838e35c1528b5c0b",
      "source": "doaj",
      "url": "https://doi.org/10.1029/2025wr041915"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2312|Hydrology and Watershed Management Studies",
      "subfield": "hydrology-soils"
    }
  ],
  "title": "Evaluating SWOT Satellite Data With Gage Information in the United States and Canada",
  "title_text": "Evaluating SWOT Satellite Data With Gage Information in the United States and Canada",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:47:29Z",
  "url": "https://research.draconitic.com/paper/0ymmte9xkwzz9",
  "venue": "Water Resources Research",
  "versions": []
}