Bidirectional Translations Between Observational and Topography‐Based Hydrographic Data Sets: MERIT‐Basins and the SWOT River Database (SWORD)

Abstract The recently launched Surface Water and Ocean Topography (SWOT) Mission is expected to provide transformative observations of water surface elevation, width, and slope and produce derived estimates of discharge for global rivers along rivers in the SWOT River Database (SWORD). However, the hydrographic representation of rivers in SWORD differs from hydrography data sets commonly used for modeling purposes, such as Multi‐Error‐Removed Improved Terrain (MERIT)‐Basins. Here, we develop links between the river networks of SWORD and MERIT‐Basins (MB) to enable interoperability between SWOT data products and hydrologic modeling frameworks. This data set, termed MERIT‐SWORD, identifies a subset of ∼277,000 global MB river reaches that most closely represent the location and extent of the SWORD river network and establishes bidirectional, one‐to‐many translations between reaches in the two hydrographic data sets. The MERIT‐SWORD data set serves to unite SWOT observations with river routing models, allowing for the seamless and standardized assimilation of SWOT vector products into global river simulations and the provision of improved a priori discharge estimates for SWOT discharge computation.

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Publication Details

Journal
Water Resources Research
Published
2025-05-01
DOI
https://doi.org/10.1029/2024wr038633
Citations
4
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
4.42
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article

Bidirectional Translations Between Observational and Topography‐Based Hydrographic Data Sets: MERIT‐Basins and the SWOT River Database (SWORD)

Manu Tom, Elyssa L. Collins, Jeffrey Wade, Stephen Coss et al.
4 citations
Water Resources Research
Flood Risk Assessment and Management
4.42
article

Bidirectional Translations Between Observational and Topography‐Based Hydrographic Data Sets: MERIT‐Basins and the SWOT River Database (SWORD)

Manu Tom, Elyssa L. Collins, Jeffrey Wade, Stephen Coss, Tamlin M. Pavelsky, Arnaud Cerbelaud, Cédric Hervé David, Michael Durand, Elizabeth H. Altenau, Hind Oubanas
article en
4 citations

Abstract

Abstract The recently launched Surface Water and Ocean Topography (SWOT) Mission is expected to provide transformative observations of water surface elevation, width, and slope and produce derived estimates of discharge for global rivers along rivers in the SWOT River Database (SWORD). However, the hydrographic representation of rivers in SWORD differs from hydrography data sets commonly used for modeling purposes, such as Multi‐Error‐Removed Improved Terrain (MERIT)‐Basins. Here, we develop links between the river networks of SWORD and MERIT‐Basins (MB) to enable interoperability between SWOT data products and hydrologic modeling frameworks. This data set, termed MERIT‐SWORD, identifies a subset of ∼277,000 global MB river reaches that most closely represent the location and extent of the SWORD river network and establishes bidirectional, one‐to‐many translations between reaches in the two hydrographic data sets. The MERIT‐SWORD data set serves to unite SWOT observations with river routing models, allowing for the seamless and standardized assimilation of SWOT vector products into global river simulations and the provision of improved a priori discharge estimates for SWOT discharge computation.

Water Resources ResearchVol. 61(5)
University of North Carolina at Chapel Hill (US), Goddard Space Flight Center (US), Jet Propulsion Laboratory (US), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Gestion de l'Eau, Acteurs, Usages (FR), Columbus Center (US), Earth System Science Interdisciplinary Center (US), Byrd Polar and Climate Research Center, The Ohio State University (US), University of Maryland, College Park (US)
Openalex Percentile: Top 6%
Flood Risk Assessment and Management
4.42
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