Journal Article

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

University of North Carolina System (UNC), Durand, Michael, Pavelsky, Tamlin, M, Université de Caroline du Nord à Chapel Hill = University of North Carolina [Chapel Hill] (UNC-Chapel Hill) ; University of North Carolina System (UNC), Oubanas, Hind, The Ohio State University [Columbus] (OSU), California Institute of Technology (CALTECH), Coss, Stephen, Cerbelaud, Arnaud, Collins, Elyssa, L, Altenau, Elizabeth, H, Jet Propulsion Laboratory (JPL) ; NASA-California Institute of Technology (CALTECH), Wade, Jeffrey, Gestion de l'Eau, Acteurs, Usages (UMR G-EAU) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Bureau de Recherches Géologiques et Minières (BRGM)-Institut de Recherche pour le Développement (IRD)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'

2025

Overview

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. Plain Language SummaryThe Surface Water and Ocean Topography (SWOT) Mission observes the water surface elevation, width, and slope of river reaches described in the SWOT River Database (SWORD). The location and extent of rivers in SWORD differ considerably from other river network data sets that are commonly used for hydrological modeling such as Multi-Error-Removed Improved Terrain (MERIT)-Basins. Here, we present and publicly share the MERIT-SWORD data set which links rivers in SWORD to rivers in MERIT-Basins (MB), and vice versa. These links between river reaches in the two data sets can allow for model simulations to be used as a first guess for SWOT measurements, and for observations from SWOT to be easily transferred to hydrologic modeling frameworks based on the MB river network for data assimilation.

• Publisher: American Geophysical Union,CCSD,John Wiley & Sons, Inc,Wiley
• Subject: Basins / data collection / Datasets / Discharge / Environmental Sciences / Estimates / Hydrographic data / Hydrography / Hydrologic models / landscapes / MERIT‐Basins / Modelling / River networks / Rivers / satellite remote sensing / Surface water / surface water hydrology / SWORD / SWOT / Topography / Translations
• ISBN: 0014935049000