Geology Reports⌕ Search
Home/Archive/USGS

USGS · 70283102

A first look at river discharge estimation from SWOT satellite observations

Konstantinos M. Andreadis·Steve P. Coss·Michael Durand·Colin J. Gleason·Travis T. Simmons·Nikki Tebaldi·David M. Bjerklie·Craig Brinkerhoff·Robert W. Dudley·Igor Gejadze·Kevin Larnier·Pierre-Olivier Malaterre·Hind Oubanas·George H. Allen·Paul D. Bates·Cédric H. David·Alessio Domeneghetti·Omid Elmi·Luciana Fenoglio Marc·Renato Prate de Moraes Frasson·Elisa Friedmann·Pierre-André Garambois·Jaclyn Gehring·Augusto Getirana·Marissa Hughes·Jonghyun Lee·Pascal Matte·J. Toby Minear·Jérôme Monnier·Aggrey Muhebwa·Mohammad J. Tourian·Tamlin M. Pavelsky·Ryan Matthew Riggs·Ernesto Rodríguez·Md Safat Sikder·Laurence C. Smith·Cassie Stuurman·Jay Taneja·Angelica Tarpanelli·Jida Wang·Brent A. Williams·Bidhyananda Yadav
View original source ↗Export metadata ↓

Abstract

The Surface Water and Ocean Topography (SWOT) satellite has the potential to transform global hydrologic science by offering simultaneous and synoptic estimates of river discharge and other hydraulic variables. Discharge is estimated from SWOT observations of water surface elevation, width, and slope. A first assessment using just the highest quality SWOT measurements, over the first 15 months (March 2023–July 2024) of the mission evaluated at 65 gauged reaches shows results consistent with pre-launch expectations. SWOT estimates track discharge dynamics without relying on any gauge information: median correlation is 0.73, with a correlation interquartile range of 0.51–0.89. SWOT estimates capture discharge magnitude correctly in some cases but are biased (median bias is 50%) in others. There are already a total of 11,274 ungauged global locations with highest quality SWOT measurements where SWOT discharge is expected to accurately track discharge variations: this value will increase as SWOT data record length grows, algorithms are refined and SWOT measurements are reprocessed. This first look indicates that SWOT discharge is performing as expected for SWOT data that achieve performance requirements, providing observed information on discharge variations in ungauged basins globally.

Explore related subjects

Geophysical Research LettersArticle
90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 34.9871351° to 42.69763224486408° latitude; -89.69660651990715° to -77.9271415° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Konstantinos M. Andreadis, Steve P. Coss, Michael Durand, Colin J. Gleason, Travis T. Simmons, Nikki Tebaldi, David M. Bjerklie, Craig Brinkerhoff, Robert W. Dudley, Igor Gejadze, Kevin Larnier, Pierre-Olivier Malaterre, Hind Oubanas, George H. Allen, Paul D. Bates, Cédric H. David, Alessio Domeneghetti, Omid Elmi, Luciana Fenoglio Marc, Renato Prate de Moraes Frasson, Elisa Friedmann, Pierre-André Garambois, Jaclyn Gehring, Augusto Getirana, Marissa Hughes, Jonghyun Lee, Pascal Matte, J. Toby Minear, Jérôme Monnier, Aggrey Muhebwa, Mohammad J. Tourian, Tamlin M. Pavelsky, Ryan Matthew Riggs, Ernesto Rodríguez, Md Safat Sikder, Laurence C. Smith, Cassie Stuurman, Jay Taneja, Angelica Tarpanelli, Jida Wang, Brent A. Williams, Bidhyananda Yadav. 2025-05-03. A first look at river discharge estimation from SWOT satellite observations. https://doi.org/10.1029/2024gl114185

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

EMIT reveals elevated calcite signatures in shorelines of Lake Powell and Lake Mead exposed by drought and Colorado River management

Nearly half of Earth’s seasonal freshwater storage variability occurs in human-managed reservoirs, resulting in large areas of reservoir-bed that are episodically inundated or subaerially exposed. Here we use hyperspectral data from NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) mission to map calcite mineral assemblages across exposed surfaces in two large U.S. reservoirs, Lake Mead and Lake Powell. Results show distinct patterns in the occurrence of carbonate, clay, and mica minerals. Reservoir-deposited sediments exhibited significantly higher calcite proportions than adjacent, lithologically similar, non-inundated terrestrial surfaces. These differences likely reflect hydrologically-driven calcite precipitation, wherein warm, clear, productive reservoir waters drive calcium carbonate out of solution. We also detect reductions in calcite proportions in areas of the shoreline disturbed by human recreation. EMIT's imaging capabilities enable rapid, high-resolution mineralogical inventories across vast areas where field sampling is infeasible. We find EMIT is a scalable tool for monitoring geochemical changes associated with large water level fluctuations.

Arizona, Nevada, Utah↗
USGS2026

First application of a coastal-dune model (AeoLiS) to simulate fluvial-aeolian morphodynamics

Quantifying aeolian processes is important to decision-making in river management and for optimizing strategies for ecosystem conservation, natural resource management, and recreation. We applied the AeoLiS aeolian transport model, originally developed for coastal environments, to a dryland river corridor to evaluate its ability to simulate sediment dynamics in a fluvial-aeolian system. The model reproduced spatial and temporal patterns of geomorphic change at a Grand Canyon sandbar, including aeolian dune formation, observed in field data. The model effectively captured trends in observed sediment movement in the spring and summer months. Thus, despite assuming a single grain-size, static vegetation, and not directly accounting for variable sediment supply from fluvial sources, the model performs well at capturing aeolian processes in a complex fluvial-aeolian system. AeoLiS demonstrates strong potential for dryland river applications and management, due to its flexibility and compatibility with coupled modeling frameworks.

Arizona↗
USGS2026

Emergent headwater types for watershed monitoring, research, and planning

Headwaters—that is headwater streams and the watersheds they drain—strongly influence water quality, ecosystem services, and hydrologic connectivity, yet remain poorly mapped, monitored, and understood at large spatial scales. Using available spatial data to classify headwater “types” could therefore enhance the utility of sparse monitoring data to advance research and watershed planning—and help update literature-based perceptual models of headwaters as steep, forested, and minimally disturbed watersheds. Here, we analyze headwaters across the contiguous United States to quantify how their attributes (climate, topography, land cover, soils) vary regionally and differ from their downstream watersheds. Our analysis (a) identified seven dominant headwater types with distinct combinations of biophysical and climatic attributes and (b) revealed systematic contrasts with downstream watersheds, with strongest differences in attributes representing potential flowpath depth. Our findings offer a transferable framework for classifying, modeling, and managing these critical yet understudied components of the hydrologic network.

conterminous United States↗