Abstract's details
Discharge Algorithm Working Group Update
Event: 2025 SWOT Science Team Meeting
Session: Hydrology: Discharge Algorithms Working Group (DAWG)
Presentation type: Poster
Discharge estimates derived from SWOT data are potentially transformative for human understanding of global hydrology, provided these estimates attain a reasonable level of accuracy. At the 2025 Science Team meeting, the Discharge Algorithm Working Group reports on progress towards global estimates of river discharge, in four areas of interest to the Science Team in general.
First, we report a first estimate of the accuracy of SWOT discharge, based on mid-2024 SWOT discharge estimates, and recently published in Geophysical Research Letters. We show that SWOT discharge tracks discharge variations, but is subject to bias, which is consistent with pre-launch studies. Bias is larger than expected based on pre-launch studies, and we explore reasons for this difference.
Second, the Confluence software has reached a new level of maturity, with major advances on multiple fronts. Confluence is now running operationally at PO.DAAC, overseen by software engineers, with both input and independence from the Science Team; Confluence will be run globally on a regular schedule going forward. Confluence has been modified to include several new modules, including the ability to process lakes alongside rivers. Confluence now can be run in “offline mode”, with many groups globally performing their own Confluence runs to estimate SWOT discharge.
Third, multiple groups have assessed the impact of various aspects of SWOT data quality on SWOT discharge accuracy. These groups have explored the impact of such factors as dark water, layover, prior bias, temporal revisit and data completeness and related to SWOT ability to tease out discharge variations. This analysis improves SWOT discharge maturity and points the way towards flags to alert users to expected SWOT discharge precision on a reach/pass basis.
Fourth, we describe work that explores the upper limit or ceiling of SWOT accuracy. We calibrate SWOT data directly to in situ gages, and show that SWOT discharge estimates follow prelaunch expectations and expected SWOT error in height width and slope, with discharge error ranging between 15-20% across hundreds of gages. We compare SWOT version C and D. Defining this ceiling provides a target for ongoing efforts to aim at.
In addition to these four advances, we provide a short update on the timeline of expected discharge estimate availability for those estimates computed by the space agencies (Level 2), and those produced by the Science Team (Level 4).
First, we report a first estimate of the accuracy of SWOT discharge, based on mid-2024 SWOT discharge estimates, and recently published in Geophysical Research Letters. We show that SWOT discharge tracks discharge variations, but is subject to bias, which is consistent with pre-launch studies. Bias is larger than expected based on pre-launch studies, and we explore reasons for this difference.
Second, the Confluence software has reached a new level of maturity, with major advances on multiple fronts. Confluence is now running operationally at PO.DAAC, overseen by software engineers, with both input and independence from the Science Team; Confluence will be run globally on a regular schedule going forward. Confluence has been modified to include several new modules, including the ability to process lakes alongside rivers. Confluence now can be run in “offline mode”, with many groups globally performing their own Confluence runs to estimate SWOT discharge.
Third, multiple groups have assessed the impact of various aspects of SWOT data quality on SWOT discharge accuracy. These groups have explored the impact of such factors as dark water, layover, prior bias, temporal revisit and data completeness and related to SWOT ability to tease out discharge variations. This analysis improves SWOT discharge maturity and points the way towards flags to alert users to expected SWOT discharge precision on a reach/pass basis.
Fourth, we describe work that explores the upper limit or ceiling of SWOT accuracy. We calibrate SWOT data directly to in situ gages, and show that SWOT discharge estimates follow prelaunch expectations and expected SWOT error in height width and slope, with discharge error ranging between 15-20% across hundreds of gages. We compare SWOT version C and D. Defining this ceiling provides a target for ongoing efforts to aim at.
In addition to these four advances, we provide a short update on the timeline of expected discharge estimate availability for those estimates computed by the space agencies (Level 2), and those produced by the Science Team (Level 4).
Contribution: ST2025HS4-Discharge_Algorithm_Working_Group_Update.pdf (pdf, 1137 ko)
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