Laurence Smith (Institute at Brown for Environment and Society, Brown University, Providence, RI, USA, United States); Bo Wang (Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, USA, United States); Cassie Stuurman (Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA, United States)

Glacial Lake Outburst Floods are a major geohazard in the Himalayas and other mountainous environments. However, high-resolution identification and tracking of such flooding hazards are limited by their extreme environment, inaccessibility, and moderate spatiotemporal resolution of traditionally available satellite programs. Recent technological breakthroughs, including high-resolution Commercial Satellite Data and NASA/CNES/CSA/UKSA Surface Water and Ocean Topography (SWOT) interferometric radar, have the potential to assist in this effort. Using a 16 August 2024 unexpected glacial lake outburst flood of Nepal Himalaya as a case study, we show that multisource satellite observations (Landsat, Sentinel-2, Planet, SWOT) detect source lake’s growing area, turbidity, and water surface elevation and storage change before and after the glacial lake outburst. We found that increased glacier meltwater runoff caused rapid, unnoticed growth of this remote glacial lake since 2008. The lake then overtopped its basin, eroding a ~95–150 m wide outlet channel that abruptly drained the lake, releasing a catastrophic flood down-valley, destroying parts of Thame village. Assimilating SWOT with other remote observations, we found that abrupt drainage of the lake caused a 5-meter drop in its water level, a 47% decrease in water area, and a 510,000 cubic meters storage change after the flood, which flowed into the downstream lake, causing it to also breach and fail. This secondary lake drainage triggered an additional 11-meter water level drop, a 72% decrease in lake area, and a 370,000 cubic meter water storage loss, further exacerbating the flood. Sentinel-2 derived Normalized Difference Turbidity Index (NDTI) retrievals over glacial lake outburst flood source area reveal the highest turbidity in the uppermost lake (NDTI= -0.04), signifying a glacial meltwater source. Water levels from this uppermost lake were not present in SWOT LakeSP but were available in the SWOT Pixel Cloud product. We conclude that SWOT observations can aid early detection of potential flood hazards for prioritization in field-based hazard assessments and mitigation strategies.