Bo Wang (Saint Louis University , United States)

River avulsions, the abrupt relocation of channels, are fundamental fluvial processes that build landscapes but pose significant hazards. Predicting these events is challenging. Particularly in dynamic, high-sediment rivers like Nepal's Koshi, these shifts threaten extensive populations and critical infrastructure, where traditional monitoring methods often fall short due to the vast scale and rapid changes involved. This study addresses the need for enhanced, quantitative avulsion risk assessment by leveraging new satellite datasets. Here we demonstrate, using synergistic analysis of SWOT (Surface Water and Ocean Topography) water surface elevations and FABDEM (Forest And Buildings removed Copernicus DEM) topography, that distinct reaches of the 70-km upper Koshi River exhibit quantifiable high risk of future avulsion. We calculated four indicators—Scv /Sdv (cross-valley slope/down-valley river slope), Ls /Sdv (levee slope/down-valley river slope), superelevation (derived from SWOT-inferred river depth using extreme low flow conditions and high-flow water surface elevation), and a composite metric (Y∗B, here Y*B is Ls/Sdv * Superelevation)—which pinpoint reaches 8 and 14 as most susceptible. The high risk in reach 8, located downstream of the 2008 Koshi avulsion in reach 7, validates our indicators' ability to identify areas primed for channel change by capturing conditions such as progressive superelevation. This approach offers a significant advance over previous qualitative or data-limited assessments by providing spatially explicit, data-driven vulnerability metrics. These findings establish a crucial, replicable framework for proactive avulsion hazard management in Koshi and other large, sediment-rich river systems globally.