Remote sensing interpretation of causes and dynamics of the Gyirong outburst flood disaster, Tibet, on July 8, 2025
摘要
In high mountain regions, glacial lake outburst floods (GLOFs) are significant geomorphic processes that reshape landscapes and have been studied extensively for their devastating impacts. On July 8, 2025, a catastrophic GLOF struck Gyirong land port, Tibet, China, causing at least nine deaths and leaving 19 people missing. This event was triggered by a rapid reduction of ~ 0.31 km2 (~ 45%) in supraglacial lake area in the upper Purepu Tsangpo, a tributary of the Donglin Tsangpo. Remote sensing analysis reveals that the lake’s surface area expanded ~ 7.65-fold, from ~ 0.08 km2 on May 9 to ~ 0.69 km2 on July 6, 2025, likely driven by global warming and intense regional rainfall, as inferred from meteorological data. Our remote sedimentological investigation indicates that the outburst flood, originating from a supraglacial lake on a debris-covered glacier, drained through supraglacial and englacial channels to downstream areas. Using the superelevation phenomenon, flow velocity and peak discharge were estimated, revealing that the flood weakened in wide, gently sloping U-shaped valleys after exiting the glacier terminus. In narrow, V-shaped valleys downstream, however, extensive erosion and entrainment substantially amplified the flood, resulting in an approximately sixfold increase in peak discharge, reaching ~ 8,400 m3/s, and ultimately evolving into a debris flow. This amplification is attributed to the topographic constraints of V-shaped valleys, where periglacial geomorphology transitions from glacier-dominated U-shaped valleys upstream to river-erosion-dominated V-shaped valleys downstream, with channels rich in erodible sediments. These conditions enhance volume amplification during GLOF evolution, increasing destructive potential. This study underscores the hazards of supraglacial lakes on debris-covered glaciers, emphasizing the urgent need for regional glacial lake hazard assessments and quantitative risk evaluations.