ABSTRACT
The retreat of Himalayan glaciers and the expansion of glacial lakes due to global warming have increased the occurrence of glacial lake outburst debris flow (GLODF), posing a serious threat to downstream communities. However, there are gaps in understanding the changes in GLODF occurrence driven by climate change, which challenges disaster management and cross-border cooperation in the Himalayas. To consider this issue, our study presents a novel framework integrating environmental evolution, a process-driven indicator system, and a hybrid machine learning model to predict Himalayan GLODF occurrence in the 21st century. Our findings indicate ongoing temperature (0.27-0.60 °C/10a) and precipitation (1.30-5.00 %/10a) increases under both SSP245 and SSP585 scenarios. Meanwhile, Himalayan glaciers are projected to lose between 70 % and 86 % of their mass by 2100 compared to 2020. Additionally, 2722 ± 207 new glacial lakes are expected to emerge by 2100. GLODF occurrence probability index is anticipated to rise to 1.27-1.30 times the current levels, with the Western Himalayas and Indus basin as high-incidence areas. Currently and in the future, the China-Nepal border remains a hotspot for cross-border GLODF. Our framework offers valuable long-term insights into Himalayan GLODF occurrence trends in response to climate change.
