RESUMEN
The current highest glacial lake outburst floods (GLOFs) risk level is centered in the eastern Himalaya. GLOFs represent a serious threat to downstream inhabitants and ecological environment. In the context of climate warming on the Tibetan Plateau, such GLOFs will continue or even intensify in the future. Remote sensing and statistical methods are often used to diagnose glacial lakes with the highest outburst probability. These methods are efficient in large-scale glacial lake risk assessment but do not take into consideration the complexity of specific glacial lake dynamics and triggering factor uncertainty. Therefore, we explored a novel approach to integrate geophysics, remote sensing, and numerical simulation in glacial lake and GLOF disaster chain assessments. In particular, geophysical techniques are rarely applied to the exploration of glacial lakes. The Namulacuo Lake located in the southeastern Tibetan Plateau is considered as the experimental site. The current status of the lake, including landform construction and identifying potential triggering factors, was first investigated. Secondly, the outburst process and disaster chain effect were evaluated by numerical simulation based on the multi-phase modeling frame proposed by Pudasaini and Mergili (2019) implemented in the open source computational tool r.avaflow. The results allowed verifying that the Namulacuo Lake dam was a landslide dam with an obvious layered structure. Also, the piping-induced flood might have more severe consequences than the short-term ultra-high discharge flood caused by surge. The blocking event caused by a surge disappeared faster than that caused by piping. Therefore, this comprehensive diagnostic approach can assist GLOF researchers to increase their understanding of key challenges they are facing regarding GLOF mechanisms.