Articles | Volume 25, issue 6
https://doi.org/10.5194/nhess-25-1841-2025
https://doi.org/10.5194/nhess-25-1841-2025
Research article
 | 
03 Jun 2025
Research article |  | 03 Jun 2025

Exploring implications of input parameter uncertainties in glacial lake outburst flood (GLOF) modelling results using the modelling code r.avaflow

Sonam Rinzin, Stuart Dunning, Rachel Joanne Carr, Ashim Sattar, and Martin Mergili

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Cited articles

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Allen, S. K., Rastner, P., Arora, M., Huggel, C., and Stoffel, M.: Lake outburst and debris flow disaster at Kedarnath, June 2013: hydrometeorological triggering and topographic predisposition, Landslides, 13, 1479–1491, https://doi.org/10.1007/s10346-015-0584-3, 2015. 
Allen, S. K., Linsbauer, A., Randhawa, S. S., Huggel, C., Rana, P., and Kumari, A.: Glacial lake outburst flood risk in Himachal Pradesh, India: an integrative and anticipatory approach considering current and future threats, Nat. Hazards, 84, 1741–1763, https://doi.org/10.1007/s11069-016-2511-x, 2016. 
Allen, S. K., Zhang, G., Wang, W., Yao, T., and Bolch, T.: Potentially dangerous glacial lakes across the Tibetan Plateau revealed using a large-scale automated assessment approach, Sci. Bull., 64, 435–445, https://doi.org/10.1016/j.scib.2019.03.011, 2019. 
Allen, S. K., Sattar, A., King, O., Zhang, G., Bhattacharya, A., Yao, T., and Bolch, T.: Glacial lake outburst flood hazard under current and future conditions: worst-case scenarios in a transboundary Himalayan basin, Nat. Hazards Earth Syst. Sci., 22, 3765–3785, https://doi.org/10.5194/nhess-22-3765-2022, 2022. 
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We modelled multiple glacial lake outburst flood (GLOF) scenarios (84 simulations) and tested the effect of nine key input parameters on the modelling results using r.avaflow. Our results highlight that GLOF modelling results are subject to uncertainty from the multiple input parameters. The variation in the volume of mass movement entering the lake causes the highest uncertainty in the modelled GLOF, followed by the DEM dataset and the origin of mass movement.
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