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Abstract

As glaciers react to rising temperatures, the risk of glacial lake outburst floods (GLOFs) endangers downstream lives and infrastructures. To assess how C-band synthetic aperture radar data can be used to determine the timeframe of interest (TOI: includes a GLOF event), an intra-annual time-series analysis based on Sentinel-1 (S1) data was conducted covering six-month seasons (April – September) from 2017 – 2022 at the debris-covered Inylchek Glacier/Lake Merzbacher, Kyrgyzstan. In total, 90 Level-1 Ground Range Detected (High-Resolution, Dual-Pol) scenes were processed, and amplitude offset-tracking was executed. This way, 102 velocity maps (temporal baseline: 24 and 12 days) were generated. The spatio-temporal time-series analysis was performed in Geographic Information Systems with the maximum horizontal surface velocity (MSV) as the critical parameter. It is found that S1 data is suitable for detecting and quantifying horizontal glacier surface movement. The statistical analysis indicates that the MSV increased at the Inylchek Glacier during the observation period, e.g., median per season: Δ_max. = 0.278 md^-1. For all seasons, TOIs were calculated. Optical imagery captured by an in-situ meteorological station was used for verification, indicating that 66.7 % of the TOIs are accurate. The GLOFs at Lake Merzbacher documented in this study continue the inter-annual trend of occurring earlier during ablation seasons. The MSV shows high potential to serve as a parameter for isolating GLOFs. Further studies on the glacier dynamics are recommended by using complementing parameters and multi-source remote sensing data to enhance precision and accuracy. Remote sensing techniques pose great potential for monitoring and assessing GLOF risk.