The mass balance of lake-terminating glaciers responds to annual atmospheric variations, while calving-induced ice loss at the front is driven by local ice–water interactions. The current glaciological studies underestimate glacier response by neglecting the significant annual ice loss at the terminus through calving processes. This study integrates field measurements with remote sensing data to investigate the glaciological characteristics and proglacial lake evolution of the Gepang Gath glacier in the Chandra basin, Western Himalaya, India. Long-term observations reveal a continuous expansion of the proglacial lake from 0.21 ± 0.06 km2 (1962) to 1.21 ± 0.05 km2 (2023), along with terminus retreat of ∼2.76 km, attributed to calving at the ice–water interface. The glacier’s surface exhibits complex debris cover, with thicknesses up to 35 cm, creating significant spatial variations in surface mass balance. In-situ, glaciological measurements reveal a highly negative glacier-wide mass balance of −0.90 ± 0.30 m w.e. a−1 between the years 2014 and 2023. The geodetic estimates also reveal a negative mass balance of −0.61 ± 0.1 m w.e. a−1 over the past decade (2013–2023). The frontal area change (0.42 km2) and geodetic mass balance show a total volumetric ice loss of −21.77 × 106 m3 w.e. during the same period. Overall, the yearly frontal ice loss exacerbates the mass loss by 17–22%. These findings suggest that the presence of proglacial lakes plays a significant role in intensifying ice mass loss from Himalayan glaciers, strongly regulating their overall evolution.

Global warming is causing glaciers in the Caucasus Mountains and around the world to lose mass at an accelerated pace. As a result of this rapid retreat, significant parts of the glacierized surface area can be covered with debris deposits, often making them indistinguishable from the surrounding land surface by optical remote-sensing systems. Here, we present the DebCovG-carto toolbox to delineate debris-covered and debris-free glacier surfaces from non-glacierized regions. The algorithm uses synthetic aperture radar-derived coherence images and the normalized difference snow index applied to optical satellite data. Validating the remotely-sensed boundaries of Ushba and Chalaati glaciers using field GPS data demonstrates that the use of pairs of Sentinel-1 images (2019) from identical ascending and descending orbits can substantially improve debris-covered glacier surface detection. The DebCovG-carto toolbox leverages multiple orbits to automate the mapping of debris-covered glacier surfaces. This new automatic method offers the possibility of quickly correcting glacier mapping errors caused by the presence of debris and makes automatic mapping of glacierized surfaces considerably faster than the use of other subjective methods.