Integrating Satellite and Field Data for Glacier Melt Modeling in High-Mountain Asia: A Case Study on Passu Glacier

Glaciers in High-Mountain Asia, the so-called “Third Pole,” are critical water sources but remain poorly monitored due to rugged topography and limited accessibility. We present an integrated approach that combines remote sensing with ground-based observations to model ice melt of the Passu Glacier (Pakistan) from 5 August to 13 October 2023. Meteorological data from two automatic weather stations and ablation measurements from four stakes were used together with satellite-derived albedo (Landsat 8 OLI), surface temperature (Landsat 9 TIRS), and topography (ALOS AW3D30 DSM) to implement an enhanced T-index melt model accounting for net shortwave and longwave radiation. Model performance was evaluated against station and satellite data and ablation stake measurements using leave-one-out cross-validation. The estimated total ice melt volume was 16 million m3 w.e. during the monitoring period, with an average melt of 3.60 m w.e. The model reproduced observed stake ablation with an uncertainty of 0.48 m w.e. (9% of average measured melt). Elevation was identified as the dominant melt driver (β = −0.501, unique R2 = 0.199), with aspect and slope exerting secondary influences through their effect on solar radiation and shading. Our findings demonstrate that combining minimal but strategically located field data with satellite products provides a physically consistent and scalable framework for glacier melt estimation in data-scarce regions of the Third Pole, with relevance for hydrological monitoring and climate adaptation.