Himalayan glaciers have been shrinking and losing mass rapidly since 1970s with an enhanced rate after 2000. The shrinkage is, however, quite heterogeneous and it is important to document individual glacier characteristics and their changes at the basin scale. We present an updated glacier inventory of the Upper Alaknanda Basin (UAB), Central Himalaya for the year 2020 and report area, debris cover and length changes for the periods 1994–2006 and 2006–2020 based on remote-sensing data. We identified 198 glaciers, comprising an area of 354.6 ± 8.5 km2, and classified them according to their size and morphology. The glaciers of the basin lost 4.2 ± 2.9% (0.16 ± 0.11% a−1) of their frontal area (from 368.6 ± 9.2 to 353.0 ± 5.3 km2) from 1994 to 2020. The average retreat rate was higher in the period 2006–2020 (13.3 ± 1.8 m a−1) in comparison to 1994–2006 (9.3 ± 1.9 m a−1). However, the area change rate was similar for the two periods (0.14 ± 0.27% a−1 for 1994–2006 and 0.16 ± 0.19% a−1 for 2006–2020). The debris-covered area has increased by 13.4 ± 4.4% from 1994 to 2020. A comparison with previous studies in UAB indicates consistent area loss of ~0.15% a−1 since the 1960s.

Glaciological ablation is computed from point-scale data at a few ablation stakes that are usually regressed as a function of elevation and averaged over the area-elevation distribution of a glacier. This method is contingent on a tight control of elevation on local ablation. However, in debris-covered glaciers, systematic and random spatial variations of debris thickness modify the ablation rates. We propose and test a method to compute sub-debris ablation where stake data are interpolated as a function of debris-thickness alone and averaged over the debris-thickness distribution at different parts of the glacier. We apply this method on Satopanth Glacier located in Central Himalaya utilising ~1000 ablation measurements obtained from a network of up to 56 stakes during 2015–2017. The estimated mean sub-debris ablation ranges between 1.5±0.2 to 1.7±0.3 cm d−1. We show that the debris-thickness-dependent regression describes the spatial variability of the sub-debris ablation better than the elevation dependent regression. The uncertainties in ablation estimates due to the corresponding uncertainties in the measurement of ablation and debris-thickness distribution, and those due to interpolation procedures are estimated using Monte Carlo methods. Possible biases due to a finite number of stakes used are also investigated.