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Avalanching is a prominent source of accumulation on glaciers that have high and steep valley-walls surrounding their accumulation zones. These glaciers are typically characterised by an extensive supraglacial debris cover and a low accumulation area ratio. Despite an abundance of such glaciers in the rugged landscapes of the High Himalaya, attempts to quantify the net avalanche contribution to mass balance and its long-term variation are almost missing. We first discuss diagnostic criteria to identify strongly avalanche-fed glaciers. Second, we develop an approximate method to quantify the magnitude of the avalanche accumulation exploiting its expected control on the dynamics of these glaciers. The procedure is based on a simplified flowline model description of the glacier concerned and utilises the known glaciological mass-balance, velocity and surface-elevation profiles of the glacier. We apply the method to three Himalayan glaciers and show that the data on the recent dynamics of these glaciers are consistent with a dominant contribution of avalanches to the total accumulation. As a control experiment, we also simulate another Himalayan glacier where no significant avalanche contribution is expected, and reproduce the recent changes in that glacier without any additional avalanche contribution.

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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.