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.
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.
Total volume of stored ice in the Himalayan glaciers is an important quantity for water resource management of the Himalayan catchments. However, direct measurement of glacier-ice thickness is rare in the Indian Himalaya. We have estimated the ice thickness of the debris-covered Satopanth Glacier (SPG) using a ground penetrating radar (GPR). Multiple bistatic, unshielded antennae with frequencies of 16, 20, 40 and 80 MHz were used for this purpose. We have done GPR surveys at various locations over the ablation zone of SPG. However, satisfactory results were obtained only on two transects. Near the glacier snout, a transverse GPR profile shows an ice thickness of 38 3.5-50 3.5 m. We have obtained 98 7-112 7 m ice thickness at a longitudinal transect in the upper ablation zone. To measure the speed of the radar waves in ice, a common midpoint survey was carried out. Our results for the speed of the electromagnetic waves are slightly lower than the standard values of such waves through pure ice.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.