Distributed surface mass balance of an avalanche-fed glacier

Abstract. Local snow redistribution processes such as avalanches can considerably impact the spatial variability of accumulation on glaciers. However, this spatial variability is particularly difficult to quantify with traditional surface mass balance measurements or geodetic observations. Here, we leverage high quality surface velocity and elevation change maps for the period 2012–2021 from Pléiades stereo images, and ice thickness measurements of Argentière Glacier (France) to invert for its distributed surface mass balance. This inversion is conducted using three different ice thickness modelling approaches constrained by observations, which all show a very good agreement between inverted surface mass balance and in situ measurements (RMSE < 0.96 m w.e. yr^-1 for the 11-year average). The detected spatial variability in surface mass balance is consistent between modelling approaches and much higher than what is predicted from an enhanced temperature-index model calibrated with measurements from a dense network of stakes. In particular, we find high accumulation rates at the base of steep headwalls on the left-hand side of the glacier, likely related to avalanching at these locations. We calculate distributed precipitation correction factors to reconcile the outputs from the enhanced temperature-index model with the inverted surface mass balance data. These correction factors agree with the outputs of a parametrization of snow redistribution by avalanching, indicating an additional 60 % mass input relative to the accumulation from solid precipitation at these specific locations. Using these correction factors in a forward modelling exercise, we show that explicitly accounting for avalanches leads to twice more ice being conserved in the Argentière catchment by 2100 in an RCP 4.5 climate scenario, and to a considerably different ice thickness distribution. Our results highlight the need to better account for such spatially variable accumulation processes in glacio-hydrological models.