Bridging glacier and river catchment scales: an efficient representation of glacier dynamics in a hydrological model

Abstract. Glacierised river catchments have been shown to be highly sensitive to climate change, while large populations depend on the water resources originating from them. Hydrological models are used to aid water resource management, yet their treatment of glacier processes is either rudimentary in large applications or linked to fully distributed glacier models that prevent larger model domains. Also, data scarcity in mountainous catchments has hampered the implementation of physically based approaches over entire river catchments. A fully integrated glacier dynamics module was developed for the eco-hydrological model SWIM (SWIM-G) that takes full account of the spatial heterogeneity of mountainous catchments but keeps in line with the semi-distributed disaggregation of the hydrological model. The glacierised part of the catchment is disaggregated into glaciological response units that are based on subbasin, elevation zone and aspect classes. They seamlessly integrate into the hydrological response units of the hydrological model SWIM. Robust and simple approaches to ice flow, avalanching, snow accumulation and metamorphism as well as glacier ablation under consideration of aspect, debris cover and sublimation are implemented in the model, balancing process complexity and data availability. The fully integrated is also capable of simulating a range of other hydrological processes that are common for larger mountainous catchments such as reservoirs, irrigation agriculture and runoff from a diverse soil and vegetation cover. SWIM-G is initialised and calibrated to initial glacier hypsometry, glacier mass balance and river discharge. While the model is intended to be used in medium to large river basins with data-scarce and glacierised headwaters, it is here validated in the data-abundant catchment of the Upper Rhone River, Switzerland and the data-scarce catchment of the Upper Aksu River, Kyrgyzstan/NW China.