Abstract. The hydrologic cycle of high mountainous catchments is frequently simulated with simple precipitation-discharge models representing the snow accumulation and ablation behavior of a very complex environment with a set of lumped equations accounting for altitudinal temperature and precipitation gradients. In this study, we present a methodology to include sparse snow depths measurements into the calibration process. Based on this methodology, we assess for a case study, the Rhonegletscher catchment (Switzerland), how much observed information we need to reliably calibrate the model, such that it reproduces the dominant system dynamics, discharge, as well as glacier mass balance. Here, we focus on the question whether observed discharge is sufficient as a calibration variable or whether we need annual or even seasonal glacier mass balance data. Introducing seasonally variable accumulation and ablation parameters is sufficient to enable the simple model to reproduce observed seasonal mass balances for the Rhonegletscher. Furthermore, our results suggest that calibrating the hydrological model exclusively on discharge can lead to wrong representations of the intra-annual accumulation and ablation processes and to a strong bias in long term glacier mass balance simulations. Adding only a few annual mass balance observations considerably reduces this bias. Calibrating exclusively on annual balance data can, in turn, lead to wrong seasonal mass balance simulations. Even if these results are case study specific, our conclusions provide valuable new insights into the benefit of different types of observations for calibrating hydrological models in glacier catchments. The presented multi-signal calibration framework and the simple method to calibrate a semi-lumped model on point observations has potential for application in other modeling contexts.
Extrapolating glacier mass balance to the mountain-range scale: the European Alps 1900–2100
