Snow is a major contributing factor of stream runoff in many alpine and high-latitude areas of the world, as well as a significant temporary reservoir of freshwater. For this reason, detailed information and knowledge on the timing, magnitude, and variability of snow processes (i.e. snowfall, accumulation, and melt) is important for successful water resources management and risk reduction in such areas. In this context, and due to the persistent limitations in data availability, hydrological models are widely used for making assessments and predictions on freshwater management and risk reduction. Among the large array of available hydrological models, the HBV model is a widely used model due to its simplicity, flexibility, and robustness. HBV’s design, representing hydrological processes in a simplified way, is particularly valuable in data-scarce areas. Additionally, the simplicity of the model is also beneficial for minimising uncertainties. Previous studies, however, show that an increased realism in the representation of some processes – e.g. snow processes – might improve the performance of hydrological models.
In this study we review and assess alternative conceptualisations to the snow routine of HBV-light, a user-friendly yet powerful version of the HBV model. Additionally, we explore the suitability of using additional input data such as relative humidity and shortwave solar radiation. We then evaluate the most promising model variations for a selected group of catchments representative of the different climatic and geographical areas of Switzerland. We also perform a further evaluation on catchments located in climate zones and landscapes different than Switzerland (e.g. USA) to ensure the robustness of the selected approaches.