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Snow, especially in mountainous regions, plays a major role acting as a quasi-reservoir, as it gradually releases fresh water during the melting season and thereby fills rivers, lakes, and groundwater aquifers. For vegetation and irrigation, the timing of the snowmelt is crucial. Therefore, it is necessary to understand how snowmelt varies under different local conditions. While differences in slope aspect and vegetation (individually) were linked to differences in snow accumulation and ablation, this study connects the two and describes their influence on the soil moisture response to snowmelt. This research focuses on the catchment of the “Brunnenkopfhütte” (BKH) in Bavaria, southern Germany, where an automatic weather station (AWS) has operated since 2016. In addition, soil temperature and moisture monitoring systems in the surrounding area on a south aspect slope on an open field (SO), on a south aspect slope in the forest (SF), and a north aspect slope in the forest (NF) have operated since 2020. On snow-free days in winter, the soil temperature at the SF site was on average 1 °C lower than on the open site. At the NF site, this soil temperature difference increased to 2.3 °C. At the same time, for a 1 °C increase in the air temperature, the soil temperature increases by 0.35 °C at the NF site. In addition, at this site, snow cover disappeared approximately one week later than on the south aspect slopes. Snow cover at the SF site disappeared even earlier than at the SO site. Finally, a significant difference in the soil moisture response was found between the sites. While the vegetation cover dampens the magnitude of the soil moisture increases, at the NF site, no sharp increases in soil moisture were observed.

Meltwater from mountainous catchments dominated by snow and ice is a valuable source of fresh water in many regions. At mid-latitudes, seasonal snow cover and glaciers act like a natural reservoir by storing precipitation during winter and releasing it in spring and summer. Snowmelt is usually modelled either by energy balance or by temperature-index approaches. The energy balance approach is process-based and more sophisticated but requires extensive input data, while the temperature-index approach uses the degree-day factor (DDF) as a key parameter to estimate melt of snow and ice merely from air temperature. Despite its simplicity, the temperature-index approach has proved to be a powerful tool for simulating the melt process especially in large and data-scarce catchments. The present study attempts to quantify the effects of spatial, temporal, and climatic conditions on the DDF of snow in order to gain a better understanding of which influencing factors are decisive under which conditions. The analysis is based on the individual energy flux components; however, formulas for estimating the DDF are presented to account for situations where observed data are limited. A detailed comparison between field-derived and estimated DDF values yields a fair agreement with bias = 0.14 mm ∘C−1 d−1 and root mean square error (RMSE) = 1.12 mm ∘C−1 d−1. The analysis of the energy balance processes controlling snowmelt indicates that cloud cover and snow albedo under clear sky are the most decisive factors for estimating the DDF of snow. The results of this study further underline that the DDF changes as the melt season progresses and thus also with altitude, since melting conditions arrive later at higher elevations. A brief analysis of the DDF under the influence of climate change shows that the DDFs are expected to decrease when comparing periods of similar degree days, as melt will occur earlier in the year when solar radiation is lower, and albedo is then likely to be higher. Therefore, the DDF cannot be treated as a constant parameter especially when using temperature-index models for forecasting present or predicting future water availability.