## 1 Introduction  
Stored moisture in soil and snow is an important factor in the hydrological cycle. Quantifying the spatiotemporal distribution of moisture is important for environmentally oriented research and for decision making in agriculture and hazard management. As the Alps provide long-term water storage for a large part of Central Europe, they provide a particularly relevant example. The weather in the Alps (e.g., warm temperatures in spring time, sustained precipitation on saturated soils) can cause flooding. In summer, melt water originating from the Alps can mitigate drought conditions downstream. Determination of moisture in soil and snow in the alpine context is therefore very important for local and downstream policy making and water resources management, which critically depends on understanding meteorological and hydrological processes in the complex alpine terrain. This includes the processes of heat and moisture transport in the atmospheric boundary layer and the interactions at the land surface. Since soil moisture determines water availability at the surface, and therefore controls the partitioning of the incoming radiation into the latent and sensible heat flux, it is one of the main controls of the land-atmosphere feedbacks and a key component in the hydrological cycle. Understanding these processes is essential for predicting natural hazards like landslides, droughts, and floods. In the agricultural context, the level of moisture in soil is an important element affecting plantation and plant growth. Hence, monitoring this attribute over the surface of an irrigated system facilitates correct and timely irrigation for consistently high yields, while avoiding application of excessive water prevents leaching of nitrates below depths of root penetration and depriving them of the needed oxygen [1, 2, 3]. Snow Water Equivalent (SWE), snow height (HS), and height of new snow (HNS) are vital parameters in cryospheric sciences such as snow hydrology, as well as in avalanche formation and snow climatology. In addition, snow cover determines albedo and is therefore also important in land-atmosphere feedbacks. In the forecast of avalanche danger, particularly for wet snow avalanches, important decisions must be made based on these parameters describing the development of the snowpack and its variability with slope angle, aspect, and altitude [4, 5]. In snow hydrology, if the spatial distribution of SWE and HS is measured over entire catchments, we can obtain an estimation of the total stored water resources [6, 7]. This information is extremely valuable for hydroelectric companies, water supply companies, and risk assessment [8, 9]. Many of the current observation techniques for quantifying soil moisture or characterizing a snow pack are performed manually or by dedicated instrumentation that relates to a specific spot or point measurement. For this reason, the observations are often limited to sporadic point-samples placed far apart, although it is well known that the distribution of moisture as well as that of snow-cover is very heterogeneous in alpine terrain. Moreover, manual snow measurement methods are laborious and destructive (hence limited in application for a single point). For these reasons, they can only be carried out at discrete time intervals and cannot be applied in areas of high avalanche danger. On the other hand, large-scale satellite-based remote measurement techniques do not yet provide the required resolution to resolve spatiotemporal variability present in such a complex and heterogeneous environment [10; 11; 12; 13]. It is therefore very desirable to establish a complementary and accurate, automated, continuous or dense, non-destructive measurement technique to close the scale-gap [14; 15]. The use of Global Navigation Satellite Signals (GNSS)-reflected signals to recover soil properties (GNSS Reflectometry or GNSS-R) is a potential solution to this problem, and has already provided promising results [16; 17; 18; 19].