Joël Borner

Predicting snow pressure forces exerted by the snow cover on structures on sloping terrain remains a challenging task. Especially with the increasing interest in alpine solar parks with little financial margin for safety, the demand for monitoring systems as well as accurate prediction models for snow pressure acting on slender supports is higher than ever before. This paper presents an experimental setup for measuring the reaction forces of the snow cover on various support and pressure bars of an snow supporting structure made of steel using strain gauges. In combination with the material properties and the entire static system of the structure, we can back calculate the pressure exerted by the snow cover. In order to interpret the measured forces correctly, additional field campaigns in winter are important to determine the local snow distribution, the snow temperature and the density of the snow cover. We extensively address challenges encountered during the measurement campaign, including eliminating temperature-induced strain, amplifying the signal in low strain ranges, handling combined bending and restraint stresses, and protecting sensors and cables against settlement and creep forces. Having overcome these challenges, the key advantages of using strain gauges are that the system is cost effective and non-invasive and therefore allows rapid installation on a large number of sections of interest. We discuss results obtained from the first winter of the campaign (2023/2024). The high measurement frequency of one measurement every five minutes provides an insight into the daily cycle of the forces. Most notably, on warm spring days with cold nights, we observed a continuous increase in forces starting at sunset, peaking at sunrise, followed by a rapid decline thereafter. The measurement data can be used to calibrate newly developed viscoelastic 3D snow creep models with various constitutive laws for the prediction of creep and glide forces on supporting structures. These models as well as the presented experimental setup show great potential to further optimise the design of supporting structures and installations of alpine solar parks.

Calculating contact/impact pressures with numerical finite element software remains a difficult task. It is especially difficult for highly compactable, plastic materials where the elastic fraction of the strain is very small. This is the case in most impact problems in natural hazards. One example is the impact of rockfall dams by large, rotating rocks. Another is the impact of pylons, walls and other obstacles by snow avalanches. We embed work-energy methods within numerical avalanche and rockfall models to make the calculation of impact pressures in natural hazards more applicable for engineering practice. Firstly, we can greatly reduce the computation time and secondly, the input parameters are much more intuitive for practitioners due to the use of purely plastic compactive material behaviour.

Accelerating glacier melt rates were observed during the last decades. Substantial ice loss occurs particularly during heat waves that are expected to intensify in the future. Because measuring and modelling glacier mass balance on a daily scale remains challenging, short-term mass balance variations, including extreme melt events, are poorly captured. Here, we present a novel approach based on computer-vision techniques for automatically determining daily mass balance variations at the local scale. The approach is based on the automated recognition of colour-taped ablation stakes from camera images and is tested and validated at six stations installed on three Alpine glaciers during the summers of 2019-2022. Our approach produces daily mass balance with an uncertainty of ±0.81 cm w.e. d-1, which is about half of the accuracy obtained from visual readouts. The automatically retrieved daily mass balances at the six sites were compared to average daily mass balances over the last decade derived from seasonal in situ observations to detect and assess extreme melt events. This allows analysing the impact that the summer heat waves which occurred in 2022 had on glacier melt. Our results indicate 23 d with extreme melt, showing a strong correspondence between the heat wave periods and extreme melt events. The combination of below-average winter snowfall and a suite of summer heat waves led to unprecedented glacier mass loss. The Switzerland-wide glacier storage change during the 25 d of heat waves in 2022 is estimated as 1.27 ± 0.10 km3 of water, corresponding to 35 % of the overall glacier mass loss during that summer. The same 25 d of heat waves caused a glacier mass loss that corresponds to 56 % of the average mass loss experienced over the entire melt season during the summers 2010-2020, demonstrating the relevance of heat waves for seasonal melt.

Definition: Snow farming – preserving large quantities of snow over the summer. Minimize melting with a thermal insulation cover.
Current relevance: Early and on schedule season opening, rising customer needs on snow availability and quality, business competition among ski resorts, snow making limitations, glacier melting
Aim of our survey: Monitoring activities, best practice, problems, potential, financing and costs to exchange and transfer Knowhow among practitioners and provide guidelines.