Mapping snow gliding distances: Bridging modelled and field observations

Abstract

Snow gliding affects soil erosion patterns and depends on various factors such as slope angle, precipitation amount, and vegetation roughness. Snow gliding distance can be assessed through measurement or modeling. However, the comparison of measured with modelled data remains limited due to the scarcity of measured data. We present a long-term dataset (2010−2021) of measured snow gliding distances for two Swiss alpine Valleys (Urseren and Val Piora) using glide shoes to address this gap. We also predicted snow gliding between 2010 and 2021 using the spatial snow gliding distance model developed by Leitinger et al. (2018). Our analysis of the measured data indicates that sites with a north aspect generally exhibit shorter snow gliding distances than those facing south. Moreover, we observed an increase in snow gliding distance with steeper slope angles and a decrease with a higher roughness coefficient. Comparing measured and modelled values, the R² and Concordance Correlation Coefficient (CCC) values are 0.23 and 0.12 for the Urseren Valley and 0.24 and 0.35 for the Val Piora. Generally, the model tended to predict higher values than the measured data for both Valleys, potentially due to the large small-scale variability observed in the replicates of the measured data that cannot be caught with large-scale models. This variability highlights the dynamic nature of snow gliding distance, making it challenging to model or measure accurately. Furthermore, a covariate importance analysis revealed precipitation and slope angle as the dominant drivers of modelled snow gliding distances versus vegetation roughness (a rather local feature) for measured values.