Spatio-temporal wet snow dynamics from model simulations and remote sensing: A case study from the Rofental, Austria

Abstract

The formation and concentration of liquid water (LW) in the snowpack constitute key processes linking snow and runoff. Hence, the LW content of the snowpack represents a crucial target variable to investigate for snowmelt-induced runoff predictions. In this study, we capture the wet snow dynamics at higher than hectometre resolution in the alpine headwater catchment Rofental, Tyrol, Austria (98.1 km²) by means of distributed model simulations and remote sensing data for the 5 year period 10/2017–09/2022. The model simulations are conducted using the intermediate complexity open-source snow-hydrological model openAMUNDSEN. Simulation results are compared to wet snow maps (WSM) derived from Sentinel-1 data. Our investigations indicate that distributed snow models of intermediate complexity, such as openAMUNDSEN and satellite-based wet snow data are well capable of capturing the wet snow dynamics in high spatial and temporal resolutions. The areal extents of wet snow as well as the upward movement of the wet snow line to higher elevation with progressing snowmelt are captured well by both approaches. In order to evaluate the snow simulations, we use fractional snow cover (FSC) data based on Sentinel-2, which proved to provide valuable small-scale snow and snow redistribution patterns in alpine catchments. The comparison of model simulations with FSC maps with more than 50% of the non-glaciated area being cloud-free (i.e. 364 images) results in an accuracy of 0.91. This study represents a further step towards a serviceable operational snow-hydrological monitoring and modelling framework for mountain regions including wet snow dynamics in high spatial and temporal resolutions.