Tracking high-alpine snow mass evolution using signals of a superconducting gravimeter combined with snowpack modelling and stereo satellite imagery

Monitoring the amount of snow, its spatiotemporal distribution as well as the onset and amount of snow-melt induced runoff generation are key challenges in alpine hydrology. Cryo-hydro-gravimetry is a non-invasive method of observing temporal gravity variations after the reduction of all other geophysical signals as the integral of all cryospheric and hydrological mass variations including snow accumulation and ablation. It has an accuracy of up to 9 decimals on a wide spectrum from high temporal resolution of up to 1 min to several years within footprints up to approx. 50 km². At the Zugspitze Geodynamic Observatory Germany (ZUGOG) with its worldwide unique installation of a superconducting gravimeter at a high-alpine summit (2.962 m a.s.l.), this method is applied for the first time on top of a well-instrumented, snow-dominated catchment. We use this instrumental setup in synthesis with in situ measured data, detailed physically-based snowpack modelling with Alpine3D as well as satellite-based snow depth maps derived by stereo photogrammetry. We will give an introduction into the novel sensor setup and will show first results, including the sensitivity of the integrative gravimetric signal regarding the spatially distributed snowpack and the cryo-hydro-gravimetric signal changes since 2019. The amount of the simulated snow water equivalent within the footprint of the gravimeter correlates well with the gravimetric signal (Pearson correlation coefficient r = 0.98). Based on the applied snowpack modelling approach including the snow depth maps for precipitation scaling, topography information as well as Newton’s Law of Gravitation, the gravimetric signal contribution and footprint can be described spatiotemporally over winter periods.