Abstract

Modelling and monitoring seasonal snow are critical for water resource management, flood forecasting and avalanche risk prediction. Snowmelt processes are of particular importance. The behaviour of liquid water in snow has a big influence on melting processes but is difficult to measure, monitor and model. Recent work has shown the promise of electrical self potential measurements for monitoring snow hydrology. To further this aim, detailed modelling of internal water fluxes in melting snow was carried out with FSM and Crocus. These models were coupled to an electrical model of unsaturated flow in snow to create synthetic electrical self potential observations. These synthetic observations were compared to measurements made during two winter field seasons at Col de Porte in the French Alps with a prototype geophysical array installed in October 2018. Different representations of liquid water flow were used to force the electrical model to evaluate its ability to reproduce the measured self potential signals, and to investigate the suitability of the self potential array as part of a coupled geophysical monitoring and modelling system.