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.