Towards the development of an automated electrical self-potential sensor of melt and rainwater flow in snow

Abstract To understand snow structure and snowmelt timing, information about flows of liquid water within the snowpack is essential. Models can make predictions using explicit representations physical processes, or through parameterization, but it difficult to verify simulations. In situ observations generally measure bulk quantities. Where internal measurements are made, they tend be destructive unsuitable for continuous monitoring. Here, we present a novel method in monitoring flow seasonal electrical self-potential (SP) geophysical method. A prototype array was installed at Col de Porte (France) October 2018. Snow hydrological meteorological were also collected. Results two periods interest during winter 2018–19 (a marked period diurnal melting refreezing, rain-on-snow event) show that SP sensitive flow. Water detected by signals before measured conventional lysimeters base snowpack. This initial feasibility study shows utility as non-destructive sensor. Future development should include combining with high-resolution physics model improve prediction melt timing.