Theory and numerical modeling of electrical self-potential signatures of unsaturated flow in melting snow - Bernd Kulessa (Water Resources Research, 2012)
We have developed a new theory and numerical model of electrical self-potential (SP) signals associated with unsaturated flow in melting snow. The model is applicable to continuous natural-melt and transient-flow phenomena such as melt-water pulses, and is tested using laboratory column experiments. SP signals fundamentally depend on the temporal evolution of snow porosity and melt-water flux, electrical conductivity (EC) and pH. We infer a reversal of the sign of the zeta potential (a fundamental electrical property of grain surfaces in porous media), consistent with well-known elution sequences of ions that cause progressive increases and decreases in melt-water pH and EC respectively. Injection of fully-melted snow samples, containing the entire natural range of ions, into melting snow columns caused additional temporary reversals of the sign of the zeta potential. Widely-used empirical relationships between effective saturation, melt-water fraction, EC and pH, as well as snow porosity, grain size and permeability are found to be robust for modelling purposes. Thus, non-intrusive SP measurements can serve as proxies for snow melt-water fluxes and the temporal evolution of fundamental snow textural, hydraulic or water-quality parameters. Adaptation of automated multi-sensor SP acquisition technology from other environmental applications thus promises to bridge the widely acknowledged gap in spatial scale between satellite remote sensing and point measurements of snow properties. SP measurements and modelling may therefore contribute to solving a wide range of problems related to the assessment of water resource availability, avalanche or flood risk, or amplification of climatic forcing of ice-shelf, ice-sheet or glacier dynamics.