Surface nuclear magnetic resonance (SNMR) is a geophysical technique that is directly sensitive to liquid water. In this study, we evaluate the feasibility of SNMR for detecting and characterizing an englacial channel within Rhonegletscher, Switzerland. Building on prior information on Rhonegletscher’s englacial hydrology, we conducted a proof-of-concept SNMR survey in the summer of 2023. Despite the high levels of electromagnetic noise, careful optimization of SNMR data processing including remote reference noise cancellation, allowed us to successfully detect interpretable signals and to estimate parameters for a simplified one-dimensional water model. Our analysis, which is based on the comparison of the error-weighted root-mean-square misfit χRMS of different models, suggests the existence of an aquifer near the bedrock, embedded within a temperate-ice column. Assuming a minimum aquifer water content of 60 %, models with χRMS≤1.9 point to a thin layer (≤ 1 m) located at a depth of 44 to 60 m, surrounded by temperate ice with a liquid water content between 0.3 % and 0.75 %. Our findings are consistent with ground-penetrating radar measurements, thereby corroborating the potential for using SNMR in englacial studies. Although limited by noise and model simplifications, our analyses show promise for quantifying liquid water volume located within or beneath glaciers.
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Gabriel et al. (2025) studied this question.
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