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Glacies, Volume 2, Issue 3 (September 2025) – 1 article

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13 pages, 4704 KiB  
Article
Freshwater Thin Ice Sheet Monitoring and Imaging with Fiber Optic Distributed Acoustic Sensing
by Meghan Quinn, Adrian K. Doran, Constantine Coclin, Levi Cass and Heath Turner
Glacies 2025, 2(3), 7; https://doi.org/10.3390/glacies2030007 - 21 Jun 2025
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Abstract
Fiber optic distributed acoustic sensing (DAS) technology can monitor vibrational strain of vast areas with fine spatial resolution at high sampling rates. The fiber optic cable portion of DAS may directly monitor, measure, and map potentially unsafe areas such as thin ice sheets. [...] Read more.
Fiber optic distributed acoustic sensing (DAS) technology can monitor vibrational strain of vast areas with fine spatial resolution at high sampling rates. The fiber optic cable portion of DAS may directly monitor, measure, and map potentially unsafe areas such as thin ice sheets. Once the fiber optic cable is emplaced, DAS can provide “rapid-response” information along the cable’s length through remote sampling. A field campaign was performed to test the sensitivity of DAS to spatial variations within thin ice sheets. A pilot field study was conducted in the northeastern United States in which fiber-optic cable was deployed on the surface of a freshwater pond. Phase velocity transformations were used to analyze the DAS response to strike testing on the thin ice sheet. The study results indicated that the ice sheet was about 5 cm thick generally, tapering to about 3.5 cm within 2 m of the pond’s edge and then disappearing at the margins. After validation of the pilot study’s methodology, a follow-up experiment using DAS to collect on a rapidly deployed, surface-laid cable atop a larger freshwater pond was conducted. Using phase velocity transformations, the ice thickness along the fiber optic cable was estimated to be between 25.5 and 28 cm and confirmed via ice auger measurements along the fiber optic cable. This field campaign demonstrates the feasibility of employing DAS systems to remotely assess spatially variable properties on thin freshwater ice sheets. Full article
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