The spatio-temporal variability of frost blisters in a perennial frozen lake along the antarctic coast as indicator of the groundwater supply

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Abstract

Remote sensing, and unmanned aerial vehicles (UAVs) in particular, can be a valid tool for assessing the dynamics of cryotic features as frost blisters and to monitor the surface changes and the sublimation rates on perennially frozen lakes that host important ecosystems. In this paper, through the use of these remote sensing techniques, we aim to understand the type of groundwater supply of an Antarctic perennial frozen lake that encompasses two frost blisters (M1 and M2) through the temporal analysis of the features’ elevation changes (frost blisters and lake ice level). The frozen lake is located at Boulder Clay (northern Victoria Land, Antarctica). We relied on several photogrammetric models, past satellite images and ground pictures to conduct differencing of digital elevation models, areal variations and pixel counting. In addition, in situ measurements of the ice sublimation or snow accumulation were carried out. The two frost blisters showed different elevation trends with M1 higher in the past (1996–2004) than recently (2014–2019), while M2 showed an opposite trend, similarly to the ice level. Indeed, the linear regression between M2 elevation changes and the ice level variation was statistically significant, as well as with the annual thawing degree days, while M1 did not show significant results. From these results we can infer that the groundwater supply of M1 can be related to a sublake open talik (hydraulic system) as confirmed also by pressurized brines found below M1, during a drilling in summer 2019. For M2 the groundwater flow is still not completely clear although the hydrostatic system seems the easiest explanation as well as for the uplift of the lake ice.

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Ponti, S., Scipinotti, R., Pierattini, S., & Guglielmin, M. (2021). The spatio-temporal variability of frost blisters in a perennial frozen lake along the antarctic coast as indicator of the groundwater supply. Remote Sensing, 13(3). https://doi.org/10.3390/rs13030435

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