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Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen

  • W. GAJEK (a1), J. TROJANOWSKI (a1) and M. MALINOWSKI (a1)
Abstract
ABSTRACT

Retreating glaciers are a consequence of a warming climate. Thus, numerous monitoring campaigns are being carried out to increase understanding of this on-going process. One phenomenon related to dynamic glacial changes is glacier-induced seismicity; however, weak seismic events are difficult to record due to the sparse seismological network in arctic areas. We have developed an automatic procedure capable of detecting glacier-induced seismic events using records from a single permanent seismological station. To distinguish between glacial and non-glacial signals, we developed a fuzzy logic algorithm based on the signal frequency and energy flow analysis. We studied the long-term changes in glacier-induced seismicity in Hornsund (southern Spitsbergen) and in Kongsfjorden (western Spitsbergen). We found that the number of detected glacial-origin events in the Hornsund dataset over the years 2013-14 has doubled. In the Kongsfjorden dataset, we observed a steady increase in the number of glacier-induced events with each year. We also observed that the seasonal event distribution correlates best with 1 month lagged temperatures, and that extreme rain events can intensify seismic emissions. Our study demonstrates the possibility of using long-term seismological observations from a single permanent station to automatically monitor the dynamic activity of nearby glaciers and retrieve its characteristic features.

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      Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen
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      Automating long-term glacier dynamics monitoring using single-station seismological observations and fuzzy logic classification: a case study from Spitsbergen
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Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Corresponding author
Correspondence: Wojciech Gajek <wgajek@igf.edu.pl>
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