Frontiers in Earth Science (Sep 2023)

Bathymetries of proglacial lakes: a new data set from the northern Tien Shan, Kazakhstan

  • Vassiliy Kapitsa,
  • Maria Shahgedanova,
  • Nikolay Kasatkin,
  • Igor Severskiy,
  • Murat Kasenov,
  • Alexandr Yegorov,
  • Mariya Tatkova,
  • Mariya Tatkova

DOI
https://doi.org/10.3389/feart.2023.1192719
Journal volume & issue
Vol. 11

Abstract

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Between 2009 and 2020, 74 bathymetric surveys of 57 glacial lakes were conducted in the northern Tien Shan using the ecosounding technique. The surveys provided data on lake depths and other parameters characterising the three-dimensional lake geometry, and bathymetrically derived lake volumes. The sample included 21 glacier-connected lakes, 27 lakes formed on the young moraines without glacier-connected with glacier tongue, eight lakes formed on the older moraines and one rock-dammed lake. The lakes’ volumes ranged between 0.029x105 and 53.89x105 m3 with the largest value of mean depth was 23 m. There is a statistically significant correlation between lake depth and width, length and area, best approximated by the power, linear, and polynomial models, with coefficients of determination ranging between 0.50 and 0.78 for the glacier-connected lakes. The power equations underestimated both depths and volumes of larger lakes but the second-order polynomial model provided a closer approximation in the study region. The obtained data were combined with the bathymetrically derived depth and volume data published in the literature extending the global data set of bathymetries of lakes with natural dams. The area-depth scaling equations derived from the combined data set showed a considerable improvement in correlation between area and depth in comparison with the earlier studies. The measured bathymetries of the glacier-connected lakes were compared with bathymetries of the same lakes simulated using GlabTOP2 model and published simulated ice thickness data. There is generally a good agreement between the measured and simulated bathymetries although GlabTOP2 tends to overestimate lake depths. The data from the bathymetric surveys and GlabTOP2 model are used by the practitioners to reduce and avoid risks associated with glacier lake outburst floods and are important instruments of the regional strategy of adaptation to climate change.

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