Journal of Glaciology (Aug 2023)

Using thermal UAV imagery to model distributed debris thicknesses and sub-debris melt rates on debris-covered glaciers

  • Rosie R. Bisset,
  • Peter W. Nienow,
  • Daniel N. Goldberg,
  • Oliver Wigmore,
  • Raúl A. Loayza-Muro,
  • Jemma L. Wadham,
  • Moya L. Macdonald,
  • Robert G. Bingham

DOI
https://doi.org/10.1017/jog.2022.116
Journal volume & issue
Vol. 69
pp. 981 – 996

Abstract

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Supraglacial debris cover regulates the melt rates of many glaciers in mountainous regions around the world, thereby modifying the availability and quality of downstream water resources. However, the influence of supraglacial debris is often poorly represented within glaciological models, due to the absence of a technique to provide high-precision, spatially continuous measurements of debris thickness. Here, we use high-resolution UAV-derived thermal imagery, in conjunction with local meteorological data, visible UAV imagery and vertically profiled debris temperature time series, to model the spatially distributed debris thickness across a portion of Llaca Glacier in the Cordillera Blanca of Peru. Based on our results, we simulate daily sub-debris melt rates over a 3-month period during 2019. We demonstrate that, by effectively calibrating the radiometric thermal imagery and accounting for temporal and spatial variations in meteorological variables during UAV surveys, thermal UAV data can be used to more precisely represent the highly heterogeneous patterns of debris thickness and sub-debris melt on debris-covered glaciers. Additionally, our results indicate a mean sub-debris melt rate nearly three times greater than the mean melt rate simulated from satellite-derived debris thicknesses, emphasising the importance of acquiring further high-precision debris thickness data for the purposes of investigating glacier-scale melt processes, calibrating regional melt models and improving the accuracy of runoff predictions.

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