Mapping the bathymetry of supraglacial lakes and streams on the Greenland Ice Sheet using field measurements and high resolution satellite images

• Main Authors: Legleiter, C. J., Tedesco, Marco, Smith, L. C., Behar, A. E., Overstreet, B. T.
• Format: Text
• Language: unknown
• Published: Columbia University 2014
• Subjects: Ice sheets > Remote sensing; Meltwater; Climatic geomorphology; Geomorphology; Ice sheets; Geology; FOS Earth and related environmental sciences; Climatic changes; Greenland; Ice Sheet
• Online Access: https://dx.doi.org/10.7916/d87w6c3b; https://academiccommons.columbia.edu/doi/10.7916/D87W6C3B

Recent melt events on the Greenland ice sheet (GrIS) accentuate the need to constrain estimates of sea level rise through improved characterization of meltwater pathways. This effort will require more precise estimates of the volume of water stored on the surface of the GrIS. We assessed the potential to obtain such information by mapping the bathymetry of supraglacial lakes and streams from WorldView2 (WV2) satellite images. Simultaneous in situ observations of depth and reflectance from two streams and a lake with measured depths up to 10.45 m were used to test a spectrally based depth retrieval algorithm. We performed optimal band ratio analysis (OBRA) of continuous field spectra and spectra convolved to the bands of the WV2, Landsat 7 (ETM+), MODIS, and ASTER sensors. The field spectra yielded a strong relationship with depth (R² = 0.94), and OBRA R² values were nearly as high (0.87–0.92) for convolved spectra, suggesting that these sensors' broader bands would be sufficient for depth retrieval. Our field measurements thus indicated that remote sensing of supraglacial bathymetry is not only feasible but potentially highly accurate. OBRA of spectra from 2 m-pixel WV2 images acquired within 3–72 h of our field observations produced an optimal R² value of 0.92 and unbiased, precise depth estimates, with mean and root mean square errors < 1% and 10–25% of the mean depth. Bathymetric maps produced by applying OBRA relations revealed subtle features of lake and channel morphology. In addition to providing refined storage volume estimates for lakes of various sizes, this approach can help provide estimates of the transient flux of meltwater through streams