Abstract
Abstract. The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of
northern Alaska is underlain by an ancient sand dune field, a geological
feature that affects regional lake characteristics. Many of these lakes,
which cover approximately 20 % of the Pleistocene sand sea, are relatively
deep (up to 25 m). In addition to the natural importance of ACP sand sea
lakes for water storage, energy balance, and ecological habitat, the need
for winter water for industrial development and exploration activities makes
lakes in this region a valuable resource. However, ACP sand sea lakes have
received little prior study. Here, we collect in situ bathymetric data to
test 12 model variants for predicting sand sea lake depth based on analysis
of Landsat-8 Operational Land Imager (OLI) images. Lake depth gradients were
measured at 17 lakes in midsummer 2017 using a Humminbird 798ci HD SI Combo
automatic sonar system. The field-measured data points were compared to
red–green–blue (RGB) bands of a Landsat-8 OLI image acquired on 8 August
2016 to select and calibrate the most accurate spectral-depth model for each
study lake and map bathymetry. Exponential functions using a simple band
ratio (with bands selected based on lake turbidity and bed substrate)
yielded the most successful model variants. For each lake, the most accurate
model explained 81.8 % of the variation in depth, on average. Modeled lake
bathymetries were integrated with remotely sensed lake surface area to
quantify lake water storage volumes, which ranged from 1.056×10-3 to 57.416×10-3 km3. Due to variations in depth
maxima, substrate, and turbidity between lakes, a regional model is
currently infeasible, rendering necessary the acquisition of additional in
situ data with which to develop a regional model solution. Estimating lake
water volumes using remote sensing will facilitate better management of
expanding development activities and serve as a baseline by which to
evaluate future responses to ongoing and rapid climate change in the Arctic.
All sonar depth data and modeled lake bathymetry rasters can be freely
accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) and
https://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.
Funder
National Science Foundation
Subject
General Earth and Planetary Sciences
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