Supporting data for: Rapid ice-marginal lake growth in Alaska driven by glacier retreat through bed overdeepenings

Published Jan 09, 2026 on Dryad. https://doi.org/10.5061/dryad.rjdfn2zrc

Abstract

In this study, we mapped ice-marginal glacial lakes in Alaska in 2018 and 2024 using Sentinel-2 optical imagery. We mapped glacier-bed overdeepenings using existing datasets and evaluated how much lake growth has occurred within these mapped overdeepenings as well as how much additional growth is possible. Here we provide seven supporting data products: i) a raster of mapped glacier-bed overdeepenings using best estimate of ice thickness, ii) a raster of glacier-bed overdeepenings using ice thickness plus uncertainty, iii) a raster of glacier-bed overdeepenings using ice thickness minus uncertainty, iv) a 2018 ice-marginal lake shapefile, v) a 2024 ice-marginal lake shapefile, vi) a 2024 ice-marginal lake shapefile joined to glacier-bed overdeepening area, and vii) RGI 6 glacier inventory joined to glacier-bed overdeepening area.

Dataset DOI: 10.5061/dryad.rjdfn2zrc

Description of the data and file structure

There are two glacial lake outline shapefiles : Lake_Outlines_2018_102225 and Lake_Outlines_2024_102225. The shapefiles consist of a .shp file (feature geometry), along with supporting files (.shx - positional index of the feature geometry, .dbf - columnar attributes for each shape, .prj - project description, .cpg - used to specify the code page). Both are projected in EPSG:3338.

Column Headers in these files include:

Lake_Outlines_2018_102225

Latitude: Latitude in decimal degrees in WGS84 format

Longitude: Longitude in decimal degrees in WGS84 format

Area_2018: Lake Area in km² from Rick et al., 2022

Area_2018r: Revised Lake Area in km² using 2018 Sentinel-2 imagery

Dam_Type: Material damming lake; see Rick et al., 2022 for additional details

Connection: Lake connection to glacier; see Rick et al., 2022 for additional details

Perimeter: Lake perimeter in km²

Name: Glacier name from Randolph Glacier Inventory

RGI6Id: ID from Randolph Glacier Inventory 6.0

OutlineYr: Year of imagery used to generate lake outline

Comments: Comments about lake status

Incl_Analysis: Lakes marked 1 were included in analysis, lakes marked with 0 were not included in analysis for reasons stated in Comments column

Lake_Outlines_2024_102225

Additional columns in this outline:

Upd_Conn: Updated lake connection if different in 2024

RmvLakArea: Lake area [m^2^] for existing mapped lakes within outlines that need to be removed when calculating total area change

Area_2024: Lake area in 2024 in km²

AreaChg: Lake area change between 2018 and 2024 in km². This column does not account for the RmvLakArea values.

Three raster (GeoTiff) files with the mapped glacier-bed overdeepenings were generated: i) using best estimate of ice thickness: COP30_minus_IceT_rseries_COP30_orig_minus_filled_clipped.tif, ii) using best estimate of ice thickness minus ice thickness uncertainty: COP30_minus_IceT_minus_err_rseries_min_042125_orig_minus_filled_clipped.tif and iii) using best estimate of ice thickness plus ice thickness uncertainty: COP30_minus_IceT_plus_err_rseries_min_042125_orig_minus_filled_clipped.tif

These raster products are projected in EPSG:3338 with approximate pixel sizes of 50.05 m.

Two additional shapefiles were generated:

Lake_Outlines_2024_joined_to_overdeepening_102225.shp (and associated files). This shapefile is similiar in structure/column headers to Lake_Outlines_2024_102225 but has the addition of Over Area that is the area [km^2^] of mapped overdeepening attached to the lake. Multiple lakes can access the same overdeepening in this file (e.g., those lakes on Seward and Agassiz glaciers). Lakes that are not connected to an overdeepening or where that overdeepening was less than 0.1 km² in area are not included in this file.

RGI6_zonalstats_merged_overdeepening_102225.shp (and associated files). This shapefile includes the same columns as the RGI 6 dataset (https://www.glims.org/RGI/randolph60.html) with the addition of five columns that summarize the mapped glacier-bed overdeepening within each glacier outline.

PxCnt - the number of mapped glacier-bed overdeepening pixels within each glacier

PxSum - sum of overdeepened pixel magnitudes (this is not volume and requires multiplying by pixel x and y)

PxMean - mean of overdeepened pixel magnitudes [units of meters]

GlOverArea - cumulative area of overdeepened ice by glacier [units of km^2^]

GlOverVol - cumulative volume of overdeepened ice by glacier [units of km^3^]

Access information

Other publicly accessible locations of the data:

Data was derived from the following sources:

Rick, B., McGrath, D., Armstrong, W., and McCoy, S. W. 2022. Dam type and lake location characterize ice-marginal lake area change in Alaska and NW Canada between 1984 and 2019, The Cryosphere, 16, 297–314, https://doi.org/10.5194/tc-16-297-2022.
RGI Consortium, 2017. Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 6. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/4m1f-gd79
Millan, R., Mouginot, J., Rabatel, A. et al. 2022. Ice velocity and thickness of the world’s glaciers. Nat. Geosci. 15, 124–129. https://doi.org/10.1038/s41561-021-00885-z
European Space Agency, Copernicus Global Digital Elevation Model. Distributed by OpenTopography (2024). https://doi.org/10.5069/G9028PQB.

Using an existing glacial lake inventory (Rick et al., 2022), we identified glacial lakes in Alaska greater than 0.5 km² (n=211) for the period 2016 to 2019 (median year 2018). Using Sentinel-2 optical imagery from 1 May to 30 September 2018 and 2024, we manually mapped lake extents at 1:10,000 scale for these two years in the open-source QGIS software program. We estimate error in lake area by multiplying the lake perimeter (in km) by half the Sentinel-2 pixel resolution (5 m or 0.005 km). We also reviewed and updated the lake connection category, which describes the lake's spatial relationship to its source glacier. These categories include: proglacial (lakes at terminus of glacier, in contact with the ice), supraglacial (lakes on surface of glacier ice), ice (ice-dammed lakes found at ice margins or tributary valleys), detached (lakes fed by glaciers but not in contact with the ice), or unconnected (detached lakes that are not fed by glaciers). This study solely assesses ice-marginal lakes (n=147 lakes), defined as having contact with a glacier and thus excludes detached and unconnected lakes.

To map glacier-bed overdeepenings in the region, we combined the Copernicus GLO-30 Digital Elevation Model (DEM) and previously modelled ice thickness estimates derived from observed ice velocities and the shallow-ice approximation (Millan et al., 2022). Imagery for GLO-30 was acquired between 2010 and 2015, while ice velocities used in Millan et al. (2022) are from 2017–18. The GLO-30 DEM was mosaicked, regridded to 50 m, and reprojected to NAD83/Alaska Albers (EPSG: 3338). The modeled ice thicknesses were mosaicked and reprojected and then subtracted from the surface DEM to generate a bed DEM. We created a filled bed surface using the “fillsinks” function in TopoToolbox in Matlab. In QGIS, we subtracted the filled bed DEM from the original bed DEM to map glacier-bed overdeepening spatial extents and magnitudes. To account for uncertainty in ice thickness estimates, we repeated the above workflow with revised ice thickness rasters that accounted for stated uncertainties.

Supporting data for: Rapid ice-marginal lake growth in Alaska driven by glacier retreat through bed overdeepenings

Data files

Abstract

README: Supporting data for: Rapid ice-marginal lake growth in Alaska driven by glacier retreat through bed overdeepenings

Description of the data and file structure

Access information

Methods