Potential Future Lake Drainage from an IfSAR-Derived Digital Surface Model, 2002-2003, Western Arctic Coastal Plain, Northern Alaska (US)

Jones, Benjamin M.; Arp, Christopher D.; Grosse, Guido; Nitze, Ingmar; Lara, Mark; Whitman, Matthew; Farquharson, Louise; Kanevskiy, Mikhail; Parsekian, Andrew; Breen, Amy; Ohara, Nori; Rangel, Rodrigo; Hinkel, Kenneth

Assessment of lakes for their future potential to drain relied on the 2002/03 airborne Interferometric Synthetic Aperture Radar (IFSAR) Digital Surface Model (DSM) data for the western Arctic Coastal Plain in northern Alaska. Lakes were extracted from the IfSAR DSM using a slope derivative and manual correction (Jones et al., 2017). The vertical uncertainty for correctly detecting lake-based drainage gradients with the IfSAR DSM was defined by comparing surface elevation differences of several overlapping DSM tile edges. This comparison showed standard deviations of elevation between overlapping IfSAR tiles ranging from 0.0 to 0.6 meters (m). Thus, we chose a minimum height difference of 0.6 m to represent a detectable elevation gradient adjacent to a lake as being most likely to contribute to a rapid drainage event. This value is also in agreement with field verified estimates of the relative vertical accuracy (~0.5 m) of the DSM dataset around Utqiaġvik (formerly Barrow) (Manley et al., 2005) and the stated vertical RMSE (~1.0 m) of the DSM data (Intermap, 2010). Development of the potential lake drainage dataset involved several processing steps. First, lakes were classified as potential future drainage candidates if the difference between the elevation of the lake surface and the lowest elevation within a 100 m buffer of the lake shoreline exceeded our chosen threshold of 0.6 m. Next, we selected lakes with a minimum size of 10 ha to match the historic lake drainage dataset. We further filtered the dataset by selecting lakes estimated to have low hydrological connectivity based on relations between lake contributing area as determined for specific surficial geology types and presented in Jones et al. (2017). This was added to the future projection workflow to isolate the lake population that likely responds to changes in surface area driven largely by geomorphic change as opposed to differences in surface hydrology. Lakes within a basin with low to no hydrologic connectivity that had an elevation change gradient between the lake surface and surrounding landscape are considered likely locations to assess for future drainage potential. Further, the greater the elevation difference, the greater the drainage potential. This dataset provided a first-order estimate of lakes classified as being prone to future drainage. We further refined our assessment of potential drainage lakes by identifying the location of the point with the lowest elevation within the 100 m buffer of the lake shoreline and manually interpreted lakes to have a high drainage potential based on the location of the likely drainage point to known lake drainage pathways using circa 2002 orthophotography or more recent high resolution satellite imagery available for the Western Coastal Arctic Plain (WACP). Lakes classified as having a high drainage potential typically had the likely drainage location associated with one or more of the following: (1) an adjacent lake, (2) the cutbank of a river, (3) the ocean, (4) were located in an area with dense ice-wedge networks, (5) appeared to coincide with a potentially headward eroding stream, or (6) were associated with thermokarst lake shoreline processes in the moderate to high ground ice content terrain. We also added information on potential lake drainage pathways to the high potential drainage dataset by manually interpreting the landform associated with the likely drainage site to draw comparisons with the historic lake drainage dataset.

Detailed information about the methods can be found in the data publication and the publication to which this dataset is a supplement.

Citation

In order to use these data, you must cite this data set with the following citation:

Benjamin Jones, Christopher Arp, Guido Grosse, Ingmar Nitze, Mark Lara, et al. 2019. Potential Future Lake Drainage for the Western Arctic Coastal Plain in northern Alaska from an Interferometric Synthetic Aperture Radar (IFSAR)-Derived Digital Surface Model, 2002-2003. Arctic Data Center. doi:10.18739/A2JH3D29N.

Contact

Jones, Benjamin M.

Metadata Access

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Data and Resources

Additional Info

Field Value
Identifier DOI:10.18739/A2JH3D29N
First Author ORCID
Project(s)
Institute Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, AK, USA
Source https://doi.org/10.18739/A2JH3D29N
Publication Date 2019
Version 1.0
Product group
Product Lake Drainage
Sensor IfSAR
Files
  • polygon feature shapefile of potential lake drainage
  • XML metadata file
Variables [Units]
  • Area_sq_km: Lake area [km²]
  • Lake_hgt_m: Lake elevation [m]
  • X100m_hgt_m: Lowest elevation within 100 meter buffer of lake [m]
  • X100m_diff: Difference between lake elevation and lowest elevation within 100 meter buffer [m]
  • High_Poten: Classification of potential future drainage candidates [0 (=low potential); 1 (=high potential)]
  • Drain_loca: Drainage location [text]
Region Northern Alaska
Spatial Reference EPSG:26905 NAD83 / UTM zone 5N
Spatial Resolution
Spatial Coverage Latitude 69.51 to 71.50, Longitude -158.76 to -150.95
Temporal Coverage
Temporal Resolution
Format Shapefile
Is Supplement to Jones, BM, Arp, CD, Grosse, G, et al. Identifying historical and future potential lake drainage events on the western Arctic coastal plain of Alaska. Permafrost and Periglac Process. 2020; 31: 110– 127. https://doi.org/10.1002/ppp.2038
Related to Benjamin Jones, Christopher Arp, Guido Grosse, Ingmar Nitze, Mark Lara, et al. 2019. Historic Lake Drainage on the Western Arctic Coastal Plain in Northern Alaska from Remote Sensing Datasets, 1955-2017. Arctic Data Center. doi:10.18739/A2DR2P85H.

Dataset extent

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