Arctic lakes located in permafrost regions are susceptible to catastrophic drainage. In this study, we reconstructed historical lake drainage events on the western Arctic Coastal Plain of Alaska between 1955 and 2017 using USGS topographic maps, historical aerial photography (1955), and Landsat Imagery (ca. 1975, ca. 2000, and annually since 2000). We identified 98 lakes larger than 10 ha that partially (>25% of area) or completely drained during the 62‐year period. Decadal‐scale lake drainage rates progressively declined from 2.0 lakes/yr (1955–1975), to 1.6 lakes/yr (1975–2000), and to 1.2 lakes/yr (2000–2017) in the ~30,000‐km2study area. Detailed Landsat trend analysis between 2000 and 2017 identified two years, 2004 and 2006, with a cluster (five or more) of lake drainages probably associated with bank overtopping or headward erosion. To identify future potential lake drainages, we combined the historical lake drainage observations with a geospatial dataset describing lake elevation, hydrologic connectivity, and adjacent lake margin topographic gradients developed with a 5‐m‐resolution digital surface model. We identified ~1900 lakes likely to be prone to drainage in the future. Of the 20 lakes that drained in the most recent study period, 85% were identified in this future lake drainage potential dataset. Our assessment of historical lake drainage magnitude, mechanisms and pathways, and identification of potential future lake drainages provides insights into how arctic lowland landscapes may change and evolve in the coming decades to centuries.
Historic Lake Drainage on the Western Arctic Coastal Plain in Northern Alaska from Remote Sensing Datasets, 1955-2017
We identified all lakes larger than 10 hectares (ha) that drained completely or partially (greater than 25 %) between 1955 and 2017 using historical (original) USGS topographic maps and aerial photography (1955) and Landsat Imagery (circa 1975, circa 2000, and annually since 2000). For each lake drainage event, we inferred the drainage mechanism and categorized the drainage pathway based on known lake drainage mechanisms using interpretation of high-resolution remote sensing data and field observations.
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- Award ID(s):
- 1806213
- NSF-PAR ID:
- 10303025
- Publisher / Repository:
- Arctic Data Center
- Date Published:
- Subject(s) / Keyword(s):
- ["Arctic Lake","Lake Drainage","Drained Lake Basin","Thermokarst Lake"]
- Format(s):
- Medium: X Other: text/xml
- Sponsoring Org:
- National Science Foundation
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Abstract -
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.more » « less
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Abstract Lakes set in arctic permafrost landscapes can be susceptible to rapid drainage and downstream flood generation. Of many thousands of lakes in northern Alaska, hundreds have been identified as having high drainage potential directly to river systems and 18 such drainage events have been documented since 1955. In 2018 we began monitoring a large lake with high drainage potential as part of a long‐term hydrological observation network designed to evaluate impacts of land use and climate change. In early June 2022, surface water was observed flowing over a 30‐m wide bluff, with active headward erosion of ice‐rich permafrost soils apparent by late June. This overflow point breached rapidly in early July, draining almost the entire lake within 12 h and generating a 191 m3/s flood to a downstream creek. Water level and turbidity sensors and time‐lapse cameras captured this rapid lake‐drainage event at high resolution. A wind‐driven surface seiche and warming waters following ice‐out helped trigger the initial thermomechanical breach. We estimate at least 600 MT of lake sediment was eroded, mobilized, and transported downstream. A flood wave peaking at 42 m3/s arrived 14 h after the initial breach at a river gauge 9‐km downstream. Comparing this event with three other quantified arctic lake‐drainage floods suggests that lake surface area coupled with drainage gradient height can predict outburst flood magnitude. Using this relationship we estimated future flood hazards from the 146 lakes in the Arctic Coastal Plain of northern Alaska (ACP) with high drainage potential, of which 20% are expected to generate outburst floods exceeding 100 m3/s to downstream rivers. This fortunate and detailed drainage‐event observation adds to a growing body of research on the impact of lakes on arctic hydrology, hazard forecasting in a region with an increasing human footprint, and broader processes of landscape evolution in arctic lowlands.
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