Periglacial Lake Origin Influences the Likelihood of Lake Drainage in Northern Alaska

Tracking lake drainage events and drained lake basin vegetation dynamics across the Arctic

Widespread lake drainage can lead to large-scale drying in Arctic lake-rich areas, affecting hydrology, ecosystems and permafrost carbon dynamics. To date, the spatio-temporal distribution, driving factors, and post-drainage dynamics of lake drainage events across the Arctic remain unclear. Using satellite remote sensing and surface water products, we identify over 35,000 (~0.6% of all lakes) lake drainage events in the northern permafrost zone between 1984 and 2020, with approximately half being relatively understudied non-thermokarst lakes. Smaller, thermokarst, and discontinuous permafrost area lakes are more susceptible to drainage compared to their larger, non-thermokarst, and continuous permafrost area counterparts. Over time, discontinuous permafrost areas contribute more drained lakes annually than continuous permafrost areas. Following drainage, vegetation rapidly colonizes drained lake basins, with thermokarst drained lake basins showing significantly higher vegetation growth rates and greenness levels than their non-thermokarst counterparts. Under warming, drained lake basins are likely to become more prevalent and serve as greening hotspots, playing an important role in shaping Arctic ecosystems.

Detection of thermokarst lake drainage events in the northern Alaska permafrost region

The rapidly warming Arctic climate is reducing the stability of near-surface permafrost, and the thawing of ice-rich permafrost causes landscape changes known as thermokarst processes. Growing evidence suggests an increasing trend in the frequency and magnitude of thermokarst lake drainage events, which would significantly alter topography and hydrology, affecting ecosystem stability and carbon cycling. Dynamic monitoring of thermokarst lakes through satellite imagery remains a challenging task, as current temporal trend analysis methods have difficulty in accurately detecting when thermokarst lake drainage events occur. In this study, to improve the detection of time series breakpoints, an advanced temporal segmentation and change detection algorithm developed for forest change detection was, for the first time, transposed to monitor thermokarst lake dynamics. Moreover, to filter out spurious signals caused by fluctuations in lake area, we developed a hybrid algorithm to validate the detected thermokarst lake drainage events at the pixel-level and lake object-level, respectively. The method developed in this study demonstrates its effectiveness in detecting thermokarst lake drainage events in Arctic permafrost ecosystems and the potential to monitor the evolution of thermokarst landscapes using Landsat archive. A time-series analysis of changes in the thermokarst lake region of northern Alaska since 2000 using all available Landsat continuous data was performed on the Google Earth Engine platform. In total, 90 drainage lakes larger than 5 ha in size were detected in our study area, nearly a third of which were almost completely drained. As thermokarst lakes drainage represent hotspots of permafrost degradation, we publicly share information on these drained lakes to help select more targeted sites for costly fieldwork and validation activities. This study provides a basis for understanding and quantifying thermokarst lake dynamics in the Arctic permafrost region, which will contribute to the goal of integrating thermokarst processes into earth system models.

Remote Sensing-Based Statistical Approach for Defining Drained Lake Basins in a Continuous Permafrost Region, North Slope of Alaska

Lake formation and drainage are pervasive phenomena in permafrost regions. Drained lake basins (DLBs) are often the most common landforms in lowland permafrost regions in the Arctic (50% to 75% of the landscape). However, detailed assessments of DLB distribution and abundance are limited. In this study, we present a novel and scalable remote sensing-based approach to identifying DLBs in lowland permafrost regions, using the North Slope of Alaska as a case study. We validated this first North Slope-wide DLB data product against several previously published sub-regional scale datasets and manually classified points. The study area covered >71,000 km2, including a >39,000 km2 area not previously covered in existing DLB datasets. Our approach used Landsat-8 multispectral imagery and ArcticDEM data to derive a pixel-by-pixel statistical assessment of likelihood of DLB occurrence in sub-regions with different permafrost and periglacial landscape conditions, as well as to quantify aerial coverage of DLBs on the North Slope of Alaska. The results were consistent with previously published regional DLB datasets (up to 87% agreement) and showed high agreement with manually classified random points (64.4–95.5% for DLB and 83.2–95.4% for non-DLB areas). Validation of the remote sensing-based statistical approach on the North Slope of Alaska indicated that it may be possible to extend this methodology to conduct a comprehensive assessment of DLBs in pan-Arctic lowland permafrost regions. Better resolution of the spatial distribution of DLBs in lowland permafrost regions is important for quantitative studies on landscape diversity, wildlife habitat, permafrost, hydrology, geotechnical conditions, and high-latitude carbon cycling.