Identifying historical and future potential lake drainage events on the western Arctic coastal plain of 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.

Ecosystem responses of shallow thermokarst lakes to climate-driven hydrological change: Insights from long-term monitoring of periphytic diatom community composition at Old Crow Flats (Yukon, Canada)

Shallow waterbodies are abundant in Arctic and subarctic landscapes where they provide productive wildlife habitat and hold cultural and socioeconomic importance for Indigenous communities. Their vulnerability to climate-driven hydrological and limnological changes enhances a need for long-term monitoring data capable of tracking aquatic ecosystem responses. Here, we evaluate biological and inferred physicochemical responses associated with a rise in rainfall-generated runoff and increasingly positive lake water balances in Old Crow Flats (OCF), a 5600 km2 thermokarst landscape in northern Yukon. This is achieved by analyzing periphytic diatom community composition in biofilms accrued on artificial-substrate samplers at 14 lakes collected mostly annually during 2008-2019 CE. Results reveal that diatom communities at 10 of the 14 lakes converged toward a composition typical of lakes with rainfall-dominated input waters. These include six of nine lakes that were not initially dominated by rainfall input. The shifts in diatom community composition infer rise of lake-water pH and ionic content, and they reveal that northern shallow lake ecosystems are responsive to climate-driven increases in rainfall. Based on data generated during the 12 -year-long monitoring period, we conclude that lakes located centrally within OCF are most vulnerable to rapid climate-driven hydroecological change due to flat terrain, larger lake surface area, and sparse terrestrial vegetation, which provide less resistance to lake expansion, shoreline erosion, and sudden drainage. This information assists the local Indigenous community and natural resource stewardship agencies to anticipate changes to traditional food sources and inform adaptation options.

New permafrost is forming on the exposed bottom of Zonag Lake on the Qinghai-Tibet Plateau

Most lakes on the Qinghai-Tibet Plateau have expanded in recent years. Zonag Lake, a critical habitat for Tibetan antelopes in the continuous permafrost zone, burst and overflowed after several years of expansion, resulting in a reduction of approximately 100 km² in the lake area. Observations have revealed new permafrost is forming on the exposed bottom, accompanied by various periglacial landscapes. The permafrost aggradation on the exposed bottom is rapid, and the permafrost base reached 4.9 m, 5.4 m, and 5.7 m in the first three years, respectively. In this study, the future changes and influencing factors of recently formed permafrost are simulated using a one-dimensional finite element model of heat flow. The simulated results indicate that the permafrost on the exposed bottom is likely to continue to develop, appearing first quick back slow trend. Besides the surface temperature, the annual amplitude is also an important factor in affecting the aggradation of permafrost. The unidirectional permafrost aggradation in the study area is different from the bidirectional permafrost aggradation on the closed taliks around the Arctic. Additionally, snow cover and vegetation are two important factors influencing the future development of permafrost on the exposed lake bottom.

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.

Vegetation grows more luxuriantly in Arctic permafrost drained lake basins

As Arctic warming, permafrost thawing, and thermokarst development intensify, increasing evidence suggests that the frequency and magnitude of thermokarst lake drainage events are increasing. Presently, we lack a quantitative understanding of vegetation dynamics in drained lake basins, which is necessary to assess the extent to which plant growth in thawing ecosystems will offset the carbon released from permafrost. In this study, continuous satellite observations were used to detect thermokarst lake drainage events in northern Alaska over the past 20 years, and an advanced temporal segmentation and change detection algorithm allowed us to determine the year of drainage for each lake. Quantitative analysis showed that the greenness (normalized difference vegetation index [NDVI]) of tundra vegetation growing on wet and nutrient-rich lake sediments increased approximately 10 times faster than that of the peripheral vegetation. It takes approximately 5 years (4-6 years for the 25%-75% range) for the drainage lake area to reach the greenness level of the peripheral vegetation. Eventually, the NDVI values of the drained lake basins were 0.15 (or 25%) higher than those of the surrounding areas. In addition, we found less lush vegetation in the floodplain drained lake basins, possibly due to water logging. We further explored the key environmental drivers affecting vegetation dynamics in and around the drained lake basins. The results showed that our multivariate regression model well simulated the growth dynamics of the drainage lake ecosystem ( Radj2=.73 , p < .001) and peripheral vegetation ( Radj2=.68 , p < .001). Among climate variables, moisture variables were more influential than temperature variables, indicating that vegetation growth in this area is susceptible to water stress. Our study provides valuable information for better modeling of vegetation dynamics in thermokarst lake areas and provides new insights into Arctic greening and carbon balance studies as thermokarst lake drainage intensifies.

Climate Signatures on Lake And Wetland Size Distributions in Arctic Deltas

Understanding how thermokarst lakes on arctic river deltas will respond to rapid warming is critical for projecting how carbon storage and fluxes will change in those vulnerable environments. Yet, this understanding is currently limited partly due to the complexity of disentangling significant interannual variability from the longer-term surface water signatures on the landscape, using the short summertime window of optical spaceborne observations. Here, we rigorously separate perennial lakes from ephemeral wetlands on 12 arctic deltas and report distinct size distributions and climate trends for the two waterbodies. Namely, we find a lognormal distribution for lakes and a power-law distribution for wetlands, consistent with a simple proportionate growth model and inundated topography, respectively. Furthermore, while no trend with temperature is found for wetlands, a statistically significant decreasing trend of mean lake size with warmer temperatures is found, attributed to colder deltas having deeper and thicker permafrost preserving larger lakes.

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.

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

Nearly 25% of all lakes on earth are located at high latitudes. These lakes are formed by a combination of thermokarst, glacial, and geological processes. Evidence suggests that the origin of periglacial lake formation may be an important factor controlling the likelihood of lakes to drain. However, geospatial data regarding the spatial distribution of these dominant Arctic and subarctic lakes are limited or do not exist. Here, we use lake-specific morphological properties using the Arctic Digital Elevation Model (DEM) and Landsat imagery to develop a Thermokarst lake Settlement Index (TSI), which was used in combination with available geospatial datasets of glacier history and yedoma permafrost extent to classify Arctic and subarctic lakes into Thermokarst (non-yedoma), Yedoma, Glacial, and Maar lakes, respectively. This lake origin dataset was used to evaluate the influence of lake origin on drainage between 1985 and 2019 in northern Alaska. The lake origin map and lake drainage datasets were synthesized using five-year seamless Landsat ETM+ and OLI image composites. Nearly 35,000 lakes and their properties were characterized from Landsat mosaics using an object-based image analysis. Results indicate that the pattern of lake drainage varied by lake origin, and the proportion of lakes that completely drained (i.e., >60% area loss) between 1985 and 2019 in Thermokarst (non-yedoma), Yedoma, Glacial, and Maar lakes were 12.1, 9.5, 8.7, and 0.0%, respectively. The lakes most vulnerable to draining were small thermokarst (non-yedoma) lakes (12.7%) and large yedoma lakes (12.5%), while the most resilient were large and medium-sized glacial lakes (4.9 and 4.1%) and Maar lakes (0.0%). This analysis provides a simple remote sensing approach to estimate the spatial distribution of dominant lake origins across variable physiography and surficial geology, useful for discriminating between vulnerable versus resilient Arctic and subarctic lakes that are likely to change in warmer and wetter climates.

Mosaicking Landsat and Sentinel-2 Data to Enhance LandTrendr Time Series Analysis in Northern High Latitude Permafrost Regions

Permafrost is warming in the northern high latitudes, inducing highly dynamic thaw-related permafrost disturbances across the terrestrial Arctic. Monitoring and tracking of permafrost disturbances is important as they impact surrounding landscapes, ecosystems and infrastructure. Remote sensing provides the means to detect, map, and quantify these changes homogeneously across large regions and time scales. Existing Landsat-based algorithms assess different types of disturbances with similar spatiotemporal requirements. However, Landsat-based analyses are restricted in northern high latitudes due to the long repeat interval and frequent clouds, in particular at Arctic coastal sites. We therefore propose to combine Landsat and Sentinel-2 data for enhanced data coverage and present a combined annual mosaic workflow, expanding currently available algorithms, such as LandTrendr, to achieve more reliable time series analysis. We exemplary test the workflow for twelve sites across the northern high latitudes in Siberia. We assessed the number of images and cloud-free pixels, the spatial mosaic coverage and the mosaic quality with spectral comparisons. The number of available images increased steadily from 1999 to 2019 but especially from 2016 onward with the addition of Sentinel-2 images. Consequently, we have an increased number of cloud-free pixels even under challenging environmental conditions, which then serve as the input to the mosaicking process. In a comparison of annual mosaics, the Landsat+Sentinel-2 mosaics always fully covered the study areas (99.9–100 %), while Landsat-only mosaics contained data-gaps in the same years, only reaching coverage percentages of 27.2 %, 58.1 %, and 69.7 % for Sobo Sise, East Taymyr, and Kurungnakh in 2017, respectively. The spectral comparison of Landsat image, Sentinel-2 image, and Landsat+Sentinel-2 mosaic showed high correlation between the input images and mosaic bands (e.g., for Kurungnakh 0.91–0.97 between Landsat and Landsat+Sentinel-2 mosaic and 0.92–0.98 between Sentinel-2 and Landsat+Sentinel-2 mosaic) across all twelve study sites, testifying good quality mosaic results. Our results show that especially the results for northern, coastal areas was substantially improved with the Landsat+Sentinel-2 mosaics. By combining Landsat and Sentinel-2 data we accomplished to create reliably high spatial resolution input mosaics for time series analyses. Our approach allows to apply a high temporal continuous time series analysis to northern high latitude permafrost regions for the first time, overcoming substantial data gaps, and assess permafrost disturbance dynamics on an annual scale across large regions with algorithms such as LandTrendr by deriving the location, timing and progression of permafrost thaw disturbances.