[1] Quantifying changes in thermokarst lake extent is of importance for understanding the permafrost-related carbon budget, including the potential release of carbon via lake expansion or sequestration as peat in drained lake basins. We used high spatial resolution remotely sensed imagery from 1950/51, 1978, and 2006/07 to quantify changes in thermokarst lakes for a 700 km 2 area on the northern Seward Peninsula, Alaska. The number of water bodies larger than 0.1 ha increased over the entire observation period (666 to 737 or +10.7%); however, total surface area decreased (5,066 ha to 4,312 ha or −14.9%). This pattern can largely be explained by the formation of remnant ponds following partial drainage of larger water bodies. Thus, analysis of large lakes (>40 ha) shows a decrease of 24% and 26% in number and area, respectively, differing from lake changes reported from other continuous permafrost regions. Thermokarst lake expansion rates did not change substantially between 1950/51 and 1978 (0.35 m/yr) and 1978 and 2006/07 (0.39 m/yr). However, most lakes that drained did expand as a result of surface permafrost degradation before lateral drainage. Drainage rates over the observation period were stable (2.2 to 2.3 per year). Thus, analysis of decadal-scale, high spatial resolution imagery has shown that lake drainage in this region is triggered by lateral breaching and not subterranean infiltration. Future research should be directed toward better understanding thermokarst lake dynamics at high spatial and temporal resolution as these systems have implications for landscape-scale hydrology and carbon budgets in thermokarst lake-rich regions in the circum-Arctic.

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[1] Application of transient storage models has become popular for characterizing hydrologic and biogeochemical processes in streams. The typical transient storage model represents exchange between the main channel and a single storage zone, essentially lumping together different exchange processes. Here we present a method to inform a transient storage model that accounts for two storage zones (2-SZ) to discriminate between surface transient storage (STS) exchange and exchange with hyporheic transient storage (HTS). This method requires that, in addition to tracer breakthrough curves from the main channel, cross-sectional stream velocity distributions and stream tracer concentration time series data from several main channel locations and adjacent representative STS zones be collected. We apply this method to a constant rate conservative tracer injection in a first-order stream and to an instantaneous slug conservative tracer injection in a fourth-order stream. The 2-SZ model simulations matched observed breakthrough curves of tracer concentration in the main channel and general STS behavior well. Additionally, we compared the optimized parameter sets of the 2-SZ model to one-storage zone model (1-SZ) simulations and found that the lumped storage terms of the 1-SZ model described the time scales of 2-SZ model HTS exchange and attributed the time scales of observed STS exchange to longitudinal dispersion. With additional field data collection efforts and data processing, this method can provide much more useful results than the 1-SZ approach to those interested in discriminating between surface and subsurface transient storage dynamics of streams, which is important for discerning processes important to the cycling and fate of biogeochemicals.

Abstract:Thermokarst lakes cover >20% of the landscape throughout much of the Alaskan Arctic Coastal Plain (ACP) with shallow lakes freezing solid (grounded ice) and deeper lakes maintaining perennial liquid water (floating ice). Thus, lake depth relative to maximum ice thickness (1Ð5-2Ð0 m) represents an important threshold that impacts permafrost, aquatic habitat, and potentially geomorphic and hydrologic behaviour. We studied coupled hydrogeomorphic processes of 13 lakes representing a depth gradient across this threshold of maximum ice thickness by analysing remotely sensed, water quality, and climatic data over a 35-year period. Shoreline erosion rates due to permafrost degradation ranged from <0Ð2 m/year in very shallow lakes (0Ð4 m) up to 1Ð8 m/year in the deepest lakes (2Ð6 m). This pattern of thermokarst expansion masked detection of lake hydrologic change using remotely sensed imagery except for the shallowest lakes with stable shorelines. Changes in the surface area of these shallow lakes tracked interannual variation in precipitation minus evaporation (P E L ) with periods of full and nearly dry basins. Shorter-term (2004Shorter-term ( -2008 specific conductance data indicated a drying pattern across lakes of all depths consistent with the long-term record for only shallow lakes. Our analysis suggests that grounded-ice lakes are ice-free on average 37 days longer than floating-ice lakes resulting in a longer period of evaporative loss and more frequent negative P E L . These results suggest divergent hydrogeomorphic responses to a changing Arctic climate depending on the threshold created by water depth relative to maximum ice thickness in ACP lakes.

Fire-induced permafrost degradation is well documented in boreal forests, but the role of fires in initiating thermokarst development in Arctic tundra is less well understood. Here we show that Arctic tundra fires may induce widespread thaw subsidence of permafrost terrain in the first seven years following the disturbance. Quantitative analysis of airborne LiDAR data acquired two and seven years post-fire, detected permafrost thaw subsidence across 34% of the burned tundra area studied, compared to less than 1% in similar undisturbed, ice-rich tundra terrain units. The variability in thermokarst development appears to be influenced by the interaction of tundra fire burn severity and near-surface, ground-ice content. Subsidence was greatest in severely burned, ice-rich upland terrain (yedoma), accounting for ~50% of the detected subsidence, despite representing only 30% of the fire disturbed study area. Microtopography increased by 340% in this terrain unit as a result of ice wedge degradation. Increases in the frequency, magnitude, and severity of tundra fires will contribute to future thermokarst development and associated landscape change in Arctic tundra regions.

In response to a need for a unified ecological map for ecoregional planning in northern Alaska by the Nature Conservancy, we developed a map of local-scale ecosystems (ecotypes) that encompasses the Brooks Range, Brooks Foothills, and Beaufort Coastal Plain ecoregions. Our approach to ecological land classification and mapping combined vegetation structure associated with existing landcover maps derived from satellite image processing, with physiography (i.e., coastal, floodplain, alpine), topography (DEM modeling), and bedrock characteristics to model ecotypes that best partition geomorphic, hydrologic, pedologic, and vegetative characteristics. We developed a classification that included 7 alpine, 9 upland, 5 lowland, 10 riverine, 4 coastal, and 1 human-modified ecotypes that encompass a broad diversity of ecological characteristics ranging from boreal forests in the southern Brooks Range to brackish meadows along the Beaufort Sea coast. As input to map development, we used four existing landcover maps for the: North Slope by Muller et al. (1999), Gates of the Arctic National Park and Preserve by the Earth Satellite Corporation and Alaska Natural Heritage Program (1999), northwest Alaska parks by the National Park Service (1999), and the Arctic National Wildlife Refuge by Markon (1986). For physiography, we manually delineated floodplains and coastal areas at 1:100,000-scale on NASA Geocover satellite imagery, and differentiated alpine, upland and lowland areas by using a digital elevation model to characterize elevation, slope, moisture index, and land position (concavity/convexity index). Bedrock geology was adapted from Moore et al. (1994). Glacial extent was obtained from USGS maps, as compiled by Manley (pers. comm.). Rule-based models were developed to recode the map classes from the individual landcover maps into ecotypes. In the resulting map of the 308,208-km 2 area, 57% of the area has upland, 18% has alpine, 17% has lowland, 5% has riverine, 3% has coastal, and <0.1% has human-modified ecotypes. Each ecotype typically is associated with 2 4 geomorphic units, 2 4 closely related soil types, 1 3 plant associations, and differing permafrost conditions. For ecoregional planning, the map was used to identify rare ecosystems and high-value wildlife habitats deserving priority protection. References

Lakes are a ubiquitous landscape feature in northern permafrost regions. They have a strong impact on carbon, energy and water fluxes and can be quite responsive to climate change. The monitoring of lake change in northern high latitudes, at a sufficiently accurate spatial and temporal resolution, is crucial for understanding the underlying processes driving lake change. To date, lake change studies in permafrost regions were based on a variety of different sources, image acquisition periods and single snapshots, and localized analysis, which hinders the comparison of different regions. Here, we present a methodology based on machine-learning based classification of robust trends of multi-spectral indices of Landsat data (TM, ETM+, OLI) and object-based lake detection, to analyze and compare the individual, local and regional lake dynamics of four different study sites (Alaska North Slope, Western Alaska, Central Yakutia, Kolyma Lowland) in the northern permafrost zone from 1999 to 2014. Regional patterns of lake area change on the Alaska North Slope (−0.69%), Western Alaska (−2.82%), and Kolyma Lowland (−0.51%) largely include increases due to thermokarst lake expansion, but more dominant lake area losses due to catastrophic lake drainage events. In contrast, Central Yakutia showed a remarkable increase in lake area of 48.48%, likely resulting from warmer and wetter climate conditions over the latter half of the study period. Within all study regions, variability in lake dynamics was associated with differences in permafrost characteristics, landscape position (i.e., upland vs. lowland), and surface geology. With the global availability of Landsat data and a consistent methodology for processing the input data derived from robust trends of multi-spectral indices, we demonstrate a transferability, scalability and consistency of lake change analysis within the northern permafrost region.

The balance of thermokarst lakes with bedfast‐ and floating‐ice regimes across Arctic lowlands regulates heat storage, permafrost thaw, winter‐water supply, and over‐wintering aquatic habitat. Using a time‐series of late‐winter synthetic aperture radar (SAR) imagery to distinguish lake ice regimes in two regions of the Arctic Coastal Plain of northern Alaska from 2003–2011, we found that 18% of the lakes had intermittent ice regimes, varying between bedfast‐ice and floating‐ice conditions. Comparing this dataset with a radar‐based lake classification from 1980 showed that 16% of the bedfast‐ice lakes had shifted to floating‐ice regimes. A simulated lake ice thinning trend of 1.5 cm/yr since 1978 is believed to be the primary factor driving this form of lake change. The most profound impacts of this regime shift in Arctic lakes may be an increase in the landscape‐scale thermal offset created by additional lake heat storage and its role in talik development in otherwise continuous permafrost as well as increases in over‐winter aquatic habitat and winter‐water supply.