The geometry of large Arctic tundra lakes observed in historical maps and satellite images

The climate of the Arctic is warming rapidly and this is causing major changes to the cycling of carbon and the distribution of permafrost in this region. Tundra lakes are key components of the Arctic climate system because they represent a source of methane to the atmosphere. In this paper, we aim to analyze the geometry of the patterns formed by large (> 0.8 km2) tundra lakes in the Russian High Arctic. We have studied images of tundra lakes in historical maps from the State Hydrological Institute, Russia (date 1977; scale 0.21166 km/pixel) and in Landsat satellite images derived from the Google Earth Engine (G.E.E.; date 2016; scale 0.1503 km/pixel). The G.E.E. is a cloud-based platform for planetary-scale geospatial analysis on over four decades of Landsat data. We developed an image-processing algorithm to segment these maps and images, measure the area and perimeter of each lake, and compute the fractal dimension of the lakes in the images we have studied. Our results indicate that as lake size increases, their fractal dimension bifurcates. For lakes observed in historical maps, this bifurcation occurs among lakes larger than 100 km2 (fractal dimension 1.43 to 1.87). For lakes observed in satellite images this bifurcation occurs among lakes larger than ∼100 km2 (fractal dimension 1.31 to 1.95). Tundra lakes with a fractal dimension close to 2 have a tendency to be self-similar with respect to their area–perimeter relationships. Area–perimeter measurements indicate that lakes with a length scale greater than 70 km2 are power-law distributed. Preliminary analysis of changes in lake size over time in paired lakes (lakes that were visually matched in both the historical map and the satellite imagery) indicate that some lakes in our study region have increased in size over time, whereas others have decreased in size over time. Lake size change during this 39-year time interval can be up to half the size of the lake as recorded in the historical map

Data evaluation and numerical modeling of hydrological interactions between active layer, lake and talik in a permafrost catchment, Western Greenland

SummaryThis study investigates annual water balance conditions and their spatiotemporal variability under a wide variety of atmospheric driving conditions in the periglacial permafrost catchment of Two Boat Lake in Western Greenland. The study uses and combines a comprehensive hydrological multi-parameter dataset measured at the site with site conceptualization and numerical model development, application and testing. The model result reproduces measured lake and groundwater levels, as well as observations made by time-lapse cameras. The results highlights the importance of numerical modeling that takes into account and combines evapotranspiration with other surface and subsurface hydrological processes at various depths, in order to quantitatively understand and represent the dynamics and complexity of the interactions between meteorology, active layer hydrology, lakes, and unfrozen groundwater below permafrost in periglacial catchments. Regarding these interactions, the water flow between the studied lake and a through talik within and beneath it is found to be small compared to other water balance components. The modeling results show that recharge and discharge conditions in the talik can shift in time, while the lake and active layer conditions in the studied catchment are independent of catchment-external landscape features, such as the unfrozen groundwater system below the permafrost and the nearby continental-scale ice sheet

Permafrost hydrology in changing climatic conditions: seasonal variability of stable isotope composition in rivers in discontinuous permafrost

Role of changing climatic conditions on permafrost degradation and hydrology was investigated in the transition zone between the tundra and forest ecotones at the boundary of continuous and discontinuous permafrost of the lower Yenisei River. Three watersheds of various sizes were chosen to represent the characteristics of the regional landscape conditions. Samples of river flow, precipitation, snow cover, and permafrost ground ice were collected over the watersheds to determine isotopic composition of potential sources of water in a river flow over a two year period. Increases in air temperature over the last forty years have resulted in permafrost degradation and a decrease in the seasonal frost which is evident from soil temperature measurements, permafrost and active-layer monitoring, and analysis of satellite imagery. The lowering of the permafrost table has led to an increased storage capacity of permafrost affected soils and a higher contribution of ground water to river discharge during winter months. A progressive decrease in the thickness of the layer of seasonal freezing allows more water storage and pathways for water during the winter low period making winter discharge dependent on the timing and amount of late summer precipitation. There is a substantial seasonal variability of stable isotopic composition of river flow. Spring flooding corresponds to the isotopic composition of snow cover prior to the snowmelt. Isotopic composition of river flow during the summer period follows the variability of precipitation in smaller creeks, while the water flow of larger watersheds is influenced by the secondary evaporation of water temporarily stored in thermokarst lakes and bogs. Late summer precipitation determines the isotopic composition of texture ice within the active layer in tundra landscapes and the seasonal freezing layer in forested landscapes as well as the composition of the water flow during winter months

Remote Sensing of Rapid Permafrost Landscape Dynamics

The global climate is warming and the northern high latitudes are affected particularly rapidly. Large areas of this region, or 24% of the northern hemisphere, are influenced by perennially frozen ground or permafrost. As permafrost is predominantly dependent on cold mean annual air temperatures, climate warming threatens the stability of permafrost. Since large amounts of organic carbon are stored within permafrost, its thaw would potentially release large amounts of greenhouse gases, which would further enhance climate warming (permafrost carbon feedback). Thermokarst and thermo-erosion are an indicator of rapid permafrost thaw, and may also trigger further disturbances in their vicinity. The vast Arctic permafrost regions and the wide distribution of thaw landforms makes the monitoring of thermokarst and thermo-erosion an important task to better understand the response of permafrost to the changing climate. Remote sensing is a key methodology to monitor the land surface from local to global spatial scales and could provide a tool to quantify such changes in permafrost regions. With the opening of satellite archives, advances in computational processing capacities and new data processing technology, it has become possible to handle and analyze rapidly growing amounts of data. In the scope of the changing climate and its influence of permafrost in conjunction with recent advances in remote sensing this thesis aims to answer the following key research questions: 1. How can the extensive Landsat data archive be used effectively for detecting typical land surface changes processes in permafrost landscapes? 2. What is the spatial distribution of lake dynamics in permafrost and which are the dominant underlying influencing factors? 3. How are key disturbances in permafrost landscapes (lake changes, thaw slumps and fire) spatially distributed and what are their primary influence factors? To answer these questions, I developed a scalable methodology to detect and analyze permafrost landscape changes in the ~29,000 km2 Lena Delta in North-East Siberia. I used all available peak summer data from the Landsat archive from 1999 through 2014 and applied a highly automated robust trend-analysis based on multi-spectral indices using the Theil-Sen algorithm. With the trends of surface properties, such as albedo, vegetation status or wetness, I was able identify local scale processes, such as thermokarst lake expansion and drainage, river bank erosion, and coastal inundation, as well as regional surface changes, such as wetting and greening at 30m spatial resolution. This method proved to be robust in indicating typical landscape change processes within an Arctic coastal lowland environment dominated by permafrost, which has been challenging for the application of optical remote sensing data. The scalability of the highly automated processing allows for further upscaling and advanced automated landscape process analysis. For a targeted analysis of well-known disturbances affecting permafrost (thermokarst lakes, retrogressive thaw slumps and wildfires), I used advanced remote sensing and image processing techniques in conjunction with the processed trend data. Here I combined the trend analysis with machine-learning classification and object based image analysis to detect lakes and to quantify their dynamics over a period from 1999 through 2014 within four different Arctic and Subarctic regions in Alaska and Siberia totaling 200,000 km². I found very strong precipitation driven lake expansion (+48.48 %) in the central Yakutian study area, while the study areas along the Arctic coast showed a slight loss of lake area (Alaska North Slope: -0.69%; Kolyma Lowland: -0.51%) or a moderate lake loss (Alaska Kobuk-Selawik Lowlands: -2.82%) due to widespread lake drainage. The lake change dynamics were characterized by a large variety of local dynamics, which are dependent on several factors, such as ground-ice conditions, surface geology, or climatic conditions. In an even broader analysis across four extensive north-south transects covering more than 2.3 million km², I focused on the spatial distribution and key factors of permafrost region disturbances. I found clear spatial patterns for the abundance of lakes (predominantly in ice-rich lowland areas), retrogressive thaw slumps (predominantly in ice-rich, sloped terrain, former glacial margin), and wildfires (boreal forest). Interestingly, apart from frequent drainage at the continuous-discontinuous permafrost interface, lake change dynamics showed spatial patterns of expansion and reduction that could not be directly related to specific variables, such as climate or permafrost conditions over large continental-scale transects. However, specific variables could get related to specific lake dynamics in within locally defined regions. Trend datasets of vegetation status (NDVI) were combined with high-resolution detailed geomorphological land-cover classification information and climate data to map tundra productivity in a heterogeneous landscape in northern Alaska. After decades of increasing productivity (greening), recently tundra vegetation showed a reverse trend of decreased productivity, which is predicted to continue with increasing temperatures and precipitation. In this thesis project I developed methods to analyze rapid landscape change processes of various scales in northern high latitudes with unprecedented detail by relying on spatially and temporally high resolution Landsat image time series analysis across very large regions. The findings allow a unique and unprecedented insight into the landscape dynamics of permafrost over large regions, even detecting rapid permafrost thaw processes, which have a small spatial footprint and thus are difficult to detect. The multi-scaled approach can help to support local-scale field campaigns to precisely prepare study site selection for expeditions, but also pan-arctic to global-scale models to improve predictions of permafrost thaw feedbacks and soil carbon emissions in a warming climate