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This study introduces a new automated system that blends multi-satellite information and citizen science data for reliable and timely observations of lake and river ice in under-observed northern regions. The system leverages the Google Earth Engine resources to facilitate the analysis and visualization of ice conditions. The adopted approach utilizes a combination of moderate and high-resolution optical data, along with radar observations. The results demonstrate the system's capability to accurately detect and monitor river ice, particularly during key periods, such as the freeze-up and the breakup. The integration citizen science data showed added values in the validation of remote sensing products, as well as filling gaps whenever satellite observations cannot be collected due to cloud obstruction. Moreover, it was shown that citizen science data can be converted to valuable quantitative information, such as the case of ice thickness, which is very useful when combined with ice extent derived from remote sensing. In this study, citizen science data were employed for the quantitative assessment of the remote sensing product. Obtained results showed a good agreement between the product and observed river status, with a Critical Success Index of 0.82. Notably, the system has shown effectiveness in capturing the spatial and temporal evolution of snow and ice conditions, as evidenced by its application in analyzing specific ice jam events in 2023. The study concludes that the developed system marks a significant advancement in river ice monitoring, combining technological innovation with community engagement. [ABSTRACT FROM AUTHOR]

People who travel on ice-covered rivers to access traditional lands and resources can be profoundly impacted by effects of climate change on river ice seasonality. We used remote sensing, bolstered by citizen science, to assess trends and geospatial patterns of the ice cover in the Copper River Basin of Southcentral Alaska. Our analysis of Landsat imagery from water years (WYs) 1973 to 2021 suggests a severely diminishing season of river ice travel (delayed or incomplete freezeup, early breakup) due to increasing air temperatures. The weekly probability of an adequate ice cover for river crossings declined by an average of 53 percentage points. Ice extent was closely related to accumulated freezing degree days (AFDD). AFDDOct-Apr decreased by 15% since WY 1943, a significant warming trend. We mapped the spatiotemporal variation of ice and open water extent with multispectral and synthetic aperture radar (SAR) imagery (Sentinel-2, Sentinel-1). We identified reaches with more reliable opportunities for winter access and others susceptible to extensive open water, differences related to flow energy and channel form. The results of this study can support local decision making and adaptation in response to rapidly changing river ice conditions, and our approach can be applied elsewhere to document change and improve travel safety. [ABSTRACT FROM AUTHOR]

Characterization of permafrost, particularly warm and near-surface permafrost which can contain significant liquid water, is critical to understanding complex interrelationships with climate change, ecosystems, and disturbances such as wildfires. Understanding the vulnerability and resilience of permafrost requires an interdisciplinary approach, relying on (for example) geophysical investigations, ecological characterization, direct observations, remote sensing, and more. As part of a multiyear investigation into the impacts of wildfires on permafrost, we have collected in situ measurements of the nuclear magnetic resonance (NMR) response of the active layer and permafrost in a variety of soil conditions, types, and saturations. In this paper, we summarize the NMR data and present quantitative relationships between active layer and permafrost liquid water content and pore sizes and show the efficacy of borehole NMR (bNMR) to permafrost studies. Through statistical analyses and synthetic freezing simulations, we also demonstrate that borehole NMR is sensitive to the nucleation of ice within soil pore spaces. [ABSTRACT FROM AUTHOR]

Climate change coupled with an intensifying wildfire regime is becoming an important driver of permafrost loss and ecosystem change in the northern boreal forest. There is a growing need to understand the effects of fire on the spatial distribution of permafrost and its associated ecological consequences. We focus on the effects of fire a decade after disturbance in a rocky upland landscape in the interior Alaskan boreal forest. Our main objectives were to (1) map near-surface permafrost distribution and drainage classes and (2) analyze the controls over landscape-scale patterns of post-fire permafrost degradation. Relationships among remote sensing variables and field-based data on soil properties (temperature, moisture, organic layer thickness) and vegetation (plant community composition) were analyzed using correlation, regression, and ordination analyses. The remote sensing data we considered included spectral indices from optical datasets (Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI)), the principal components of a time series of radar backscatter (Advanced Land Observing Satellite-Phased Array type L-band Synthetic Aperture Radar (ALOS-PALSAR)), and topographic variables from a Light Detection and Ranging (LiDAR)-derived digital elevation model (DEM). We found strong empirical relationships between the normalized difference infrared index (NDII) and post-fire vegetation, soil moisture, and soil temperature, enabling us to indirectly map permafrost status and drainage class using regression-based models. The thickness of the insulating surface organic layer after fire, a measure of burn severity, was an important control over the extent of permafrost degradation. According to our classifications, 90% of the area considered to have experienced high severity burn (using the difference normalized burn ratio (dNBR)) lacked permafrost after fire. Permafrost thaw, in turn, likely increased drainage and resulted in drier surface soils. Burn severity also influenced plant community composition, which was tightly linked to soil temperature and moisture. Overall, interactions between burn severity, topography, and vegetation appear to control the distribution of near-surface permafrost and associated drainage conditions after disturbance. [ABSTRACT FROM AUTHOR]