Thawing-triggered slope failures and landslides are becoming an increasing concern in cold regions due to the ongoing climate change. Predicting and understanding the behaviour of frozen soils under these changing conditions is therefore critical and has led to a growing interest in the research community. To address this challenge, we present the first mesh-free smoothed particle hydrodynamics (SPH) computational framework designed to handle the multi-phase and multi-physic coupled thermo-hydro-mechanical (THM) process in frozen soils, namely the THM-SPH computational framework. The frozen soil is considered a tri-phase mixture (i.e., soil, water and ice), whose governing equations are then established based on u-p-T formulations. A critical-state elasto-plastic Clay and Sand Model for Frozen soils (CASM-F), formulated in terms of solid-phase stress, is then introduced to describe the transition response and large deformation behaviour of frozen soils due to thawing action for the first time. Several numerical verifications and demonstrations highlight the usefulness of this advanced THM-SPH computational framework in addressing challenging problems involving thawing-induced large deformation and failures of slopes. The results indicate that our proposed single-layer, fully coupled THM-SPH model can predict the entire failure process of thawing-induced landslides, from the initiation to post-failure responses, capturing the complex interaction among multiple coupled phases. This represents a significant advancement in the numerical modelling of frozen soils and their thawing-induced failure mechanisms in cold regions.

Small modular reactors (SMRs) are an alternative for clean energy solutions in Canada's remote northern communities, owing to their safety, flexibility, and reduced capital requirements. Currently, these communities are heavily reliant on fossil fuels, and the transition to cleaner energy sources, such as SMRs, becomes imperative for Canada to achieve its ambitious net-zero emissions target by 2050. However, applying SMR technology in permafrost regions affected by climate change presents unique challenges. The degradation of permafrost can lead to significant deformations and settlements, which can result in increased maintenance expenses and reduced structural resilience of SMR infrastructure. In this paper, we studied the combined effect of climate nonstationarity in terms of ground surface temperature and heat dissipation from SMR reactor cores for the first time in two distinct locations in Canada's North: Salluit in Quebec and Inuvik in the Northwest Territories. It was shown that these combined effects can make significant changes to the ground thermal conditions within a radius of 15-20 m around the reactor core. The change in the ground thermal conditions poses a threat to the integrity of the permafrost table. The implementation of mitigation strategies is imperative to maintain the structural integrity of the nuclear infrastructure in permafrost regions. The thermal modeling presented in this study paves the way for the development of advanced coupled thermo-hydromechanical models to examine the impact of SMRs and climate nonstationarity on permafrost degradation.

This manuscript presents a comprehensive presentation of ground temperature data collected at 16 nodes of the 121 of the Crater Lake Circumpolar Active Layer Monitoring (CALM) site on Deception Island, Antarctica, from 2008 to early 2022. Each one of the 16 shallow boreholes has been equipped with miniature temperature loggers, providing valuable insights into the thermal regime of the ground at a depth of 50 cm, which corresponds to the mean depth of the top of the permafrost table as observed by annual mechanical probing in the CALM site. Despite a 9-month long gap in data collection during 2017 due to persistent snow cover, the time series remains largely intact, with annual measurements taken every 3 h. The manuscript details the methodologies employed for data collection, including the use of iButton loggers, and outlines the challenges faced in retrieving and processing the data in the harsh Antarctic environment. The cleaned dataset, which consolidates data from various nodes while removing erroneous records, is made freely accessible to the scientific community without any additional processing of the data such as offset corrections or gaps interpolation. This resource is expected to facilitate further research into the thermal dynamics of the active layer and permafrost and its implications for climate change since both are influenced by external factors such as snow cover, air temperature and others. Overall, the presented dataset contributes to the limited body of knowledge regarding Antarctic permafrost and provides a foundation for future investigations into the effects of climate change on frozen ground dynamics. The dataset serves as a vital tool for researchers aiming to model ground thermal behaviour and assess the impacts of environmental changes in polar regions.

Southern boundary areas of high-latitude permafrost regions may represent the future permafrost temperature regimes; therefore, understanding the carbon stocks and their stability in these systems can shed light on the permafrost carbon cycle under a warming climate. In this study, we sampled soils at three sites representing three differing land covers (forest swamp, dry forest, and shrub swamp) located in the southern boundary area of a high-latitude permafrost region and investigated their carbon fractions and the relationships of these fractions with soil physicochemical parameters in the active and permafrost layers. The results show that the proportion of active carbon is higher in permafrost than in the active layer under forest swamp and dry forest, implying that carbon pools in the permafrost are more decomposable. However, in shrub swamp, the active carbon components in the permafrost layer are lower than in the active layer. Soil pH and water content are the most significant factors associated with soil organic carbon concentration both in the active layers and in the permafrost layers. Our results suggest that, although soil organic carbon concentrations largely decrease with depth, the proportion of the forest swamp, dry forest labile carbon is higher in the permafrost layer than in the active layer and that the vertical distribution of labile carbon proportions is related to land covers.

In the context of global warming, understanding the impact of thaw slump on soil hydrothermal processes and its responses to climate is essential for protecting engineering facilities in cold regions. This study aimed to investigate the effect of thaw slump development on active layer soil. We considered the early thaw slump development in the Tibetan Plateau as research object and conducted long-term monitoring of soil hydrothermal activity in the active layer of various parts of the landslide and the regional meteorology. The results showed that thaw slump development shortened the freezing and thawing time of the active layer, increased the freezing and thawing rates of the shallow soil (10-20 cm), and enhanced the heat exchange between the active layer soil and the atmosphere and the heat transfer between the soils. The heat-exchange efficiency of the active layer, from largest to smallest, was headwall > collapsed area > unaffected area (bottom of the slope) > unaffected area (top of the slope). Furthermore, thaw slump development lowered the water storage of the active layer prof ile and weakened the dynamic response of soil water to precipitation. The events of soil water responses and soil water increments were smaller in the landslide area than in the unaffected area. During a co-precipitation event, the overall soil water storage increment (SWSI) of the profile was significantly smaller in the landslide area than in the unaffected area (P < 0.05), with an SWSI of 2.04 mm in the headwall and 1.77 mm in the collapsed area. In addition, thaw slump development altered the mechanism of soil water transport driven by soil temperature changes, which affected soil water redistribution of profile. The study gives ecohydrology-related research in cold climates a scientific foundation, thereby guiding the construction and maintenance of infrastructure projects.

Permafrost is one of the crucial components of the cryosphere, covering about 25% of the global continental area. The active layer thickness (ALT), as the main site for heat and water exchange between permafrost and the external atmosphere, its changes significantly impact the carbon cycle, hydrological processes, ecosystems, and the safety of engineering structures in cold regions. This study constructs a Stefan CatBoost-ET (SCE) model through machine learning and Blending integration, leveraging multi-source remote sensing data, the Stefan equation, and measured ALT data to focus on the ALT in the Qinghai-Tibet Plateau (QTP). Additionally, the SCE model was verified via ten-fold cross-validation (MAE: 20.713 cm, RMSE: 32.680 cm, R2: 0.873, and MAPE: 0.104), and its inversion of QTP's ALT data from 1958 to 2022 revealed 1998 as a key turning point with a slow growth rate of 0.25 cm/a before 1998 and a significantly increased rate of 1.26 cm/a afterward. Finally, based on multiple model input factor analysis methods (SHAP, Pearson correlation, and Random Forest Importance), the study analyzed the ranking of key factors influencing ALT changes. Meanwhile, the importance of Stefan equation results in SCE model is verified. The research results of this paper have positive implications for eco-hydrology in the QTP region, and also provide valuable references for simulating the ALT of permafrost.

Ongoing and widespread permafrost degradation potentially affects terrestrial ecosystems, whereas the changes in its effects on vegetation under climate change remain unclear. Here, we estimated the relative contribution of progressive active layer thickness (ALT) increases to vegetation gross primary productivity (GPP) in the northern permafrost region during the 21st century. Our results revealed that ALT changes accounted for 40% of the GPP increase in the permafrost region during 2000-2021, with amplified effects observed in late growing season (September-October) (43.2%-45.4%) and was especially notable in tundra ecosystems (51%-52.6%). However, projections indicated that this contribution could decrease considerably in the coming decades. Model simulations suggest that once ALT increments (relative to the 2001-2021 baseline) reach approximately 90 cm between 2035 and 2045, the promoting effect of ALT increase on vegetation growth may disappear. These findings provide crucial insights for accurately modelling and predicting ecosystem carbon dynamics in northern high latitudinal regions.

This study employs the Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) technique, along with in situ hydrothermal data, to explore the details and mechanisms of permafrost ground surface deformation in the hinterland Tibetan Plateau. Through analyzing GNSS data collected from November 2021 to April 2024, seasonal deformation of up to approximately 5 cm, caused by active layer freeze-thaw cycles, was identified. Additionally, more than 2 years of continuous monitoring revealed a clear ground subsidence rate of 2.7 cm per year due to permafrost thawing. We compared the GNSS-IR monitored deformation with simulated deformation using in situ soil moisture and temperature profiles at 5-220 cm depth and found that the correlation reached 0.9 during the active-layer thawing and freezing period; we also observed that following an exceptionally thawing season, the subsequent thawing season experiences notably greater thaw subsidence. Furthermore, we analyzed the differences in GNSS-IR monitoring results with and without the inclusion of Beidou Navigation Satellite System (BDS) signals, and found that the inclusion of BDS signals reduced the standard deviation of GNSS-IR results by an average of 0.24 mm on snow-free periods, but increased by an average of 0.12 mm during the snow cover periods. This may be due to the longer wavelength of the BDS signal, which exhibits greater diffraction through snow and reduces signal reflectivity compared to other satellite systems. The research results demonstrate the potential and ability of continuous GNSS-IR ground surface deformation monitoring in revealing and exploring the hydrothermal processes within permafrost under climate change.

The extent of wildfires in tundra ecosystems has dramatically increased since the turn of the 21st century due to climate change and the resulting amplified Arctic warming. We simultaneously studied the recovery of vegetation, subsurface soil moisture, and active layer thickness (ALT) post-fire in the permafrost-underlain uplands of the Yukon-Kuskokwim Delta in southwestern Alaska to understand the interaction between these factors and their potential implications. We used a space-for-time substitution methodology with 2017 Landsat 8 imagery and synthetic aperture radar products, along with 2016 field data, to analyze tundra recovery trajectories in areas burned from 1953 to 2017. We found that spectral indices describing vegetation greenness and surface albedo in burned areas approached the unburned baseline within a decade post-fire, but ecological succession takes decades. ALT was higher in burned areas compared to unburned areas initially after the fire but negatively correlated with soil moisture. Soil moisture was significantly higher in burned areas than in unburned areas. Water table depth (WTD) was 10 cm shallower in burned areas, consistent with 10 cm of the surface organic layer burned off during fire. Soil moisture and WTD did not recover in the 46 years covered by this study and appear linked to the long recovery time of the organic layer.

Arctic permafrost soils contain a vast reservoir of soil organic carbon (SOC) vulnerable to increasing mobilization and decomposition from polar warming and permafrost thaw. How these SOC stocks are responding to global warming is uncertain, partly due to a lack of information on the distribution and status of SOC over vast Arctic landscapes. Soil moisture and organic matter vary substantially over the short vertical distance of the permafrost active layer. The hydrological properties of this seasonally thawed soil layer provide insights for understanding the dielectric behavior of water inside the soil matrix, which is key for developing more effective physics-based radar remote sensing retrieval algorithms for large-scale mapping of SOC. This study provides a coupled hydrologic-electromagnetic framework to model the frequency-dependent dielectric behavior of active layer organic soil. For the first time, we present joint measurement and modeling of the water matric potential, dielectric permittivity, and basic physical properties of 66 soil samples collected across the Alaskan Arctic tundra. The matric potential measurement allows for estimating the soil water retention curve, which helps determine the relaxation time through the Eyring equation. The estimated relaxation time of water molecules in soil is then used in the Debye model to predict the water dielectric behavior in soil. A multi-phase dielectric mixing model is applied to incorporate the contribution of various soil components. The resulting organic soil dielectric model accepts saturation water fraction, organic matter content, mineral texture, temperature, and microwave frequency as inputs to calculate the effective soil dielectric characteristic. The developed dielectric model was validated against lab-measured dielectric data for all soil samples and exhibited robust accuracy. We further validated the dielectric model against field-measured dielectric profiles acquired from five sites on the Alaskan North Slope. Model behavior was also compared against other existing dielectric models, and an indepth discussion on their validity and limitations in permafrost soils is given. The resulting organic soil dielectric model was then integrated with a multi-layer electromagnetic scattering forward model to simulate radar backscatter under a range of soil profile conditions and model parameters. The results indicate that low frequency (P-,L-band) polarimetric synthetic aperture radars (SARs) have the potential to map water and carbon characteristics in permafrost active layer soils using physics-based radar retrieval algorithms.