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27 pages, 39231 KiB  
Article
Study on the Distribution Characteristics of Thermal Melt Geological Hazards in Qinghai Based on Remote Sensing Interpretation Method
by Xing Zhang, Zongren Li, Sailajia Wei, Delin Li, Xiaomin Li, Rongfang Xin, Wanrui Hu, Heng Liu and Peng Guan
Water 2025, 17(15), 2295; https://doi.org/10.3390/w17152295 - 1 Aug 2025
Viewed by 117
Abstract
In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research [...] Read more.
In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects. Full article
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18 pages, 4713 KiB  
Article
Analysis of Embankment Temperature Regulation Efficiency of V-Shaped Bidirectional Heat Conduction Thermosyphon in Permafrost Regions
by Feike Duan, Bo Tian, Sen Hu and Lei Quan
Sustainability 2025, 17(13), 6048; https://doi.org/10.3390/su17136048 - 2 Jul 2025
Viewed by 349
Abstract
The complex climate in permafrost regions poses severe challenges to infrastructure, and freeze-thaw cycles accelerate the deformation and damage of road embankments. Conventional thermosyphon technology, though effective in lowering permafrost temperatures, has a limited range of effect, making it hard to meet the [...] Read more.
The complex climate in permafrost regions poses severe challenges to infrastructure, and freeze-thaw cycles accelerate the deformation and damage of road embankments. Conventional thermosyphon technology, though effective in lowering permafrost temperatures, has a limited range of effect, making it hard to meet the demand for large-scale temperature regulation. This paper proposes a V-shaped transverse thermosyphon design with bidirectional heat conduction. It connects at the embankment centerline and transversely penetrates the entire cross-section to expand the temperature regulation range. Using a hydro-thermal coupling model, the temperature regulation effects of vertical, inclined, and V-shaped thermosyphons were calculated. Results show that the V-shaped design outperforms the other two in temperature control across different embankment areas. Transverse temperature analysis indicates uniform cooling around the embankment center, while depth temperature analysis reveals more stable temperature control with lower and less fluctuating temperatures at greater depths. Long-term temperature analysis demonstrates superior annual temperature regulation, providing consistent cooling. This research offers a scientific basis for embankment temperature regulation design in permafrost regions and is crucial for ensuring long-term embankment stability and safety. Full article
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36 pages, 7227 KiB  
Review
Formation of Low-Centered Ice-Wedge Polygons and Their Orthogonal Systems: A Review
by Yuri Shur, Benjamin M. Jones, M. Torre Jorgenson, Mikhail Z. Kanevskiy, Anna Liljedahl, Donald A. Walker, Melissa K. Ward Jones, Daniel Fortier and Alexander Vasiliev
Geosciences 2025, 15(7), 249; https://doi.org/10.3390/geosciences15070249 - 2 Jul 2025
Viewed by 835
Abstract
Ice wedges, which are ubiquitous in permafrost areas, play a significant role in the evolution of permafrost landscapes, influencing the topography and hydrology of these regions. In this paper, we combine a detailed multi-generational, interdisciplinary, and international literature review along with our own [...] Read more.
Ice wedges, which are ubiquitous in permafrost areas, play a significant role in the evolution of permafrost landscapes, influencing the topography and hydrology of these regions. In this paper, we combine a detailed multi-generational, interdisciplinary, and international literature review along with our own field experiences to explore the development of low-centered ice-wedge polygons and their orthogonal networks. Low-centered polygons, a type of ice-wedge polygonal ground characterized by elevated rims and lowered wet central basins, are critical indicators of permafrost conditions. The formation of these features has been subject to numerous inconsistencies and debates since their initial description in the 1800s. The development of elevated rims is attributed to different processes, such as soil bulging due to ice-wedge growth, differential frost heave, and the accumulation of vegetation and peat. The transition of low-centered polygons to flat-centered, driven by processes like peat accumulation, aggradational ice formation, and frost heave in polygon centers, has been generally overlooked. Low-centered polygons occur in deltas, on floodplains, and in drained-lake basins. There, they are often arranged in orthogonal networks that comprise a complex system. The prevailing explanation of their formation does not match with several field studies that practically remain unnoticed or ignored. By analyzing controversial subjects, such as the degradational or aggradational nature of low-centered polygons and the formation of orthogonal ice-wedge networks, this paper aims to clarify misconceptions and present a cohesive overview of lowland terrain ice-wedge dynamics. The findings emphasize the critical role of ice wedges in shaping Arctic permafrost landscapes and their vulnerability to ongoing climatic and landscape changes. Full article
(This article belongs to the Section Cryosphere)
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15 pages, 4293 KiB  
Article
A Study on the Vertical Bearing Characteristics of Screw Piles in Permafrost Regions
by Tao Liu, Jun Lv, Xuyan Deng, Chunxiang Guo, Weijia Zhang and Daijun Jiang
Appl. Sci. 2025, 15(13), 7416; https://doi.org/10.3390/app15137416 - 1 Jul 2025
Viewed by 295
Abstract
The screw piles used in permafrost regions represent a new type of pile, and their vertical bearing characteristics play a crucial role in ensuring the normal operation of engineering buildings. This study establishes a numerical calculation model to simulate the interaction between screw [...] Read more.
The screw piles used in permafrost regions represent a new type of pile, and their vertical bearing characteristics play a crucial role in ensuring the normal operation of engineering buildings. This study establishes a numerical calculation model to simulate the interaction between screw piles and soil in permafrost regions and verifies the numerical simulation results through model tests. The bearing mechanism of screw piles in permafrost areas is studied and compared with common, bored, cast-in-place piles widely used. Finally, a method for estimating the bearing capacity of screw piles in permafrost regions is proposed. The research indicates that approximately 90% of the bearing capacity of screw piles in permafrost regions is derived from the mechanical interaction between the concrete pile’s side and the permafrost soil. The shear strength of the permafrost is the primary determinant of the pile foundation’s bearing capacity, while the seasonally active layer has a minimal impact on its bearing capacity, resulting in a stable year-round performance. In permafrost regions, the equivalent friction resistance of screw piles is significantly greater than that of the conventional cast-in-place piles. When the pile reaches its ultimate bearing capacity, the plastic zone on the pile’s side becomes connected, and shear failure occurs in the surrounding soil. The design value of the bearing capacity of a single pile can be effectively estimated in engineering practice by improving the formula of the code for calculating the vertical bearing capacity. Full article
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41 pages, 1393 KiB  
Article
The Tropical Peatlands in Indonesia and Global Environmental Change: A Multi-Dimensional System-Based Analysis and Policy Implications
by Yee Keong Choy and Ayumi Onuma
Reg. Sci. Environ. Econ. 2025, 2(3), 17; https://doi.org/10.3390/rsee2030017 - 1 Jul 2025
Viewed by 622
Abstract
Tropical peatlands store approximately 105 gigatons of carbon (GtC), serving as vital long-term carbon sinks, yet remain critically underrepresented in climate policy. Indonesia peatlands contain 57GtC—the largest tropical peatland carbon stock in the Asia–Pacific. However, decades of drainage, fires, and lax enforcement practices [...] Read more.
Tropical peatlands store approximately 105 gigatons of carbon (GtC), serving as vital long-term carbon sinks, yet remain critically underrepresented in climate policy. Indonesia peatlands contain 57GtC—the largest tropical peatland carbon stock in the Asia–Pacific. However, decades of drainage, fires, and lax enforcement practices have degraded vast peatland areas, turning them from carbon sinks into emission sources—as evidenced by the 1997 and 2015 peatland fires which emitted 2.57 Gt CO2eq and 1.75 Gt CO2eq, respectively. Using system theory validated against historical data (1997–2023), we develop a causal loop model revealing three interconnected feedback loops driving irreversible collapse: (1) drainage–desiccation–oxidation, where water table below −40 cm triggers peat oxidation (2–5 cm subsistence) and fires; (2) fire–climate–permafrost, wherein emissions intensify radiative forcing, destabilizing monsoons and accelerating Arctic permafrost thaw (+15% since 2000); and (2) economy–governance failure, perpetuated by palm oil’s economic dominance and slack regulatory oversight. To break these vicious cycles, we propose a precautionary framework featuring IoT-enforced water table (≤40 cm), reducing emissions by 34%, legally protected “Global Climate Stabilization Zones” for peat domes (>3 m depth), safeguarding 57 GtC, and ASEAN transboundary enforcement funded by a 1–3% palm oil levy. Without intervention, annual emissions may reach 2.869 GtCO2e by 2030 (Nationally Determined Contribution’s business-as-usual scenario). Conversely, rewetting 590 km2/year aligns with Indonesia’s FOLU Net Sink 2030 target (−140 Mt CO2e) and mitigates 1.4–1.6 MtCO2 annually. We conclude that integrating peatlands as irreplaceable climate infrastructure into global policy is essential for achieving Paris Agreement goals and SDGs 13–15. Full article
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26 pages, 20113 KiB  
Article
Enhanced Detection of Permafrost Deformation with Machine Learning and Interferometric SAR Along the Qinghai–Tibet Engineering Corridor
by Peng Fan, Hong Lin, Zhengjia Zhang and Heming Deng
Remote Sens. 2025, 17(13), 2231; https://doi.org/10.3390/rs17132231 - 29 Jun 2025
Viewed by 374
Abstract
Interferometric synthetic aperture radar (InSAR) plays a significant role in monitoring permafrost deformation. However, owing to environmental constraints in permafrost regions, some regions exhibit temporal incoherence, which results in deformation with fewer measurement points and difficulties with deformation automatic detection. In this study, [...] Read more.
Interferometric synthetic aperture radar (InSAR) plays a significant role in monitoring permafrost deformation. However, owing to environmental constraints in permafrost regions, some regions exhibit temporal incoherence, which results in deformation with fewer measurement points and difficulties with deformation automatic detection. In this study, a full-coverage deformation rate map of the 10 km buffer of the Qinghai–Tibet Engineering Corridor (QTEC) was generated by combining nine driving factors and the deformation rate of the 5 km buffer along the QTEC based on three machine learning methods. The importance of the factors contributing to ground deformation was explored. The experimental results show that support vector regression (SVR) yielded the best performance (R2 = 0.98, RMSE = 0.76 mm/year, MAE = 0.74 mm/year). The 10 km buffer of deformation data obtained not only preserved the original deformation data well, but it also filled the blank areas in the deformation map. Subsequently, we trained the Faster R-CNN model on the deformation rate map simulated by SVR and used it for the automatic detection of permafrost thaw settlement areas. The results showed that the Faster R-CNN could identify the permafrost thawing slump quickly and accurately. More than 300 deformation areas along the QTEC were detected through our proposed method, with some of these areas located near thaw slump and thermokarst lake regions. This study confirms the significant potential of combining InSAR and deep learning techniques for permafrost degradation monitoring applications. Full article
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26 pages, 3234 KiB  
Article
Time-Series Deformation and Kinematic Characteristics of a Thaw Slump on the Qinghai-Tibetan Plateau Obtained Using SBAS-InSAR
by Zhenzhen Yang, Wankui Ni, Siyuan Ren, Shuping Zhao, Peng An and Haiman Wang
Remote Sens. 2025, 17(13), 2206; https://doi.org/10.3390/rs17132206 - 26 Jun 2025
Viewed by 356
Abstract
Based on ascending and descending orbit SAR data from 2017–2025, this study analyzes the long time-series deformation monitoring and slip pattern of an active-layer detachment thaw slump, a typical active-layer detachment thaw slump in the permafrost zone of the Qinghai-Tibetan Plateau, by using [...] Read more.
Based on ascending and descending orbit SAR data from 2017–2025, this study analyzes the long time-series deformation monitoring and slip pattern of an active-layer detachment thaw slump, a typical active-layer detachment thaw slump in the permafrost zone of the Qinghai-Tibetan Plateau, by using the small baseline subset InSAR (SBAS-InSAR) technique. In addition, a three-dimensional displacement deformation field was constructed with the help of ascending and descending orbit data fusion technology to reveal the transportation characteristics of the thaw slump. The results show that the thaw slump shows an overall trend of “south to north” movement, and that the cumulative surface deformation is mainly characterized by subsidence, with deformation ranging from −199.5 mm to 55.9 mm. The deformation shows significant spatial heterogeneity, with its magnitudes generally decreasing from the headwall area (southern part) towards the depositional toe (northern part). In addition, the multifactorial driving mechanism of the thaw slump was further explored by combining geological investigation and geotechnical tests. The analysis reveals that the thaw slump’s evolution is primarily driven by temperature, with precipitation acting as a conditional co-factor, its influence being modulated by the slump’s developmental stage and local soil properties. The active layer thickness constitutes the basic geological condition of instability, and its spatial heterogeneity contributes to differential settlement patterns. Freeze–thaw cycles affect the shear strength of soils in the permafrost zone through multiple pathways, and thus trigger the occurrence of thaw slumps. Unlike single sudden landslides in non-permafrost zones, thaw slump is a continuous development process that occurs until the ice content is obviously reduced or disappears in the lower part. This study systematically elucidates the spatiotemporal deformation patterns and driving mechanisms of an active-layer detachment thaw slump by integrating multi-temporal InSAR remote sensing with geological and geotechnical data, offering valuable insights for understanding and monitoring thaw-induced hazards in permafrost regions. Full article
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18 pages, 3125 KiB  
Article
Influences of the China–Russia Crude Oil Pipelines on the Characteristics of Soil Bacterial and Fungal Communities in Permafrost Regions of the Da Xing’anling Mountains, Northeast China
by Xue Yang, Yanling Shi, Xiaoying Jin, Zuwang Li, Wenhui Wang, Shuai Huang and Huijun Jin
Forests 2025, 16(7), 1038; https://doi.org/10.3390/f16071038 - 20 Jun 2025
Viewed by 346
Abstract
Engineering disturbances are increasing in permafrost regions of northeastern China, where soil microorganisms play essential roles in biogeochemical cycling and are highly sensitive to linear infrastructure disturbances. However, limited research has addressed how microbial communities respond to different post-engineering-disturbance recovery stages. This study [...] Read more.
Engineering disturbances are increasing in permafrost regions of northeastern China, where soil microorganisms play essential roles in biogeochemical cycling and are highly sensitive to linear infrastructure disturbances. However, limited research has addressed how microbial communities respond to different post-engineering-disturbance recovery stages. This study investigated the impacts of the China–Russia Crude Oil Pipelines (CRCOPs) on soil microbial communities in a typical boreal forest permafrost zone of the Da Xing’anling Mountains. Soil samples were collected from undisturbed forest (the control, CK); short-term disturbed sites associated with Pipeline II, which was constructed in 2018 (SD); and long-term disturbed sites associated with Pipeline I, which was constructed in 2011 (LD). Pipeline engineering disturbances significantly increased soil clay content and pH while reducing soil water content (SWC), soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) (p < 0.05). No significant differences in these soil properties were observed between SD and LD. Bacterial diversity increased significantly, whereas fungal diversity significantly decreased following pipeline disturbances (p < 0.05). The beta diversity of both bacterial and fungal communities differed significantly among the three disturbance types. At the phylum level, pipeline disturbance increased the relative abundances of Proteobacteria, Acidobacteriota, Actinobacteriota, Ascomycota, and Mortierellomycota while reducing those of Bacteroidota and Basidiomycota. These shifts were associated with disturbance-induced changes in soil properties. Microbial co-occurrence networks in SD exhibited greater complexity and connectivity than those in CK and LD, suggesting intensified biotic interactions and active ecological reassembly during the early recovery phase. These findings suggest that pipeline disturbance could drive soil microbial systems into a new stable state that is difficult to restore over the long term, highlighting the profound impacts of linear infrastructure on microbial ecological functions in cold regions. This study provides a scientific basis for ecological restoration and biodiversity conservation in permafrost-affected areas. Full article
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28 pages, 7612 KiB  
Article
Machine Learning Models for Predicting Freeze–Thaw Damage of Concrete Under Subzero Temperature Curing Conditions
by Yanhua Zhao, Bo Yang, Kai Zhang, Aojun Guo, Yonghui Yu and Li Chen
Materials 2025, 18(12), 2856; https://doi.org/10.3390/ma18122856 - 17 Jun 2025
Viewed by 439
Abstract
In high-elevation or high-latitude permafrost areas, persistent subzero temperatures significantly impact the freeze–thaw durability of concrete structures. Traditional methods for studying the frost resistance of concrete in permafrost regions do not provide a complete picture for predicting properties, and new approaches are needed [...] Read more.
In high-elevation or high-latitude permafrost areas, persistent subzero temperatures significantly impact the freeze–thaw durability of concrete structures. Traditional methods for studying the frost resistance of concrete in permafrost regions do not provide a complete picture for predicting properties, and new approaches are needed using, for example, machine learning algorithms. This study utilizes four machine learning models—Support Vector Machine (SVM), extreme learning machine (ELM), long short-term memory (LSTM), and radial basis function neural network (RBFNN)—to predict freeze–thaw damage factors in concrete under low and subzero temperature conservation conditions. Building on the prediction results, the optimal model is refined to develop a new machine learning model: the Sparrow Search Algorithm-optimized Extreme Learning Machine (SSA-ELM). Furthermore, the SHapley Additive exPlanations (SHAP) value analysis method is employed to interpret this model, clarifying the relationship between factors affecting the freezing resistance of concrete and freeze–thaw damage factors. In conclusion, the empirical formula for concrete freeze–thaw damage is compared and validated against the prediction results from the SSA-ELM model. The study results indicate that the SSA-ELM model offers the most accurate predictions for concrete freeze–thaw resistance compared to the SVM, ELM, LSTM, and RBFNN models. SHAP value analysis quantitatively confirms that the number of freeze–thaw cycles is the most significant input parameter affecting the freeze–thaw damage coefficient of concrete. Comparative analysis shows that the accuracy of the SSA-ELMDE prediction set is improved by 15.46%, 9.19%, 21.79%, and 11.76%, respectively, compared with the prediction results of SVM, ELM, LSTM, and RBF. This parameter positively influences the prediction results for the freeze–thaw damage coefficient. Curing humidity has the least influence on the freeze–thaw damage factor of concrete. Comparing the prediction results with empirical formulas shows that the machine learning model provides more accurate predictions. This introduces a new approach for predicting the extent of freeze–thaw damage to concrete under low and subzero temperature conservation conditions. Full article
(This article belongs to the Special Issue Artificial Intelligence in Materials Science and Engineering)
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16 pages, 3817 KiB  
Article
Machine Learning and Morphometric Analysis for Evaluating the Vulnerability of Tundra Landscapes to Thermokarst Hazards in the Lena Delta: A Case Study of Arga Island
by Andrei Kartoziia
GeoHazards 2025, 6(2), 31; https://doi.org/10.3390/geohazards6020031 - 13 Jun 2025
Viewed by 954
Abstract
Analyses of thermokarst hazard risk are becoming increasingly crucial in the context of global warming. A significant aspect of thermokarst research is the mapping of landscapes based on their vulnerability to thermokarst processes. The exponential growth of remote sensing data and the advent [...] Read more.
Analyses of thermokarst hazard risk are becoming increasingly crucial in the context of global warming. A significant aspect of thermokarst research is the mapping of landscapes based on their vulnerability to thermokarst processes. The exponential growth of remote sensing data and the advent of novel techniques have paved the way for the creation of sophisticated techniques for the study of natural disasters, including thermokarst phenomena. This study applies machine learning techniques to assess the vulnerability of tundra landscapes to thermokarst by integrating supervised classification using random forest with morphometric analysis based on the Topography Position Index. We recognized that the thermokarst landscape with the greatest potential for future permafrost thawing occupies 20% of the study region. The thermokarst-affected terrains and water bodies located in the undegraded uplands account for 13% of the total area, while those in depressions and valleys account for 44%. A small part (6%) of the study region represents areas with stable terrains within depressions and valleys that underwent topographic alterations and are likely to maintain stability in the future. This approach enables big geodata-driven predictive modeling of permafrost hazards, improving thermokarst risk assessment. It highlights machine learning and Google Earth Engine’s potential for forecasting landscape transformations in vulnerable Arctic regions. Full article
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25 pages, 15092 KiB  
Article
Simulation of Active Layer Thickness Based on Multi-Source Remote Sensing Data and Integrated Machine Learning Models: A Case Study of the Qinghai-Tibet Plateau
by Guoyu Wang, Shuting Niu, Dezhao Yan, Sihai Liang, Yanan Su, Wei Wang, Tao Yin, Xingliang Sun and Li Wan
Remote Sens. 2025, 17(12), 2006; https://doi.org/10.3390/rs17122006 - 10 Jun 2025
Viewed by 449
Abstract
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 [...] Read more.
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. Full article
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45 pages, 3412 KiB  
Article
Microalgae as Bioindicators of Changes in Permafrost Catchments: A Reference Area of the Olyokma Nature Reserve, Yakutia
by Sophia Barinova, Viktor A. Gabyshev, Olga I. Gabysheva and Eduard M. Gabyshev
Water 2025, 17(11), 1686; https://doi.org/10.3390/w17111686 - 2 Jun 2025
Viewed by 453
Abstract
Olyokma Nature Reserve, where we conducted our research, is in Eastern Siberia in the middle taiga zone in an area characterized by continuous permafrost. This is the only protected area in the region with a complete reserve regime, where there is no human [...] Read more.
Olyokma Nature Reserve, where we conducted our research, is in Eastern Siberia in the middle taiga zone in an area characterized by continuous permafrost. This is the only protected area in the region with a complete reserve regime, where there is no human activity. Here, we studied 14 different types of water bodies located along the Olyokma River valley, 13 of which were studied for the first time. For some of the studied water bodies, a high content of biogenic elements was noted, which may be associated with the characteristics of permafrost water bodies, which are under nutrient release from permafrost thaw. The concentration of several biogenic elements, including ammonium, nitrates and phosphates, increases in the water of the lakes toward the bottom of the river valley. In the composition of various communities of these water bodies, including both planktonic and non-planktonic, we identified 246 species and varieties of microalgae. The abundance and biomass of phytoplankton, as well as the number of species, decreased down the river valley. At the same time, at the upper stations there were more diatoms; while at the stations down the valley, green algae came to the fore; and even lower down, cyanobacteria prevailed. At the lower stations, the indicators of microalgae development were minimal. In accordance with the bioindicative properties of microalgae, a decrease in the trophic status of water bodies was noted down the river valley, which, in our opinion, is a characteristic feature of the waters of an undisturbed catchment basin in the permafrost area. This indicates that the studied aquatic ecosystem changes within a set of environmental and biological indicators, that is, it exists in natural conditions for this catchment basin. Research on the territory of Olyokma Nature Reserve allowed us to obtain information on natural transformation and removal of nutrients in permafrost catchments, while excluding the likelihood of anthropogenic impact on these processes. Full article
(This article belongs to the Special Issue Nutrient Cycling and Removal in Watersheds)
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19 pages, 3373 KiB  
Article
A Review of Potential Geological Hazards and Precautions in the Mining of Submarine Natural Gas Hydrate
by Zhanghuang Ye, Wenqi Hu and Qiang Yan
Processes 2025, 13(6), 1669; https://doi.org/10.3390/pr13061669 - 26 May 2025
Viewed by 372
Abstract
Natural gas hydrate (NGH hereafter), commonly known as combustible ice ((CH4)n·mH2O), is an abundant non-conventional clean energy resource. It is mainly located in permafrost areas and submarine sediment layers at depths of 0–200 m and 300~3000 m underwater. Submarine [...] Read more.
Natural gas hydrate (NGH hereafter), commonly known as combustible ice ((CH4)n·mH2O), is an abundant non-conventional clean energy resource. It is mainly located in permafrost areas and submarine sediment layers at depths of 0–200 m and 300~3000 m underwater. Submarine NGH accounts for about 97%. Its commercial mining may be a solution to mankind’s future energy problems, as well as the beginning of a series of geological risks. These risks can be divided into two categories: natural geological hazards and secondary geological accidents. Based on the viewpoints of Earth system science researchers, this paper discusses the main potential geo-hazards of submarine NGH mining: stratum subsidence, seafloor landslides, the greenhouse effect, sand piping, well blowout, and wellbore instability. To minimize the potential catastrophic impacts on the Earth’s ecosystem or mechanical accidents, corresponding technical precautions and policy suggestions have been put forward. Hopefully, this paper will provide a useful reference for the commercial mining of NGH. Full article
(This article belongs to the Special Issue Production of Energy-Efficient Natural Gas Hydrate)
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19 pages, 19558 KiB  
Article
Time-Series InSAR Monitoring of Permafrost-Related Surface Deformation at Tiksi Airport: Impacts of Climate Warming and Coastal Erosion on the Northernmost Siberian Mainland
by Qingkai Yan, Ze Zhang, Xianglong Li, Aoxiang Yan, Lisha Qiu, Andrei Zhang, Andrey Melnikov and Leonid Gagarin
Remote Sens. 2025, 17(10), 1757; https://doi.org/10.3390/rs17101757 - 17 May 2025
Viewed by 646
Abstract
The Arctic is the fastest-warming region on Earth, exhibiting a pronounced “amplifying effect”, which has triggered widespread permafrost thaw and increased the risk of surface deformation. In the Arctic coastal lowlands, permafrost is also affected by shoreline retreat. The impact of these dual [...] Read more.
The Arctic is the fastest-warming region on Earth, exhibiting a pronounced “amplifying effect”, which has triggered widespread permafrost thaw and increased the risk of surface deformation. In the Arctic coastal lowlands, permafrost is also affected by shoreline retreat. The impact of these dual stressors on surface deformation processes in the Arctic coastal lowlands remains poorly understood, particularly in terms of how permafrost thaw and shoreline retreat interact to influence surface stability. To address this gap, we employed PS-InSAR technology to monitor surface deformation from 2017 to 2021 at Tiksi Airport, the northernmost airport on the Siberian mainland, situated adjacent to the Laptev Sea. The results show that Tiksi Airport experiences localized significant surface subsidence, with deformation velocity ranging from −42 to 39 mm/yr. The near-coastal area of Tiksi Airport is strongly influenced by the ocean. Specifically, for extreme subsidence deformation (around –40 mm/yr), the surface subsidence velocity increases by 0.2 mm/yr for every 100 m closer to the coastline. Analysis of these deformation characteristics suggests that the primary causes of subsidence are land surface temperature (LST) warming and erosion by the Laptev Sea, which together lead to increased permafrost thaw. By revealing the combined effects of climate warming and coastal erosion on permafrost stability, this study contributes to enhancing the understanding of infrastructure safety and quality of life for residents in Arctic coastal subsidence areas. Full article
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21 pages, 8587 KiB  
Article
Spatio-Temporal Evolution and Susceptibility Assessment of Thaw Slumps Associated with Climate Change in the Hoh Xil Region, in the Hinterland of the Qinghai–Tibet Plateau
by Xingwen Fan, Zhanju Lin, Miaomiao Yao, Yanhe Wang, Qiang Gu, Jing Luo, Xuyang Wu and Zeyong Gao
Remote Sens. 2025, 17(9), 1614; https://doi.org/10.3390/rs17091614 - 1 May 2025
Viewed by 424
Abstract
Influenced by a warm and humid climate, the permafrost on the Qinghai–Tibet Plateau is undergoing significant degradation, leading to the occurrence of extensive thermokarst landforms. Among the most typical landforms in permafrost areas is thaw slump. This study, based on three periods of [...] Read more.
Influenced by a warm and humid climate, the permafrost on the Qinghai–Tibet Plateau is undergoing significant degradation, leading to the occurrence of extensive thermokarst landforms. Among the most typical landforms in permafrost areas is thaw slump. This study, based on three periods of data from keyhole images of 1968–1970, the fractional images of 2006–2009 and the Gaofen (GF) images of 2018–2019, combined with field surveys for validation, investigates the distribution characteristics and spatiotemporal variation trends of thaw slumps in the Hoh Xil area and evaluates the susceptibility to thaw slumping in this area. The results from 1968 to 2019 indicate a threefold increase in the number and a twofold increase in total area of thaw slumps. Approximately 70% of the thaw slumps had areas less than 2 × 104 m2. When divided into a grid of 3 km × 3 km, about 1.3% (128 grids) of the Hoh Xil region experienced thaw slumping from 1968 to 1970, while 4.4% (420 grids) showed such occurrences from 2018 to 2019. According to the simulation results obtained using the informativeness method, the area classified as very highly susceptible to thaw slumping covers approximately 26% of the Hoh Xil area, while the highly susceptible area covers about 36%. In the Hoh Xil, 61% of the thaw slump areas had an annual warming rate ranging from 0.18 to 0.25 °C/10a, with 70% of the thaw slump areas experiencing a precipitation increase rate exceeding 12 mm/10a. Future assessments of thaw slump development suggest a possible minimum of 41 and a maximum of 405 thaw slumps occurrences annually in the Hoh Xil region. Under rapidly changing climatic conditions, apart from environmental risks, there also exist substantial potential risks associated with thaw slumping, such as the triggering of large-scale landslides and debris flows. Therefore, it is imperative to conduct simulated assessments of thaw slumping throughout the entire plateau to address regional risks in the future. Full article
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