Impact of a retrogressive thaw slump on surrounding vegetation communities in the Fenghuoshan mountains,Qinghai-Tibet Plateau

Under global warming,permafrost around the world is experiencing degradation which is especially so on the Third Pole,the Qinghai-Tibet Plateau(QTP),China.Retrogressive thaw slump(RTS)is one of the thermokarst features caused by rapid degradation of ice rich permafrost,which transforms landforms and threatens infrastructures,and even affects the terrestrial carbon cycle.In this work,vegetation communities surrounding a RTS in the Fenghuoshan Mountains of the interior portion of the Qinghai-Tibet Plateau have been investigated to examine the impact from RTS.This investigation indicates that the occurrence of RTS influences the vegetation community by altering their habitats,especially the soil water content,which forces the vegetation community to evolve in order to adapt to the alterations.In the interior part of RTS where it has been disturbed tremendously,alterations have produced a wider niche and richer plant species.This favors species of a wet environment in a habitat where it was a relatively dry environment of alpine steppe prior to the occurrence of RTS.This study adds to limited observations regarding the impact of RTS to vegetation community on the QTP and helps us to reach a broader understanding of the effects of permafrost degradation as well as global warming.

High-resolution assessment of retrogressive thaw slump susceptibility in the Qinghai-Tibet Engineering Corridor

Under the rapidly warming climate in the Arctic and high mountain areas,permafrost is thawing,leading to various hazards at a global scale.One common permafrost hazard termed retrogressive thaw slump(RTS)occurs extensively in ice-rich permafrost areas.Understanding the spatial and temporal distributive features of RTSs in a changing climate is crucial to assessing the damage to infrastructure and decision-making.To this end,we used a machine learning-based model to investigate the environmental factors that could lead to RTS occurrence and create a susceptibility map for RTS along the Qinghai-Tibet Engineering Corridor(QTEC)at a local scale.The results indicate that extreme summer climate events(e.g.,maximum air temperature and rainfall)contributes the most to the RTS occurrence over the flat areas with fine-grained soils.The model predicts that 13%(ca.22,948 km^(2))of the QTEC falls into high to very high susceptibility categories under the current climate over the permafrost areas with mean annual ground temperature at 10 m depth ranging from-3 to-1℃.This study provides insights into the impacts of permafrost thaw on the stability of landscape,carbon stock,and infrastructure,and the results are of value for engineering planning and maintenance.

Machine learning-based predictions of current and future susceptibility to retrogressive thaw slumps across the Northern Hemisphere

Retrogressive thaw slumps(RTSs)caused by the thawing of ground ice on permafrost slopes have dramatically increased and become a common permafrost hazard across the Northern Hemisphere during previous decades.However,a gap remains in our comprehensive understanding of the spatial controlling factors,including the climate and terrain,that are conducive to these RTSs at a global scale.Using machine learning methodologies,we mapped the current and future RTSs susceptibility distributions by incorporating a range of environmental factors and RTSs inventories.We identified freezing-degree days and maximum summer rainfall as the primary environmental factors affecting RTSs susceptibility.The final ensemble susceptibility map suggests that regions with high to very high susceptibility could constitute(11.6±0.78)%of the Northern Hemisphere's permafrost region.When juxtaposed with the current(2000-2020)RTSs susceptibility map,the total area with high to very high susceptibility could witness an increase ranging from(31.7±0.65)%(SSP585)to(51.9±0.73)%(SSP126)by the 2041-2060.The insights gleaned from this study not only offer valuable implications for engineering applications across the Northern Hemisphere,but also provide a long-term insight into the potential change of RTSs in permafrost regions in response to climate change.

Potential of Multi‑temporal InSAR for Detecting Retrogressive Thaw Slumps: A Case of the Beiluhe Region of the Tibetan Plateau

Permafrost degradation due to climate warming is severely reducing slope stability by increasing soil pore water pressure and decreasing shear strength.Retrogressive thaw slumps(RTSs)are among the most dynamic landforms in permafrost areas,which can result in the instability of landscape and ecosystem.However,the spatiotemporal characteristics of surface deformation of RTSs are still unclear,and the potentials of deformation properties in mapping large-scale RTSs need to be further assessed.In this study,we applied a multi-temporal Interferometric Synthetic Aperture Radar(MT-InSAR)method to map the spatiotemporal variations in surface deformation of RTSs in the Beiluhe region of the Tibetan Plateau by using 112 scenes of Sentinel-1 SAR data acquired from 2017 to 2021.The deformation rates of RTSs ranged from−35 to 20 mm/year,and three typical motion stages were inferred by analyzing the deformation variation trend of the headwall of RTSs:stable,abrupt thaw,and linear subsidence.A total of 375 RTSs were identifed in the Mati Hill region by combining InSAR-based deformation results with visual interpretation of optical remote sensing images.Among them,76 RTSs were newly developed,and 26%more than the inventory derived from the optical images alone.This study demonstrated that the combination of InSAR-derived deformation with optical images has signifcant potential for detecting RTSs with high accuracy and efciency at the regional scale.

Three‑Dimensional Numerical Modeling of Ground Ice Ablation in a Retrogressive Thaw Slump and Its Hydrological Ecosystem Response on the Qinghai‑Tibet Plateau,China

Retrogressive thaw slumps(RTSs),which frequently occur in permafrost regions of the Qinghai-Tibet Plateau(QTP),China,can cause signifcant damage to the local surface,resulting in material losses and posing a threat to infrastructure and ecosystems in the region.However,quantitative assessment of ground ice ablation and hydrological ecosystem response was limited due to a lack of understanding of the complex hydro-thermal process during RTS development.In this study,we developed a three-dimensional hydro-thermal coupled numerical model of a RTS in the permafrost terrain at the Beilu River Basin of the QTP,including ice–water phase transitions,heat exchange,mass transport,and the parameterized exchange of heat between the active layer and air.Based on the calibrated hydro-thermal model and combined with the electrical resistivity tomography survey and sample analysis results,a method for estimating the melting of ground ice was proposed.Simulation results indicate that the model efectively refects the factual hydro-thermal regime of the RTS and can evaluate the ground ice ablation and total suspended sediment variation,represented by turbidity.Between 2011 and 2021,the maximum simulated ground ice ablation was in 2016 within the slump region,amounting to a total of 492 m^(3),and it induced the reciprocal evolution,especially in the headwall of the RTS.High ponding depression water turbidity values of 28 and 49 occurred in the thawing season in 2021.The simulated ground ice ablation and turbidity events were highly correlated with climatic warming and wetting.The results ofer a valuable approach to assessing the efects of RTS on infrastructure and the environment,especially in the context of a changing climate.