Qinghai-Tibet Engineering Corridor Research Articles

Enhanced detection of freeze‒thaw induced landslides in Zhidoi county (Tibetan Plateau, China) with Google Earth Engine and image fusion

Freeze‒thaw induced landslides (FTILs) in grasslands on the Tibetan Plateau are a geological disaster leading to soil erosion. These landslides reduce biodiversity and intensify landscape fragmentation, which in turn are strengthen by the persistent climate change and increased anthropogenic activities. However, conventional techniques for mapping FTILs on a regional scale are impractical due to their labor-intensive, costly, and time-consuming nature. This study focuses on improving FTILs detection by implementing image fusion-based Google Earth Engine (GEE) and a random forest algorithm. Integration of multiple data sources, including texture features, index features, spectral features, slope, and vertical‒vertical polarization data, allow automatic detection of the spatial distribution characteristics of FTILs in Zhidoi county, which is located within the Qinghai‒Tibet Engineering Corridor (QTEC). We employed statistical techniques to elucidate the mechanisms influencing FTILs occurrence. The enhanced method identifies two schemes that achieve high accuracy using a smaller training sample (scheme A: 94.1%; scheme D: 94.5%) compared to other methods (scheme B: 50.0%; scheme C: 95.8%). This methodology is effective in generating accurate results using only ∼10% of the training sample size necessitated by other methods. The spatial distribution patterns of FTILs generated for 2021 are similar to those obtained using various other training sample sources, with a primary concentration observed along the central region traversed by the QTEC. The results highlight the slope as the most crucial feature in the fusion images, accounting for 93% of FTILs occurring on gentle slopes ranging from 0° to 14°. This study provides a theoretical framework and technological reference for the identification, monitoring, prevention and control of FTILs in grasslands. Such developments hold the potential to benefit the management of grassland ecosystem, reduce economic losses, and promote grassland sustainability.

Accelerating thermokarst lake changes on the Qinghai–Tibetan Plateau

As significant evidence of ice-rich permafrost degradation due to climate warming, thermokarst lake was developing and undergoing substantial changes. Thermokarst lake was an essential ecosystem component, which significantly impacted the global carbon cycle, hydrology process and the stability of the Qinghai–Tibet Engineering Corridor. In this paper, based on Sentinel-2 (2021) and Landsat (1988–2020) images, thermokarst lakes within a 5000 m range along both sides of Qinghai–Tibet Highway were extracted to analyse the spatio-temporal variations. The results showed that the number and area of thermokarst lake in 2021 were 3965 and 4038.6 ha (1 ha = 10,000 m2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{2}$$\\end{document}), with an average size of 1.0186 ha. Small thermokarst lakes (<\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$<\\,$$\\end{document}1 ha) accounted for 85.65% of the entire lake count, and large thermokarst lakes (>\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>\\,$$\\end{document}10 ha) occupied for 44.92% of the whole lake area. In all sub-regions, the number of small lake far exceeds 75% of the total lake number in each sub-region. R1 sub-region (around Wudaoliang region) had the maximum number density of thermokarst lakes with 0.0071, and R6 sub-region (around Anduo region) had the minimum number density with 0.0032. Thermokarst lakes were mainly distributed within elevation range of 4300 m–5000 m a.s.l. (94.27% and 97.13% of the total number and size), on flat terrain with slopes less than 3∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document} (99.17% and 98.47% of the total number and surface) and in the north, south, and southeast aspects (51.98% and 50.00% of the total number and area). Thermokarst lakes were significantly developed in warm permafrost region with mean annual ground temperature (MAGT) > − 1.5 ∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}C, accounting for 47.39% and 54.38% of the total count and coverage, respectively. From 1988 to 2020, in spite of shrinkage or even drain of small portion of thermokarst lake, there was a general expansion trend of thermokarst lake with increase in number of 195 (8.58%) and area of 1160.19 ha (41.36%), which decreased during 1988–1995 (− 702 each year and − 706.27 ha/yr) and then increased during 1995–2020 (184.96–702 each year and 360.82 ha/yr). This significant expansion was attributed to ground ice melting as rising air temperature at a rate of 0.03–0.04 ∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}C/yr. Followed by the increasing precipitation (1.76–3.07 mm/yr) that accelerated the injection of water into lake.

Spatial distribution of supra-permafrost groundwater in the Qinghai‒Tibet Engineering Corridor using inversion models

Supra-permafrost groundwater (SPG) is a key factor that causes damage to highways and railways in the Qinghai‒Tibet Engineering Corridor (QTEC). It is difficult to monitor SPG in the field due to their complex formation mechanisms and movement characteristics. Traditional single-site field monitoring studies limit the spatial and temporal precision of SPG spatial distribution. To determine the moisture content of shallow soils and the SPG distribution along the QTEC, this work employed the temperature vegetation dryness index and remote sensing models for groundwater table distribution models. The accuracies of the models were validated using measurements obtained from different sites in the corridor. In the permafrost zones of the QTEC, 72%, 22% and 6% of the SPG were located at depths of 0.5–1, <0.5 and >1 m, respectively. Meanwhile, 79.4% of the area along the Qinghai‒Tibet Highway (QTH) (Xidatan‒Tanggula) section contained SPG. In these sections with SPG, 37.9% have an SPG table at depths of 0.5–0.8 m. This study preliminarily explored the SPG distribution in the QTEC with a 30 m resolution. The findings can help improve the spatial scale of SPG research, provide a basis for the analysis of the hydrothermal mechanisms, and serve as a guide in the assessment of operational risks and road structure designs.

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 km2) 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 °C. 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.

Influence of Climate Warming on the Ground Surface Stability over Permafrost along the Qinghai–Tibet Engineering Corridor

The warming climate has posed a serious threat on ground surface stability. In permafrost regions, ground surface instability may induce engineering and geological disasters, especially for the engineering corridor. It is difficult to evaluate ground surface stability over permafrost because the stability is influenced by various factors in permafrost regions. Many single index models cannot comprehensively evaluate the ground surface stability for permafrost. We, therefore, proposed an evaluation model considering different influential factors based on the trapezoidal fuzzy Analytical Hierarchy Process (AHP) method. And the ground surface stability was calculated and analyzed along the Qinghai–Tibet Engineering Corridor under three climate warming conditions (the slow climate warming, the medium climate warming and the rapid climate warming). The results show that the ground surface stability influential factors, including the mean annual ground temperature, the active layer thickness, and the volume ice content, will be greatly changed with the warming climate. By 2100, the percentage of high-temperature permafrost (−0.5 °C &lt; T ≤ 0 °C) will increase about 29.45% with rapid climate warming. The active layer thickness will have an average thickening rate of about 0.030 m/year. Most of the high ice content permafrost will change to low ice content permafrost. The ground surface stability, therefore, will be greatly changed with the warming climate along the Qinghai–Tibet Engineering Corridor. Compared to the present, the stable area will decrease about 5.28% by 2050 under the slow climate warming. And that is approximately 7.91% and 21.78% under the medium and rapid climate warming, respectively. While in year 2100, the decrement is obviously increased. The stable area will decrease about 11.22% under the slow climate warming and about 17.3% under the medium climate warming. The proportion of stable area, however, has an increasing trend under the rapid climate warming. This phenomenon is mainly caused by the warming climate which can lead to the permafrost being degraded to melting soil. The unstable area is mainly distributed near the Chumaer River high plain, Tuotuohe–Yanshiping, Wudaoliang, Tangula Mountains, and other high-temperature permafrost areas. This paper provides a reference for geological hazard prevention and engineering construction along the Qinghai–Tibet Engineering Corridor.

Risk Zoning of Permafrost Thaw Settlement in the Qinghai–Tibet Engineering Corridor

The Qinghai–Tibet Plateau is the highest and largest permafrost area in the middle and low latitudes of China. In this region, permafrost thaw settlement is the main form of expressway subgrade disaster. Therefore, the quantitative analysis and regionalization study of permafrost thaw settlement deformation are of great significance for expressway construction and maintenance in the Qinghai–Tibet region. This paper establishes a thaw settlement prediction model using the thaw settlement coefficient and thaw depth. The thaw depth was predicted by the mean annual ground temperatures and active-layer thicknesses using the Radial Basis Function (RBF) neural network model, and the thaw settlement coefficient was determined according to the type of ice content. Further, the distribution characteristics of thaw settlement risk of the permafrost subgrade in the study region were mapped and analyzed. The results showed that the thaw settlement risk was able to be divided into four risk levels, namely significant risk, high risk, medium risk and low risk levels, with the areas of these four risk levels covering 3868.67 km2, 1594.21 km2, 2456.10 km2 and 558.78 km2, respectively, of the total study region. The significant risk level had the highest proportion among all the risk levels and was mainly distributed across the Chumar River Basin, Beiluhe River Basin and Gaerqu River Basin regions. Moreover, ice content was found to be the main factor affecting thaw settlement, with thaw settlement found to increase as the ice content increased.

Preliminary Study on InSAR-Based Uplift or Subsidence Monitoring and Stability Evaluation of Ground Surface in the Permafrost Zone of the Qinghai–Tibet Engineering Corridor, China

Against the background of global warming, permafrost areas are facing increasing thawing, and the threat to the surface of the Qinghai–Tibet Engineering Corridor (QTEC) is serious. It is imperative to understand the current surface deformation and analyze the changes spatiotemporal characteristics for future warnings. At present, observation of a long time series and overall coverage of vertical ground deformation in QTEC are lacking. This paper takes the permafrost deformation of the QTEC as its research object. It uses the pretreated LiCSAR product and combines it with the LiCSBAS package to obtain monitoring results of the long time series deformation of the engineering corridor’s surface. The SAR image acquisition date is taken as the constraint, the results covering the whole processing area are selected, and then the vertical deformation information covering the entire engineering corridor area by ignoring the north–south displacement is calculated. The results show that the surface of the study area, as a whole, slightly subsided between May 2017 and March 2022, and the vertical deformation rate was mostly distributed at −27.068 mm/yr − 18.586 mm/yr, with an average of −1.06 mm/yr. Vertical deformation dominated at 52.84 percent of the study area, of which settlement accounted for 27.57 percent and uplift accounted for 25.27 percent. According to the statistics of the normal distribution of deformation velocity per pixel, a total of 77% of the engineering corridor was stable, with a vertical deformation rate between −6.964 mm/yr and −4.844 mm/yr, and 17.7% of the region was sub-stable, with a settling rate of −12.868 mm/yr − –6.964 mm/yr. The unstable regions included areas with settlement rates greater than 12.868 mm/yr and uplift rates greater than 10.748 mm/yr, representing 4.4 percent and 0.9 percent of the total area, respectively, for a total of 5.3 percent. The results of this paper can be used as the theoretical basis and as basic data for decision making and scientific research in various departments, and they are of great significance for surface stability assessment and early warnings along engineering corridors and traffic projects.

Changes in the ground surface temperature in permafrost regions along the Qinghai–Tibet engineering corridor from 1900 to 2014: A modified assessment of CMIP6

Numerous studies were published in the last two decades to evaluate and project the permafrost changes in its thermal state, mainly based on the soil temperature datasets from the Coupled Model Intercomparison Project (CMIP), and discuss the impacts of permafrost changes on regional hydrological, ecological and climatic systems and even carbon cycles. However, limited monitored soil temperature data are available to validate the CMIP outputs, resulting in the over-projection of future permafrost changes in CMIP3 and CMIP5. Moreover, future permafrost changes in CMIP6, particularly over the Qinghai–Tibet Plateau (QTP), where permafrost covers more than 40% of its territory, are still unknown. To address this gap, we evaluated and calibrated the monthly ground surface temperature (GST; 5 cm below the ground surface), which was often used as the upper boundary to simulate and project permafrost changes derived from 19 CMIP6 Earth System Models (ESMs) against in situ measurements over the QTP. We generated the monthly GST series from 1900 to 2014 for five sites based on the linear calibration models and validated them through the three other sites using the same calibration methods. Results showed that all of the ESMs could capture the dynamics of in situ GST with high correlations (r > 0.90). However, large errors were detected with a broad range of centred root-mean-square errors (1.14–4.98 °C). The Top 5 model ensembles (MME5) performed better than most individual ESMs and averaged multi-model ensembles (MME19). The calibrated GST performed better than the GST obtained from MME5. Both annual and seasonal GSTs exhibited warming trends with an average annual rate of 0.04 °C per decade in the annual GST. The average seasonal warming rate was highest in winter and spring and lowest in summer. This reconstructed GST data series could be used to simulate the long-term permafrost temperature over the QTP.

Spatiotemporal Variations of Soil Temperature at 10 and 50 cm Depths in Permafrost Regions along the Qinghai-Tibet Engineering Corridor

Soil temperature plays an essential role in the permafrost thermal state and degradation process. Especially the soil temperatures at 10 cm and 50 cm depths in the active layer, which are much easier to be observed in situ, have great effects on the surface water cycles and vegetation, and could be used as the upper boundary for permafrost models to simulate the thermal state of the permafrost and active layer thicknesses. However, due to the limitations of the observation data, there are still large uncertainties in the soil temperature data, including at these two depths, in the permafrost region of Qinghai–Tibet Plateau (QTP). In this study, we evaluated and calibrated the applicability of four daily shallow soil temperature datasets (i.e., MERRA-2, GLDAS-Noah, ERA5-Land, and CFSR) by using the in situ soil temperature data from eight observation sites from 2004 to 2018 in the permafrost region along the Qinghai–Tibet Engineering Corridor. The results revealed that there were different uncertainties for all four sets of reanalysis data, which were the largest (Bias = −2.44 °C) in CFSR and smallest (Bias= −0.43 °C) in GLDAS-Noah at depths of 10 cm and 50 cm. Overall, the reanalysis datasets reflect the trends of soil temperature, and the applicability of reanalysis data at 50 cm depth is better than at 10 cm depth. Furthermore, the GLDAS-Noah soil temperatures were recalibrated based on our observations using multiple linear regression and random forest models. The accuracy of the corrected daily soil temperature was significantly improved, and the RMSE was reduced by 1.49 °C and 1.28 °C at the depth of 10 cm and 50 cm, respectively. The random forest model performed better in the calibration of soil temperature data from GLDAS-Noah. Finally, the warming rates of soil temperature were analyzed, which were 0.0994 °C/a and 0.1005 °C/a at 10 cm and 50 cm depth from 2004 to 2018, respectively.

Reconstruction of past permafrost temperature sequences at three monitoring sites along the Qinghai-Tibet Engineering Corridor

Reconstruction of past permafrost temperature sequences at three monitoring sites along the Qinghai-Tibet Engineering Corridor

Ground Surface Freezing and Thawing Index Distribution in the Qinghai-Tibet Engineering Corridor and Factors Analysis Based on GeoDetector Technique

The land surface temperature obtained from remote sensing was widely used in the simulation of permafrost mapping instead of air temperature with the rapid development of remote sensing technology. The land surface freezing and thawing index (LFI and LTI), which is commonly regarded as the ground surface freezing and thawing index (GFI and GTI), can produce certain errors in the simulation of permafrost distribution on the Qinghai–Tibet Plateau. This paper improved the accuracy of the thermal condition of the surface soil in the Qinghai–Tibet Engineering Corridor (QTEC) by calculating the LFI (or LTI) and N-factors. The environmental factors affecting the spatial distribution of the GFI and GTI were detected by the GeoDetector model. Finally, the multiple linear relationships between the GFI (or GTI) and the environmental factors were established. The results from 25 monitoring sites in the QTEC show that the Nf (ratio of GFI to LFI) is 1.088, and the Nt (ratio of GTI to LTI) is 0.554. The explanatory power of the interaction between elevation and latitude for the GFI and GTI is 79.3% and 85.6%, respectively. The multiple linear regression model with six explanatory variables established by GFI (or GTI) has good accuracy. This study can provide relatively accurate upper boundary conditions for the simulation of permafrost distribution in the QTEC region.

Spatial Variability of Active Layer Thickness along the Qinghai–Tibet Engineering Corridor Resolved Using Ground-Penetrating Radar

Active layer thickness (ALT) is a sensitive indicator of response to climate change. ALT has important influence on various aspects of the regional environment such as hydrological processes and vegetation. In this study, 57 ground-penetrating radar (GPR) sections were surveyed along the Qinghai–Tibet Engineering Corridor (QTEC) during 2018–2021, covering a total length of 58.5 km. The suitability of GPR-derived ALT was evaluated using in situ measurements and reference datasets, for which the bias and root mean square error were approximately −0.16 and 0.43 m, respectively. The GPR results show that the QTEC ALT was in the range of 1.25–6.70 m (mean: 2.49 ± 0.57 m). Observed ALT demonstrated pronounced spatial variability at both regional and fine scales. We developed a statistical estimation model that explicitly considers the soil thermal regime (i.e., ground thawing index, TIg), soil properties, and vegetation. This model was found suitable for simulating ALT over the QTEC, and it could explain 52% (R2 = 0.52) of ALT variability. The statistical model shows that a difference of 10 °C.d in TIg is equivalent to a change of 0.67 m in ALT, and an increase of 0.1 in the normalized difference vegetation index (NDVI) is equivalent to a decrease of 0.23 m in ALT. The fine-scale (&lt;1 km) variation in ALT could account for 77.6% of the regional-scale (approximately 550 km) variation. These results provide a timely ALT benchmark along the QTEC, which can inform the construction and maintenance of engineering facilities along the QTEC.

Time-Series Spaceborne InSAR Monitoring of Permafrost Deformation Combined With Backscattering Characteristics: Case Study From the Qinghai–Tibet Engineering Corridor

Global warming and human activities continue to affect the dynamic balance of the Qinghai–Tibet Plateau (QTP) frozen soil environment, affecting the safety and stability of its infrastructure. Spaceborne synthetic aperture radar interferometry (InSAR) is a well-developed Earth observation technology in the last two decades. This study investigated the feasibility of extracting surface deformation in complex and diverse geomorphic landscape regions using ascending–descending orbit combination synthetic aperture radar (SAR) interferometry. The temporal and spatial distribution characteristics of frozen soil deformation and its relationship with climate change were further analyzed. A total of 110 Sentinel-1A ascending and descending SLC images from October 2017 to May 2021 were employed to cover the Qinghai–Tibet engineering corridor. A time-series InSAR (TS-InSAR) method based on a small baseline strategy and backscattering characteristics analysis was developed to estimate the surface deformation in the LOS directions. Then, combined with the geometric parameters of the SAR system, the 2-D deformation results of frozen soil were calculated. Global navigation satellite system (GNSS) data gained from the QHTT Crustal Movement Observation Network of China (CMONOC) reference station was used for validation, demonstrating good agreement in displacement rates and time series. Our study has observed the seasonal components of the GNSS and TS-InSAR results based on a time-series decomposition model. It was revealed that both sets of results are consistent with the existing climate change law, which can reflect the freeze–thaw cycle of frozen soil.

Retrogressive thaw slumps along the Qinghai–Tibet Engineering Corridor: a comprehensive inventory and their distribution characteristics

Abstract. The important Qinghai–Tibet Engineering Corridor (QTEC) covers the part of the Highway and Railway underlain by permafrost. The permafrost on the QTEC is sensitive to climate warming and human disturbance and suffers accelerating degradation. Retrogressive thaw slumps (RTSs) are slope failures due to the thawing of ice-rich permafrost. They typically retreat and expand at high rates, damaging infrastructure, and releasing carbon preserved in frozen ground. Along the critical and essential corridor, RTSs are commonly distributed but remain poorly investigated. To compile the first comprehensive inventory of RTSs, this study uses an iteratively semi-automatic method built on deep learning to delineate thaw slumps in the 2019 PlanetScope CubeSat images over a ∼ 54 000 km2 corridor area. The method effectively assesses every image pixel using DeepLabv3+ with limited training samples and manually inspects the deep-learning-identified thaw slumps based on their geomorphic features and temporal changes. The inventory includes 875 RTSs, of which 474 are clustered in the Beiluhe region, and 38 are near roads or railway lines. The dataset is available at https://doi.org/10.5281/zenodo.6397029​​​​​​​ (Xia et al., 2021a), with the Chinese version at DOI: https://doi.org/10.11888/Cryos.tpdc.272672 (Xia et al. 2021b). These RTSs tend to be located on north-facing slopes with gradients of 1.2–18.1∘ and distributed at medium elevations ranging from 4511 to 5212 m a.s.l. They prefer to develop on land receiving relatively low annual solar radiation (from 2900 to 3200 kWh m−2), alpine meadow covered, and loam underlay. Our results provide a significant and fundamental benchmark dataset for quantifying thaw slump changes in this vulnerable region undergoing strong climatic warming and extensive human activities.

Spatial distribution of saline (salinization) frozen soil in the Qinghai-Tibet Engineering Corridor

Spatial distribution of saline (salinization) frozen soil in the Qinghai-Tibet Engineering Corridor

Identification and Correlation Analysis of Engineering Environmental Risk Factors along the Qinghai–Tibet Engineering Corridor

Global warming has increased the security risk of permafrost environment in the Tibetan Plateau, which has been threatening infrastructures along the Qinghai–Tibet Engineering Corridor (QTEC). Combined with the traditional risk identification and the causal feedback relationship of system dynamics, the authors present a novel engineering environment risk identification model including five risk subsystems, i.e., regional geomorphology, climate change, ecological environment, permafrost environment and water environment. Our model could successfully identify the interaction relationships and transmission path among risk factors of the environment of the QTEC. The basic data calculation, interaction degree analysis and regional distribution characteristic analysis of the identified risk factors were carried out by using a geographic information system (GIS), a partial correlation analysis and a zoning analysis. The results show that the static factors (i.e., elevation, slope, aspect, relief degree of land surface and volume ice content) mainly affected the spatial distribution of environmental risk factors, while the climate change factors (i.e., mean annual air temperature, mean annual precipitation and surface solar radiation), among the dynamic factors, were the root factors of the dynamic changes in environmental risks. The model identified five types of parallel risk paths in the QTEC. This novel method and proposed model can be used to identify and assess multi-scale engineering environmental risks in the cryosphere.

Analysis of Necessity and Feasibility for Ground Improvement in Warm and Ice-Rich Permafrost Regions

Characterized by low bearing capacity and high compressibility, warm and ice-rich frozen soil is a kind of problematic soil, which makes the original frozen ground formed by of that unreliable to meet the stability requirements of engineering infrastructures and foundations in permafrost regions. With the design and construction of major projects along the Qinghai-Tibet Engineering Corridor (QTEC), such as expressway and airport runway, it is a great challenge to favor the stability of overlying structures by formulating the proper engineering design principles and developing the valid engineering supporting techniques. The investigations carried out in recent years indicated that warm and ice-rich permafrost foundations were widespread, climate warming was significant, and the stability of existing engineering structures was poor, along the QTEC. When the warm and ice-rich frozen ground is used as the foundation soil, the implementation of ground improvement is an alternative measure to enhance the bearing capacity of foundation soil and eliminate the settlement of structures during operation, in order to guarantee the long-term stability of the structures. Based on the key factors determining the physicomechanical properties of frozen soil, an innovative idea of stabilizing the warm and ice-rich frozen soil based on chemical stabilization is proposed in this study, and then, an in situ ground improvement technique is introduced. This study intends to explore the feasibility of ground improvement in warm and ice-rich permafrost regions along the QTEC based on in situ chemical stabilization and provide the technical support and scientific reference to prevent and mitigate the hazards in the construction of major projects in the future.

Detection of Soil Freeze/Thaw States at a High Spatial Resolution in Qinghai-Tibet Engineering Corridor

The freeze/thaw (F/T) state of the soil is an essential indicator for permafrost monitoring. However, current soil F/T products with a coarse spatial resolution (>1 km) have limited their use on a fine scale. In this letter, a new approach integrating two microwave sensors [i.e., Sentinel-1 and advanced microwave scanning radiometer 2 (AMSR-2)] is developed to identify the soil F/T state at a spatial resolution of 10 m in the Qinghai-Tibet engineering corridor (QTEC). Using a linear regression model to integrate the coarse AMSR-2 data with the finer Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST), the frozen frequency product at a 1-km resolution can be obtained. Then, the high-spatial-resolution F/T map based on Sentinel-1 synthetic aperture radar (SAR) time-series images can be produced using the threshold extracted from each pixel of frozen-frequency products. We tested soil F/T results via both visual and quantitative evaluations. The overall accuracy of the 10-m soil F/T map achieves 84.63% and 77.09% for ascending and descending orbits based on four meteorological stations, respectively.

InSAR measurements of surface deformation over permafrost on Fenghuoshan Mountains section, Qinghai-Tibet Plateau

The permafrost development in the Qinghai-Tibet Engineering Corridor (QTEC) is affected by natural environment changes and human engineering activities. Human engineering activities may damage the permafrost growing environment, which in turn impact these engineering activities. Thus high spatial-temporal resolution monitoring over the QTEC in the permafrost region is very necessary. This paper presents a method for monitoring the frozen soil area using the intermittent coherence-based small baseline subset (ICSBAS). The method can improve the point density of the results and enhance the interpretability of deformation results by identifying the discontinuous coherent points according to the coherent value of time series. Using the periodic function that models the seasonal variation of permafrost, we separate the long wavelength atmospheric delay and establish an estimation model for the frozen soil deformation. Doing this can raise the monitoring accuracy and improve the understanding of the surface deformation of the frozen soil. In this study, we process 21 PALSAR data acquired by the Alos satellite with the proposed ICSBAS technique. The results show that the frozen soil far from the QTR in the study area experiences frost heave and thaw settlement (4.7 cm to 8.4 cm) alternatively, while the maximum settlement along the QTR reaches 12 cm. The interferomatric syntnetic aperture radar (In-SAR)-derived results are validated using the ground leveling data nearby the Beiluhe basin. The validation results show the InSAR results have good consistency with the leveling data in displacement rates as well as time series. We also find that the deformation in the permafrost area is correlated with temperature, human activities and topography. Based on the interfering degree of human engineering activities on the permafrost environment, we divide the QTEC along the Qinghai-Tibet Railway into engineering damage zone, transition zone and natural permafrost.

An integrated observation dataset of the hydrological and thermal deformation in permafrost slopes and engineering infrastructure in the Qinghai–Tibet Engineering Corridor

Abstract. Across the Qinghai–Tibet Plateau (QTP) there is a narrow engineering corridor with widely distributed slopes called the Qinghai–Tibet Engineering Corridor (QTEC), where a variety of important infrastructures are concentrated. These facilities are transportation routes for people, materials, energy, etc. from inland China to the Tibet Autonomous Region. From Golmud to Lhasa, the engineering corridor covers 632 km of permafrost containing the densely developed Qinghai–Tibet Railway and Qinghai–Tibet Highway, as well as power and communication towers. Slope failure in permafrost regions, caused by permafrost degradation, ground ice melting, etc., affects the engineering construction and permafrost environments in the QTEC. We implement a variety of sensors to monitor the hydrological and thermal deformation between permafrost slopes and permafrost engineering projects in the corridor. In addition to soil temperature and moisture sensors, the global navigation satellite system (GNSS), terrestrial laser scanning (TLS), and unmanned aerial vehicles (UAVs) were adopted to monitor the spatial distribution and changes in thermal deformation. An integrated dataset of hydrological and thermal deformation in permafrost engineering and slopes in the QTEC from the 1950s to 2020, including meteorological and ground observations, TLS point cloud data, and RGB and thermal infrared (TIR) images, can be of great value for estimating the hydrological and thermal impact and stability between engineering and slopes under the influence of climate change and engineering disturbance. The dataset and code were uploaded to the Zenodo repository and can be accessed through https://zenodo.org/communities/qtec (last access: 23 June 2021), including meteorological and ground observations at https://doi.org/10.5281/zenodo.5009871 (Luo et al., 2020d), TLS measurements at https://doi.org/10.5281/zenodo.5009558 (Luo et al., 2020a), UAV RGB and TIR images at https://doi.org/10.5281/zenodo.5016192 (Luo et al., 2020b), and R code for permafrost indices and visualisation at https://doi.org/10.5281/zenodo.5002981 (Luo et al., 2020c).