Qinghai-Tibet Plateau Permafrost Research Articles

Thermokarst landslides susceptibility evaluation across the permafrost region of the central Qinghai-Tibet Plateau: Integrating a machine learning model with InSAR technology

Thermokarst landslides (TLs), which are made up of retrogressive thaw slumps (RTSs) and active-layer detachments slides (ALDSs), are quickly increasing in the central Qinghai-Tibet Plateau (QTP) permafrost area. TLs induce many environmental problems and threaten the safety of infrastructure. A landslide susceptibility map is crucial to prevent the negative impacts of these landslides. However, traditional thermokarst landslides susceptibility (TLS) evaluations do not consider real-time surface deformation information. Therefore, we propose a novel method that integrates a conventional machine learning model with ground surface deformation. Nine influencing factors, including slope, normalized difference vegetation index, elevation, precipitation, thawing degree days, soil content, active layer thickness, water content, and vegetation type were selected based on the q-index detector, and support vector machine was employed to obtain an initial model (IM). We obtained surface deformation in the study area using the enhanced Small Baseline Subset (SBAS) method. The accuracy of the InSAR results was validated through comparison with data from two field monitoring cross-sections. Subsequently, we established an integrated model (ITM) by combining the initial model with surface deformation using the contribution matrix, and confirmed the fusion model’s higher rationality and accuracy through comparison with the IM. Furthermore, we examined the impact of the quadtree segmentation method on atmospheric correction and validated the TLS results obtained using the ITM with high-resolution optical remote sensing imagery from GF6. Finally, the influencing factors and distribution characteristics of TLS was analyzed, and the results indicated that climatic conditions are the primary factors affecting the distribution of TLS.

Methane Emissions From the Qinghai‐Tibet Plateau Ponds and Lakes: Roles of Ice Thaw and Vegetation Zone

AbstractComprehensive seasonal observation is essential for accurately quantifying methane (CH4) emissions from ponds and lakes in permafrost regions. Although CH4 emissions during ice thaw are important and highly variable in high‐latitude freshwater ponds and lakes (north of ∼50°N), their contribution is seldom included in estimates of aquatic‐atmospheric CH4 exchange across different alpine ecosystems. Here, we characterized annual CH4 emissions, including emissions during ice thaw, from ponds and lakes across four alpine vegetation zones in the Qinghai‐Tibet Plateau (QTP) permafrost region. We observed significant spatial variability in annual CH4 emission rates (8.44−421.05 mmol m−2 yr−1), CH4 emission rates during ice thaw (0.26−144.39 mmol m−2 yr−1), and the contribution of CH4 emissions during ice thaw to annual emissions (3−33%) across different vegetation zones. Dissolved oxygen concentration under ice, along with substrate availability and water salinity, played critical roles in influencing CH4 flux during ice thaw. We estimated annual CH4 emissions from ponds and lakes in the QTP permafrost region as 0.04 (0.03−0.05) Tg CH4 yr−1 (median (first quartile−third quartile)), with approximately 20% occurring during ice thaw. Notably, the average areal CH4 emission rate from ponds and lakes in the QTP permafrost region amounts to only 8% of that from high‐latitude waterbodies, primarily due to the dominance of large saline lakes with lower CH4 emission rates in the alpine permafrost region. Our findings emphasize the significance of incorporating comprehensive seasonal observation of CH4 emissions across different vegetation zones in better predicting CH4 emissions from alpine ponds and lakes.

Estimation of Permafrost Ground Ice to 10 m Depth on the Qinghai‐Tibet Plateau

ABSTRACTPermafrost ground ice melting could alter hydrological processes in cold regions by releasing water. Currently, there is a lack of gridded data of ground ice from the Qinghai‐Tibet Plateau (QTP). Using 664 borehole sample records, we applied a random forest (RF) method to predict the ground ice content of permafrost between 2 and 10 m depth in three layers (2–3, 3–5, and 5–10 m) at a spatial resolution of 1 km. The RF predictions demonstrated an R2 value exceeding 0.80 for all three layers with a negligible positive overestimation (0.98%–1.85%). The ground ice content of the first layer (2–3 m) can be predicted primarily using climate variables, but the contribution of terrain and soil variables increases as the depth increases. The total water storage of ground ice across the QTP permafrost (2–10 m depth) is approximately 3330.0 km3, with 403.5 km3 in the 2–3 m layer, 857.2 km3 in the 3–5 m layer, and 2069.3 km3 in the 5–10 m layer. This study generated for the first time a gridded dataset of the shallow permafrost ground ice content across the entire QTP which can be used to improve simulations of hydrological processes in the permafrost regions.

Thermokarst lake changes along the Qinghai-Tibet Highway during 1991–2020

Thermokarst lake development significantly affects hydrologic systems, infrastructure stability and biogeochemical processes, while the spatial and temporal changes in thermokarst lakes remain largely unknown. Here, we created a thermokarst lake dataset on the Qinghai-Tibet Plateau (QTP) using a threshold-based mapping method based on Google Earth Engine (GEE) data associated with visual inspection. The dataset includes a thermokarst lake inventory on the QTP at a 10 m resolution produced from Sentinel-2A images and a multitemporal inventory along the Qinghai-Tibet Highway (QTH) from Landsat and Sentinel-2A images. We analyzed the temporal and spatial changes in thermokarst lake area and their relationships to environmental factors. Our results showed that thermokarst lakes on the QTP permafrost region covered a total area of 1572 ± 184 km2, with most of the thermokarst lakes <10,000 m2 in area. The spatial distributions of thermokarst lakes are affected by the ground thermal stability, active layer thickness, vegetation type, and ground ice content. Over the past 30 years, the number and surface area of thermokarst lakes along the QTH have increased by 58.8 % and 83.1 %, respectively, with the increase in lakes likely caused by climate warming and precipitation increasing. This study provides deep insight in the long-term interannual variations and its driving factors in thermokarst lakes along the QTH.

Field test study of a novel solar refrigeration pile in permafrost regions

Cast-in-place piles are popular foundation forms in permafrost regions. The freezing force at the pile-soil interface is the main source of bearing capacity, which is quite sensitive to ground temperature. The warming climate and engineering activities can cause the permafrost to thaw, affecting the long-term stability of the pile foundation. However, the method of cooling pile foundations is rarely reported. This paper proposes a solar refrigeration pile consisting of a solar power system, a compression refrigeration system, and a concrete pile to control the surrounding permafrost temperature. A field test was conducted in the Qinghai-Tibet Plateau permafrost regions to assess the actual cooling performance. The test results showed that the new pile effectively cooled the surrounding permafrost in the warm season without human intervention. After 10 days of cooling, the influence radius of the solar refrigeration pile exceeded 1 m. Furthermore, the solar refrigeration pile significantly improved the bearing capacity. This study provides a practical solution for addressing the challenge of maintaining the stability and bearing capacity of pile foundations in permafrost regions under the influence of climate change and human activities.

Vegetation Types Variations to the South of Ngoring Lake from 2013 to 2020, Analyzed by Hyperspectral Imaging

Studying the variation in vegetation types within the source region of the Yellow River (SRYR) is of great significance for understanding the response of vegetation to climate change and human activities on the Qinghai-Tibet Plateau (QTP) permafrost. In order to understand the characteristics of the variation in vegetation associations in the SRYR under the influence of climate and human activities, two hyperspectral remote sensing images from HJ-1A in 2013 and OHS-3C in 2020 were used to extract the vegetation types located in the area south of Ngoring Lake, covering 437.11 km2 in Maduo County, from the perspective of vegetation associations. Here, the hybrid spectral CNN (HybridSN) model, which is dependent on both spatial and spectral information, was used for vegetation association classifications. On this basis, the variations in vegetation associations from 2013 to 2020 were studied using the transition matrix, and the variation in noxious weeds across different altitude and slope gradients was analyzed. As an example, Thermopsis lanceolata’s spatial distribution pattern and diffusion mechanism were analyzed. The results showed that (1) in addition to noxious weeds, herbage such as Poa poophagorum, Stipa purpurea, Kobresia humilis, and Carex moorcroftii increased, indicating that the overall ecological environment tended to improve, which may be attributed mainly to the development of a warm and humid climate. (2) Most of the noxious weeds were located at low altitudes with an area increase in the 4250–4400 m altitude range and a decrease in the 4400–4500 m altitude range. More attention should be given to the fact that the noxious weeds area increased from 2.88 km2 to 9.02 km2 between 2013 and 2020, which was much faster than that of herbage and may threaten local livestock development. (3) The Thermopsis lanceolate association characterized by an aggregated distribution tended to spread along roads, herdsmen sites, and degraded swamps, which were mainly affected by human activities and swamp degradation.

Phaeochromycins I-K, Three Methylene-Bridged Dimeric Polyketides from Streptomyces sp. 166.

Three new dimeric polyketides, i.e., phaeochromycins I-K (1-3, respectively) and a known polyketide phaeochromycin F (4), were isolated from the culture broth of a saline Qinghai-Tibet Plateau permafrost soil-derived Streptomyces sp. 166#. The structures were determined by analyzing one-dimensional and two-dimensional NMR as well as HRESIMS data. Compounds 2 and 3 exhibited a selective antiproliferative activity against H1299 and HUCCT1 cell lines, exhibiting IC50 values ranging from 8.83 to 10.52 μM.

Variation characteristics of high flows and their responses to climate change in permafrost regions on the Qinghai-Tibet Plateau, China

River flow characteristics in permafrost regions on the Qinghai-Tibet Plateau (QTP) have changed rapidly with the intensification of global warming. However, the specific change characteristics and their responses to changes in influencing factors remain unclear. Based on the multi-year flow data of several typical basins in the QTP permafrost regions, combined with the flow duration curve and percentile flow, this study analyzed the variability of annual peak discharge, Q5, Q10, and Q30 (5%, 10%, and 30% percentile flows in the flow duration curve, respectively) and their response relationships with different climate change factors. In addition, the corresponding relationships between different percentile high flows and annual hydrographs were analyzed. The results indicate that, in the context of global warming, changes in the high flows in permafrost regions are bidirectional, either rising or falling, or both. Moreover, the responses of different percentile high flows to climate change are seasonally distinct. Spring high flows are more sensitive to changes in air temperature and normalized difference vegetation index (NDVI), and summer and autumn high flows are more susceptible to corresponding changes in seasonal average precipitation and rainfall intensity. In addition, different percentile high flows can be used to predetermine the level of annual flood events. Among them, the largest, the larger, and all other general flood events during the annual flood season, can be defined by Q5, Q10, and Q30, respectively. The analysis of different high flows combined with the flow duration curve is essential for the further clarification of the hydrological processes in permafrost regions. The prudent utilization of water resources benefits the sustainable development of human society.

Qinghai‐Tibet Plateau Permafrost at Risk in the Late 21st Century

AbstractGlobal warming has led to permafrost degradation worldwide. The Qinghai‐Tibet Plateau (QTP) hosts most of the world's alpine permafrost, yet its impending changes remain largely unclear, thereby affecting regional hydrological and ecological processes and the global carbon budget. By employing a land surface model adapted to simulate frozen ground, and using state‐of‐the‐art multi‐model and multi‐scenario data from the Coupled Model Intercomparison Project Phase 6, changes in permafrost distribution and its thermal regimes on the QTP are systematically predicted under various shared socioeconomic pathways (SSPs). Projections for SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5 show that most of the continuous permafrost region of the QTP will persist through 2050. Much of the permafrost is likely to degrade in the late 21st century, with projected area losses of 44 ± 4%, 59 ± 5%, and 71 ± 7%, respectively, by 2100. In particular, the Three Rivers Source region in the central eastern part of the QTP is a key area of permafrost degradation, where permafrost is most vulnerable and degradation occurs earliest. The mean annual ground temperature of QTP permafrost will increase by 0.8 ± 0.2°C, 2.0 ± 0.3°C, and 2.6 ± 0.3°C under SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, respectively, and the active layer thickness will increase by 0.7 ± 0.1 m, 1.5 ± 0.3 m, and 3.0 ± 1.0 m, respectively. The surviving permafrost under SSP3‐7.0 and SSP5‐8.5 will be thermally unstable, which is a clear warning sign of complete disappearance. The analysis of permafrost sensitivity to climate change signifies that alpine permafrost on the QTP has low resilience to climate change, in contrast to permafrost in pan‐Artic high latitudes.

Atmospheric moisture sources of drought and wet events during 1979–2019 in the Three-River Source Region, Qinghai-Tibetan Plateau

The soil moisture observation data from the Qinghai-Tibetan Plateau permafrost and alpine wetland (PAW) monitoring network and from the National Center for Environmental Prediction (NCEP) Final Analysis (FNL) from 1989 to 2019 were adopted to drive the Lagrangian backward trajectory model to simulate the water vapour transportation paths and source regions to the three-river source region during dry and wet episodes. The results showed that the water vapour transport paths mainly came from the land and ocean in the west during the extreme drought episodes based on the standardized precipitation index (SPI), including the northern African continent, the eastern European plains, and the mid-latitudes of the Atlantic Ocean. The water vapour source regions were mainly concentrated in the Kashmir region, northeast India and southern Motuo on the Qinghai-Tibet Plateau. When the SPI indicated an extremely wet state, the transport mainly occurred to the east and south, including the Pacific Ocean and the South China Sea, where water vapour entered the mainland from East/South China, passed through the Yangtze River Basin, and finally reached the three-river source region from east or south of the Qinghai-Tibet Plateau, while the water vapour from the Indian Ocean and Arabian Sea passed through the Indian Peninsula and the Bay of Bengal and entered the three-river source region from the western and southern sides of the Qinghai-Tibet Plateau.

River runoff components change variably and respond differently to climate change in the Eurasian Arctic and Qinghai-Tibet Plateau permafrost regions

Cryohydrological processes in the Eurasian Arctic and Qinghai-Tibet Plateau (QTP) permafrost regions have been changing rapidly, yet the details of the river runoff changes are still obscure. Here we use multidecadal natural daily discharge data to compute annual flow duration curves (FDCs) and percentile flows for 20 Eurasian Arctic and QTP river basins with permafrost underlain. We provide detailed trends of various percentile flows that almost all runoff components change variably, either with the distinct magnitude or opposite direction or both. We demonstrate that the lower flows increase monotonically faster than higher flows. Most low flows increase while the high flows show spatial heterogeneity with both increased and decreased trends observed. The portion of deep and total groundwater flow in total discharge increases, with the deep groundwater flow increases faster. Interestingly, the river runoff components respond differently to climatic change factors. The low flows, mainly sustained by groundwater, are more sensitive to warming than high flows, while the high flows are more sensitive to precipitation than low flows. Our results may suggest an increased subsurface hydrological connectivity under the warming climate and thawing permafrost. We show that FDCs have the potential to reveal the long-term runoff components change. Future climatic change may alter the shapes and distributions of FDCs since the asynchronous changes of runoff components, which have important implications for cold region river management and mitigation under climatic change.

Simulation of the Present and Future Projection of Permafrost on the Qinghai‐Tibet Plateau with Statistical and Machine Learning Models

AbstractThe comprehensive understanding of the occurred changes of permafrost, including the changes of mean annual ground temperature (MAGT) and active layer thickness (ALT), on the Qinghai‐Tibet Plateau (QTP) is critical to project permafrost changes due to climate change. Here, we use statistical and machine learning (ML) modeling approaches to simulate the present and future changes of MAGT and ALT in the permafrost regions of the QTP. The results show that the combination of statistical and ML method is reliable to simulate the MAGT and ALT, with the root‐mean‐square error of 0.53°C and 0.69 m for the MAGT and ALT, respectively. The results show that the present (2000–2015) permafrost area on the QTP is 1.04 × 106 km2 (0.80–1.28 × 106 km2), and the average MAGT and ALT are −1.35 ± 0.42°C and 2.3 ± 0.60 m, respectively. According to the classification system of permafrost stability, 37.3% of the QTP permafrost is suffering from the risk of disappearance. In the future (2061–2080), the near‐surface permafrost area will shrink significantly under different Representative Concentration Pathway scenarios (RCPs). It is predicted that the permafrost area will be reduced to 42% of the present area under RCP8.5. Overall, the future changes of MAGT and ALT are pronounced and region‐specific. As a result, the combined statistical method with ML requires less parameters and input variables for simulation permafrost thermal regimes and could present an efficient way to figure out the response of permafrost to climatic changes on the QTP.

Soil Moisture Estimation based on the Distributed Scatterers Adaptive Filter over the QTP Permafrost Region using Sentinel-1 and High-resolution TerraSAR-X Data

ABSTRACT Synthetic aperture radar (SAR) data have been widely and primarily used for soil-moisture estimation. The original radar backscattering coefficients show great noise and temporal-spatial decorrelation due to complex surface features and seasonal vegetation changes, which increase the difficulty of soil-moisture estimation over the Qinghai-Tibet Plateau (QTP). To overcome these limitations, a soil-moisture retrieval method based on the Distributed Scatterers Adaptive Filter (DSAF) is proposed and applied in this paper. First, the statistically homogeneous pixels (SHP) with similar scatter behaviour are identified using the Anderson-Darling (AD) test method. Then, the Distributed Scatterers (DSs) are selected according to the SHPs threshold, and the backscattering coefficients of DSs are filtered using the SHPs distribution and coherences. In order to eliminate the negative influence of vegetation and roughness, the filtered backscattering coefficients are further processed by coupling the Water Cloud Model (WCM) and the images acquired in the winter season. The response of soil moisture to backscattering coefficients is greatly improved. Finally, the backscatter coefficients () are transformed into soil-moisture units by using the Least Square Regression (LSR) model and multi-temporal Change Detection (CD) method, respectively. The 15 scenes of TerraSAR-X images and 18 scenes of Sentinel-1 images in Northern Piedmont river, Northern Tibet, were used for experimental study. The results reveal that the response of the filtered backscattering coefficients to in-situ soil moisture is greatly improved. The soil-moisture content estimated by LSR and CD model using TerraSAR-X data is consistent with in-situ measurements, with coefficient of determination (R 2) of 0.52 and 0.56, Root Mean Square Error (RMSE) of 0.08 and 0.06, respectively. The results show that the proposed method can improve the accuracy of soil-moisture estimation, especially over the complex surface features of the QTP permafrost region.

Small-Baseline Approach for Monitoring the Freezing and Thawing Deformation of Permafrost on the Beiluhe Basin, Tibetan Plateau Using TerraSAR-X and Sentinel-1 Data.

The dynamic changes of the thawing and freezing processes of the active layer cause seasonal subsidence and uplift over a large area on the Qinghai–Tibet Plateau due to ongoing climate warming. To analyze and investigate the seasonal freeze–thaw process of the active layer, we employ the new small baseline subset (NSBAS) technique based on a piecewise displacement model, including seasonal deformation, as well as linear and residual deformation trends, to retrieve the surface deformation of the Beiluhe basin. We collect 35 Sentinel-1 images with a 12 days revisit time and 9 TerraSAR-X images with less-than two month revisit time from 2018 to 2019 to analyze the type of the amplitude of seasonal oscillation of different ground targets on the Beiluhe basin in detail. The Sentinel-1 results show that the amplitude of seasonal deformation is between −62.50 mm and 11.50 mm, and the linear deformation rate ranges from −24.50 mm/yr to 5.00 mm/yr (2018–2019) in the study area. The deformation trends in the Qinghai–Tibet Railway (QTR) and Qinghai–Tibet Highway (QTH) regions are stable, ranging from −18.00 mm to 6 mm. The InSAR results of Sentinel-1 and TerraSAR-X data show that seasonal deformation trends are consistent, exhibiting good correlations 0.78 and 0.84, and the seasonal and linear deformation rates of different ground targets are clearly different on the Beiluhe basin. Additionally, there are different time lags between the maximum freezing uplift or thawing subsidence and the maximum or minimum temperature for the different ground target areas. The deformation values of the alpine meadow and floodplain areas are higher compared with the alpine desert and barren areas, and the time lags of the freezing and thawing periods based on the Sentinel-1 results are longest in the alpine desert area, that is, 86 days and 65 days, respectively. Our research has important reference significance for the seasonal dynamic monitoring of different types of seasonal deformation and the extensive investigations of permafrost in Qinghai Tibet Plateau.

Application of fracturing technology to increase gas production in low-permeability hydrate reservoir: A numerical study

Low temperature and low permeability are the challenges for the development of hydrate reservoirs in permafrost. The ice produced around the production well caused by high depressurization driving force reduces the gas production, and it is necessary to reduce the effect of ice production on gas production. In this work, a new combination of fracturing technology and depressurization method was proposed to evaluate the gas production potential at the site DK-2 in Qinghai-Tibet Plateau Permafrost. A relatively higher intrinsic permeability of the fracture zone surround the horizontal production well was created by the fracturing technology. The simulation results showed that the fracture zone reduced the blocking of production ice to production wells and promoted the propagation of production pressure. And the gas production increased by 2.1 times as the radius of the fracture zone increased from 0 to 4 m in 30 years. Nearly half of the hydrate reservoirs were dissociated in 30 years, and greater than 51.7% of the gas production was produced during the first 10 years. Moreover, production behaviours were sensitive to the depressurization driving force but not to the thermal conductivity. The growth of gas production was not obvious with the intrinsic permeability of the fracture zone higher than 100 mD. The effect of ice production on gas production by fracturing technology and depressurization method was limited.

Warming and monsoonal climate lead to large export of millennial-aged carbon from permafrost catchments of the Qinghai-Tibet Plateau

Permafrost carbon pool destabilization causes substantial fluvial export of soil carbon, yet the export patterns and magnitudes are not well understood. Here we investigated the radiocarbon (14C) in dissolved organic and inorganic carbon (DOC and DIC, respectively) exported from a mid-sized river in the central Qinghai-Tibet Plateau (QTP) permafrost region. We utilized the radiocarbon dating technique to reveal the ages of riverine dissolved carbon and a statistical model to partition the riverine carbon from different age categories. DOC and DIC showed bomb-depleted 14C signatures corresponding to millennial ages. Seasonally, 14C-depleted DOC and DIC ages were associated with active layer thaw and flow path deepening. Spatially, older DOC and DIC were found in the valley sites correlated with warmer permafrost and higher groundwater flow. Further, isotopic mixing models suggested that 83 ± 27% of riverine DOC was derived from active layer and permafrost layer aged carbon. DIC export was comprised of a smaller portion of aged carbon (47.3 ± 2.6%) but a much larger flux of aged carbon due to higher annual DIC export. Interestingly, approximately 56% of annual aged DOC and DIC were exported in the short summer season (July to September). The monsoon climate-induced overlap of high discharge and maximum active layer thaw depth in summer enhanced the remarkably rapid fluvial export of millennial-aged carbon. Annual aged carbon yields in YRSR (275 ± 90 and 1661 ± 91 kg km−2 yr−1 for DOC and DIC, respectively) are much larger than those of Kolyma River (160 ± 89 and 234 ± 105 kg km−2 yr−1 for DOC and DIC, respectively). These results suggest a unique old carbon loss pattern in the QTP permafrost region compared to higher latitude permafrost regions with a non-monsoonal climate. As climate warms, more old carbon export is expected, which may affect the permafrost carbon pool and the river biogeochemical processes.

Net ecosystem carbon budget of a grassland ecosystem in central Qinghai-Tibet Plateau: integrating terrestrial and aquatic carbon fluxes at catchment scale

The effects of aquatic carbon exports on grassland ecosystem carbon balance is unclear. Here we quantified the seasonal and annual net ecosystem carbon budget (NECB) of an alpine grassland ecosystem in the Qinghai-Tibet Plateau (QTP) permafrost region with integrative terrestrial and aquatic carbon flux measurements. The terrestrial carbon fluxes, including the net ecosystem production (NEP) and CH4 flux, were derived from eddy covariance and previous chamber-based measurements. The aquatic carbon fluxes, including dissolved organic carbon, biogenic dissolved inorganic carbon, particulate carbon, and riverine CO2 efflux of the catchment, were determined with stream monitoring. We found that NECB exhibited distinct seasonal features for the grassland ecosystem, which shifted from a carbon sink in growing season (68.8±8.7 g C m−2) to a carbon source in non-growing season (−41.1±2.4 g C m−2), while the NECB (27.7±6 g C m−2 yr−1) demonstrated a net carbon sink at an annual basis. The total aquatic carbon flux (TAC, 11.8±1.5 g C m−2 yr−1) offset 14% of the land carbon assimilation for growing season and 30% of the annual land carbon assimilation after subtracting ecosystem respiration. The higher TAC/NEP ratios in low NEP months indicated that aquatic carbon was more important on offsetting terrestrial carbon sink when NEP was low. Our results show a large contribution of aquatic carbon to NECB in a QTP grassland ecosystem, which suggest that disregarding the aquatic carbon flux can substantially overestimate the strength of terrestrial carbon sink. As aquatic carbon is coupled with hydrological processes, TAC is crucially important for NECB in the cryosphere ecosystem since the drastic hydrology and permafrost change can transport more soil carbon into the fluvial networks. More studies on NECB is needed, especially when the ecosystem have a low NEP and actively changing hydrological processes.

Soil Moisture Calibration Equations for Active Layer GPR Detection—a Case Study Specially for the Qinghai–Tibet Plateau Permafrost Regions

Ground-penetrating radar (GPR) is a convenient geophysical technique for active-layer soil moisture detection in permafrost regions, which is theoretically based on the petrophysical relationship between soil moisture (θ) and the soil dielectric constant (ε). The θ–ε relationship varies with soil type and thus must be calibrated for a specific region or soil type. At present, there is lack of such a relationship for active-layer soil moisture estimation for the Qinghai–Tibet plateau permafrost regions. In this paper, we utilize the Complex Refractive Index Model to establish such a calibration equation that is suitable for active-layer soil moisture estimation with GPR velocity. Based on the relationship between liquid water, temperature, and salinity, the soil water dielectric constant was determined, which varied from 84 to 88, with an average value of 86 within the active layer for our research regions. Based on the calculated soil-water dielectric constant variation range, and the exponent value range within the Complex Refractive Index Model, the exponent value was determined as 0.26 with our field-investigated active-layer soil moisture and dielectric data set. By neglecting the influence of the soil matrix dielectric constant and soil porosity variations on soil moisture estimation at the regional scale, a simple active-layer soil moisture calibration curve, named CRIM, which is suitable for the Qinghai–Tibet plateau permafrost regions, was established. The main shortage of the CRIM calibration equation is that its calculated soil-moisture error will gradually increase with a decreasing GPR velocity and an increasing GPR velocity interpretation error. To avoid this shortage, a direct linear fitting calibration equation, named as υ-fitting, was acquired based on the statistical relationship between the active-layer soil moisture and GPR velocity with our field-investigated data set. When the GPR velocity interpretation error is within ±0.004 m/ns, the maximum moisture error calculated by CRIM is within 0.08 m3/m3. While when the GPR velocity interpretation error is larger than ±0.004 m/ns, a piecewise formula calculation method, combined with the υ-fitting equation when the GPR velocity is lower than 0.07 m/ns and the CRIM equation when the GPR velocity is larger than 0.07 m/ns, was recommended for the active-layer moisture estimation with GPR detection in the Qinghai–Tibet plateau permafrost regions.

Acceleration of thaw slump during 1997–2017 in the Qilian Mountains of the northern Qinghai-Tibetan plateau

Climate warming increases thermokarst landscapes and thus leads to land degradation in the Circum-Arctic regions. Thermokarst landscapes were estimated to cover ~ 20% of the northern permafrost region, and their development is related to ground ice content and topographic conditions. However, changes in thaw slump distribution and development in mid- to low-latitude permafrost areas largely remain unknown. Here, we selected the Qilian Mountains of the northern Qinghai-Tibetan Plateau (QTP) as the study area. Combined with field investigation to measure the boundary of thaw slump using Real Time Kinematic (RTK), we analyzed historical changes in thaw slumps using 1969 and 1997 aerial photographs, 2009 and 2015 satellite imagery, and 2017 unmanned aerial vehicle (UAV) aerial images. The results showed that there are 15 thaw slumps covering an area of 0.03 km2, which were mainly distributed in terrain with a slope of 2–8° and elevation of 3552–3611 m. For the time periods of 1997–2009, 2009–2015, and 2015–2017, the average increase rates of thaw slump areas were approximately 61.8, 60.0, and 156.8 m2/y, and annual headwall retreat rates were approximately 1.3, 1.6 and 2.0 m/y. Based on the slopes, aspects, and altitudes from the Digital Elevation Model generated by UAV imagery, it suggested that geomorphic factors have no significant effect on the growth rates of thaw slump due to high heterogeneities of alpine environments. Our results showed that thaw slumps with polycyclic and active characteristics covered at least 0.9% of northern QTP permafrost regions and are expected to rapidly accelerate with climate warming.

Permafrost Deformation Monitoring Along the Qinghai-Tibet Plateau Engineering Corridor Using InSAR Observations with Multi-Sensor SAR Datasets from 1997-2018.

As the highest elevation permafrost region in the world, the Qinghai-Tibet Plateau (QTP) permafrost is quickly degrading due to global warming, climate change and human activities. The Qinghai-Tibet Engineering Corridor (QTEC), located in the QTP tundra, is of growing interest due to the increased infrastructure development in the remote QTP area. The ground, including the embankment of permafrost engineering, is prone to instability, primarily due to the seasonal freezing and thawing cycles and increase in human activities. In this study, we used ERS-1 (1997–1999), ENVISAT (2004–2010) and Sentinel-1A (2015–2018) images to assess the ground deformation along QTEC using time-series InSAR. We present a piecewise deformation model including periodic deformation related to seasonal components and interannual linear subsidence trends was presented. Analysis of the ERS-1 result show ground deformation along QTEC ranged from −5 to +5 mm/year during the 1997–1999 observation period. For the ENVISAT and Sentinel-1A results, the estimated deformation rate ranged from −20 to +10 mm/year. Throughout the whole observation period, most of the QTEC appeared to be stable. Significant ground deformation was detected in three sections of the corridor in the Sentinel-1A results. An analysis of the distribution of the thaw slumping region in the Tuotuohe area reveals that ground deformation was associated with the development of thaw slumps in one of the three sections. This research indicates that the InSAR technique could be crucial for monitoring the ground deformation along QTEC.