Search Results (12)

The Qinghai–Tibet Railway is located in the most fragile and sensitive terrestrial ecosystem of the Qinghai–Tibet Plateau in China, and once the ecological environment is damaged, it is difficult to restore. This study, based on the Google Earth Engine platform, focuses on the section of the Qinghai–Tibet Railway from Xining to Jianghe. It utilizes Landsat series satellite imagery data from 1986 to 2020 to calculate the Remote Sensing Ecological Index (RSEI). This approach enables large-scale and long-term dynamic monitoring, analysis, and assessment of the ecological changes along the Qinghai–Tibet Railway corridor. The results indicate that (1) the average RSEI of the study area increased from 0.37 in 1986 to 0.53 in 2020, showing an overall trend of improvement. The ecological environment quality is mainly categorized as medium and good. (2) The quality of the ecological environment in the areas along the railway experienced fluctuations during different periods of railway construction and operation. From 1986 to 1994, after the first phase of the railway opened, the overall ecological environment showed a relative decline in quality. From 1994 to 2002, the ecological quality of 60% of the region saw slight improvements. During the extension construction of the second phase of the railway from 2002 to 2007, the regional ecology fluctuated again. However, from 2013 to 2020, during the operational period, a stable recovery trend was observed in the ecological environment. (3) The ecological environment in the study area is influenced by multiple factors. Different railway station areas exhibit strong spatial heterogeneity. The impact of single factors is significant, with the existence of spatial stratification and enhanced interactions among multiple factors. The strongest interactive effects are observed between land use types, the intensity of human activities, and temperature. Full article

The use of water detection (WD) indices to infer daily discharge (Q_d) has a great potential to enrich needed hydrological data for understanding fluvial processes driving the morphological changes of braided rivers. However, no consensus has been reached on which one stands out for use in mid-sized braided rivers. In this study, we compared the physical characteristics of three most commonly used WD indices, the Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Moisture Index (NDMI), for two mid-sized braided reach segments in the Qinghai-Tibet Plateau, China, that have different morphological structures. Relying on the Google Earth Engine web interface, we calculated the total mean water width (WWt) based on the detected surface-water areas (A_s) and braiding index (BI), as well as the mean values (m) of these indices over about four decades at the braided corridor scale (cs) (mNDWIcs, mMNDWIcs, and mNDMIcs). We then examined different responses of these indices to water and non-water features and their best threshold values for characterizing channel structures. Our analyses demonstrated that (1) NDWI and MNDWI perform well for detecting braided channel structures with the threshold of zero; (2) WWt is generally better correlated to Q_d in a linear style than WD indices do, particularly when calculated from MNDWI; and (3) among WD indices calculated at the braided corridor scale, mMNDWIcs shows a better relationship with Q_d than mNDMIcs does. Finally, we provided mechanisms that may explain these differences in terms of photometric discrepancies in calculating WWt and WD indices and the impact of image resolution on their calculations. Full article

The Qinghai–Tibet Plateau (QTP) is among one of the most sensitive regions to global environmental change worldwide. Although climate change and engineering construction on the QTP have jointly modified the regional vegetation activity, little is known about how this affects the vegetation variation. Using Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) data from 2000–2021, this study investigated the spatiotemporal variation of vegetation activity and the compound effects of climate change and reconstruction along the Tibetan section of the G318 national highway (TG318) through a novel contribution quantification model and partial correlation analysis, as well as through a structural equation model (SEM). The results showed that the mean growing-season EVI increased significantly at a rate of about 0.0020/year in the western side of the TG318 after reconstruction but fluctuated in the east. Reconstruction generally had a significant effect on the mean growing-season EVI, with contributions of 7.67%, 19.12%, 18.24%, and −4.15% in different sections of the TG318, whereas climate change contributed from −10.14% to 8.84% of the total variation. The mean growing-season EVI negatively correlated with snow cover and minimum temperature in humid and sub-humid regions, whereas it was positively related with vapor pressure in semi-arid regions. Moreover, there existed an obvious lag effect of climate change on the mean growing-season EVI, with lag time generally decreasing from west to east and apparent heterogeneity among different months and regions. These findings will help better understand the environmental impacts along the engineering corridors and provide a scientific basis for ecological conservation in the QTP regions. Full article

The Three-North Shelterbelt Project is the largest ecological engineering initiative in China to date, distinguished by its immense scale, extended construction period, and widespread benefits for the population. The gross ecosystem product (GEP) serves as a crucial indicator for assessing ecological benefits. This study focuses on the Three Northern Protection Forest Project Area, utilizing GEP calculations for the years 2000 to 2020. This study evaluates variations in the production values of different ecosystem services to reflect the ecological conservation benefits of the restoration project. Additionally, it analyzes the spatiotemporal evolution and trends of the GEP calculations, offering data references and decision support for the enduring efficacy of ecological restoration projects. The findings are as follows. (i) Between 2000 and 2020, the GEP of the Three-North region exhibited significant growth with continuous enhancement of various ecosystem service functions; the most substantial rate of change was observed in the water conservation function, followed by carbon sequestration and oxygen release, soil retention, windbreak and sand fixation, flood regulation, and environmental purification functions. (ii) The per-unit area value of different ecosystem types generally increased; the forest ecosystem displayed the largest growth rate at 61.18%, followed by shrubland ecosystems at 49.84%. (iii) The spatial distribution of ecosystem service in the Three-North region displayed a clustering trend alongside notable spatial heterogeneity. High-high clustering zones were identified in areas such as the Tianshan Mountains, Altai Mountains, Qilian Mountains, and Greater and Lesser Khingan Mountains. Conversely, low-low clustering areas were scattered, forming patchy distributions in regions like the Tarim Basin, northern Qinghai-Tibet Plateau, and the Hexi Corridor. This study, by analyzing the gross ecosystem product of the Three-North Shelterbelt Project region, unveils the spatial distribution characteristics, trends, and variations in ecosystem service values over the past two decades. It provides data support and decision guidance for the long-term efficacy of future ecological conservation and restoration projects. This study incorporates the GEP accounting method into the assessment of the effectiveness of major conservation projects. Compared to the traditional methods of effectiveness assessment, this represents a significant exploration and innovation. Full article

Due to the impact of climate warming and engineering construction, thaw-slumping has developed extensively along the Qinghai–Tibet Project Corridor. These landslide disasters not only destroy the fragile ecology of the Qinghai–Tibet Plateau but also threaten the security of the Qinghai–Tibet Project Corridor. Because remote-sensing images lack imaging data inside the landslide body, and the excavation of boreholes has blindness and inefficiency, the ground-penetrating radar method with high efficiency and deep imaging has been developed and applied in the detection and treatment of thaw-slumping. To more accurately divide the soil-layered structure of the thaw-slumping body and obtain the key elements of the thaw-slumping such as temperature change trend and relative water content, we propose the use of amplitude event axis tracking and amplitude energy attenuation calculation to divide the fine layering of the thaw-slumping body. In addition, based on layer division, we introduce two attribute parameters to participate in the calculation of relative water content. These two attribute parameters are the weighted average frequency attribute, which reflects the temperature change trend, and the sweetness attribute, which reflects the change in the physical properties of the underground medium. The calculated 3D profile and time slice of the relative water content comprehensively show the change characteristics and enrichment area of the internal relative water content of the thaw-slumping. These methods and results are valuable for the characterization, evaluation, and treatment of thaw-slumping. Full article

Engineering corridors on the Qinghai–Tibet Plateau have substantially modified the regional ecosystem functions and environment, resulting in changes in the alpine ecosystem. In addition, the building and operation of these engineering corridors have led to rapid permafrost degradation, which in turn has impacted local vegetation along these corridors. This study investigated vegetation changes and their driving factors by the methods of coefficient of variation, correlation analysis, and GeoDetector in a 30 km wide buffer zone at each side along the National Highway G214 (G214) at the northern and southern flanks of the Bayan Har Mountains in part of the source area of the Yellow and Yangtze rivers on the southern Qinghai Plateau, West China. The following results were obtained: (1) The Normalized Difference Vegetation Index in Growing Season (NDVI_gs) rose slightly in 2010–2019, with an average annual change rate of 0.006/a. Patterns of NDVI_gs along the G214 exhibited “low at the northern flank and high at the southern flank of the Bayan Har Mountains”. (2) Spatially, average NDVI_gs increased from the first buffer zone at the distance of 0–10 km from the highway centerline to the second buffer zone at 20–30 km perpendicularly away from the G214. Furthermore, the first buffer zone had the lowest coefficient of variation, possibly due to a low vegetation recovery as a result of the greatest influence of the G214 on NDVI_gs at 0–10 km. (3) Furthermore, annual precipitation (AP) was the dominant factor for significantly (p < 0.01) and positively influencing the variations in NDVI_gs (R = 0.75, p < 0.01). Additionally, NDVI_gs was more strongly influenced by the two combined factors than any single one, with the highest q-value (0.74) for the interactive influences of AP and annual average air temperature (AAAT) and followed by that of the AP and mean annual ground temperature (MAGT) at the depth of zero annual amplitude (15 m). Evidently, the construction and operation of the G214 have directly and indirectly affected vegetation through changing environmental variables, with significant impacts on NDVI_gs extended at least 20 km outwards from the highway. This study helps better understand the environmental impacts along the engineering corridors in elevational permafrost regions at mid and low latitudes and their management. Full article

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. Full article

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 N_f (ratio of GFI to LFI) is 1.088, and the N_t (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. Full article

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. Full article

Thermokarst lakes (TLs) caused by the thaw of massive ground ice in ice-rich permafrost landscapes are increasing and have strong impacts on the hydro–ecological environment and human infrastructure on the Qinghai–Tibet Plateau (QTP), however, its spatial distribution characteristics and environmental controls have not been underrepresented at the local scale. Here, we analyzed the spatial distribution of small TLs along the Qinghai–Tibet Engineering Corridor (QTEC) based on high-resolution (up to 2.0 m) satellite images. The TLs gathered in the plains and upland plateau and covered 8.3% of the QTEC land. We deployed a random-frost method to investigate the suitable environmental conditions for TLs. Climate including summer rainfall and the air temperature was the most important factor controlling the TL distribution, followed by topography and soil characteristics that affected the ground ice content. TL susceptibility was mapped based on the combinations of climate, soil, and topography grid data. On average, around 20% of the QTEC area was in a high to very-high-susceptibility zone that is likely to develop TLs in response to climate change. This study improved the understanding of controlling factors for TL development but also provided insights into the conditions of massive ground ice and was helpful to assess the impacts of climate change on ecosystem processes and engineering design. Full article

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. Full article

The Qinghai-Tibet (QT) Plateau Engineering Corridor is located in the hinterland of the QT Plateau, which is highly sensitive to global climate change. Climate change causes permafrost degradation, which subsequently affects vegetation growth. This study focused on the vegetation dynamics and their relationships with climate change and human activities in the region surrounding the QT Plateau Engineering Corridor. The vegetation changes were inferred by applying trend analysis, the Mann-Kendall trend test and abrupt change analysis. Six key regions, each containing 40 nested quadrats that ranged in size from 500 × 500 m to 20 × 20 km, were selected to determine the spatial scales of the impacts from different factors. Cumulative growing season integrated enhanced vegetation index (CGSIEVI) values were calculated for each of the nested quadrats of different sizes to indicate the overall vegetation state over the entire year at different spatial scales. The impacts from human activities, a sudden increase in precipitation and permafrost degradation were quantified at different spatial scales using the CGSIEVI values and meteorological data based on the double mass curve method. Three conclusions were derived. First, the vegetation displayed a significant increasing trend over 23.6% of the study area. The areas displaying increases were mainly distributed in the Hoh Xil. Of the area where the vegetation displayed a significant decreasing trend, 72.4% was made up of alpine meadows. Second, more vegetation, especially the alpine meadows, has begun to degenerate or experience more rapid degradation since 2007 due to permafrost degradation and overgrazing. Finally, an active layer depth of 3 m to 3.2 m represents a limiting depth for alpine meadows. Full article