This page has only limited features, please log in for full access.
On 18 January 2016, the Zhangjiazhuang high-speed railway tunnel in Ledu, Qinghai Province, China, underwent serious deformation and structural damage. A crack formed at the top of the tunnel and the concrete on the crown peeled off. As a result, the tunnel could not be operated for three months. In order to determine the types and spatial distribution of the landslides in the region and the surface deformation characteristics associated with the tunnel deformation, we used field geological and geomorphological surveys, unmanned aerial vehicle image interpretation and differential interferometric synthetic aperture radar (D-InSAR) surface deformation monitoring. Nine ancient and old landslides were identified and analysed in the study area. Surface deformation monitoring and investigation of buildings in several villages on the slope front showed that the tunnel deformation was not related to deep-seated gravitational slope deformation. However, surface deformation monitoring revealed an active NEE-SWW fault in the area intersecting the tunnel at the location of the tunnel rupture. This constitutes a plausible mechanism for the deformation of the tunnel. Our study highlights the need for detailed engineering geomorphological investigations to better predict the occurrence of tunnel deformation events in the future.
Xing-Min Meng; Tian-Jun Qi; Yan Zhao; Tom Dijkstra; Wei Shi; Yin-Fei Luo; Yuan-Zhao Wu; Xiao-Jun Su; Fu-Meng Zhao; Jin-Hui Ma; Yi Zhang; Guan Chen; Dong-Xia Chen; Mao-Sheng Zhang. Deformation of the Zhangjiazhuang high-speed railway tunnel: an analysis of causal mechanisms using geomorphological surveys and D-InSAR monitoring. Journal of Mountain Science 2021, 18, 1920 -1936.
AMA StyleXing-Min Meng, Tian-Jun Qi, Yan Zhao, Tom Dijkstra, Wei Shi, Yin-Fei Luo, Yuan-Zhao Wu, Xiao-Jun Su, Fu-Meng Zhao, Jin-Hui Ma, Yi Zhang, Guan Chen, Dong-Xia Chen, Mao-Sheng Zhang. Deformation of the Zhangjiazhuang high-speed railway tunnel: an analysis of causal mechanisms using geomorphological surveys and D-InSAR monitoring. Journal of Mountain Science. 2021; 18 (7):1920-1936.
Chicago/Turabian StyleXing-Min Meng; Tian-Jun Qi; Yan Zhao; Tom Dijkstra; Wei Shi; Yin-Fei Luo; Yuan-Zhao Wu; Xiao-Jun Su; Fu-Meng Zhao; Jin-Hui Ma; Yi Zhang; Guan Chen; Dong-Xia Chen; Mao-Sheng Zhang. 2021. "Deformation of the Zhangjiazhuang high-speed railway tunnel: an analysis of causal mechanisms using geomorphological surveys and D-InSAR monitoring." Journal of Mountain Science 18, no. 7: 1920-1936.
Artificial dams are one of the most common hydraulic structures for mitigating debris flow disasters in alpine valley regions. However, performance alteration and failure after successive debris flows can lead to dam failure, releasing large amounts of materials within a very short time; moreover, the contribution of artificial dam failures to debris flows is poorly understood. This study quantitatively analyzed the artificial dam failure effects based on the numerical simulations of the Zhouqu '8.8' debris flow, with three scenarios: all nine dams failed (S1); no dams were ever built (S2); all nine dams remained intact (S3). The results showed that artificial dam failures had a significant amplifying effect on the magnitude of a debris flow. The maximum velocity and flow depth decreased by 20% and 11.2% if all the dams did not collapse; comparison of S1 and S2 showed that discharge and velocity at the front of the debris flow increased by 54.6% and 89%, the bulk density and yield stress increased by 3.3% and 5.7%, due to artificial dam failures. This could increase the destructive capacity of a debris flow and the possibility of a river blockage. A single artificial dam failure could locally amplify the magnitude of debris flow. Overall, on the catchment scale, the magnitude of a debris flow was dominated by topography and channel geometry, which can reduce the amplification effect of dam failures at locations where the channel was curved. However, where the channel was straight and flat, the flow velocity and discharge increased cumulatively by 3 m/s and 637 m3/s due to cascading failure. In addition, a comprehensive scheme combining ecological and engineering measures to mitigate debris flow disasters is discussed. This quantitative study is important and urgent needed to understand the amplification effect of dam failures and to implement debris flow mitigation in alpine valley regions.
Yan Chong; Guan Chen; Xingmin Meng; Yunpeng Yang; Wei Shi; Shiqiang Bian; Yi Zhang; Dongxia Yue. Quantitative analysis of artificial dam failure effects on debris flows – A case study of the Zhouqu ‘8.8’ debris flow in northwestern China. Science of The Total Environment 2021, 792, 148439 .
AMA StyleYan Chong, Guan Chen, Xingmin Meng, Yunpeng Yang, Wei Shi, Shiqiang Bian, Yi Zhang, Dongxia Yue. Quantitative analysis of artificial dam failure effects on debris flows – A case study of the Zhouqu ‘8.8’ debris flow in northwestern China. Science of The Total Environment. 2021; 792 ():148439.
Chicago/Turabian StyleYan Chong; Guan Chen; Xingmin Meng; Yunpeng Yang; Wei Shi; Shiqiang Bian; Yi Zhang; Dongxia Yue. 2021. "Quantitative analysis of artificial dam failure effects on debris flows – A case study of the Zhouqu ‘8.8’ debris flow in northwestern China." Science of The Total Environment 792, no. : 148439.
Groups of landslides induced by heavy rainfall are widely distributed on a global basis and they usually result in major losses of human life and economic damage. However, compared with landslides induced by earthquakes, inventories of landslides induced by heavy rainfall are much less common. In this study we used high-precision remote sensing images before and after continuous heavy rainfall in southern Tianshui, China, from 20 June to 25 July 2013, to produce an inventory of 14,397 shallow landslides. Based on the results of landslide inventory, we utilized machine learning and the geographic information system (GIS) to map landslide susceptibility in this area and evaluated the relative weight of various factors affecting landslide development. First, 18 variables related to geomorphic conditions, slope material, geological conditions, and human activities were selected through collinearity analysis; second, 21 selected machine learning models were trained and optimized in the Python environment to evaluate the susceptibility of landslides. The results showed that the ExtraTrees model was the most effective for landslide susceptibility assessment, with an accuracy of 0.91. This predictive ability means that our landslide susceptibility results can be used in the implementation of landslide prevention and mitigation measures in the region. Analysis of the importance of the factors showed that the contribution of slope aspect (SA) was significantly higher than that of the other factors, followed by planar curvature (PLC), distance to river (DR), distance to fault (DTF), normalized difference vehicle index (NDVI), distance to road (DTR), and other factors. We conclude that factors related to geomorphic conditions are principally responsible for controlling landslide susceptibility in the study area.
Tianjun Qi; Yan Zhao; Xingmin Meng; Guan Chen; Tom Dijkstra. AI-Based Susceptibility Analysis of Shallow Landslides Induced by Heavy Rainfall in Tianshui, China. Remote Sensing 2021, 13, 1819 .
AMA StyleTianjun Qi, Yan Zhao, Xingmin Meng, Guan Chen, Tom Dijkstra. AI-Based Susceptibility Analysis of Shallow Landslides Induced by Heavy Rainfall in Tianshui, China. Remote Sensing. 2021; 13 (9):1819.
Chicago/Turabian StyleTianjun Qi; Yan Zhao; Xingmin Meng; Guan Chen; Tom Dijkstra. 2021. "AI-Based Susceptibility Analysis of Shallow Landslides Induced by Heavy Rainfall in Tianshui, China." Remote Sensing 13, no. 9: 1819.
In recent years, the intensified influences of global climate change and human activities have increased the frequency of large-scale debris flow disasters. As a result, main river channels often become blocked, thus forming a disaster chain of rivers dammed by debris flow followed by outburst flooding. In order to quickly and easily reveal the dynamic process of a debris flow dam breach, and quantitatively predict the outburst flood hazard, this study takes the Zhouqu “8.8” debris flow barrier dam in Western China as an example. Based on a stability assessment, China Institute of Water Resources and Hydropower Research’s Dam Breach Slope (DBS-IWHR), China Institute of Water Resources and Hydropower Research’s Dam Breach (DB-IWHR), and Hydrologic Engineering Center’s River Analysis System (HEC-RAS) were integrated to simulate the development of dam breach, breach flood, and outburst flood evolution, respectively, under different scenarios. The simulated peak discharge flow of the actual spillway was 317.15 m3/s, which was consistent with the actual discharge of 316 m3/s. The results under different scenarios showed that, with the increased inflow of the barrier lake, the erosion rate of the dam increased, the peak discharge of the dam break flood increased, the peak arrival time shortened, and the downstream flooding area increased. These findings could provide scientific support for risk management and emergency decision-making with respect to barrier dam failure.
Heyi Yang; Guan Chen; Yan Chong; Jiacheng Jin; Wei Shi. Quantitative Prediction of Outburst Flood Hazard of the Zhouqu “8.8” Debris Flow-Barrier Dam in Western China. Water 2021, 13, 639 .
AMA StyleHeyi Yang, Guan Chen, Yan Chong, Jiacheng Jin, Wei Shi. Quantitative Prediction of Outburst Flood Hazard of the Zhouqu “8.8” Debris Flow-Barrier Dam in Western China. Water. 2021; 13 (5):639.
Chicago/Turabian StyleHeyi Yang; Guan Chen; Yan Chong; Jiacheng Jin; Wei Shi. 2021. "Quantitative Prediction of Outburst Flood Hazard of the Zhouqu “8.8” Debris Flow-Barrier Dam in Western China." Water 13, no. 5: 639.
Land subsidence is one of the major urban geological hazards, which seriously restricts the development of many cities in the world. As one of the major cities in China, Xi’an has also been experiencing a large area of land subsidence due to excessive exploitation of groundwater. Since the Heihe Water Transfer Project (HWTP) became fully operational in late 2003, the problem of subsidence has been restrained, but other issues, such as ground rebounds, have appeared, and the effect of the underground space utilization on land subsidence remains unsolved. The spatial-temporal pattern of land subsidence and rebound in Xi’an after HWTP and their possible cause have so far not been well understood. In this study, the evolutionary characteristics of land subsidence and rebound in Xi’an city from 2007–2019 was investigated using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-SAR) technology to process the Advanced Land Observing Satellite (ALOS) and Sentinel-1A SAR datasets, and their cause and the correlation with groundwater level changes and the underground space utilization were discussed. We found that the land subsidence rate in the study area slowed from 2007–2019, and the subsidence area shrank and gradually developed into three relatively independent and isolated subsidence areas primarily. Significant local rebound deformation up to 22 mm/y commenced in the groundwater recharge region during 2015–2019. The magnitude of local rebound was dominated by the rise in groundwater level due to HWTP, whereas tectonic faults and ground fissures control the range of subsidence and the uplift area. The influence of building load on surface deformation became increasingly evident and primarily manifested by slowing the subsidence reduction trend. Additionally, land subsidence caused by the disturbances during the subway construction period was stronger than that in the operational stage. Future land subsidence in Xi’an is predicted to be alleviated overall, and the areas of rebound deformation will continue increasing for a limited time. However, uneven settlement range may extend to the Qujiang and Xixian New District due to the rapid urban construction. Our results could provide a scientific basis for land subsidence hazard mitigation, underground space planning, and groundwater management in Xi’an or similar regions where severe ground subsidence was induced by rapid urbanization.
Wei Shi; Guan Chen; Xingmin Meng; Wanyu Jiang; Yan Chong; Yi Zhang; Ying Dong; Maosheng Zhang. Spatial-Temporal Evolution of Land Subsidence and Rebound over Xi’an in Western China Revealed by SBAS-InSAR Analysis. Remote Sensing 2020, 12, 3756 .
AMA StyleWei Shi, Guan Chen, Xingmin Meng, Wanyu Jiang, Yan Chong, Yi Zhang, Ying Dong, Maosheng Zhang. Spatial-Temporal Evolution of Land Subsidence and Rebound over Xi’an in Western China Revealed by SBAS-InSAR Analysis. Remote Sensing. 2020; 12 (22):3756.
Chicago/Turabian StyleWei Shi; Guan Chen; Xingmin Meng; Wanyu Jiang; Yan Chong; Yi Zhang; Ying Dong; Maosheng Zhang. 2020. "Spatial-Temporal Evolution of Land Subsidence and Rebound over Xi’an in Western China Revealed by SBAS-InSAR Analysis." Remote Sensing 12, no. 22: 3756.
Previous studies have shown that the mechanical effects of vegetation roots on slope stability can be classified as additional cohesion effects and anchorage effects. The present study investigated the combined mechanical effects (additional cohesion effects and anchorage effects) of vegetation on a slope with coarse-grained soil in the mountainous region (significantly prone to slope failure) of Gansu Province, China. A detailed survey of tree density, root system morphology and slope profiles was conducted, and we also assessed the soil cohesion provided by the root systems of monospecific stands of Robinia pseudoacacia growing in different locations on the slope. The measured data were incorporated into a numerical slope model to calculate the stability of the slope under the influence of trees. The results indicated that it was necessary to consider the anchoring effect of coarse roots when estimating the mechanical effects of trees on slope stability. In particular, the FoS (factor of safety) of the slope was increased by the presence of trees. The results also demonstrated that vegetation increased slope stability. The reinforcing effects were most significant when the trees were planted along the entire slope. Although the reinforcing effects contributed by trees were limited (only 4–11%), they were essential for making optimal use of vegetation for enhancing slope stability. Overall, vegetation development can make a major contribution to ecosystem restoration in the study region.
Siyuan Wang; Minmin Zhao; Xingmin Meng; Guan Chen; Runqiang Zeng; Qiang Yang; Yi Liu; Biao Wang. Evaluation of the Effects of Forest on Slope Stability and Its Implications for Forest Management: A Case Study of Bailong River Basin, China. Sustainability 2020, 12, 6655 .
AMA StyleSiyuan Wang, Minmin Zhao, Xingmin Meng, Guan Chen, Runqiang Zeng, Qiang Yang, Yi Liu, Biao Wang. Evaluation of the Effects of Forest on Slope Stability and Its Implications for Forest Management: A Case Study of Bailong River Basin, China. Sustainability. 2020; 12 (16):6655.
Chicago/Turabian StyleSiyuan Wang; Minmin Zhao; Xingmin Meng; Guan Chen; Runqiang Zeng; Qiang Yang; Yi Liu; Biao Wang. 2020. "Evaluation of the Effects of Forest on Slope Stability and Its Implications for Forest Management: A Case Study of Bailong River Basin, China." Sustainability 12, no. 16: 6655.
Geological conditions along the Karakorum Highway (KKH) promote the occurrence of frequent natural disasters, which pose a serious threat to its normal operation. Landslide susceptibility mapping (LSM) provides a basis for analyzing and evaluating the degree of landslide susceptibility of an area. However, there has been limited analysis of actual landslide activity processes in real-time. The SBAS-InSAR (Small Baseline Subsets-Interferometric Synthetic Aperture Radar) method can fully consider the current landslide susceptibility situation and, thus, it can be used to optimize the results of LSM. In this study, we compared the results of LSM using logistic regression and Random Forest models along the KKH. Both approaches produced a classification in terms of very low, low, moderate, high, and very high landslide susceptibility. The evaluation results of the two models revealed a high susceptibility of land sliding in the Gaizi Valley and the Tashkurgan Valley. The Receiver Operating Characteristic (ROC) curve and historical landslide verification points were used to compare the evaluation accuracy of the two models. The Area under Curve (AUC) value of the Random Forest model was 0.981, and 98.79% of the historical landslide points in the verification points fell within the range of high and very high landslide susceptibility degrees. The Random Forest evaluation results were found to be superior to those of the logistic regression and they were combined with the SBAS-InSAR results to conduct a new LSM. The results showed an increase in the landslide susceptibility degree for 2808 cells. We conclude that this optimized landslide susceptibility mapping can provide valuable decision support for disaster prevention and it also provides theoretical guidance for the maintenance and normal operation of KKH.
Fumeng Zhao; Xingmin Meng; Yi Zhang; Guan Chen; Xiaojun Su; Dongxia Yue. Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology. Sensors 2019, 19, 2685 .
AMA StyleFumeng Zhao, Xingmin Meng, Yi Zhang, Guan Chen, Xiaojun Su, Dongxia Yue. Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology. Sensors. 2019; 19 (12):2685.
Chicago/Turabian StyleFumeng Zhao; Xingmin Meng; Yi Zhang; Guan Chen; Xiaojun Su; Dongxia Yue. 2019. "Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology." Sensors 19, no. 12: 2685.
Lanzhou New District is the first and largest national-level new district in the Loess Plateau region of China. Large-scale land creation and rapid utilization of the land surface for construction has induced various magnitudes of land subsidence in the region, which is posing an increasing threat to the built environment and quality of life. In this study, the spatial and temporal evolution of surface subsidence in Lanzhou New District was assessed using Persistent Scatterer Interferometric Synthetic Aperture radar (PSInSAR) to process the ENVISAT SAR images from 2003–2010, and the Small Baseline Subset (SBAS) InSAR to process the Sentinel-1A images from 2015–2016. We found that the land subsidence exhibits distinct spatiotemporal patterns in the study region. The spatial pattern of land subsidence has evidently extended from the major urban zone to the land creation region. Significant subsidence of 0–55 mm/year was detected between 2015 and 2016 in the land creation and urbanization area where either zero or minor subsidence of 0–17.2 mm/year was recorded between 2003 and 2010. The change in the spatiotemporal pattern appears to be dominated mainly by the spatial heterogeneity of land creation and urban expansion. The spatial associations of subsidence suggest a clear geological control, in terms of the presence of compressible sedimentary deposits; however, subsidence and groundwater fluctuations are weakly correlated. We infer that the processes of land creation and rapid urban construction are responsible for determining subsidence over the region, and the local geological conditions, including lithology and the thickness of the compressible layer, control the magnitude of the subsidence process. However, anthropogenic activities, especially related to land creation, have more significant impacts on the detected subsidence than other factors. In addition, the higher collapsibility and compressibility of the loess deposits in the land creation region may be the underlying mechanism of macro-subsidence in Lanzhou New District. Our results provide a useful reference for land creation, urban planning and subsidence mitigation in the Loess Plateau region, where the large-scale process of bulldozing mountains and valley infilling to create level areas for city construction is either underway or forthcoming.
Guan Chen; Yi Zhang; Runqiang Zeng; Zhongkang Yang; Xi Chen; Fumeng Zhao; Xingmin Meng. Detection of Land Subsidence Associated with Land Creation and Rapid Urbanization in the Chinese Loess Plateau Using Time Series InSAR: A Case Study of Lanzhou New District. Remote Sensing 2018, 10, 270 .
AMA StyleGuan Chen, Yi Zhang, Runqiang Zeng, Zhongkang Yang, Xi Chen, Fumeng Zhao, Xingmin Meng. Detection of Land Subsidence Associated with Land Creation and Rapid Urbanization in the Chinese Loess Plateau Using Time Series InSAR: A Case Study of Lanzhou New District. Remote Sensing. 2018; 10 (2):270.
Chicago/Turabian StyleGuan Chen; Yi Zhang; Runqiang Zeng; Zhongkang Yang; Xi Chen; Fumeng Zhao; Xingmin Meng. 2018. "Detection of Land Subsidence Associated with Land Creation and Rapid Urbanization in the Chinese Loess Plateau Using Time Series InSAR: A Case Study of Lanzhou New District." Remote Sensing 10, no. 2: 270.
The determining of landslide-prone areas in mountainous terrain is essential for land planning and hazard mitigation. In this paper, a comparative study using three statistical models including weight of evidence model (WoE), logistic regression model (LR) and support vector machine method (SVM) was undertaken in the Zhouqu to Wudu segment in the Bailong River Basin, Southern Gansu, China. Six conditionally independent environmental factors, elevation, slope, aspect, distance from fault, lithology and settlement density, were selected as the explanatory variables that may contribute to landslide occurrence based on principal component analysis (PCA) and Chi-square test. The relation between landslide distributions and these variables was analyzed using the three models and the results then used to calculate the landslide susceptibility (LS). The performance of the models was then evaluated using both the highly accurate deformation signals produced by using the Small Baseline Subset Interferometric Synthetic Aperture Radar technique and Receiver Operating Characteristic (ROC) curve. Results show more deformation points in areas with high and very high LS levels, and also more stable points in areas with low and very low LS levels for the SVM model. In addition, the SVM has larger area under the ROC curve. It indicates that the SVM has better prediction accuracy and classified ability. For the interpretability, the WoE derives the class of factors that most contributed to landsliding in the study area, and the LR reveals that factors including elevation, settlement density and distance from fault played major roles in landslide occurrence and distribution, whereas the SVM cannot provide relative weights for the variables. The outperformed SVM could be employed to determine potential landslide zones in the study area. Outcome of this research would provide preliminary basis for general land planning such as choosing new urban areas and infrastructure construction in the future, as well as for landslide hazard mitigation in Bailong River Basin.
Zhengtuan Xie; Guan Chen; Xingmin Meng; Yi Zhang; Liang Qiao; Long Tan. A comparative study of landslide susceptibility mapping using weight of evidence, logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin, China. Environmental Earth Sciences 2017, 76, 313 .
AMA StyleZhengtuan Xie, Guan Chen, Xingmin Meng, Yi Zhang, Liang Qiao, Long Tan. A comparative study of landslide susceptibility mapping using weight of evidence, logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin, China. Environmental Earth Sciences. 2017; 76 (8):313.
Chicago/Turabian StyleZhengtuan Xie; Guan Chen; Xingmin Meng; Yi Zhang; Liang Qiao; Long Tan. 2017. "A comparative study of landslide susceptibility mapping using weight of evidence, logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin, China." Environmental Earth Sciences 76, no. 8: 313.