2023 Vol. 14, No. 4

Display Method:
Integrated Disaster Risk Research of the Qinghai-Tibet Plateau Under Climate Change
Tao Ye, Peijun Shi, Peng Cui
2023, 14(4): 507-509. doi: 10.1007/s13753-023-00510-0
Impacts of Climate Change on Snow Avalanche Activity Along a Transportation Corridor in the Tianshan Mountains
Jiansheng Hao, Xueqin Zhang, Peng Cui, Lanhai Li, Yan Wang, Guotao Zhang, Chaoyue Li
2023, 14(4): 510-522. doi: 10.1007/s13753-023-00475-0
Snow avalanches can repeatedly occur along the same track under different snowpack and meteorological conditions during the snow season in areas of snow avalanche activity. The snowfall, air temperature, and snow cover can change dramatically in a warming climate, causing significant changes in the snow avalanche risk. But how the risk of snow avalanche activity during the snow season will change under a warming climate remains an open question. Based on the observed meteorological and snowpack data from 1968 to 2021 and the snow avalanche activity data during the 2011–2021 snow seasons along a transportation corridor in the central Tianshan Mountains that has a typical continental snow climate, we analyzed the temporal distribution of the snow avalanche activity and the impacts of climate change on it. The results indicate that the frequency of the snow avalanche activity is characterized by a Gaussian bimodal distribution, resulting from interactions between the snowfall, air temperature, and snowpack evolution. In addition, the active period of wet snow avalanches triggered by temperature surges and high solar radiation has gradually moved forward from the second half to the first half of March with climate warming. The frequency and size of snowfall-triggered snow avalanches showed only a slight and insignificant increase. These findings are important for rationally arranging snow avalanche relief resources to improve the risk management of snow avalanche disasters, and highlight the necessity to immediately design risk mitigation strategies and disaster risk policies to improve our adaptation to climate change.
Potential of Multi-temporal InSAR for Detecting Retrogressive Thaw Slumps: A Case of the Beiluhe Region of the Tibetan Plateau
Zhiping Jiao, Zhida Xu, Rui Guo, Zhiwei Zhou, Liming Jiang
2023, 14(4): 523-538. doi: 10.1007/s13753-023-00505-x
Permafrost degradation due to climate warming is severely reducing slope stability by increasing soil pore water pressure and decreasing shear strength. Retrogressive thaw slumps (RTSs) are among the most dynamic landforms in permafrost areas, which can result in the instability of landscape and ecosystem. However, the spatiotemporal characteristics of surface deformation of RTSs are still unclear, and the potentials of deformation properties in mapping large-scale RTSs need to be further assessed. In this study, we applied a multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method to map the spatiotemporal variations in surface deformation of RTSs in the Beiluhe region of the Tibetan Plateau by using 112 scenes of Sentinel-1 SAR data acquired from 2017 to 2021. The deformation rates of RTSs ranged from - 35 to 20 mm/year, and three typical motion stages were inferred by analyzing the deformation variation trend of the headwall of RTSs: stable, abrupt thaw, and linear subsidence. A total of 375 RTSs were identified in the Mati Hill region by combining InSAR-based deformation results with visual interpretation of optical remote sensing images. Among them, 76 RTSs were newly developed, and 26% more than the inventory derived from the optical images alone. This study demonstrated that the combination of InSAR-derived deformation with optical images has significant potential for detecting RTSs with high accuracy and efficiency at the regional scale.
Automatic Identification of Thaw Slumps Based on Neural Network Methods and Thaw Slumping Susceptibility
Huarui Zhang, Huini Wang, Jun Zhang, Jing Luo, Guoan Yin
2023, 14(4): 539-548. doi: 10.1007/s13753-023-00504-y
Thaw slumping is a periglacial process that occurs on slopes in cold environments, where the ground becomes unstable and the surface slides downhill due to saturation with water during thawing. In this study, GaoFen-1 remote sensing and fused multi-source feature data were used to automatically map thaw slumping landforms in the Beilu River Basin of the Qinghai–Tibet Plateau. The bi-directional cascade network structure was used to extract edges at different scales, where an individual layer was supervised by labeled edges at its specific scale, rather than directly applying the same supervision to all convolutional neural network outputs. Additionally, we conducted a 5-year multi-scale feature analysis of small baseline subset interferometric synthetic aperture radar deformation, normalized difference vegetation index, and slope, among other features. Our study analyzed the performance and accuracy of three methods based on edge object supervised learning and three preconfigured neural networks, ResNet101, VGG16, and ResNet152. Through verification using site surveys and multi-data fusion results, we obtained the best ResNet101 model score of intersection over union of 0.85 (overall accuracy of 84.59%).The value of intersection over union of the VGG and ResNet152 are 0.569 and 0.773, respectively. This work provides a new insight for the potential feasibility of applying the designed edge detection method to map diverse thaw slumping landforms in larger areas with high-resolution images.
Heterogeneity of Surface Heat Exchange of Slopes and Potential Drivers of the Initiation of Thaw Slump, Qinghai-Tibet Plateau
Xingwen Fan, Wenjiao Li, Xuyang Wu, Miaomiao Yao, Fujun Niu, Zhanju Lin
2023, 14(4): 549-565. doi: 10.1007/s13753-023-00508-8
In the mountainous permafrost area, most thaw slumps are distributed in north or northeast-facing shady slope areas. It is commonly known that there is a heterogeneity in permafrost between different slope aspects, but there has been a lack of detailed measured data to quantitatively evaluate their relationships, and in-depth understandings on how the slope aspects are linked to the distribution of thaw slumps. This study examined the heterogenous thermal regime, soil moisture content, and surface radiation at two slope sites with opposing aspects in a warming permafrost region on the Qinghai-Tibet Plateau (QTP). The results indicate that similar air temperatures (Ta) were monitored on the two slopes, but there were significant differences in ground temperature and moisture content in the active layer from 2016 to 2021. The sunny slope exhibited a higher mean annual ground surface temperature (Ts), and over the five years the mean annual temperature at the top of permafrost was 1.3–1.4℃ warmer on the sunny slope than the shady slope. On the contrary, the near-surface soil moisture content was about 10–13% lower on the sunny slope (~22–27%) than the shady slope (~35–38%) during the thawing season (June–September). Radiation data indicate that significantly higher shortwave downward radiation (DR) appeared at the sunny slope site. However, due to the greater surface albedo, the net radiation (Rn) was lower on the sunny slope. Slope aspect also affects the ground ice content due to its influence on ground temperature, freeze-thaw cycles, and soil moisture. Shady slopes have a shallower burial of ice-rich permafrost compared to sunny slopes. The results highlight greatly different near-surface ground thermal conditions at the two slope sites with different aspects in a mountainous permafrost region. This helps identify the slope-related causes of increasing thaw slumps and provides a basis for predicting their future development.
Three-Dimensional Numerical Modeling of Ground Ice Ablation in a Retrogressive Thaw Slump and Its Hydrological Ecosystem Response on the Qinghai-Tibet Plateau, China
Fujun Niu, Chenglong Jiao, Jing Luo, Junlin He, Peifeng He
2023, 14(4): 566-585. doi: 10.1007/s13753-023-00503-z
Retrogressive thaw slumps (RTSs), which frequently occur in permafrost regions of the Qinghai-Tibet Plateau (QTP), China, can cause significant damage to the local surface, resulting in material losses and posing a threat to infrastructure and ecosystems in the region. However, quantitative assessment of ground ice ablation and hydrological ecosystem response was limited due to a lack of understanding of the complex hydro-thermal process during RTS development. In this study, we developed a three-dimensional hydro-thermal coupled numerical model of a RTS in the permafrost terrain at the Beilu River Basin of the QTP, including ice–water phase transitions, heat exchange, mass transport, and the parameterized exchange of heat between the active layer and air. Based on the calibrated hydro-thermal model and combined with the electrical resistivity tomography survey and sample analysis results, a method for estimating the melting of ground ice was proposed. Simulation results indicate that the model effectively reflects the factual hydro-thermal regime of the RTS and can evaluate the ground ice ablation and total suspended sediment variation, represented by turbidity. Between 2011 and 2021, the maximum simulated ground ice ablation was in 2016 within the slump region, amounting to a total of 492 m3, and it induced the reciprocal evolution, especially in the headwall of the RTS. High ponding depression water turbidity values of 28 and 49 occurred in the thawing season in 2021. The simulated ground ice ablation and turbidity events were highly correlated with climatic warming and wetting. The results offer a valuable approach to assessing the effects of RTS on infrastructure and the environment, especially in the context of a changing climate.
Risk Assessment of Debris Flows Along the Karakoram Highway (Kashgar-Khunjerab Section) in the Context of Climate Change
Yamei Li, Qiang Zou, Jiansheng Hao, Lijun Su
2023, 14(4): 586-599. doi: 10.1007/s13753-023-00501-1
The Karakoram highway (KKH) is renowned for its complex natural environment and geological conditions. The climate changes drastically and directly influences the frequency and magnitude of debris flows in this region, resulting in significant casualties and economic losses. However, the risk assessment of debris flows along the KKH in the context of climate change has been rarely explored. Therefore, in this study we used the debris flow data, historical meteorological data and future climate prediction data to assess the debris flow risk of the study region during the baseline period (2009–2018), 2025s (2021–2030), 2035s (2031–2040) and 2045s (2041–2050) under the Representative Concentration Pathway 8.5 scenario. The results show that the risk of debris flows increases with climate change, with the highest risk level in the 2025s. Among different parts of this highway, the upper reaches of the Ghez River and the second half of Tashkorgan-Khunjerab are the sections with the highest risk. These findings are helpful for debris flow prevention and can offer coping strategies for the existing line of the KKH. They also provide some reference for the renovation, improvement, operation, and maintenance of the KKH.
Effects of Tectonic Setting and Hydraulic Properties on Silent Large-Scale Landslides: A Case Study of the Zhaobishan Landslide, China
Shufeng Tian, Guisheng Hu, Ningsheng Chen, Mahfuzur Rahman, Huayong Ni, Marcelo Somos-Valenzuela
2023, 14(4): 600-617. doi: 10.1007/s13753-023-00502-0
Unlike strong earthquake-triggered or heavy rainfall-triggered landslides, silent large-scale landslides (SLL) occur without significant triggering factors and cause unexpected significant disaster risks and mass casualties. Understanding the initiation mechanism of SLLs is crucial for risk reduction. In this study, the mechanism of the Zhaobishan SLL was investigated, and the SLL was jointly controlled by weak-soil (fractured rock mass) and strong-water (abundant water replenishment) conditions under the impact of active tectonism and complex hydraulic properties. Strong tectonic uplift, high fault density, and historical earthquakes led to weak-soil conditions conducive to the Zhaobishan SLL. The combined effect of unique lithology, antiform, and cultivated land contributed to the water replenishment characteristics of extensive runoff confluence (3.16 times that of the landslide body) and supported long-distance groundwater replenishment, thereby forming strong-water conditions for the landslide. The amplified seepage amount caused the strength of the soil mass on the sliding surface to decrease to 0.4 times its initial strength, eventually triggering the Zhaobishan SLL, which occurred 4.6 days after the peak rainfall. Moreover, the landslide deposits have accumulated on the semi-diagenetic clay rock, thereby controlling the subsequent recurring debris flows in the Lengzi Gully. To reduce disaster risk of SLL in vulnerable mountainous regions, the water confluence area behind the main scarp of the landslides and the hysteresis characteristics between landslides and peak rainfall should be further considered, and recurring debris flows following massive landslides also should be focused.
Estimation of Shallow Landslide Susceptibility Incorporating the Impacts of Vegetation on Slope Stability
Hu Jiang, Qiang Zou, Bin Zhou, Yao Jiang, Junfang Cui, Hongkun Yao, Wentao Zhou
2023, 14(4): 618-635. doi: 10.1007/s13753-023-00507-9
This study aimed to develop a physical-based approach for predicting the spatial likelihood of shallow landslides at the regional scale in a transition zone with extreme topography. Shallow landslide susceptibility study in an area with diverse vegetation types as well as distinctive geographic factors (such as steep terrain, fractured rocks, and joints) that dominate the occurrence of shallow landslides is challenging. This article presents a novel methodology for comprehensively assessing shallow landslide susceptibility, taking into account both the positive and negative impacts of plants. This includes considering the positive effects of vegetation canopy interception and plant root reinforcement, as well as the negative effects of plant gravity loading and preferential flow of root systems. This approach was applied to simulate the regional-scale shallow landslide susceptibility in the Dadu River Basin, a transition zone with rapidly changing terrain, uplifting from the Sichuan Plain to the Qinghai–Tibet Plateau. The research findings suggest that: (1) The proposed methodology is effective and capable of assessing shallow landslide susceptibility in the study area; (2) the proposed model performs better than the traditional pseudo-static analysis method (TPSA) model, with 9.93% higher accuracy and 5.59% higher area under the curve; and (3) when the ratio of vegetation weight loads to unstable soil mass weight is high, an increase in vegetation biomass tends to be advantageous for slope stability. The study also mapped the spatial distribution of shallow landslide susceptibility in the study area, which can be used in disaster prevention, mitigation, and risk management.
A Heterogeneous Sampling Strategy to Model Earthquake-Triggered Landslides
Hui Yang, Peijun Shi, Duncan Quincey, Wenwen Qi, Wentao Yang
2023, 14(4): 636-648. doi: 10.1007/s13753-023-00489-8
Regional modeling of landslide hazards is an essential tool for the assessment and management of risk in mountain environments. Previous studies that have focused on modeling earthquake-triggered landslides report high prediction accuracies. However, it is common to use a validation strategy with an equal number of landslide and non-landslide samples, scattered homogeneously across the study area. Consequently, there are overestimations in the epicenter area, and the spatial pattern of modeled locations does not agree well with real events. In order to improve landslide hazard mapping, we proposed a spatially heterogeneous non-landslide sampling strategy by considering local ratios of landslide to non-landslide area. Coseismic landslides triggered by the 2008 Wenchuan Earthquake on the eastern Tibetan Plateau were used as an example. To assess the performance of the new strategy, we trained two random forest models that shared the same hyperparameters. The first was trained using samples from the new heterogeneous strategy, and the second used the traditional approach. In each case the spatial match between modeled and measured (interpreted) landslides was examined by scatterplot, with a 2 km-by-2 km fishnet. Although the traditional approach achieved higher AUCROC (0.95) accuracy than the proposed one (0.85), the coefficient of determination (R2) for the new strategy (0.88) was much higher than for the traditional strategy (0.55). Our results indicate that the proposed strategy outperforms the traditional one when comparing against landslide inventory data. Our work demonstrates that higher prediction accuracies in landslide hazard modeling may be deceptive, and validation of the modeled spatial pattern should be prioritized. The proposed method may also be used to improve the mapping of precipitation-induced landslides. Application of the proposed strategy could benefit precise assessment of landslide risks in mountain environments.
Dynamic Assessment of Spatiotemporal Population Distribution Based on Mobile Phone Data: A Case Study in Xining City, China
Benyong Wei, Guiwu Su, Fenggui Liu
2023, 14(4): 649-665. doi: 10.1007/s13753-023-00480-3
High-resolution, dynamic assessments of the spatiotemporal distributions of populations are critical for urban planning and disaster management. Mobile phone big data have real-time collection, wide coverage, and high resolution advantages and can thus be used to characterize human activities and population distributions at fine spatiotemporal scales. Based on six days of mobile phone user-location signal (MPLS) data, we assessed the dynamic spatiotemporal distribution of the population of Xining City, Qinghai Province, China. The results show that strong temporal regularity exists in the daily activities of local residents. The spatiotemporal distribution of the local population showed a significant downtown-suburban attenuation pattern. Factors such as land use types, holidays, and seasons significantly affect the spatiotemporal patterns of the local population. By combining other spatiotemporal trajectory data, high-resolution and dynamic real-time population distribution evaluations based on mobile phone location signals could be better developed and improved for use in urban management and disaster assessment research.
Assessment of Building Physical Vulnerability in Earthquake-Debris Flow Disaster Chain
Hao Zheng, Zhifei Deng, Lanlan Guo, Jifu Liu, Lianyou Liu, Tiewei Li, Huan Zheng, Tao Zheng
2023, 14(4): 666-679. doi: 10.1007/s13753-023-00509-7
Large earthquakes not only directly damage buildings but also trigger debris flows, which cause secondary damage to buildings, forming a more destructive earthquake-debris flow disaster chain. A quantitative assessment of building vulnerability is essential for damage assessment after a disaster and for pre-disaster prevention. Using mechanical analysis based on pushover, a physical vulnerability assessment model of buildings in the earthquake-debris flow disaster chain is proposed to assess the vulnerability of buildings in Beichuan County, China. Based on the specific sequence of events in the earthquake-debris flow disaster chain, the seismic vulnerability of buildings is 79%, the flow impact and burial vulnerabilities of damaged buildings to debris flow are 92% and 28% respectively, and the holistic vulnerability of buildings under the disaster chain is 57%. By comparing different vulnerability assessment methods, we observed that the physical vulnerability of buildings under the disaster chain process is not equal to the statistical summation of the vulnerabilities to independent hazards, which implies that the structural properties and vulnerability of buildings have changed during the disaster chain process. Our results provide an integrated explanation of building vulnerability, which is essential for understanding building vulnerability in earthquake-debris flow disaster chain and building vulnerability under other disaster chains.
Distress Characteristics in Embankment-Bridge Transition Section of the Qinghai-Tibet Railway in Permafrost Regions
Peifeng He, Fujun Niu, Yunhui Huang, Saize Zhang, Chenglong Jiao
2023, 14(4): 680-696. doi: 10.1007/s13753-023-00506-w
The Qinghai-Tibet Railway has been operating safely for 16 years in the permafrost zone and the railroad subgrade is generally stable by adopting the cooling roadbed techniques. However, settlement caused by the degradation of subgrade permafrost in the embankment-bridge transition sections (EBTS) is one of the most representative and severe distresses. A field survey on 440 bridges (including 880 EBTSs) was carried out employing terrestrial laser scanning and ground-penetrating radar for comprehensively assessing all EBTSs in the permafrost zone. The results show that the types of distresses of EBTSs were differential settlement, upheaval mounds of the protection-cone slopes, subsidence of the protection-cone slopes, surface cracks of the protection cones and longitudinal and transverse dislocation of the wing walls. The occurrence rates of these distresses were 78.93, 3.47, 11.56, 3.36, 21.18 and 4.56%, respectively. The most serious problem was differential settlement, and the average differential settlement amount (ADSA) was 15.3 cm. Furthermore, the relationships between differential settlement and 11 influencing factors were examined. The results indicate that ADSA is greater on the northern side of a bridge than on the southern side and on the sunny slope than on the shady slope. It is also greater in the high-temperature permafrost region than in the low-temperature permafrost region and in the high-ice content area than in the low-ice content area. The EBTSs are more influenced by ice content than by ground temperature. The ADSA increases when the embankment height increases, the particle size of subgrade soil decreases and the surface vegetation cover decreases.
Residents’ Preferences for Rural Housing Disaster Insurance Attributes in Central and Western Tibet
Tingting Yang, Zitong Li, Yuan Bai, Xinli Liu, Tao Ye
2023, 14(4): 697-711. doi: 10.1007/s13753-023-00469-y
Understanding the heterogeneous preferences of individuals for disaster insurance attributes is critical for product improvement and policy design. In an era of global environmental change, the Qinghai-Tibet Plateau is a hotspot of natural hazards. Improving the capability of rural housing disaster insurance to foster local residents’ disaster resilience is of great significance but remains under addressed. We used a discrete choice experiment approach to provide the first estimates of rural residents’ preferences for rural housing disaster insurance attributes in central and western Tibet. We estimated residents’ preferences and willingness-to-pay for the sum insured, subsidy rate, insured object, and perils covered. The potential impacts of increasing the sum insured, expanding the insured object, and lowering subsidy rates were evaluated. Our results suggest that residents prefer products with a high sum insured, high subsidy rate, and a complete list of insured objects. Residents who have experienced specific hazards tend to prefer the corresponding perils covered. Females and residents who have a closer social network are more likely to purchase insurance. Product improvement and policy simulation results suggest that, while lowering the subsidy rate, increasing the sum insured and expanding the insured object could promote participation and improve residents’ welfare. Our results could improve the understanding of the preferences of households in remote regions and support policy implementations.