Article
Environmental Sciences
Tiandong Zhang, Zizhao Zhang, Cheng Xu, Ruihua Hao, Qianli Lv, Junyu Jia, Shichuan Liang, Haiyu Zhu
Summary: This research investigates the variations in pore water pressure and vertical stresses during rainfall infiltration in Karahaisu landslide in the Ili River Valley, China. The findings show that rainfall significantly increases water saturation, pore water pressure, and vertical stresses in the slope. The research also reveals the changes in soil particles and pores during rainfall infiltration, leading to soil body subsidence and accelerated deformation and damage to the slopes.
Article
Multidisciplinary Sciences
Guojun Sun, Haijun Liu, Dong Cui, Chunmei Chai
Summary: This study used traditional statistical methods to explore the spatial variability and influencing factors of soil nutrients in the Yili River Valley. The results showed significant correlations between different nutrients, and the ordinary Kriging interpolation results revealed the distribution patterns of the nutrients. These findings are important for the rational exploitation of land resources in the Yili River Basin.
Article
Engineering, Geological
Yu Xian, Xueli Wei, Haibo Zhou, Ningsheng Chen, Yu Liu, Feng Liu, Hao Sun
Summary: This study investigates the mechanism of snowmelt-driven landslides through the analysis of a high-level loess landslide in the Yili River Valley, Xinjiang, China. The study reveals that the landslide has experienced two large-scale failures and identified inherited slope deformations. Human grazing activities and the strong water sensitivity of loess were found to be the main factors contributing to the formation and development of the landslide. The results provide important information for understanding early warning systems and risk assessment for snowmelt-triggered landslides in cold areas.
Article
Green & Sustainable Science & Technology
Yanxiao Mu, Zizhao Zhang, Tiansheng Zhou, Zekun Guo
Summary: Natural disasters such as collapse, landslides, and debris flows are common in the Yili River Valley due to its unique terrain and climate. The occurrence of loess landslides, which are a significant proportion of these disasters, is crucial to study. This study investigates the impact of mica content on the mechanical properties of loess in the Yili River Valley under freeze-thaw cycling conditions. The findings show that the shear strength of the loess is negatively affected by both mica content and freeze-thaw cycles.
Article
Engineering, Geological
Nicoletta Santangelo, Giovanni Forte, Melania De Falco, Giovanni Battista Chirico, Antonio Santo
Summary: This study collected over 200 events described as debris flow in the Campania Region of Southern Italy between 1924 and 2020, classifying them as gravity processes or fluvial processes. The classification is essential for designing early warning systems and risk mitigation plans based on different rainfall events triggering the two phenomena. The research explored a large rainfall database to identify the time scales and seasonality of the rainfall events triggering the two classes of phenomena.
Article
Environmental Sciences
Xin Wang, Shibiao Bai
Summary: This research compares landslide susceptibility maps obtained from unclassified landslides directly and the spatial superposition of different types of landslide susceptibility map. It explores the interpretability using cartographic principles of the two methods of map-making. Various background factors were used to assess rainfall and seismic landslide susceptibility, and the accuracy of the models was verified using confusion matrix and ROC curve. The study found high accuracy for the coupling model and significant differences in results between the two methods of evaluating landslide susceptibility.
Article
Meteorology & Atmospheric Sciences
Yubo Liu, Chi Zhang, Qiuhong Tang, Seyed-Mohammad Hosseini-Moghari, Gebremedhin Gebremeskel Haile, Laifang Li, Wenhong Li, Kun Yang, Ruud J. van der Ent, Deliang Chen
Summary: This study analyzed the moisture sources of different rainfall intensities in the Huaihe River Valley from 1980 to 2018, revealing that the contribution of the Indian Ocean to heavy rainfall is greater than to light rainfall, while the local HRV plays a dominant role in light rainfall.
Article
Environmental Sciences
Li Luo, Wen-Zhao Guo, Pei Tian, Yi-li Liu, Shao-Kun Wang, Jia-Wei Luo
Summary: Currently, vegetation has recovered well in most areas of the Loess Plateau in China, but a heavy rainfall event in July 2018 triggered numerous instances of a unique type of loess landslides called slide-flows. These slide-flows occur on gully-slopes with vegetation recovery and have become a new geological hazard and erosion process on the plateau. The vegetation and soil characteristics have significant effects on the scale of the landslides, and attention should be given to this ecological and environmental problem in the future.
INTERNATIONAL JOURNAL OF SEDIMENT RESEARCH
(2023)
Article
Engineering, Geological
S. Romeo, D. D'Angio, A. Fraccica, V. Licata, V. Vitale, V. Chiessi, M. Amanti, M. Bonasera
Summary: On the 26th of November 2022, heavy rainfall triggered diffuse landslides in the Northern sector of Ischia. This study investigated the characteristics of a debris flow that occurred in Casamicciola Terme Municipality. The debris flow originated from the Northern slope of Mt. Epomeo and caused significant damage to buildings, resulting in casualties, injuries, displacement, and severe damage to the road network. The study used field investigations, environmental data, and numerical models to assess the event and emphasized the need for careful monitoring and risk management activities in the future.
Article
Environmental Sciences
Tianjun Qi, Yan Zhao, Xingmin Meng, Guan Chen, Tom Dijkstra
Summary: The study focused on landslides induced by heavy rainfall in southern Tianshui, China, using high-precision remote sensing images and machine learning models to produce an inventory of 14,397 shallow landslides. The ExtraTrees model was found to be the most effective for landslide susceptibility assessment, with slope aspect identified as the most influential factor in landslide development.
Article
Environmental Sciences
Xiaohui Sun, Jianping Chen, Yanrong Li, Ngambua N. Rene
Summary: This study uses InSAR technology and field geological survey to map landslides and assess susceptibility in the upper reaches of Jinsha River. The results show that the random forest model is optimal for predicting and classifying landslide susceptibility in this area. The study suggests that the double disaster effect of the rapid uplift of the Tibetan Plateau and the significant decrease in sea level during a glacial period controls landslide geological hazards in the upper reaches of Jinsha River.
Article
Geography, Physical
Heping Shu, Fanyu Zhang
Summary: This study investigates the relationship between susceptibility of soil-water hazards and human activities, geoheritage sites in the Loess Plateau, China. Landslide and gully erosion susceptibility were obtained using gradient boosting and support vector machines, and a hazard matrix was formed to couple landslide and gully erosion susceptibility. The study found different trends in the magnification times of soil-water hazards chain under different scenarios.
Article
Engineering, Geological
Marcos Barreto de Mendonca, Fernanda Cristina Goncalves Gonzalez, Glauco Valle da Silva Coelho
Summary: This paper proposes a method to predict the probability of landslides based on accumulated rainfall, and conducted a case study in the Quitandinha river basin region in Petropolis, Brazil. The results showed that the accumulated rainfall within 24 and 96 hours had the strongest correlation with landslide occurrence.
Article
Engineering, Geological
Xin Liang, Samuele Segoni, Kunlong Yin, Juan Du, Bo Chai, Veronica Tofani, Nicola Casagli
Summary: This study investigates a landslide disaster in Daoshi Town, China, caused by extreme rainfall and urbanization. The research identifies geological, topographical, and human factors that contributed to the disaster. The study improves the understanding of landslide development in the area and provides basic data and information for further studies and mitigation strategies.
Article
Geosciences, Multidisciplinary
Wanyu Jiang, Guan Chen, Xingmin Meng, Jiacheng Jin, Yan Zhao, Linxin Lin, Yajun Li, Yi Zhang
Summary: The damage caused by rainfall-induced landslides has increased globally. Urbanisation has led to the expansion of residential areas in mountainous areas, accelerating slope instability. However, the limited data records in mountainous zones have resulted in low-precision landslide rainfall thresholds. This study uses the Bailong River Basin in western China as a case study to establish a high-precision rainfall threshold curve and a regional landslide early warning model based on Bayes' theorem, the frequency method, and deep learning techniques. The research findings provide effective support for early warning and risk management of geological disasters in mountainous areas with limited data.