Abstract To address the high risk of shallow landslides and hydraulic erosion on Loess Plateau slopes induced by intense dry-wet cycles, this study explored the disaster mitigation effect and mechanism of biological soil crusts (BSCs) through indoor scaled slope model tests.
Xuanyu Yang, Yong Wang
openaire +1 more source
Extreme rainfall-induced forest aboveground biomass (AGB) loss poses a serious threat to ecosystem stability and carbon stocks amid intensifying climate extremes.
Xiaoqing Luo +8 more
doaj +1 more source
The continuous downward movement exhibited by the Lashagou landslide group in recent years poses a significant threat to the safety of both vehicles and pedestrians traversing the highway G310.
Qianyou Fan +7 more
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Responses of Loess Ground with Different Slopes and Vegetation Covers to Rainfall Infiltration
[Objective] To investigate the soil moisture response to rainfall in loess ground with different slopes and vegetation types. [Methods] Eight in-situ observation plots were established, including flat surfaces with bare soil, Artemisia cover, and Robinia
ZHANG Lina +6 more
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The sediment source characteristics of cascading hazards are critical to understanding their formation mechanisms, evolutionary processes, and implications for regional risk assessment.
Yuzhu Zhang +13 more
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Distributed Optical Fiber Strain Sensing for Monitoring Rainfall-Induced Deformation of Landslide-Prone Soil Slopes: A Physical Model Test. [PDF]
Cheng L +8 more
europepmc +1 more source
Multi-parameter dataset of self-potential, electrical resistivity tomography, soil properties, and UAV LiDAR topography from the Fengjiaping loess-mudstone landslide, China. [PDF]
Bai G +11 more
europepmc +1 more source
Exploring rainfall effects on the Xingfu Dayuan Landslide in Yecheng, Xinjiang, China using time-series InSAR technology and numerical simulation. [PDF]
Tian Z +6 more
europepmc +1 more source
Characteristics and mechanisms of large-scale old landslides and landslide dams in the Loess Plateau-A case study from Daning County, Shanxi Province, China. [PDF]
Zhao Z +6 more
europepmc +1 more source
Research on interpretable machine learning modeling and spatial prediction of cross-landform landslide disaster mechanism: A case study of Shaanxi Province. [PDF]
Han M, Yang Y.
europepmc +1 more source

