Landslides can behave as dynamic processes, which emerge from the complex interplay of tectonics, erosion, weathering and gravitational influences, triggered by various hydrological, mineralogical, biological and geotechnical factors. Integral studies to assess the mechanisms underlying landslide initiation and progression are mainly focussed on specific cases with high geohazard potential. The landslide near Stadtschlaining (Austria) represents a key study site to elucidate the impacts of pelitic sediment composition, weathering regime, alteration patterns and hydrochemistry on recurrent damage progression in the local infrastructure. Based on field work, soil-mechanical logging (Atterberg limits, undrained strength, friction angles), water chemistry (ICP-OES, IC, hydrochemical modeling), solid-phase characterization (XRD, XRF, SEM) and sorption experiments we establish a conceptual model for initiating and progressing of landslides: Infiltration of low mineralized meteoric water (EC: <200 μS/cm) in permeable limonitic gravels triggers chemical weathering of greenschist-derived detritus and promotes its transformation into kaolinite and smectite. The clayey strata (>50 wt% of clay minerals) create zones of mechanical and chemical weakness in the underground (~4-6 m below ground level), which are characterized by particle disintegration/delamination, slip bedding and deformations, and development of porous layers depicting water flow paths. Subsequent Na exchange for bivalent ions in the smectite interlayer delivered by percolating, highly mineralized water (EC: 1600-5100 μS/cm) is caused by de-icing salt and fertilizer applications during winter and late summer, and yield in i) decohesion and physical breakdown of the particle aggregates and ii) swelling of the clay matrix in early spring and autumn. These processes reduce the shear strength of the pelitic sediments, resulting in failure and initiation of landslides (deformation: ~500 mm within a month) and subsequent steady creeping motion (deformation: ~100 mm in 6 months). Customized engineered solutions to prevent landslides in this area are presented, which can be conveyed to analogous landslide-affected areas worldwide.
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http://dx.doi.org/10.1016/j.scitotenv.2021.146300 | DOI Listing |
Sci Rep
January 2025
School of Highway, Chang'an University, Xi'an, 710064, Shaanxi, China.
The long-term safety and durability of anchor systems are the focus of slope maintenance management and sustainable operation. This study presents the observed temperature, humidity, and anchor bolt stress at varying depths from four-year remote real-time monitoring of the selected loess highway cut-slope. The potential correlation between slope hydrothermal environment and anchor stress is analyzed.
View Article and Find Full Text PDFMethodsX
June 2025
Department of Mathematics, Faculty of Mathematics and Natural Science, Mulawarman University.
Modeling rainfall data is critical as one of the steps to mitigate natural disasters due to weather changes. This research compares the goodness of traditional and machine learning models for predicting rainfall in Samarinda City. Monthly rainfall data was recapitulated by the Meteorology, Climatology, and Geophysics Agency from 2000 to 2020.
View Article and Find Full Text PDFPLoS One
December 2024
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China.
The existing landslide monitoring methods are unable to accurately reflect the true deformation of the landslide body, and the use of a single SAR satellite, affected by its revisit cycle, still suffers from the limitation of insufficient temporal resolution for landslide monitoring. Therefore, this paper proposes a method for the dynamic reconstruction and evolutionary characteristic analysis of the Gaojiawan landslide's along-slope deformation based on ascending and descending orbit time-series InSAR observations using Kalman filtering. Initially, the method employs a gridded selection approach during the InSAR time-series processing, filtering coherent points based on the standard deviation of residual phases, thereby ensuring the density and quality of the extracted coherent points.
View Article and Find Full Text PDFJ Imaging
December 2024
Department of Mathematics, University of Bologna, 40126 Bologna, Italy.
Accurate estimation of landslide depth is essential for practical hazard assessment and risk mitigation. This work addresses the problem of determining landslide depth from satellite-derived elevation data. Using the principle of mass conservation, this problem can be formulated as a linear inverse problem.
View Article and Find Full Text PDFYing Yong Sheng Tai Xue Bao
October 2024
Institute of Geological Natural Disaster Prevention and Control, Gansu Academy of Sciences, Lanzhou 730000, China.
Accurately analyzing the type of land use and change characteristics of disaster damage in landslide areas is of great significance to scientifically promote the optimization of regional land use pattern and disaster prevention and mitigation. We analyzed the characteristic parameters of landslides as well as the characteristics and driving factors of land use change from 1985 to 2020 in Tongwei County, Gansu Province, using ALOS DEM data and 1985-2020 land use data, GIS spatial analysis, land-use dynamic attitude, transfer matrix, and Geodetector. The results showed that a total of 1012 landslide samples were identified, characterized by medium elevation, gentle gradient, low elevation difference, short length, and small size.
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