Recent Advances in Modeling, Assessment, and Mitigation of Landslide Hazards

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: 10 August 2024 | Viewed by 2632

Special Issue Editors


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Guest Editor
Department of Applied Mathematics, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: numerical modeling in geotechnical engineering; landslides; smooth particle hydrodynamics; computational methods

E-Mail Website
Guest Editor
Department of Applied Mathematics, Universidad Politécnica de Madrid, 28040 Madrid, Spain
Interests: applied and computational mathematics; fluid mechanics; landslides; geotechnical engineering; finite element method; numerical modeling; soil mechanics; geology; slope stability; constitutive modelling

Special Issue Information

Dear Colleagues,

In this Special Issue, we embark on a comprehensive exploration of the dynamic field of landslide research. Landslides, natural geohazards with profound implications for both human settlements and the environment, continue to demand our attention in an ever-changing world. Our understanding of these complex phenomena has evolved considerably over time, driven by technological innovations, enhanced modeling techniques, and an increasing recognition of the imperative for effective mitigation strategies.

Landslides are emblematic of the intricate interplay between geological, climatic, and anthropogenic factors, presenting a formidable challenge to researchers, engineers, and policymakers alike. As we confront the realities of a changing climate and ongoing human interventions in our landscapes, the need to grasp landslide mechanisms, employ susceptibility mapping, and execute comprehensive risk assessments has never been more critical. This Special Issue aims to illuminate innovative solutions, novel methodologies, and the power of interdisciplinary collaboration as we strive to address the enduring threat of landslides.

We envision this collection of articles not only as a valuable resource for researchers, practitioners, and policymakers, but also as a catalyst for fostering collaboration and innovation in the realm of landslide hazard management. By advancing our knowledge and sharing best practices, we collectively work towards minimizing the devastating consequences of landslides, ultimately forging more resilient communities in the face of this persistent geological threat.

Dr. Saeid Moussavi Tayyebi
Prof. Dr. Manuel Pastor
Guest Editors

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Keywords

  • numerical methods and its applications
  • reliability and risk analysis
  • continuous and discontinuous models
  • GIS, remote sensing, and machine learning
  • landslide susceptibility modeling and mapping
  • monitoring techniques
  • early warning techniques and disaster management systems
  • landslide mitigation techniques

Published Papers (3 papers)

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Research

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32 pages, 18574 KiB  
Article
Analysis of the Occurrent Models of Potential Debris-Flow Sources in the Watershed of Ching-Shuei River
by Ji-Yuan Lin, Jen-Chih Chao and Lung-Kun Yang
Appl. Sci. 2024, 14(9), 3802; https://doi.org/10.3390/app14093802 - 29 Apr 2024
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Abstract
The areas around the Ching-Shuei River saw numerous landslides (2004–2017) after the Jiji earthquake, profoundly harming the watershed’s geological environment. The 33 catchment areas in the Ching-Shuei River watershed and five typhoon and rainstorm events, with a total of 165 occurrences and non-occurrences, [...] Read more.
The areas around the Ching-Shuei River saw numerous landslides (2004–2017) after the Jiji earthquake, profoundly harming the watershed’s geological environment. The 33 catchment areas in the Ching-Shuei River watershed and five typhoon and rainstorm events, with a total of 165 occurrences and non-occurrences, were analyzed, and the training and validation were categorized into 70% training and 30% validation. A landslide disaster is deemed, for the purposes of this research, to have taken place if SPOT satellite images taken before and after an incident show a Normalized Difference Vegetation Index difference larger than 0.25, a slope of less than 30 degrees, and a number of connected grids greater than 10. The analysis was carried out using the instability index method analysis with Rogers regression analysis and artificial neural network. The accuracy rates of neural network, logit regression, and instability index analyses were, respectively, 93.3%, 80.6%, and 70.9%. The neural network’s area under the curve was 0.933, indicating excellent discrimination ability; that of the logit regression analysis was 0.794, which is considered good; and that of the instability index analysis was 0.635, or fair. This suggests that any of the three models are suitable for the danger assessment of large post-earthquake debris flows. The results of this study also provide a reference and evidence for specific sites’ potential susceptibility to debris flows. Full article
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17 pages, 14357 KiB  
Article
Earthquake-Induced Landslides in Italy: Evaluation of the Triggering Potential Based on Seismic Hazard
by Sina Azhideh, Simone Barani, Gabriele Ferretti and Davide Scafidi
Appl. Sci. 2024, 14(8), 3435; https://doi.org/10.3390/app14083435 - 18 Apr 2024
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Abstract
In this study, we defined screening maps for Italy that classify sites based on their potential for triggering landslides. To this end, we analyzed seismic hazard maps and hazard disaggregation results on a national scale considering four spectral periods (0.01 s, 0.2 s, [...] Read more.
In this study, we defined screening maps for Italy that classify sites based on their potential for triggering landslides. To this end, we analyzed seismic hazard maps and hazard disaggregation results on a national scale considering four spectral periods (0.01 s, 0.2 s, 0.5 s, and 1.0 s) and three return periods (475, 975, and 2475 years). First, joint distributions of magnitude (M) and distance (R) from hazard disaggregation were analyzed by means of an innovative approach based on image processing techniques to find all modal scenarios contributing to the hazard. In order to obtain the M-R scenarios controlling the triggering of earthquake-induced landslides at any computation node, mean and modal M-R pairs were compared to empirical curves defining the M-R bounds associated with landslide triggering. Three types of landslides were considered (i.e., disrupted slides and falls, coherent slides, and lateral spreads and flows). As a result, screening maps for all of Italy showing the potential for triggering landslides based on the level of seismic hazard were obtained. The maps and the related data are freely accessible. Full article
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Review

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21 pages, 3761 KiB  
Review
Factors Affecting the Stability of Loess Landslides: A Review
by Liucheng Wei, Zhaofa Zeng and Jiahe Yan
Appl. Sci. 2024, 14(7), 2735; https://doi.org/10.3390/app14072735 - 25 Mar 2024
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Abstract
The stability of loess landslides affects the production and livelihood of the people in its vicinity. The stability of loess landslides is influenced by various factors, including internal structure, collapsibility, water content, and shear strength. The landslide stability of loesses can be analyzed [...] Read more.
The stability of loess landslides affects the production and livelihood of the people in its vicinity. The stability of loess landslides is influenced by various factors, including internal structure, collapsibility, water content, and shear strength. The landslide stability of loesses can be analyzed by several geophysical methods, such as seismic refraction tomography (SRT), electrical resistivity tomography (ERT), micro-seismic technology, and ground penetrating radar (GPR). Geotechnical tests (compression and shear tests) and remote sensing techniques (Global Navigation Satellite System (GNSS), Interferometric Synthetic Aperture Radar (InSAR) and airborne 3D laser technology) are used for studying the landslide stability of loesses as well. Some of the methods above can measure parameters (e.g., fractures, water content, shear strength, creep) which influence the stability of loess landslides, while other methods qualitatively indicate the influencing factors. Integrating parameters measured by different methods, minimizing disturbances to landslides, and assessing landslide stability are important steps in studying landslide hazards. This paper comprehensively introduces the methods used in recent studies on the landslide stability of loesses and summarizes the factors which affect the landslide stability. Furthermore, the relationships between different parameters and methods are examined. This paper enhances comprehension of the underlying mechanisms of the stability of loess landslides to diminish disastrous consequences. Full article
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