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Recent Advances in Modeling, Assessment, and Mitigation of Landslide Hazards, 2nd Edition

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

Deadline for manuscript submissions: 20 March 2025 | Viewed by 734

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
Special Issues, Collections and Topics in MDPI journals

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 modeling
Special Issues, Collections and Topics in MDPI journals

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 as a valuable resource for researchers, practitioners, and policymakers and 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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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

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Published Papers (1 paper)

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Research

16 pages, 5748 KiB  
Article
Probabilistic Analysis of Infinite Slope Stability Considering Variation in Soil Depth
by Taejin Kim, Taeho Bong and Donggeun Kim
Appl. Sci. 2025, 15(2), 936; https://doi.org/10.3390/app15020936 - 18 Jan 2025
Viewed by 490
Abstract
In probabilistic slope stability analysis, soil depth has been treated as a deterministic variable, although it is a highly variable parameter. This study aims to identify soil depth variability using seismic refraction survey data and to analyze its impact on probabilistic analysis of [...] Read more.
In probabilistic slope stability analysis, soil depth has been treated as a deterministic variable, although it is a highly variable parameter. This study aims to identify soil depth variability using seismic refraction survey data and to analyze its impact on probabilistic analysis of slope stability. Seismic refraction survey data were collected from 70 slopes in South Korea and employed to identify the variability of soil depth within natural slopes. As a result, the average soil depth across 70 slopes was 2.5 m, with an average coefficient of variation (COV) of 29%, indicating high variability. To investigate the influence of soil depth variability on the probability of slope failure, probabilistic slope stability analysis was conducted by considering the shear strength parameters of soil and soil depth as random variables. Accordingly, the influences of the variability of soil depth on the probabilistic analysis of slope stability were evaluated by comparing the probability of slope failure and distribution of the failure occurrence frequency by depth. Additionally, global sensitivity analysis was conducted to understand the relative contribution of input parameters on the probability of slope failure. Consequently, the probability of slope failure can vary significantly depending on soil depth variability, emphasizing the importance of considering this factor in probabilistic slope stability analysis. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of research process.</p>
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<p>Location of surveyed slopes in South Korea.</p>
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<p>Estimation of slope depth by P-wave velocity.</p>
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<p>Cross-section for slope stability analysis.</p>
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<p>Flowchart for the probabilistic slope stability analysis.</p>
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<p>Soil depth extraction at 5 m intervals to determine the variability in depth along the slope.</p>
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<p>Examples of slopes based on the average soil depth and its COV.</p>
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<p>Box plots of statistics of soil depth.</p>
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<p>Comparison of change in <span class="html-italic">P<sub>f</sub></span> according to saturation depth for each case.</p>
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<p>Comparison of frequency distribution of failure occurrences with depth: (<b>a</b>) saturation depth = 1.5 m and (<b>b</b>) saturation depth = 2.5 m.</p>
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<p>CDF of the minimum <span class="html-italic">F</span><sub>S</sub> for a saturation depth of 1.5 m.</p>
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<p>CDF of the minimum <span class="html-italic">F</span><sub>S</sub> for a saturation depth of 2.5 m.</p>
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<p>Changes in sensitivity of random variables according to saturation depth: (<b>a</b>) Case 2; (<b>b</b>) Case 3; and (<b>c</b>) Case 4.</p>
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