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Sustainable Study on Landslide Disasters and Restoration

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: closed (24 October 2023) | Viewed by 4956

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Special Issue Editors

Dr. Barbara Schneider-Muntau

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Guest Editor

Unit of Geotechnical Engineering, University of Innsbruck, Technikerstraße 13, 6020 Innsbruck, Austria
Interests: slope stability; landslides; natural hazards; sustainability; nature-based solutions; laboratory experiments; numerical approaches

Dr. Bernhard Gems

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Guest Editor

Unit of Geotechnical Engineering, University of Innsbruck, Technikerstraße 13, 6020 Innsbruck, Austria
Interests: natural hazards; cascading processes; fluviatile processes

Special Issue Information

Dear Colleagues,

The creation and renovation of existing buildings to make them sustainable is one of the great challenges in construction. Apart from the important approaches to emissions and energy reduction as well as resource conservation, there is an additional need for sustainability. The basis of the ecological, economic and social sustainability of a structure also lies in its resistance to alpine hazards. The current and predicted climate changes, but also past damage, illustrate the need for safe construction with regard to natural hazards and their changing scenarios. Fundamental to this is an understanding of the natural hazard processes and their triggering mechanisms.

This Special Issue focuses on landslides and landslide disasters and their triggering mechanisms considering a changing climate environment. A special focus will be laid on sustainable and green solutions for protection and restoration measures. The following topics are addressed:

Triggers of landslides
Influence of climate change on triggers
Design of sustainable landslide protection
Design of sustainable landslide restoration measures
Nature-based solutions

Dr. Barbara Schneider-Muntau
Dr. Bernhard Gems
Guest Editors

Manuscript Submission Information

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Keywords

landslides
natural hazards
sustainable solutions
nature-based solutions

Published Papers (4 papers)

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Research

24 pages, 14034 KiB

Open AccessArticle

Rainfall-Induced Landslide Susceptibility Assessment and the Establishment of Early Warning Techniques at Regional Scale

by Chia-Feng Hsu

Sustainability 2023, 15(24), 16764; https://doi.org/10.3390/su152416764 - 12 Dec 2023

Viewed by 754

Abstract

This study builds upon deterministic evaluations of the extensive cumulative rainfall thresholds associated with shallow landslides in the Gaoping River Basin, with a specific focus on the necessary response times during typhoon and intense rainfall events. Following the significant impact of Typhoon Morakot on the Liugui area, our investigation enhances previous research by employing a downscaled approach. We aim to establish early warning models for village-level, intermediate-scale landslide cumulative rainfall thresholds and to create action thresholds for small-scale, key landslide-prone slopes. Our inquiry not only combines various analytical models but also validates their reliability through comprehensive case studies. Comparative analysis with the empirical values set by the Soil and Water Conservation Bureau (SWCB) and the National Center for Disaster Reduction (NCDR) provides a median response time of 6 h, confirming that our findings are consistent with the response time frameworks established by these institutions, thus validating their effectiveness for typhoon-related landslide alerts. The results not only highlight the reference value of applying downscaled cumulative rainfall thresholds at the village level but also emphasize the significance of the evaluated warning thresholds as viable benchmarks for early warnings in landslide disaster management during Taiwan’s flood and typhoon seasons. This research offers a refined methodological approach to landslide early warning systems and provides scientific support for decision making by local governments and disaster response teams. Full article

(This article belongs to the Special Issue Sustainable Study on Landslide Disasters and Restoration)

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18 pages, 34574 KiB

Open AccessArticle

Susceptibility Assessment of Landslides in the Loess Plateau Based on Machine Learning Models: A Case Study of Xining City

by Li He, Xiantan Wu, Zhengwei He, Dongjian Xue, Fang Luo, Wenqian Bai, Guichuan Kang, Xin Chen and Yuxiang Zhang

Sustainability 2023, 15(20), 14761; https://doi.org/10.3390/su152014761 - 11 Oct 2023

Viewed by 764

Abstract

Landslide susceptibility assessment can effectively predict the spatial distribution of potential landslides, which is of great significance in fields such as geological disaster prevention, urban planning, etc. Taking Xining City as an example, based on GF-2 remote sensing image data and combined with field survey data, this study delineated the spatial distribution range of developed landslides. Key factors controlling landslides were then extracted to establish a landslide susceptibility assessment index system. Based on this, the frequency ratio (FR), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) models were applied to spatially predict landslide susceptibility with slope units as the basis. The main results are as follows: (1) The overall spatial distribution of landslide susceptibility classes in Xining City is consistent, but the differences between different landslide susceptibility classes are significant. (2) The high-susceptibility area predicted by the FR-RF model is the largest, accounting for 15.48% of the total study area. The prediction results of the FR-ANN and FR-SVM models are more similar, with high-susceptibility areas accounting for 13.96% and 12.97%, respectively. (3) The accuracy verification results show that all three coupled models have good spatial prediction capabilities in the study area. The order of landslide susceptibility prediction capabilities from high to low is FR-RF model > FR-ANN model > FR-SVM model. This indicates that in the study area, the FR-RF model is more suitable for carrying out landslide susceptibility assessment. Full article

(This article belongs to the Special Issue Sustainable Study on Landslide Disasters and Restoration)

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21 pages, 6866 KiB

Open AccessArticle

Failure Mechanism of Anti-Dip Layered Soft Rock Slope under Rainfall and Excavation Conditions

by Jun Jia, Xiangjun Pei, Gang Liu, Guojun Cai, Xiaopeng Guo and Bo Hong

Sustainability 2023, 15(12), 9398; https://doi.org/10.3390/su15129398 - 12 Jun 2023

Cited by 3 | Viewed by 1324

Abstract

The phenomenon of toppling deformation and failure is common in slopes with anti-dip structures, especially in soft metamorphic rock slopes. This paper aims to explore the instability mechanism of anti-dip layered soft metamorphic rock landslides. Taking the slope of a mining area in the southern Qinling Mountains of China as a geological prototype, a large-scale centrifuge model test and a numerical simulation based on the combined finite and discrete element method (FDEM) were performed. The deformation and failure process, failure mode, and failure path of the slope under rainfall and excavation conditions were simulated. The results show that both the physical centrifuge model test and the new numerical model test can simulate the instability process of anti-dip layered soft metamorphic rock slopes, and the phenomena simulated by the two methods are also very close. Rainfall mainly weakens the mechanical properties of rock, while the excavation at the slope toe mainly changes the stress field distribution and provides space for slope deformation, both of which accelerate the instability of the anti-dip soft metamorphic rock slope. The failure process of an anti-dip layered soft rock slope can be described as follows: bending of the rock layer–tensile fracture along the layer–flexural toppling and cracking perpendicular to the rock layer–extension and penetration of the tensile fracture surface–sliding and instability of the slope. Full article

(This article belongs to the Special Issue Sustainable Study on Landslide Disasters and Restoration)

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19 pages, 31351 KiB

Open AccessArticle

Landslide Susceptibility Assessment Using the Analytic Hierarchy Process (AHP): A Case Study of a Construction Site for Photovoltaic Power Generation in Yunxian County, Southwest China

by Jinxuan Zhou, Shucheng Tan, Jun Li, Jian Xu, Chao Wang and Hui Ye

Sustainability 2023, 15(6), 5281; https://doi.org/10.3390/su15065281 - 16 Mar 2023

Cited by 11 | Viewed by 1542

Abstract

China is actively promoting the construction of clean energy to reach its objective of achieving carbon neutrality. However, engineering constructions in mountainous regions are susceptible to landslide disasters. Therefore, the assessment of landslide disaster susceptibility is indispensable for disaster prevention and risk management in construction projects. In this context, the present study involved conducting a field survey at 42 landslide points in the selected planned site region. According to the geological and geographical conditions of the study region, the existing regulation, and the influencing factors of landslides, the assessment in the field survey was performed based on 11 impact factors, namely, the slope, slope aspect, curvature, relative relief, NDVI, road, river, fault, lithology, the density of the landslide points, and the land-use type. Next, based on their respective influences, these impact factors were further divided into subfactors according to AHP, and the weights of each factor and subfactor were calculated. The GIS tools were employed for linear combination calculation and interval division, and accordingly, a landslide susceptibility zone map was constructed. The ROC curve was adopted to test the partition evaluation results, and the AUC value was determined to be 0.845, which indicated the high accuracy of the partition evaluation results. Full article

(This article belongs to the Special Issue Sustainable Study on Landslide Disasters and Restoration)

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