Assessment of landslide susceptibility along the Araniko Highway in Poiqu/Bhote Koshi/Sun Koshi Watershed, Nepal Himalaya

Nepal, Nirdesh; Chen, Jiangang; Chen, Huayong; Xian, Wang; Sharma, Til Prasad Pangali

doi:10.1016/j.pdisas.2019.100037

Cited by 41 publications

(27 citation statements)

References 61 publications

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“…Slopes in combination with the slope material cohesion, angle of repose, and moisture conditions normally determine slope stability conditions. It is a very important parameter in the slope stability analysis, and it is frequently used in preparing landslide susceptibility maps (Pradhan and Kim, 2014;Nepal et al, 2019;Shrestha, Kang and Choi, 2019). Elevation-relief ratio The elevation-relief ratio is defined as mean elevation minus minimum elevation divided by relief.…”

Section: Slope Gradientmentioning

confidence: 99%

Assessment of denudation rate and erosion susceptibility in the upper Tamakoshi basin in the higher Himalayas, Nepal

Ghimire

Timalsina

2021

Geog. J. Nepal

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The higher rate of slope erosion in the Himalayan basins is contributing to rapid change in landform in the mountainous terrain, which has caused sedimentation, and inundation downstream. The Tamakoshi basin is a trans-boundary river that originates from Tibet and flows through Dolakha and Ramechap districts before joining the Sapta Koshi river. Few studies exist in Nepal attempting to quantify the erosion rate and susceptibility. However, they are scattered and mainly focus on either rill-sheet erosion or landslide only. Hence, this study attempted to estimate slope erosion by applying the Revised Universal Soil Loss Equation (RUSLE), and soil and debris erosion from landslide (2000-2019). Spatially distributed erosion intensity maps derived from the RUSLE model, as well as index-based landslide susceptibility map, were integrated to capture both running water and gravity erosion processes. The novelty of this research is that it examined the soil erosion rate using a process-based model as well as from the soil or rock displaced by the observed landslides over the last 20 years. The study estimated gross annual erosion by running water of 9.1million tons/yr, equivalent to the denudation rate of 3.34 mm/yr. Of these, landslide erosion accounts for 7.6 million ton/yr, i.e., 2.88 mm/yr, this covers about 84% of total slope erosion. High landslide and erosion potential areas are associated with high rainfall, steep slopes, scarps, lower segment of valley side slopes, high relief, and highly fractured and deformed parts of high-grade metamorphic rocks, such as gneiss, quartzite, marbles, migmatite, and granitic gneiss.

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Section: Slope Gradientmentioning

confidence: 99%

Assessment of denudation rate and erosion susceptibility in the upper Tamakoshi basin in the higher Himalayas, Nepal

Ghimire

Timalsina

2021

Geog. J. Nepal

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“…TWI index is defined as the function of both the slope and upstream contributing area per unit width orthogonal to the flow direction [14,47]. The calculation method of TWI is showed in Eq (2).…”

Section: Spi ¼ a S � Tanb ð1þmentioning

confidence: 99%

“…Taking the highway slope as the disaster bearing body and the surrounding environment as the disaster pregnant environment, highway landslide disaster (HLD) is one of the main reasons for long-term highway interruption [1][2][3]. HLDs occur frequently in some areas of China, resulting in serious economic losses and casualties [4], for example, the volume of the K1428+800 landslide of G108 Shaanxi segment exceeded 1×10 5 m 3 , resulting in highway interruption for more than 3 years [5]; the Jiuzhaigou Valley's 7.0-magnitude earthquake led to the formation of 1,594 landslides, covering a total volume of 11.52×10 6 m 3 [6,7].…”

Section: Introductionmentioning

confidence: 99%

Susceptibility mapping and zoning of highway landslide disasters in China

Yin

Li²,

Che

et al. 2020

PLoS ONE

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Prominent regional differentiations of highway landslide disasters (HLDs) bring great difficulties in highway planning, designing and disaster mitigation, therefore, a comprehensive understanding of HLDs from the spatial perspective is a basis for reducing damages. Statistical prediction methods and machine learning methods have some defects in landslide susceptibility mapping (LSM), meanwhile, hybrid methods have been developed by combining the statistical prediction methods with machine learning methods in recent years, and some of them were reported to perform better than conventional methods. In view of this, the principal component analysis (PCA) method was used to extract the susceptibility evaluation indexes of HLDs; the particle swarm optimization-support vector machine (PSO-SVM) model and genetic algorithm-support vector machine (GA-SVM) model were implemented to the susceptibility mapping and zoning of HLDs in China. The research results show that the accumulative contribution rate of the four principal components is 92.050%; evaluation results of the PSO-SVM model are better than those of the GA-SVM model; micro dangerous areas, moderate dangerous areas, severe dangerous areas and extreme dangerous areas account for 24.24%, 19.49%, 36.53% and 19.74% of the total areas of China; among the 1543 disaster points in the HLDs inventory, there are 134, 182, 421 and 806 located in the above areas respectively.

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“…Topography affects the post-earthquake landslides in many aspects. It is widely accepted that a high angle slope is prone to landslides because a larger inclination increases the shear stress on soil [48]. Elevation and aspect impact vegetation cover, moisture retention and soil strength which can influence landslide initiation [49,50].…”

Section: Topographymentioning

confidence: 99%

“…Elevation and aspect impact vegetation cover, moisture retention and soil strength which can influence landslide initiation [49,50]. In addition, because of the direction of the seismic wave propagation, different altitudes and aspects may suffer different movements [48,51]. In this paper, the slope and aspect were both computed from the SRTM digital elevation model (DEM) using ArcGIS10.6.…”

Section: Topographymentioning

confidence: 99%

Mapping Post-Earthquake Landslide Susceptibility: A U-Net Like Approach

et al. 2020

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A serious earthquake could trigger thousands of landslides and produce some slopes more sensitive to slide in future. Landslides could threaten human’s lives and properties, and thus mapping the post-earthquake landslide susceptibility is very valuable for a rapid response to landslide disasters in terms of relief resource allocation and posterior earthquake reconstruction. Previous researchers have proposed many methods to map landslide susceptibility but seldom considered the spatial structure information of the factors that influence a slide. In this study, we first developed a U-net like model suitable for mapping post-earthquake landslide susceptibility. The post-earthquake high spatial airborne images were used for producing a landslide inventory. Pre-earthquake Landsat TM (Thematic Mapper) images and the influencing factors such as digital elevation model (DEM), slope, aspect, multi-scale topographic position index (mTPI), lithology, fault, road network, streams network, and macroseismic intensity (MI) were prepared as the input layers of the model. Application of the model to the heavy-hit area of the destructive 2008 Wenchuan earthquake resulted in a high validation accuracy (precision 0.77, recall 0.90, F1 score 0.83, and AUC 0.90). The performance of this U-net like model was also compared with those of traditional logistic regression (LR) and support vector machine (SVM) models on both the model area and independent testing area with the former being stronger than the two traditional models. The U-net like model introduced in this paper provides us the inspiration that balancing the environmental influence of a pixel itself and its surrounding pixels to perform a better landslide susceptibility mapping (LSM) task is useful and feasible when using remote sensing and GIS technology.

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Assessment of landslide susceptibility along the Araniko Highway in Poiqu/Bhote Koshi/Sun Koshi Watershed, Nepal Himalaya

Cited by 41 publications

References 61 publications

Assessment of denudation rate and erosion susceptibility in the upper Tamakoshi basin in the higher Himalayas, Nepal

Assessment of denudation rate and erosion susceptibility in the upper Tamakoshi basin in the higher Himalayas, Nepal

Susceptibility mapping and zoning of highway landslide disasters in China

Mapping Post-Earthquake Landslide Susceptibility: A U-Net Like Approach

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