Effects of soil depth and subsurface flow along the subsurface topography on shallow landslide predictions at the site of a small granitic hillslope

Kim, Min Seok; Onda, Yuichi; Uchida, Tatsuo; Kim, Jin Kwan

doi:10.1016/j.geomorph.2016.07.031

Cited by 30 publications

(8 citation statements)

References 57 publications

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“…Further, measuring the amount of variability and its spatial structure could help determine the extent to which landslides will result from localization or coalescing and thus their expected size. Pioneering work by researchers in Japan and South Korea, using cone penetrometers (65)(66)(67) to map soil susceptible to failure is a start. We now need to develop data on the form and amplitude and wavelength of strength variability and what controls that structure.…”

Section: Discussionmentioning

confidence: 99%

Controls on the size distributions of shallow landslides

Bellugi

Milledge

Cuffey

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Rainfall-triggered shallow landslides are destructive hazards and play an important role in landscape processes. A theory explaining the size distributions of such features remains elusive. Prior work connects size distributions to topography, but field-mapped inventories reveal pronounced similarities in the form, mode, and spread of distributions from diverse landscapes. We analyze nearly identical distributions occurring in the Oregon Coast Range and the English Lake District, two regions of strikingly different topography, lithology, and vegetation. Similarity in minimum sizes at these sites is partly explained by theory that accounts for the interplay of mechanical soil strength controls resisting failure. Maximum sizes, however, are not explained by current theory. We develop a generalized framework to account for the entire size distribution by unifying a mechanistic slope stability model with a flexible spatial-statistical description for the variability of hillslope strength. Using hillslope-scale numerical experiments, we find that landslides can occur not only in individual low strength areas but also across multiple smaller patches that coalesce. We show that reproducing observed size distributions requires spatial strength variations to be strongly localized, of large amplitude, and a consequence of multiple interacting factors. Such constraints can act together with the mechanical determinants of landslide initiation to produce size distributions of broadly similar character in widely different landscapes, as found in our examples. We propose that size distributions reflect the systematic scale dependence of the spatially averaged strength. Our results highlight the critical need to constrain the form, amplitude, and wavelength of spatial variability in material strength properties of hillslopes.

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Section: Discussionmentioning

confidence: 99%

Controls on the size distributions of shallow landslides

Bellugi

Milledge

Cuffey

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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“…In this study, we assumed that the potential landslide thickness is the soil depth to the bedrock. Therefore, soil depth is another important input data that has an effect on landslide FOS calculations 54 . The majority of landslide constituents in the study area is soil from weathered rock, and the sliding surface is usually along the soil-bedrock interface.…”

Section: Methodology and Datamentioning

confidence: 99%

Failure probability assessment of landslides triggered by earthquakes and rainfall: a case study in Yadong County, Tibet, China

Chen

Mei

Zeng

et al. 2020

Sci Rep

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Yadong County located in the southern Himalayan mountains in Tibet, China, is an import frontier county. It was affected by landslides after the 2011 Sikkim earthquake (Mw = 6.8) and the 2015 Gorkha earthquake (Mw = 7.8). Casualties and property damage were caused by shallow landslides during subsequent rainfall on the earthquake-destabilized slopes. Existing researches have generally examined rainfall- and earthquake-triggered landslides independently, whereas few studies have considered the combined effects of both. Furthermore, there is no previous study reported on landslide hazards in the study area, although the area is strategically applicable for trade as it is close to Bhutan and India. This study developed a new approach that coupled the Newmark method with the hydrological model based on geomorphological, geological, geotechnical, seismological and rainfall data. A rainfall threshold distribution map was generated, indicating that the southeast part of Yadong is prone to rainfall-induced landslides, especially when daily rainfall is higher than 45 mm/day. Permanent displacement predictions were used to identify landslide hazard zones. The regression model used to calculate these permanent displacement values was 71% accurate. Finally, landslide probability distribution maps were generated separately for dry and wet conditions with rainfall of varying intensities. Results can serve as a basis for local governments to manage seismic landslide risks during rainy seasons.

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“…Ketebalan tanah merupakan salah satu karakteristik tanah yang penting. Informasi ketebalan tanah berkaitan dengan jasa ekosistem terutama pada aktivitas karbon tanah, suhu, dan air (Horst-Heinen et al, 2021), kesesuaian lahan dan pertumbuhan vegetasi (Chen et al, 2019), kondisi aliran permukaan (Han et al, 2018), dan kerawanan longsor (Ho et al, 2012;Kim et al, 2016) (Bostan et al, 2012;Lamichhane et al, 2019;Yang et al, 2019;John et al, 2022). Pendekatan dari dua metode ini cukup berbeda sehingga hasil pemetaan dapat memiliki perbedaan dalam konteks variasi spasial.…”

Section: Pendahuluanunclassified

Perbandingan Metode Multiple Linear Regression (Mlr) Dan Regression Kriging (Rk) Dalam Pemetaan Ketebalan Tanah Digital

Ramadhan

Samodra

Nugraha

et al. 2023

J. Tanah Sumberd. Lahan

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Soil thickness has a significant influence on many of earth surface processes, and it can be mapped using various methods. Digital soil mapping can be used to estimate the spatial distribution of soil thickness and can estimate the uncertainty of the soil prediction map. Digital soil mapping using regression methods such as Multiple Linear Regression (MLR) and Regression Krigging (RK) was used to estimate soil thickness of the slope of Bener Reservoir. Bener Dam is a national strategic project which is built for irrigation to improve farming quantity. The aim of this research was to determine the spatial variation of the soil thickness at the slope of Bener Reservoir. The accuracy of MLR and RK were compared to select the best soil thickness prediction. There were 212 and 53 soil thickness samples from fieldwork which were used for data training and testing, respectively. There were 5 environmental variables such as elevation, distance from river, slope, plan curvature, and topographic wetness index. R programming language with gstat, krige, and stats Packages was employed for MLR and RK prediction. The result showed that KR is more accurate than MLR.

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Effects of soil depth and subsurface flow along the subsurface topography on shallow landslide predictions at the site of a small granitic hillslope

Cited by 30 publications

References 57 publications

Controls on the size distributions of shallow landslides

Controls on the size distributions of shallow landslides

Failure probability assessment of landslides triggered by earthquakes and rainfall: a case study in Yadong County, Tibet, China

Perbandingan Metode Multiple Linear Regression (Mlr) Dan Regression Kriging (Rk) Dalam Pemetaan Ketebalan Tanah Digital

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