A 3D model applied to analyze the mechanical stability of real-world forested hillslopes prone to landslides

Temgoua, André Guy Tranquille; Kokutse, Nomessi; Kavazović, Zanin; Richard, Martin

doi:10.1016/j.ecoleng.2017.06.043

Cited by 13 publications

(6 citation statements)

References 29 publications

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“…Adequately accounting for the uncertainty in the RAR, even relatively close to the base of large trees, remains a significant challenge for deterministic models of root reinforcement, particularly those interested in determining the location of landslide initiation on a hillslope (e.g. Arnone et al ., ; Cislaghi et al ., ; Temgoua et al ., ). When combined with the challenges of estimating the depth of colluvium on a hillslope (Parker et al ., ) and with the spatial distribution of soil material properties (Milledge et al ., ), a more deterministic understanding of landslide initiation requires further work.…”

Section: Resultsmentioning

confidence: 97%

“…Commonly used slope stability models such as SHALSTAB (Montgomery and Dietrich, ) and SINMAP (Pack et al ., ) extrapolate an average or uniform distribution of point measurements to estimate cohesion. Others have used the size, geometry and distribution of different trees within a stand to estimate local minima in root strength (Roering et al ., ; Sakals and Sidle, ; Cislaghi et al ., ; Temgoua et al ., ). Alternatively, remotely sensed metrics of vegetation, such as normalized density vegetation index (NDVI) and light detection and ranging (LiDAR)‐derived canopy heights, have also been related to root reinforcement (Chiang and Chang, ; Hwang et al ., ).…”

Section: Introductionmentioning

confidence: 97%

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Modelling biome‐scale root reinforcement and slope stability

Hales

2018

Earth Surf Processes Landf

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Rapid changes in the composition of hillslope vegetation due to a combination of changing climate and land use make estimating slope stability a significant challenge. The dynamics of root growth on any individual hillslope result in a wide range of root distributions and strengths that are reflected as up to an order of magnitude variability in root cohesion. Hence the challenge of predicting the magnitude of root reinforcement for hillslopes requires both an understanding of the magnitude and variability of root distributions and material properties (e.g. tensile strength, elasticity). Here I develop a model for estimating the reinforcement provided by plant roots based on the distribution of biomass measured at the biome level and a compilation of root tensile strength measurements measured across a range of vegetation types. The model modifies the Wu/Waldron method of calculating root cohesion to calculate the average lateral root cohesion and its variability with depth using the Monte Carlo method. The model was validated in two ways, the first against the predicted depth-reinforcement characteristics of Appalachian soils and the second using a global dataset of landslides. Model results suggest that the order of magnitude difference in root cohesions measured on individual hillslopes can be captured by the Monte Carlo approach and provide a simple tool to estimate root reinforcement for data-poor areas. The model also suggests that future hotspots of slope instability will occur in areas where land use and climate convert forest to grassland, rather than changes between different forest structures or forest and shrubland.

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Section: Resultsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 97%

Modelling biome‐scale root reinforcement and slope stability

Hales

2018

Earth Surf Processes Landf

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“…(51) Nevertheless, predicting the location of the source area of shallow landslides originating in mountainous regions remains an important task. (23,24,52) Various physical-based models, such as the SHALSTAB model, have been developed, and various analysis techniques have been used to verify the accuracy of the model. On the basis of the prediction of the critical rainfall using the SHALSTAB simulation results, the landslide susceptibility can be determined by calculating the optimal cut-off point using the Youden index.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the Effect of Root Cohesion on Shallow Landslides for Physically Based Modeling

Jang¹,

Kim²,

Kim³

et al. 2021

Sensors and Materials

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“…While advances in modelling offer a potential solution, they are often limited by availability of parameter data or are designed to work only at limited scales (e.g. Temgoua et al, 2016Temgoua et al, , 2017. Resolving the question of how many trees are needed, where to place them and their spacing, and determining when they become effective in terms of limiting the incidence of shallow landslides remains a challenge for catchment managers (Stokes et al, 2014).…”

Section: Management Of Forest Cover and Space Planted Treesmentioning

confidence: 99%