Root reinforcement: continuum framework for constitutive modelling

The mechanical contribution of plant roots to soil strength has typically been studied at the ultimate limit state only. Since many geotechnical problems are related to serviceability, such as deformation of infrastructure, a new constitutive modelling framework is introduced. The rooted soil is treated as a composite material with separate constitutive relationships for soil and roots, and a comprehensive stress-strain relationship for the root constituent is presented. The model is compared to direct shear experiments on field soil reinforced with gorse, grass and willow roots, as well as an existing root reinforcement model based on Winkler-spring supported beam theory. The results show that both the newly developed model and the beam-type model yield good predictions for the evolution of root-reinforced shear strength as a function of increasing shear displacements. Both successfully capture the large deformations required to reach peak reinforcement, the reduction in reinforcement due to root breakage and the presence of significant reinforcement even after very large deformations, associated with root slippage. Since both fibre and beam models only require physically meaningful input parameters, they can be useful tools to study the mobilisation of rooted soil strength and simulate the response of rooted soil in continuum-based numerical simulations.

A generic form of fibre bundle models for root reinforcement of soil

Purpose The mechanical contribution of plant roots to the soil shear strength is commonly modelled using fibre bundle models (FBM), accounting for sequential breakage of roots. This study provides a generic framework, able to includes the many different existing approaches, to quantify the effect of various model assumptions. Methods The framework uses (1) a single model parameter determining how load is shared between all roots, (2) a continuous power-law distribution of root area ratio over a range of root diameters, and (3) power-law relationships between root diameters and biomechanical properties. A new load sharing parameter, closely resembling how roots mobilise strength under landslide conditions, is proposed. Exact analytical solutions were found for the peak root reinforcement, thus eliminating the current need for iterative algorithms. Model assumptions and results were validated against existing biomechanical and root reinforcement data. Results Root reinforcements proved very sensitive to the user-defined load sharing parameter. It is shown that the current method of discretising all roots in discrete diameter classes prior to reinforcement calculations leads to significant overestimations of reinforcement. Addition of a probabilistic distribution of root failure by means of Weibull survival functions, thus adding a second source of sequential mobilisation, further reduced predicted reinforcements, but only when the reduction due to load sharing was limited. Conclusion The presented solutions greatly simplify root reinforcement calculations while maintaining analytical exactness as well as clarity in the assumptions made. The proposed standardisation of fibre bundle-type models will greatly aid comparison and exchange of data.

Temporal Dynamics of Root Reinforcement in European Spruce Forests

The quantification of post-disturbance root reinforcement (RR) recovery dynamics is of paramount importance for the optimisation of forest ecosystem services and natural hazards risk management in mountain regions. In this work we analyse the long-term root reinforcement dynamic of spruce forests combining data of the Swiss National Forest Inventory with data on root distribution and root mechanical properties. The results show that root reinforcement recovery depends primarily on stand altitude and slope inclination. The maximum root reinforcement recovery rate is reached at circa 100 years. RR increases continuously with different rates for stand ages over 200 years. These results shows that RR in spruce stands varies considerably depending on the local conditions and that its recovery after disturbances requires decades. The new method applied in this study allowed for the first time to quantify the long term dynamics of RR in spruce stands supporting new quantitative approaches for the analysis of shallow landslides disposition in different disturbance regimes of forests.

Introducing SlideforMap; a probabilistic finite slope approach for modelling shallow landslide probability in forested situations

Worldwide, shallow landslides repeatedly pose a risk to infrastructure and residential areas. To analyse and predict the risk posed by shallow landslides, a wide range of scientific methods and tools to model shallow landslide probability exist for both local and regional scale However, most of these tools do not take the protective effect of vegetation into account. Therefore, we developed SlideforMap (SfM), which is a probabilistic model that allows for a regional assessment of shallow landslide probability while considering the effect of different scenarios of forest cover, forest management and rainfall intensity. SfM uses a probabilistic approach by distributing hypothetical landslides to uniformly randomized coordinates in a 2D space. The surface areas for these hypothetical landslides are derived from a distribution function calibrated from observed events. For each randomly generated landslide, SfM calculates a factor of safety using the limit equilibrium approach. Relevant soil parameters, i.e. angle of internal friction, soil cohesion and soil depth, are assigned to the generated landslides from normal distributions based on mean and standard deviation values representative for the study area. The computation of the degree of soil saturation is implemented using a stationary flow approach and the topographic wetness index. The root reinforcement is computed based on root proximity and root strength derived from single tree detection data. Ultimately, the fraction of unstable landslides to the number of generated landslides, per raster cell, is calculated and used as an index for landslide probability. Inputs for the model are a digital elevation model, a topographic wetness index and a file containing positions and dimensions of trees. We performed a calibration of SfM for three test areas in Switzerland with a reliable landslide inventory, by randomly generating 1000 combinations of model parameters and then maximising the Area Under the Curve (AUC) of the receiver operation curve (ROC). These test areas are located in mountainous areas ranging from 0.5–7.5 km2, with varying mean slope gradients (18–28°). The density of inventoried historical landslides varied from 5–59 slides/km2. AUC values between 0.67 and 0.92 indicated a good model performance. A qualitative sensitivity analysis indicated that the most relevant parameters for accurate modeling of shallow landslide probability are the soil depth, soil cohesion and the root reinforcement. Further, the use of single tree detection in the computation of root reinforcement significantly improved model accuracy compared to the assumption of a single constant value of root reinforcement within a forest stand. In conclusion, our study showed that the approach used in SfM can reproduce observed shallow landslide occurrence at a catchment scale.

Root Reinforcement in Slope Stability Models: A Review

The influence of vegetation on mechanical and hydrological soil behavior represents a significant factor to be considered in shallow landslides modelling. Among the multiple effects exerted by vegetation, root reinforcement is widely recognized as one of the most relevant for slope stability. Lately, the literature has been greatly enriched by novel research on this phenomenon. To investigate which aspects have been most treated, which results have been obtained and which aspects require further attention, we reviewed papers published during the period of 2015–2020 dealing with root reinforcement. This paper—after introducing main effects of vegetation on slope stability, recalling studies of reference—provides a synthesis of the main contributions to the subtopics: (i) approaches for estimating root reinforcement distribution at a regional scale; (ii) new slope stability models, including root reinforcement and (iii) the influence of particular plant species, forest management, forest structure, wildfires and soil moisture gradient on root reinforcement. Including root reinforcement in slope stability analysis has resulted a topic receiving growing attention, particularly in Europe; in addition, research interests are also emerging in Asia. Despite recent advances, including root reinforcement into regional models still represents a research challenge, because of its high spatial and temporal variability: only a few applications are reported about areas of hundreds of square kilometers. The most promising and necessary future research directions include the study of soil moisture gradient and wildfire controls on the root strength, as these aspects have not been fully integrated into slope stability modelling.

Investigation on Parameter Calibration Method and Mechanical Properties of Root-Reinforced Soil by DEM

The behavior of root-soil system has raised more and more attention in both ecological and geotechnical fields. In this study, a two-dimensional discrete element method is employed using PFC2D to simulate the root-reinforced soil. The root system is mimicked by chains of bonded discs, while the soil is modeled by granular particles. The tensile strength of the root is modeled by interdiscs’ bonding strength. Three laboratory tests were studied to calibrate the micromechanical parameters of DEM. Finally, direct shear tests on rooted soil are simulated to investigate the influence of different root characteristics on the root reinforcement effect.

Root Reinforcement Effect on Cover Slopes of Solid Waste Landfill in Soil Bioengineering

This study investigated the effect of vegetation plant roots on the stability of the cover slopes of solid waste landfills. A large direct shear test and a root tensile strength test were conducted to quantify the effect of rooted soil of revegetation plants on the increment in shear strength of the soil as a method to protect the cover slope of solid waste landfills. In the large direct shear test, an increase in the shear strength of the ground with the presence of roots was observed, and the root reinforcement proposed in the literature was modified and proposed by analyzing the correlation between the root diameter and the tensile strength according to water content. The stability of the slope revegetation of a landfill facility, considering the root reinforcement effect of revegetation, was calculated by conducting a slope stability analysis reflecting the unsaturated seepage analysis of rainfall conditions for various analysis conditions, such as the gradient, the degree of compactness, the thickness of the cover, and the rooted soil depth of the landfill facility.

Using SlideforMAP and SOSlope to identify susceptible areas to shallow landslides in the Foreste Casentinesi National Park (Tuscany, Italy)

<p>SlideforMAP and SOSlope are part of a suite of software available through ecorisQ (www.ecorisq.org), an international, non-profit association promoting solutions for risk reduction of natural hazards. SlideforMap is a probabilistic model that quantifies the stabilizing effect of vegetation at the regional scale and localizes potential areas where forest protection could be improved. SOSlope is a hydro-mechanical model that computes the factor of safety at the slope scale, using a strain-step discrete element method, which includes the effects of vegetation root structure and composition. The research aims at investigating the landslide susceptibility at two different spatial scales, using both models. </p><p>The study area is located on a vegetated slope near an interregional connecting road (Tuscany, Emilia-Romagna, central Italy), which crosses the Foreste Casentinesi National Park (Tuscany) an important natural area for both touristic and recreational activities. </p><p>A shallow landslide susceptibility analysis was performed at two different spatial scales, combining the use of the two previously mentioned models. In particular, SlideforMap was applied to identify the main susceptible areas to landslides at regional scale. Next, the identified unstable areas were investigated at detailed scale using SOSlope which simulated an intense rainfall event. Specifically, both distributions of root and soil forces along the slope were analyzed; for the sake of comparison, beech (<em>Fagus sylvatica</em> L.) and spruce (<em>Picea abies</em> L.) parameters were used. Finally, a back-analysis was performed on real landslides. </p><p>The results showed the activation of root reinforcement spatially distributed in the studied slope. The basal root reinforcement map highlights significant differences, with beech showing higher reinforcement values compared to spruce. According to the factor of safety map, landslides may occur along the investigated unstable area. </p><p>SlideforMap and SOSlope may be useful tools to support land and forestry planning, allowing the localization and quantification of the protective effects of forests, root reinforcement included. Results demonstrated that the factor of safety can be used as benchmarks for silvicultural interventions, thus improving the whole planning activities in both forest and surrounding natural and man-made systems.</p>

Does Vegetation Really Affect Earthquake-Induced Landslides? Preliminary Analysis of Worldwide Database

<p>Vegetation is one of key factors controlling landslide occurrence, including frequency, size, and depth. Both horizontal and vertical root networks have important roles in stabilizing hillslopes. For instance, landslide density can be moderated by dense and deep tree root reinforcement below the potential soil slip surfaces. Landslide size can be reduced by extended dense and thick tree root networks, providing cohesive and lateral hillslope reinforcement. Vegetation conditions such as density and composition also alter the landslide occurrence because they are linked to root network density and strength, which are affected by different biogeoclimatic conditions. These findings regarding landslide-vegetation interactions were mostly based on rainfall-induced landslide cases. Preliminary, but yet to be confirmed, findings in Eastern Iburi Earthquake-Induced Landslides (EIL) showed that lateral root reinforcement might moderate the size of landslide scars in forested areas compared to logged areas.  Therefore, our primary objective was to examine the effect of different vegetation composition on EIL based on global data and supplemental analysis.</p><p>Our global database of EIL was compiled for a 20-yr period using a literature review and GIS analysis. Documented landslides were restricted to shallow mass movements with depths approximately less than 3 m. For vegetation-related analysis, we used Net Primary Production (NPP) and Leaf Area Index (LAI) derived from MODIS-Terra satellite images. Twenty-seven EIL cases were recorded in our database occurring from 2002 to 2018. Among these, 26% of the total cases occurred in Japan, followed by 18% for both in China and New Zealand. Based on climate types, 22% of total EIL cases occurred in temperate oceanic climate (Cfb) dominated by New Zealand EIL cases, and 15% cases occurred in humid subtropical climate region (Cfa), such as Japan. Moreover, 7% cases occurred in tropical rainforests (Af) and 7% cases in hot desserts climate regions (BWh). Among the 27 recorded cases of EIL, we selected eight EIL cases based on biomass classes, which are low (0-2 gC/m<sup>2</sup>/day), moderate (3-5 gC/m<sup>2</sup>/day), and high (>5 gC/m<sup>2</sup>/day). A power-law cumulative-area distribution of landslide areas showed that low biomass sites had the largest landslides (11,000 m<sup>2</sup>), followed by moderate biomass (3000 m<sup>2</sup>), and high biomass (200-3000 m<sup>2</sup>) with the smallest landslides, possibly associated with the density of vegetation. In low biomass regions, the average LAI was 1.8 m<sup>2</sup>/m<sup>2</sup>, which was three times lower compared to regions with higher biomass. This indicates that in regions with sparse vegetation, slope reinforcement by dense lateral root networks was minimal. Future research is focusing on compiling information on landslide scars and root depth to assess the effects of vegetation density and vertical root reinforcement on landslide characteristics in each biomass class.</p>