Root Reinforcement in Slope Stability Models: A Review

نویسندگان

چکیده

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 most relevant for slope stability. Lately, literature has been greatly enriched novel research this phenomenon. To investigate which aspects have treated, results obtained require further attention, we reviewed papers published during period 2015–2020 dealing with reinforcement. This paper—after introducing main stability, recalling studies reference—provides synthesis contributions subtopics: (i) approaches estimating distribution at regional scale; (ii) new stability models, including (iii) particular plant species, forest management, structure, wildfires moisture gradient Including analysis resulted topic receiving growing particularly Europe; addition, interests are also emerging Asia. Despite recent advances, into models still challenge, because its high spatial temporal variability: only few applications reported about areas hundreds square kilometers. promising necessary future directions include study wildfire controls strength, these not fully integrated

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Soil moisture causes dynamic adjustments to root reinforcement that reduce slope stability

In steep soil-mantled landscapes, the initiation of shallow landslides is strongly controlled by the distribution of vegetation, whose roots reinforce the soil. The magnitude of root reinforcement depends on the number, diameter distribution, orientation and the mechanical properties of roots that cross potential failure planes. Understanding how these properties vary in space and time in fores...

متن کامل

Using three-dimensional plant root architecture in models of shallow-slope stability.

BACKGROUND The contribution of vegetation to shallow-slope stability is of major importance in landslide-prone regions. However, existing slope stability models use only limited plant root architectural parameters. This study aims to provide a chain of tools useful for determining the contribution of tree roots to soil reinforcement. METHODS Three-dimensional digitizing in situ was used to ob...

متن کامل

A Proposed Modeling Method in Finite Element Slope Stability Analysis

Limit-equilibrium method (LEM) and finite element method (FEM) with strength reduction method (SRM) techniques are the most widely used analysis tools in slope stability assessment. Recently, researchers have reported that both factor of safety (FOS) values and failure surfaces obtained from LEM and FEM are generally in good agreement, except in some particular cases. In this paper, the FOS and...

متن کامل

Enhanced application of root-reinforcement algorithms for bank-stability modeling

Riparian vegetation is known to exert a number of mechanical and hydrologic controls on bank stability. In particular, plant roots provide mechanical reinforcement to a soil matrix due to the different responses of soils and roots to stress. Root reinforcement is largely a function of the strength of the roots crossing potential shear planes, and the number and diameter of such roots. However, ...

متن کامل

Slope Stability Analysis Using a Self-Adaptive Genetic Algorithm

This paper introduces a methodology for soil slope stability analysis based on optimization, limit equilibrium principles and method of slices. In this study, the slope stability analysis problem is transformed into a constrained nonlinear optimization problem. To solve that, a Self-Adaptive Genetic Algorithm (GA) is utilized. In this study, the slope stability safety factors are the objective ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Geosciences

سال: 2021

ISSN: ['2076-3263']

DOI: https://doi.org/10.3390/geosciences11050212