Academic literature on the topic 'Rainfall-triggered shallow landslides, Regional slope stability analysis, Root reinforcement, Vegetation'

Abstract. In this work, we apply a physically based model, namely the HIRESSS (HIgh REsolution Slope Stability Simulator) model, to forecast the occurrence of shallow landslides at the regional scale. HIRESSS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions during a rainfall event. The modeling software is made up of two parts: hydrological and geotechnical. The hydrological model is based on an analytical solution from an approximated form of the Richards equation, while the geotechnical stability model is based on an infinite slope model that takes the unsaturated soil condition into account. The test area is a portion of the Aosta Valley region, located in the northwest of the Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400 m a.s.l. on the Dora Baltea River's floodplain to 4810 m a.s.l. at Mont Blanc. In the study area, the mean annual precipitation is about 800–900 mm. These features make the territory very prone to landslides, mainly shallow rapid landslides and rockfalls. In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslide formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed using 12 survey points. The data collected contributed to the generation of an input map of parameters for the HIRESSS model. In order to consider the effect of vegetation on slope stability, the soil reinforcement due to the presence of roots was also taken into account; this was done based on vegetation maps and literature values of root cohesion. The model was applied using back analysis for two past events that affected the Aosta Valley region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, provided good results and a good prediction accuracy for the HIRESSS model from both a temporal and spatial point of view.

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.

Abstract. Shallow landslides pose a risk to infrastructure and residential areas. Therefore, we developed SlideforMAP, 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. SlideforMAP 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 on observed events. For each generated landslide, SlideforMAP calculates a factor of safety using the limit equilibrium approach. Relevant soil parameters are assigned to the generated landslides from log-normal distributions based on mean and standard deviation values representative of 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 by root proximity and root strength derived from single-tree-detection data. The ratio of unstable landslides to the number of generated landslides, per raster cell, is calculated and used as an index for landslide probability. We performed a calibration of SlideforMAP for three test areas in Switzerland with a reliable landslide inventory by randomly generating 1000 combinations of model parameters and then maximizing the area under the curve (AUC) of the receiver operation curve. The test areas are located in mountainous areas ranging from 0.5–7.5 km2 with mean slope gradients from 18–28∘. The density of inventoried historical landslides varies from 5–59 slides km−2. AUC values between 0.64 and 0.93 with the implementation of single-tree detection indicated a good model performance. A qualitative sensitivity analysis indicated that the most relevant parameters for accurate modelling of shallow-landslide probability are the soil thickness, soil cohesion and the precipitation intensity / transmissivity ratio. Furthermore, we show that the inclusion of single-tree detection improves overall model performance compared to assumptions of uniform vegetation. In conclusion, our study shows that the approach used in SlideforMAP can reproduce observed shallow-landslide occurrence at a catchment scale.

Background: Rainfall-triggered shallow landslides on steep slopes cause significant soil loss and can be hazards for property and people in many parts of the world. In New Zealand’s hill country, they are the dominant erosion process and are responsible for soil loss and subsequent impacts on regional water quality. Use of wide-spaced trees and afforestation with fast growing conifers are the primary land management tools in New Zealand to help control erosion and improve water quality. To decide where to implement erosion controls in the landscape requires determining the most susceptible places to these processes and models that incorporate how trees reinforce soils to understand if, and when, such treatments become effective. Methods: This paper characterises the mechanical properties of Pinus radiata D.Don roots (the common tree species used for afforestation in New Zealand) by means of field pullout tests and by measuring the root distribution at 360 degrees around trees. The Root Bundle Model (RBM) was used to calculate the root reinforcement. Statistical analysis was carried out to assess the statistical reduction coefficients of root reinforcement that depend on the number of measurements, used in geotechnical analysis to reduce the mean value of a parameter to a so-called characteristic value. Results: We show that to reach an effective level of root reinforcement, trees of 0.5 m DBH require a density of about 300 trees per hectare. Trees of this size are about 30 years of age across many sites and have generally reached the recommended conditions for clear-fell harvesting. The analysis of variance shows that 4 trees are the minimum number to be excavated to obtain sufficient root information to obtain less than 5% of error with a 95% of probability on the estimation of a design value of root reinforcement in accord with geotechnical standards. Conclusions: We found that the variability of lateral and basal root reinforcement does not limit the implementation of vegetation in slope stability models for Pinus radiata. We adopt for the first time the concept of a minimum sampling requirement and characteristic value, similarly to what is assumed for the value of effective soil cohesion in geotechnical guidelines for slope stability calculations.

The shallow landslides are hazardous mass movements commonly triggered by intense rainfall. The hazardousness of these events is mainly due to their common evolution in rapid mass movements as debris avalanches and flows and to the frequently occurring in the form of clusters of events. Because of their characteristics, the forecasting is a particularly valuable tool to protect people and infrastructures from this kind of landslide events. The presence of vegetation on hillslopes significantly reduces the slopes susceptibility to the shallow landslides, and the stabilising action is mainly due to the reinforcement of the soil by the roots. The spatial variation of the root reinforcement should be therefore considered in distributed slope stability analyses. However, the natural variability of the parameter makes it challenging to insert the root reinforcement into the models. Many approaches to the problem were tested, but nowadays there are still lacking a distributed slope stability model capable of very quick processing in which the root reinforcement is considered and an approach to estimate the root cohesion at the regional scale that it has been tested in very wide areas and for long period-simulations. In this study, we present the effect of the root cohesion on slope stability simulations at the regional scale obtained using a physically-based distributed slope stability model, the HIRESSS (HIgh REsolution Slope Stability Simulator). The HIRESSS model was selected for the purposes, being capable of rapid processing even in wide areas thanks to the parallel structure of its code. The simulator was modified to insert the root reinforcement among the geotechnical parameters considered to computing the factor of safety in probabilistic terms, and for this purpose a commonly adopted model for the root cohesion was chosen. To build a map of the root cohesion for the study areas, the distribution of plant species in the area was obtained from vegetation distribution map and in situ surveys, then a value of root cohesion and a range of variation was defined for each plant species based on the most recent literature in this field, finally, to reproduce the natural variability, the root reinforcement was treated as variable in Monte Carlo simulations, as well as the other geotechnical parameters. The results of the simulations for the study areas were processed and analysed in order to evaluate the effect of the root cohesion on the failure probabilities and the adopted approach to estimate the root cohesion at the regional scale. The comparative analyses carried out on the results of the simulations performed inserting or not the root reinforcement brought out little differences between the two from the point of view the failure probabilities, particularly when the saturated conditions of the soil are reached. 10 Based on the findings of this research, it is considered that a root cohesion model different to the one adopted is preferable in the context of the shallow landslides, in applications in which working with failure probabilities (instead of factor of safety values) is desirable, and in areas similar to the ones of the study.