Rainfall-triggered Shallow Landslides Research Articles

Mobility characteristics of rainfall-triggered shallow landslides in a forest area in Mengdong, China

Mobility characteristics of rainfall-triggered shallow landslides in a forest area in Mengdong, China

Fast physically-based probabilistic modelling of rainfall-induced shallow landslide susceptibility at the regional scale considering geotechnical uncertainties and different hydrological conditions

The inherent uncertainty in hydro-geotechnical parameters presents a significant challenge for accurately predicting rainfall-triggered shallow landslides in mountainous regions. In this study, a novel probabilistic framework was developed and implemented in the “Py.GIS-FSLAM-FORM” software, designed to address the complexities associated with parameter uncertainty, correlation, and distribution. By combining the Fast Shallow Landslide Assessment Model (FSLAM) with the First-Order Reliability Method (FORM), we have enhanced the traditional probabilistic approach to create more accurate landslide susceptibility maps. This study emphasizes the uncertainly of geotechnical parameters and the critical influence of hydrological conditions on landslide susceptibility, especially focusing on the interaction between antecedent recharge (qa) and event rainfall (Pe). In our study area (Val d’Aran, Spain), the probabilistically based results revealed that areas of very high susceptibility are significantly affected by event rainfall, particularly on slopes of 30–40 degrees and aspects between 100 and 250 degrees. The variability in geotechnical parameters, especially the coefficient of variation (COV) in cohesion and friction angle, plays a crucial role in landslide susceptibility assessment, with increased COVs leading to greater landslide uncertainty. Additionally, cross-negative correlations and non-normal distributions of geotechnical parameters substantially influence the spatial distribution of landslides, notably when combining antecedent recharge with event rainfall. These results highlight the importance of incorporating parameter variability and hydrological conditions in susceptibility models to improve the precision of regional landslide forecasts. While the study was performed in Val d'Aran, its methodologies and conclusions are relevant to mountainous areas worldwide, offering insights for refining landslide prediction models and susceptibility assessments, contributing to global efforts in landslide disaster prevention.

Hydromechanical modeling of evolving post-wildfire regional-scale landslide susceptibility

Post-wildfire mass wasting is a major problem throughout many regions worldwide. Recent dramatic increases in global wildfire activities coupled with a shift in wildfire-prone elevation to higher altitudes raise the need to better predict post-fire rainfall-triggered landslides. Despite its importance, only a limited number of studies have investigated landslide susceptibility in areas hit by wildfires using hydromechanical models. However, most of these studies follow either qualitative or semi-quantitative approaches without explicitly considering the fire's effects on the impacted area's physical behavior. This study aims to develop and employ a physics-based framework to generate susceptibility maps of rainfall-triggered shallow landslides in areas disturbed by wildfire. A coupled hydromechanical model considering unsaturated flow and root reinforcement is integrated into an infinite slope stability model to simulate the triggering of shallow landslides from rainfall. The impact of fire is considered through its effects on soil and land cover properties, near-surface processes, and canopy interception. The developed model is then integrated into a geographic information system (GIS) to characterize the regional distribution of landslide potential and its variability considering topography, geology, land cover, and burn severity. The proposed framework was tested for a study site in Southern California. The site was burned in the San Gabriel Complex Fire in June 2016 and experienced widespread landsliding almost three years later following an extreme rainstorm in January 2019. The proposed framework could successfully model the location of observed shallow landslides. The model also revealed a significantly higher likelihood for slope failure in areas burned at moderate to high severities as opposed to unburned and low-burn severity areas. The findings of this study can be employed to predict the timing and general locations of rainfall-triggered shallow landslides following wildfires.

Comparison of different hydrological and stability assumptions for physically-based modeling of shallow landslides

Physically-based models are reliable techniques for landslide susceptibility assessment, therefore, several models have been proposed in the literature. In this study, two different hydrological models (FSLAM and TRIGRS) and two slope stability calculation methods (infinite slope and limit equilibrium method with spherical failure surface in SCOOPS3D) were compared. The rainfall-triggered shallow landslides that occurred in Kaptanpaşa, Rize (Turkey) in 2017 were selected as a case study. The main focus is investigating the impact of landslide morphology on the success of the slope stability models. For this purpose, landslides in the inventory were grouped according to their morphological characteristics, such as the landslide depth, length, width and their ratios, and their compatibility with model assumptions (e.g. the infinite slope assumption). Then, the model performances in different landslide types were evaluated separately. To calibrate the model parameters a new time-saving, semi-automated calibration strategy, based on a sensitivity analysis, is proposed. Concretely, stability parameters c′∅′Z were calibrated via a MATLAB code by considering the area under the curve (AUC) and extreme conditions: saturated and initial conditions. Overall, SCOOPS3D is deduced to have better performance than infinite slope analysis. However, the accuracy of SCOOPS3D is revealed to decrease for landslides with a high ratio of length/depth and width/depth. From the comparison of hydrological models, FSLAM yielded more plausible results than TRIGRS with the available data. It is demonstrated that the morphological features of the landslides significantly influence the performance of the physically-based stability models. Furthermore, it is highlighted that the resolution of the Digital Elevation Model in comparison to the width and length of the landslides in an inventory can be influential in the performance of the physical model. 10 m resolution of DEM is deemed to be suitable for the study area judging the predictive performance in small landslides.

Analysis of Poplar’s (Populus nigra ita.) Root Systems for Quantifying Bio-Engineering Measures in New Zealand Pastoral Hill Country

Populus nigra ita. is an important tree species for preventing rainfall-triggered shallow landslides and hydraulic bank erosion in New Zealand. However, the quantification of its spatial root distribution and reinforcement remains challenging. The objective of this study is to calibrate and validate models for the spatial upscaling of root distribution and root reinforcement. The data were collected in a 26-year-old “Tasman” poplar stand at Ballantrae Hill Country Research Station in New Zealand. We assessed root distribution at different distances from the stem of four poplar trees and from eleven soil pits along a transect located in a sparse to densely planting poplar stand. 124 laboratory tensile tests and 66 field pullout tests on roots with diameters up to 0.04 m were carried out to estimate root mechanical properties. The results show that the spatial distribution of roots can be well predicted in trenches of individual tree root systems (R2 = 0.78), whereas it tends to overestimate root distribution when planting density was higher than 200 stems per hectare. The root reinforcement is underestimated within single tree root systems (R2 = 0.64), but it performs better for the data along the transect. In conclusion, our study provided a unique and detailed database for quantifying root distribution and reinforcement of poplars on a hillslope. The implementation of these models for the simulation of shallow landslides and hydraulic bank erosion is crucial for identifying hazardous zones and for the prioritization of bio-engineering measures in New Zealand catchments. Results from this study are useful in formulating a general guideline for the planning of bio-engineering measures considering the temporal dynamics of poplar’s growth and their effectiveness in sediment and erosion control.

Sensitivity Analysis of a Physically Based Model to Assess Rainfall-Triggered Shallow Landslides

Rainfall-triggered shallow landslides are one of the most frequent geomorphological processes in tropical mountainous terrains, and they deserve special attention due to their potential negative consequences in society. Such processes involve several variables including those regarding precipitation, terrain morphology, and hydraulic and shear strength parameters of saturated and unsaturated soils. A spatially distributed and physically-based model for transient rainfall infiltration and grid-based regional slope stability analysis (TRIGRS), was implemented. It was used to analyze the influence of the mentioned variables on the triggering of shallow landslides by rainfall. A robust sensitivity analysis was carried out to quantify the influence of parameter variation on the change of the factor of safety (Delta f_textrm{s}) for shallow landslides, including a one-parameter-at-a-time analysis of a unique cell representing the simplest model space. Four combinations of saturated/unsaturated models and finite/infinite infiltration models were analyzed. The interaction among the hydraulic parameters was analyzed through small-multiple plots to observe their influence on Delta f_textrm{s}. It was found that Delta f_textrm{s} is most sensitive to variation in the maximum depth at which the landslide can be triggered, the slope angle, the cohesion, and the friction angle. In addition, it was found that the parameters of the soil–water characteristic curve for unsaturated soils have little influence on Delta f_textrm{s}. Finally, the interactions among the remaining parameters determine the impact of each one of these on Delta f_textrm{s}. Thus, the results showed that when the baseline set of parameters is changed, the influence of each parameter is modified.

Triggering-runout modelling of rainfall-triggered debris flows: A case study in the Campania region, Italy

Debris flows are unpredictable phenomena, listed among the hugest natural hazards, since they can cause important damages to humans and structures. Rainfall can trigger this type of movements, as it provokes the pore water pressure increasing, and so the soil strength reduction. The phenomenon modelling is a key aspect to predict and prevent damages. This article shows an approach for triggering and runout analysis: triggering is studied through an infinite slope stability model of rainfall-triggered shallow landslides, while runout is modelled using a depth-averaged numerical method, which replace the real heterogeneous flow with an equivalent homogeneous fluid. The work focuses the attention to events characterized by multiple triggering zones and releases converging on the same area, whose complexity is represented by the time- and space-distribution of the different flows. The proposed approach is applied to an event that hit part of the Campania region, Italy, in 1998, causing several damages. Two rheological laws are considered and compared for the analysis. The back-analysis allows the calibration of the rheological parameters and validation of the method. Results are discussed to identify the most suitable rheology for the benchmark event.

Towards Establishing Empirical Rainfall Thresholds for Shallow Landslides in Guangzhou, Guangdong Province, China

Empirical rainfall thresholds for predicting rainfall-triggered shallow landslides are proposed for Guangzhou city, which is prone to widespread geological hazards during the annual flood season due to the subtropical monsoon climate and frequent tropical storms and typhoons. In this study, the cumulated event rainfall (E, in mm), the duration of rainfall event (D, in day) (E–D) thresholds, normalized cumulated event rainfall, and the duration of rainfall event (EMAP–D) thresholds were defined. Thresholds based on five lithological units were obtained at 5%, 20%, and 50% probability levels using quantile regression methods. More than two-thirds of the landslides occurred within units of intrusive rock. The 20-day cumulative rainfall of 97 mm integrating cumulative event rainfall and the duration of rainfall events (CED) is introduced into the three-dimensional spatial threshold. The areas under the receiver operating characteristic curves for the CED threshold and E–D threshold were 0.944 and 0.914, respectively, and the true-positive rate of the CED threshold with the same probability level was slightly lower than that of the E–D threshold, but the CED threshold false-positive rate was much better than the E–D threshold, which can significantly reduce false alarm rate since many non-triggering rainfalls were filtered out.

Shallow landslides and vegetation at the catchment scale: A perspective

Shallow, rainfall-triggered landslides are an important catchment process that affect the rate and calibre of sediment within river networks and create a significant hazard, particularly when shallow landslides transform into rapidly moving debris flows. Forests and trees modify the magnitude and rate of shallow landsliding and have been used by land managers for centuries to mitigate their effects. We understand that at the tree and slope scale root reinforcement provides a significant role in stabilising slopes, but at the catchment scale root reinforcement models only partially explain where shallow landslides are likely to occur due to the complexity of subsurface material properties and hydrology. The challenge of scaling from slopes to catchments (from 1-D to 2-D) reflects the scale gap between geomorphic process understanding and modelling, and temporal evolution of material properties. Hence, our understanding does not, as yet, provide the necessary tools to allow vegetation to be targeted most effectively for landslide reduction. This paper aims to provide a perspective on the science underpinning the challenges land and catchment managers face in trying to reduce shallow landslide hazard, manage catchment sediment budgets, and develop tools for catchment targeting of vegetation. We use our understanding of rainfall-triggered shallow landslides in New Zealand and how vegetation has been used as a tool to reduce their incidence to demonstrate key points.

Controls on the size distributions of shallow landslides

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.

Minimum representative root distribution sampling for calculating slope stability in Pinus radiata D.Don plantations in New Zealand

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.

Determination of Empirical Rainfall Thresholds for Shallow Landslides in Slovenia Using an Automatic Tool

Rainfall-triggered shallow landslides represent a major threat to people and infrastructure worldwide. Predicting the possibility of a landslide occurrence accurately means understanding the trigger mechanisms adequately. Rainfall is the main cause of slope failures in Slovenia, and rainfall thresholds are among the most-used tools to predict the possible occurrence of rainfall-triggered landslides. The recent validation of the prototype landslide early system in Slovenia highlighted the need to define new reliable rainfall thresholds. In this study, several empirical thresholds are determined using an automatic tool. The thresholds are represented by a power law curve that links the cumulated event rainfall (E, in mm) with the duration of the rainfall event (D, in h). By eliminating all subjective criteria thanks to the automated calculation, thresholds at diverse non-exceedance probabilities are defined and validated, and the uncertainties associated with their parameters are estimated. Additional thresholds are also calculated for two different environmental classifications. The first classification is based on mean annual rainfall (MAR) with the national territory divided into three classes. The area with the highest MAR has the highest thresholds, which indicates a likely adaptation of the landscape to higher amounts of rainfall. The second classification is based on four lithological units. Two-thirds of the considered landslides occur in the unit of any type of clastic sedimentary rocks, which proves an influence of the lithology on the occurrence of shallow landslides. Sedimentary rocks that are prone to weathering have the lowest thresholds, while magmatic and metamorphic rocks have the highest thresholds. Thresholds obtained for both classifications are far less reliable due to the low number of empirical points and can only be used as indicators of rainfall conditions for each of the classes. Finally, the new national thresholds for Slovenia are also compared with other regional, national, and global thresholds. The thresholds can be used to define probabilistic schemes aiming at the operative prediction of rainfall-induced shallow landslides in Slovenia, in the framework of the Slovenian prototype early warning system.

Physically-based landslide prediction over a large region: Scaling low-resolution hydrological model results for high-resolution slope stability assessment

Rainfall-triggered shallow landslides are widespread natural hazards around the world, causing many damages to human lives and property. In this study, we focused on predicting landslides in a large region by coupling a 1 km-resolution hydrological model and a 90 m-resolution slope stability model, where a downscaling method for soil moisture via topographic wetness index was applied. The modeled hydrological processes show generally good agreements with the observed discharges: relative biases and correlation coefficients at three validation stations are all <20% and >0.60, respectively. The derived scaling law for soil moisture allows for near-conservative downscaling of the original 1-km soil moisture to 90-m resolution for slope stability assessment. For landslide prediction, the global accuracy and true positive rate are 97.2% and 66.9%, respectively. This study provides an effective and computationally efficient coupling method to predict landslides over large regions in which fine-scale topographical information is incorporated.

Geoelectrical characterization and monitoring of slopes on a rainfall-triggered landslide simulator

In this paper, we present the results of time-lapse electrical resistivity tomography (ERT) monitoring of rainfall-triggered shallow landslides reproduced on a laboratory-scale physical model. The main objective of our experiments was to monitor rainwater infiltration through landslide body in order to improve our understanding of the precursors of failure. Time-domain reflectometry (TDR) data were also acquired to obtain the volumetric water content. Knowing the porosity, water saturation was calculated from the volumetric water content and we could calibrate Archie's equation to calculate water saturation maps from inverted resistivity values. Time-lapse ERT images proved to be effective in monitoring the hydrogeological conditions of the slope as well as in detecting the development of fracture zones before collapse. We performed eight laboratory tests and the results show that the landslide body becomes unstable at zones where the water saturation exceeds 45%. It was also observed that instability could occur at the boundaries between areas with different water saturations. Our study shows that time-lapse ERT technique can be employed to monitor the hydrogeological conditions of landslide bodies and the monitoring strategy could be extended to field-scale applications in areas prone to the development of shallow landslides.

Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China

This study investigated the characteristics of rainfall-triggered landslides during the Typhoon Bilis in the Dongjiang Reservoir Watershed, China. The comparative shallow landslide susceptibility mappings (LSMs) were produced by the ensemble data-driven statistical models in a GIS environment. At first, the landslide inventory for the study area was prepared from the high-resolution QuickBird images, and China–Brazil Earth Resources Satellite images, and field survey. Other necessary data for landslide susceptibility analysis such as the amount of rainfall, geology, and topography were also collected from the respective agencies. Twelve predisposing factors were then prepared using this available dataset. To reduce the subjectivity of models and caution in the selection of predisposing factors, and to avoid the spatial autocorrelation redundancy, certainty factor approach was attempted to optimize these twelve set of parameters. For validating the accuracy of the model, the original landslide data were randomly divided into two parts: 70% (1545 landslides) for training the model and the remaining 30% (662 landslides) for validation. The verified results showed that using the optimized predisposing factors has a higher performance than using all the original twelve factors. The results of ensemble models also showed that LSM maps prepared using binary logistic regression (accuracy is 0.848) model are more accurate than those prepared using bivariate statistical analysis (accuracy is 0.837) model. Additionally, our analysis concludes that the short duration and high-intensity rainfall, drainage density, lithology, and curvature are the major influencing factors for landslide occurrences in this case study area. This research provides an improved understanding of the mechanism of landslides caused by the typhoons for the adjoining watersheds nearby the reservoir. The preliminary understandings and approach could also be applied in similar geological and rainfall-triggered case study sites in the other parts of the world for risk mitigation.

Physical-based rainfall-triggered shallow landslide forecasting

This study demonstrates the applications of two physical-based early warning methods for rainfall-induced shallow landslide and compare their relative performance. One method is rainfall threshold-based method and the other method is by real-time simulation. The former establishes landslide threshold in advance using 50 historical rainfall events, in conjunction with physical-based rainfall-triggered shallow landslide model, to evaluate the stability of a concerned slope. Quantitative precipitation estimation (QPE) for nowcast is used in the rainfall threshold-based method for landslide predictions. The latter method also applies rainfall-triggered landslide model in real-time simulation by feeding QPE and quantitative precipitation forecast (QPF) of specified lead-time. Both methods are integrated into an early warning system (e.g. Delft-FEWS) for real-time nowcast and/or forecast purposes. The two shallow landslide early warning methods are applied to a slope in the vicinity of a highway section in Taiwan. Comparisons between the two methods are made to evaluate their performance using rainfall data from three past typhoon events. Despite of some discrepancies found in the results, both methods can predict landslide quite consistently. Without sufficient number of actual landslide records for model validation, the true accuracy of both landslide early warning methods cannot be assessed. However, the consistency of predicted landslide occurrence times during three historical typhoon events in the case study indicated that they could be viable for providing good supportive information for decision-making in landslide hazard mitigation.

The Weather Radar Observations Applied to Shallow Landslides Prediction: A Case Study From North-Western Italy

In northern Italy rainfall-triggered shallow landslides are recurrent hazardous phenomena that cause casualties and extensive damages. In the last decades several early warning systems (EWSs) have been developed based on rainfall intensity–event duration (I-D) thresholds derived by long rain gauges time series. However, rain gauges density and their representativeness limit reliability of such EWSs. In the past decades, several studies explored successfully the usefulness of reliable quantitative precipitation estimates (QPEs) by weather radar. The availability of high spatial and temporal resolution QPEs with short latency of the data makes those observations appealing as input data to automatic EWSs. Nevertheless, weather radar based QPEs can be affected by several sources of errors and uncertainties (miscalibration, partial beam blocking, overhanging precipitation, and so on). Analysing the heavy precipitations that hit Piemonte, north-western Italy, on November 2016, causing floods and triggering widespread shallow landslides, this work presents a fruitful case study of operational weather radar application in shallow landslides early warning system.

Rainfall thresholds for the activation of shallow landslides in the Italian Alps: the role of environmental conditioning factors

The aim of the present work is to investigate the role exerted by selected environmental factors in the activation of rainfall-triggered shallow landslides and to identify site-specific rainfall thresholds. The study concerns the Italian Alps. The region is exposed to widespread slope instability phenomena due to its geological, morphological and climatic features. Furthermore, the high level of anthropization that characterizes wide portions of the territory increases the associated risk. Hence, the analysis of potential predisposing factors influencing landslides triggering is worthwhile to improve the current prediction skills and to enhance the preparedness and the response to these natural hazards.During the last years, the Italian National Research Council's Research Institute for Hydro-geological Protection (CNR-IRPI) has contributed to the analysis of triggering conditions for rainfall-induced landslides in the framework of a national project. The project, funded by the National Department for Civil Protection (DPC), focuses on the identification of the empirical rainfall thresholds for the activation of shallow landslides in Italy. The first outcomes of the project reveal a certain variability of the pluviometric conditions responsible for the mass movements activation, when different environmental settings are compared. This variability is probably related to the action of local environmental factors, such as lithology, climatic regime or soil characteristics. Based on this hypothesis, the present study aims to identify separated domains within the Italian Alps, where different triggering conditions exist and different countermeasures are needed for risk prevention. For this purpose, we collected information concerning 511 landslides activated in the period 2000–2012 and reconstructed 453 rainfall events supposed to be responsible for the activations. Then, we selected a set of thematic maps to represent the hypothesised landslide conditioning factors and to identify the supposed homogeneous domains within the study area. We employed an existing statistical method for the definition of the cumulated event rainfall vs. rainfall duration (ED) thresholds, for both the entire catalogue of rainfall events and for the events falling in the separated domains. The obtained results contribute to a better understanding of the role exerted by geological, pedological and climatic factors in landslides activation and help identifying separated domains where different risk managing strategies should be adopted. The proposed methodology can be a valid support for risk reduction strategies planning at regional scale.

Tree-root control of shallow landslides

Abstract. Tree roots have long been recognized to increase slope stability by reinforcing the strength of soils. Slope stability models usually include the effects of roots by adding an apparent cohesion to the soil to simulate root strength. No model includes the combined effects of root distribution heterogeneity, stress-strain behavior of root reinforcement, or root strength in compression. Recent field observations, however, indicate that shallow landslide triggering mechanisms are characterized by differential deformation that indicates localized activation of zones in tension, compression, and shear in the soil. Here we describe a new model for slope stability that specifically considers these effects. The model is a strain-step discrete element model that reproduces the self-organized redistribution of forces on a slope during rainfall-triggered shallow landslides. We use a conceptual sigmoidal-shaped hillslope with a clearing in its center to explore the effects of tree size, spacing, weak zones, maximum root-size diameter, and different root strength configurations. Simulation results indicate that tree roots can stabilize slopes that would otherwise fail without them and, in general, higher root density with higher root reinforcement results in a more stable slope. The variation in root stiffness with diameter can, in some cases, invert this relationship. Root tension provides more resistance to failure than root compression but roots with both tension and compression offer the best resistance to failure. Lateral (slope-parallel) tension can be important in cases when the magnitude of this force is comparable to the slope-perpendicular tensile force. In this case, lateral forces can bring to failure tree-covered areas with high root reinforcement. Slope failure occurs when downslope soil compression reaches the soil maximum strength. When this occurs depends on the amount of root tension upslope in both the slope-perpendicular and slope-parallel directions. Roots in tension can prevent failure by reducing soil compressive forces downslope. When root reinforcement is limited, a crack parallel to the slope forms near the top of the hillslope. Simulations with roots that fail across this crack always resulted in a landslide. Slopes that did not form a crack could either fail or remain stable, depending on root reinforcement. Tree spacing is important for the location of weak zones but tree location on the slope (with respect to where a crack opens) is as important. Finally, for the specific cases tested here, intermediate-sized roots (5 to 20 mm in diameter) appear to contribute most to root reinforcement. Our results show more complex behaviors than can be obtained with the traditional slope-uniform, apparent-cohesion approach. A full understanding of the mechanisms of shallow landslide triggering requires a complete re-evaluation of this traditional approach that cannot predict where and how forces are mobilized and distributed in roots and soils, and how these control shallow landslides shape, size, location, and timing.

Transient modeling of regional rainfall-triggered shallow landslides

This study investigates the transient modeling of regional rainfall-triggered shallow landslides in unsaturated soil using the Richards equation. To model shallow landslides within a distributed regional-scale framework, infinite slope stability analysis coupled with the hydrological model with consideration of the fluctuation of time-dependent pore water pressure and the soil–water characteristic curve proposed by van Genuchten was developed. The validity of the proposed model is established through several test problems by comparing the numerical results with the analytical solutions. A new procedure to set up wide-range shallow landslide analysis and to integrate regional distribution variations for input data such as geology, groundwater level, hydrogeological characteristics, and rainfall intensity and duration was presented. The results obtained demonstrate that the computed distribution of the safety factor is consistent with the distribution of actual landslides. In addition, the fluctuation of pore water pressure in unsaturated soil dominates the stability of landslides during typhoons accompanied by heavy rainfall. The findings observed in this study are a fundamental contribution to environmental effects for landslides in areas with higher occurrence and vulnerability to extreme precipitation.