Rainfall-induced Shallow Landslides Research Articles

Failure behaviors of rainfall-induced shallow landslides: insights from a novel large angle-adjustable plane shear apparatus

Failure behaviors of rainfall-induced shallow landslides: insights from a novel large angle-adjustable plane shear apparatus

SLEM (Shallow Landslide Express Model): A Simplified Geo-Hydrological Model for Powerlines Geo-Hazard Assessment

Powerlines are strategic infrastructures for the Italian electro-energetic network, and natural threats represent a potential risk that may influence their operativity and functionality. Geo-hydrological hazards triggered by heavy rainfall, such as shallow landslides, have historically affected electrical infrastructure networks, causing pylon failures and extensive blackouts. In this work, an application of the reworked version of the model proposed by Borga et al. and Tarolli et al. for rainfall-induced shallow landslide hazard assessment is presented. The revised model is called SLEM (Shallow Landslide Express Model) and is designed to merge in a closed-from equation the infinite slope stability with a simplified hydrogeological model. SLEM was written in Python language to automatise the parameter calculations, and a new strategy for evaluating the Dynamic Contributing Area (DCA) and its dependence on the initial soil moisture condition was included. The model was tested for the case study basin of Trebbia River, in the Emilia-Romagna region (Italy) which in the recent past experienced severe episodes of geo-hydrological hazards. The critical rainfall ratio (rcrit) able to trigger slope instability prediction was validated against the available local rainfall threshold curves, showing good performance skills. The rainfall return time (TR) was calculated from rcrit identifying the most hazardous area across the Trebbia basin with respect to the position of powerlines. TR was interpreted as an index of the magnitude of the geo-hydrological events considering the hypothesis of iso-frequency with precipitation. Thanks to its fast computing, the critical rainfall conditions, the temporal recurrence and the location of the most vulnerable powerlines are identified by the model. SLEM is designed to carry out risk analysis useful for defining infrastructure resilience plans and for implementing mitigation strategies against geo-hazards.

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.

Spatio-Temporal Prediction of Three-Dimensional Stability of Highway Shallow Landslide in Southeast Tibet Based on TRIGRS and Scoops3D Coupling Model

National Highway G559 is the first highway in Southeast Tibet into Motuo County, which has not only greatly improved the difficult situation of local roads, but also promoted the economic development of Tibet. However, rainfall-induced shallow landslides occur frequently along the Bomi–Motuo section, which seriously affects the safe operation and construction work of the highway. Therefore, it is urgent to carry out geological disaster assessment and zoning along the highway. Based on remote-sensing interpretation and field investigation, the distribution characteristics and sliding-prone rock mass of shallow landslides along the Bomi–Motuo Highway were identified. Three-dimensional stability analysis of regional landslides along the Bomi-Motuo Highway under different rainfall scenarios was carried out based on the TRIGRS and Scoops3D coupled model (T-S model). The temporal and spatial distribution of potential rainfall landslides in this area is effectively predicted, and the reliability of the predicted results is also evaluated. The results show that: (1) The slope structure along the highway is mainly composed of loose gravel soil on the upper part and a strong weathering layer of bedrock on the lower part. The sliding surface is mostly a circular and plane type, and the main failure types are creep–tensile failure and flexural–tensile failure. (2) Based on the T-S coupling model, it is predicted that the potential landslide along the Bomi–Motuo Highway in the natural state is scattered. The distribution area of extremely unstable and unstable areas accounts for 4.92% of the total area. In the case of extreme rainfall once in a hundred years, the proportion of instability area (Fs < 1) predicted by the T-S coupling model 1 h after rainfall is 7.74%, which is 1.57 times that of the natural instability area. The instability area (Fs < 1) accounted for 43.40% of the total area after 12 h of rainfall. The potential landslides were mainly distributed in the Bangxin–Zhamu section and the East Gedang section. (3) The TRIGRS and T-S coupling model is both suitable for predicting the temporal–spatial distribution of rainfall-induced shallow landslides, but the TRIGRS model has the problem of over-prediction. The instability area predicted by the T-S coupling model accounted for 43.30%, and 74% of the historical landslide disaster points in the area were correctly predicted. (4) In terms of rainfall response, the T-S coupling model shows higher sensitivity. The %LRclass (Fs < 1) index of the T-S coupling model is above 50% in different time periods, and its landslide-prediction effect (%LRclass = 78.80%) was significantly better than that of the one-dimensional TRIGRS model (%LRclass = 45.50%) under a 12 h rainfall scenario. The research results have important reference significance for risk identification and disaster reduction along the G559 Bomi–Motuo Highway.

ERT-based experimental integrated approach for soil hydrological characterization in rainfall-induced shallow landslides prone areas

Shallow landslides triggered by heavy rainfalls are slope instabilities, developed in the most superficial eluvial layers, involving the first 2 m from the ground level. A crucial predisposing factor in shallow landslides occurrence is the soil water content, generally measured trough sensors installed in the first soil layers. However, despite being a very precise approach, this monitoring technique provides for a site-specific dataset. An integrated method to extend the hydrological characterization from site-specific to slope scale is presented, combining geotechnical analyses, field data monitoring, and geophysical investigations, in two experimental test sites located on Italian Apennines. Ten Electrical Resistivity Tomographies (ERT) of the first soil horizons were performed through different array geometries (2D-3D-Time-Lapse), calibrated and interpreted basing on stratigraphic logs, trenches, and monitored soil water content field data. The test sites colluvial covers composition was analyzed and compared to resistivity values to build conceptual hydrogeological models of the deep-water circulation. In addition, two time-lapse (4D) ERT surveys were performed in both test sites simulating very intense precipitations, to determine the resistivity variations at different soil drainage conditions, thus estimating the average bulk permeability. Bulk permeability can be also a useful input parameter for slope stability models, widely employed in engineering practices. This integrated method proved to be very useful for the hydrogeological characterization of the subsoil at slope scale, where it is susceptible to slope instability, improving the knowledge of water circulation, as well as the bulk permeability heterogeneities, which are shallow landslides triggering parameters.

Mechanism of Root Reinforcement Involved in Rainfall-Induced Shallow Landslide Mitigation: A Review

Mechanism of Root Reinforcement Involved in Rainfall-Induced Shallow Landslide Mitigation: A Review

Assessment of Rainfall-Induced Shallow Landslides in Kavre District, Nepal

Steep slopes and fragile geology make Nepal a landslide-prone country. Kavre district experiences a large number of shallow landslides in the monsoon season. This research aims to establish rainfall intensity relation with rainfall duration along with rainfall threshold for the initiation of shallow landslides in the Kavre district, Nepal. The six rain gauge stations' rainfall data in the Kavre district from 1987-2016 and landslide data from 1987-2013 were used for establishing rainfall thresholds. The rainfall that risks the landslide event was sorted and the regression analysis of the rainfall and landslide yielded a relationship I =86.738 *D-1.066 having a coefficient of determination R2 = 0.1257. The analysis also incorporates the drawing of the lower boundary which is the 48-h rainfall depth that indicates the rainfall threshold for the initiation of landslide in the Kavre district. The 48-hour rainfall intensity and rainfall depth at which the risk of landslide initiation is high in the Kavre district is 1.4 mm/h. and 67.18mm. Analysis of the antecedent rainfall and the landslide occurrence event indicated that the daily rainfall at failure conditions is better correlated with 3 days of cumulative rainfall at failure than with 5, 7, 10, 15, and 30 days. The study is significant for rainfall-induced landslide disaster management.

Quantification of climate change impact on rainfall-induced shallow landslide susceptibility: a case study in central Norway

ABSTRACT Climate change impact on rainfall-induced landslide susceptibility of a certain region is often implied based on expected changes in rainfall patterns and rarely explicitly quantified. This study aims to address this gap by implementing coupled landslide and climate modelling chains to explicitly assess the effects of changing rainfall patterns on rainfall-induced landslide susceptibility. The effects of climate change are integrated into the landslide modelling chain via Intensity-Duration-Frequency (IDF) curves for the present and future climate conditions for a landslide-prone study area located in central Norway. The effects of climate change on landslide susceptibility are examined by using a physical-based landslide prediction model with rainfall events of varying duration and intensity that are simulated based on the climate-dependent IDF curves. The novelty of this study is the proposition of a novel probabilistic framework to assess the climate change impact on landslide susceptibility for rainfall events with a given duration. The proposed framework accounts for both the uncertainties of rainfall events through probabilistic interpretation of IDF curves and the uncertainties in the landslide model with the Monte Carlo method. Compared to results based on only intense rainfall events, the proposed framework leads to a lower increase in the probability of landslide initiation and landslide-susceptible extents due to climate change.

Optical and Thermal Image Processing for Monitoring Rainfall Triggered Shallow Landslides: Insights from Analogue Laboratory Experiments

This study explores the innovative use of digital image processing (DIP) techniques, also named PhotoMonitoring, for analysing the triggering conditions of shallow landslides. The approach, based on the combination of optical and infrared thermographic imaging (IRT), was applied to a laboratory-scale slope, reproduced in a flume test apparatus. Three experiments were conducted to replicate rainfall-induced shallow landslides, applying change detection and digital image correlation analysis to both optical and thermal images. The method combines IRT’s ability to measure ground surface temperature changes with DIP’s capacity to track movement and displacement. Results showed the high reliability of the displacement time-series obtained through IRT-DIP with respect to the reference optical-DIP. The IRT-DIP technique also detects anomaly signals two minutes before landslide occurrence that can be regarded as a possible failure precursor. This study testifies to the potential of image analysis as a remote sensing technique, demonstrating the ability of DIP to capture the dynamics of shallow landslides, as well as the advantages of optical–IRT combinations to follow slope deformation processes during night-time. This approach, if properly adapted to real-scale scenarios, may contribute to a better understanding of landslide behaviour, improve landslide monitoring strategies, and promote more effective early warning systems (EWS).

Comparison between mechanical and hydrological reinforcement effects of cultivated plants on shallow slope stability

Root reinforcement, provided by plants in soil, can be exerted by a mechanical effect, increasing soil shear strength for the presence of roots, or by a hydrological effect, induced by plant transpiration. No comparisons have been still carried out between mechanical and hydrological reinforcements on shallow slope stability in typical agroecosystems. This paper aims to compare these effects induced by sowed fields and vineyards and to assess their effects towards the shallow slope staibility. Root mechanical reinforcement has been assessed through Root Bundle Model-Weibull. Root hydrological reinforcement has been evaluated using an empirical relationship with monitored or modelled pore water pressure. Each reinforcement has been inserted in a stability model to quantify their impacts on susceptibility towards shallow landslides. Considering the same environment, corresponding to a typical agroecosystem of northern Italian Apennines, land use has significant effects on saturation degree and pore water pressure, influencing hydrological reinforcement. Root hydrological reinforcement effect is higher in summer, although rainfall-induced shallow landslides rarely occur in this period due to dry soil conditions. Instead, in wet and cold periods, when shallow landslides can develop more frequently, the stabilizing contribution of mechanical reinforcement is on average higher than the hydrological reinforcement. In vineyards, the hydrological reinforcement effect could be observed also during autumn, winter and spring periods, giving a contribution to slope stability also in these conditions. This situation occurs when plants uptake enough water from soil to reduce significantly pore water pressure, guaranteeing values of hydrological reinforcement of 1–3 kPa at 1 m from ground, in agreement with measured mechanical root reinforcement (up to 1.6 kPa). These results suggest that both hydrological and mechanical effects of vegetation deserve high regard in susceptibility towards shallow landslides, helping in selection of the best land uses to reduce probability of occurrence of these failures over large territories.

A data-driven method for the estimation of shallow landslide runout

Rainfall-induced shallow landslides cause damages and casualties. Estimating the development of the runout is essential, however, the methods which are traditionally employed to predict the runout distance are either reliable but complex and applicable at a local scale or applicable at a larger scale but highly simplified.The present work aims to develop a method based on data-driven algorithms for predicting the runout of shallow landslides at a large scale, taking into account geological, geomorphological, and land use heterogeneities.The model, which was tested in the Oltrepò Pavese (Italy), a hilly area of over 1000 km2, requires as inputs a set of predictors collected from geological maps, land use maps and freely available satellite images. Different algorithms were tested, identifying the Random Forest algorithm as the best performing, with a Coefficient of Determination of 0.94 and Mean Absolute Error of 4–5.8 m. The size of the source area strongly influences runout estimation, as do land use, lithology, and slope angle. The model provides a probable runout length, which can be estimated, based on past observations in the test area, to propagate along the line of the greatest slope.The main novelties of this work include: a) the development of a methodology to study the previously overlooked runout dynamics, b) the exploitation of remotely-derived, freely available input data, c) the application at a large scale in a heterogenous area, d) the adaptability of the model different study areas and e) the dependency of the model on land use, which allows for land use change scenarios to be made. If coupled with a susceptibility assessment tool to identify where a landslide might develop, it could be used to give a fast yet accurate assessment of the probable runout length and to identify which targets could potentially be affected by the landslide.

Analysis of the Role of Precipitation and Land Use on the Size of the Source Area of Shallow Landslides

Rainfall-induced shallow landslides cause damage to human activities and infrastructureseach year, and although the size of a landslide correlates to the damage that it causes, very few studies have previously investigated the factors that influence the size of a shallow landslide. The aim of this work was to assess the role of precipitation and land use in controlling the size of the source area of rainfall-induced shallow landslides. After ruling out the impact of the slope angle and bedrock lithology in the two selected catchments, the role of land use was investigated: the statistical tests showed that woodlands and vineyards had statistically different source area size distributions, possibly due to the different hydrological behaviours between the two. A correlation was additionally found between the size of a source area and the amount of cumulated rainfall in the three days prior to each analysed event. In both cases, an increase in source area size was linked to an increase in pore pressure. This study aimed to fill the existing gap in the research to help implement policies aimed at reducing the size, and consequently the impact, of shallow landslides.

Evaluation of influences of forest cover change on landslides by comparing rainfall-induced landslides in Japanese artificial forests with different ages

In this study, we evaluated the influence of forest cover changes on rainfall-induced shallow landslides by comparing two shallow landslides and debris flows that occurred on plantation forests of different ages in Japan: the Kake disaster in 1988 and the Asakura disaster in 2017. At Kake, the trees ranged in age from 10 to 30 years, whereas at Asakura the trees were over 40 years old. The rainfall characteristics that triggered each landslide were estimated using a three-layer tank model, and the results, as well as the volume of driftwood produced by the landslides, were then compared. Both landslides occurred when the first tank storage layer value, corresponding to the temporal variation in groundwater level in the shallow soil layer, exceeded its previous maximum. The return period of this value at the time of the landslides was 3.0-fold higher in the more mature forests of Asakura than in the young forests of Kake. The upper limit of driftwood volume was 30-fold higher in Asakura than in Kake. Our findings indicated that shallow landslides and debris flows become increasingly rare as forests mature; however, the large volume of driftwood produced by landslides in mature forests may cause substantial damage when extreme rainfall events exceed the landslide resistance of those forests. These insights may be applied to effective landslide risk management.

Stability Prediction of Rainfall-Induced Shallow Landslides: A Case Study of Mountainous Area in China

Heavy rainfall induces shallow landslides in the mountainous areas of China. There is a need for regional slope stability prediction to reduce the damage to infrastructure, residents, and the economy. This study attempts to demarcate areas prone to rainfall-induced shallow landslides using the transient rainfall infiltration and grid-based slope stability (TRIGRS) model under different rainfall conditions. After inputting the engineering geological and geotechnical characteristic data of the area in China, the slope stability was simulated and verified by a deformation monitoring landslide. The slope stability gradually declined under the influence of precipitation from 5–8 July 2021. Slope stability gradually decreased under the predicted rainfall intensity of 60 mm/d for 6 days. The percentage of the slope area with a factor of safety (FS) less than 1.0 increased from 0.00% (1 d) to 3.18% (6 d). The study results could be used for hazards mitigation in this region.

Effects of Topography on Vegetation Recovery after Shallow Landslides in the Obara and Shobara Districts, Japan

Intense rainfall-induced shallow landslides can have severe consequences, including soil erosion and vegetation loss, making in-depth research essential for disaster risk management. However, vegetation recovery processes after shallow landslides and their influencing multivariate factors are not well known. This study aims to address this gap by investigating the vegetation recovery processes after shallow landslides and the impact of topography on this recovery. We focus on two regions in Japan: the Shobara district in Hiroshima Prefecture and the Obara district in Aichi Prefecture. The Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from long-term Landsat images, as well as aerial photographs and environmental datasets, are used to measure vegetation recovery. Then, statistical analysis and the Seasonal Autoregressive Integrated Moving Averages (SARIMA) model were employed to investigate the dynamic response of vegetation under different combinations of environmental conditions using NDVI and EVI time series. Historical aerial photographs and vegetation index trend analysis suggest that vegetation in the study areas will take more than ten years to return to a stable state. The results also demonstrate the influence of atmospheric and land cover conditions when monitoring vegetation response using NDVI and EVI. In Obara, concave and convergent terrain positively influenced NDVI, while non-steep, low-elevation, and north-facing terrain positively influenced EVI. In Shobara, gentle and northwest-facing slopes were positively correlated with NDVI, and gentle and west-facing slopes were positively correlated with EVI. SARIMA modeling found that NDVI is more suitable for modeling the middle and late stages of vegetation recovery within 10–25 years after the landslide. In comparison, EVI is better for modeling the early stage of vegetation recovery within 10 years after the landslide.

Time-resolved triggering and runout analysis of rainfall-induced shallow landslides

AbstractRainfall-induced shallow landslides often turn into flows. These phenomena occur worldwide and pose severe hazard to infrastructure and human lives on mountainous areas. Risk assessment, and the design of mitigation measures, can both be informed by back-analysis of previous events. However, shallow instabilities are frequently spread over a large area, with the generated flows occurring in sequences, or surges. Conventionally, back-analysis exercises tackle the problem by simulating runout as a single event, with all surges happening simultaneously. This simplification has repercussions that have not been explored in the literature so far, and whose impact in hazard assessment practice is unclear. Therefore, a novel time-resolving procedure is proposed in this paper, which can for the first time be applied to resolve instability sequences of arbitrary duration. The methodology discretizes the event, detecting instabilities at equally spaced time intervals as a function of rainfall. Thanks to this, the post-failure behaviour of each surge can be tracked by a runout model, with a separate simulation performed every time a new instability is detected. The methodology robustness is tested on two documented case studies. The results reveal that, under some conditions, the time-resolving procedure can lead to significantly different results in terms of runout path, flooded area, and flow heights. This leads to criticism on how back-analysis is conventionally applied, prompting for a review of historical cases.

Incorporating Rainfall Forecast Data in X-SLIP Platform to Predict the Triggering of Rainfall-Induced Shallow Landslides in Real Time

Extreme and prolonged rainfall resulting from global warming determines a growing need for reliable Landslide Early Warning Systems (LEWS) to manage the risk of rainfall-induced shallow landslides (also called soil slips). Regional LEWS are typically based on data-driven methods because of their greater computational effectiveness, which is greater than the ones of physically based models (PBMs); however, the latter reproduces the physical mechanism of the modelled phenomena, and their modelling is more accurate. The purpose of this research is to investigate the prediction quality of the simplified PBM SLIP (implemented in the X-SLIP platform) when applied on a regional scale by analysing the stability of rain forecasts. X-SLIP was updated to handle the GRIB files (format for weather forecast). Four real-time predictions were simulated on some towns of the Emilia Apennines (northern Italy) involved in widespread soil slips on 5 April 2013; specifically, maps of factors of safety related to this event were derived assuming that X-SLIP had run 72 h, 48 h, 24 h and 12 h in advance. The results indicated that the predictions with forecasts (depending on the forecast quality) are as accurate as the ones derived with rainfall recordings only (benchmark). Moreover, the proposed method provides a reduced number of false alarms when no landslide was reported to occur in the whole area. X-SLIP with rain forecasts can, therefore, represent an important tool to predict the occurrence of future soil slips at a regional scale.

Discussion of “A Simple Method for Predicting Rainfall-Induced Shallow Landslides”

Discussion of “A Simple Method for Predicting Rainfall-Induced Shallow Landslides”

Closure to “A Simple Method for Predicting Rainfall-Induced Shallow Landslides”

Closure to “A Simple Method for Predicting Rainfall-Induced Shallow Landslides”

Rainfall infiltration and slope stability of alpine colluvial terraces subject to storms (NE Italy)

In the alpine environment, rainfall-induced shallow landslides can involve thin covers of colluvial soil (50–300 cm) on terraced belts that were formed as a result of fill-and-cut sedimentary processes that followed the deglaciation of the alpine valleys. Notably, research on shallow slope failures involving alpine terraces consisting of a near-flat upper ground surface (“tread”) and a moderately steep scarp (“riser”) is lacking in the literature. This paper describes the engineering geological characteristics and failure mechanisms of a large number of shallow landslides (soil slips or slide-debris flows) that were activated on alpine stratified colluvial terraces due to a rainstorm that hit the mountain area of the Friuli Venezia Giulia Region (NE Italy) on 21–22 June 1996. The paper reports data on the geomorphological and engineering geological characteristics of the soil slips acquired through extensive fieldwork and shows the outcomes of some two-dimensional seepage and slope stability analyses that were carried out in order to investigate the critical hydrological conditions and mechanisms that were responsible for the soil slip activation during and after rainfall. The soil slip activation can occur at two different stages during the infiltration process, based on the interacting water flows through the terrace tread and riser. The first critical stability condition is reached during the phases of greater precipitation intensity or at the end of the rainstorm because of the saturation of the top soil layer on the terrace riser and the subsequent formation of an ephemeral water table accompanied by a seepage sub-parallel to the slope face. The second critical condition is achieved some hours after the end of rainfall as a result of a tread-to-riser water outflow that is supplied by the water amount stored within the near-flat terrace tread during the peak rainfall stages (reservoir-like effect). This study also shows that a critical value of rainfall intensity of about 40–45 mm/h can cause the activation of soil slips in mountain basins characterised by a humid continental climate and by the occurrence of colluvial deposits with a high content of fine fraction. This critical value of rainfall intensity should be considered as a rainfall threshold for a basin-scale under geomorphological and geological conditions similar to those investigated in this paper.