Infinite Slope Stability Model Research Articles

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.

Updating Active Deformation Inventory Maps in Mining Areas by Integrating InSAR and LiDAR Datasets

Slope failures, subsidence, earthworks, consolidation of waste dumps, and erosion are typical active deformation processes that pose a significant hazard in current and abandoned mining areas, given their considerable potential to produce damage and affect the population at large. This work proves the potential of exploiting space-borne InSAR and airborne LiDAR techniques, combined with data inferred through a simple slope stability geotechnical model, to obtain and update inventory maps of active deformations in mining areas. The proposed approach is illustrated by analyzing the region of Sierra de Cartagena-La Union (Murcia), a mountainous mining area in southeast Spain. Firstly, we processed Sentinel-1 InSAR imagery acquired both in ascending and descending orbits covering the period from October 2016 to November 2021. The obtained ascending and descending deformation velocities were then separately post-processed to semi-automatically generate two active deformation areas (ADA) maps by using ADATool. Subsequently, the PS-InSAR LOS displacements of the ascending and descending tracks were decomposed into vertical and east-west components. Complementarily, open-access, and non-customized LiDAR point clouds were used to analyze surface changes and movements. Furthermore, a slope stability safety factor (SF) map was obtained over the study area adopting a simple infinite slope stability model. Finally, the InSAR-derived maps, the LiDAR-derived map, and the SF map were integrated to update a previously published landslides’ inventory map and to perform a preliminary classification of the different active deformation areas with the support of optical images and a geological map. Complementarily, a level of activity index is defined to state the reliability of the detected ADA. A total of 28, 19, 5, and 12 ADAs were identified through ascending, descending, horizontal, and vertical InSAR datasets, respectively, and 58 ADAs from the LiDAR change detection map. The subsequent preliminary classification of the ADA enabled the identification of eight areas of consolidation of waste dumps, 11 zones in which earthworks were performed, three areas affected by erosion processes, 17 landslides, two mining subsidence zone, seven areas affected by compound processes, and 23 possible false positive ADAs. The results highlight the effectiveness of these two remote sensing techniques (i.e., InSAR and LiDAR) in conjunction with simple geotechnical models and with the support of orthophotos and geological information to update inventory maps of active deformation areas in mining zones.

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.

Analyzing Rainfall Threshold for Shallow Landslides Using Physically Based Modeling in Rasuwa District, Nepal

On 25 April 2015, an M7.8 large earthquake happened in Nepal, and 4312 landslides were triggered during or after the earthquake. The 2015 earthquake happened years ago, but the risk of rainfall-induced landslides is still high. Rainfall-induced shallow landslides threaten both human lives and economy development, especially in the Rasuwa area. Due to financial conditions and data availability, a regional-scale rainfall threshold can be an effective method to reduce the risk of shallow landslides. A physically based model was used with limited data. The dynamic hydrological model provides the soil moisture and groundwater change, and the infinite slope stability model produces the factor of safety. Remote sensing data, field investigation, soil sample tests, and literature review were used in the model parameterization. The landslide stability condition of 2016 was simulated. In addition, intensity-antecedent rainfall thresholds were defined based on the physically based modelling output. Sixty groups of data were used for validation, and the 15-day intensity-antecedent rainfall threshold has the best performance with an accuracy of 88.33%.

Influence of changes in extreme daily rainfall distribution on the stability of residual soil slopes

ABSTRACT Many landslides triggered by intense rainfall have occurred in mountainous areas in Thailand, causing major economic losses and infrastructure damage. Extreme daily rainfall is a significant trigger for hillslope instability. Increases in extreme daily rainfall intensity due to climate change may be one of the key factors responsible for the increased landslides. Thus, in this context, changes in the intensity of extreme daily rainfall in Chiang Mai Province in North Thailand and their effects on hillslope stability are analyzed. Extreme rainfall is modeled using a generalized extreme value distribution and estimated for various return periods. A numerical analysis of seepage and an infinite slope stability model are combined to understand the hillslope response under extreme rainfall conditions. The analysis period is divided into two periods of 34 years: 1952 to 1985 and 1986 to 2019. According to the analysis results, the distribution of extreme daily rainfall changes in terms of location. The average annual daily maximum rainfall increased by approximately 11.13%. The maximum decrease in the safety factor is approximately 4.5%; therefore, these changes in extreme daily rainfall should be considered in future landslide prevention policies.

Four-Year Monitoring Study of Shallow Landslide Hazards Based on Hydrological Measurements in a Weathered Granite Soil Slope in South Korea

To build a comprehensive understanding of long-term hydro-mechanical processes that lead to shallow landslide hazards, this study explicitly monitored the volumetric water content (VWC) and rainfall amount for a weathered granite soil slope over a four year period. From the 12 operational landslide monitoring stations installed across South Korea, the Songnisan station was selected as the study site. VWC sensors were placed in the subsurface with a grid-like arrangement at depths of 0.5 and 1.0 m. Shallow landslide hazards were evaluated by applying an infinite slope stability model that adopted a previously proposed unified effective stress concept. By analyzing the variations in the monitored VWC values, the derived matric suctions and suction stresses, and the calculated factor of safety values, we were able to obtain numerous valuable insights. In particular, the seasonal effects of drainage and evapotranspiration on the slope moisture conditions and slope stability were addressed. Preliminary test results indicated that continuous rainfall successfully represented the derived matric suction conditions at a depth of 1.0 m in the lower slope, although this was not the case for the upper and middle slopes. The significance of a future study on cumulative field monitoring data from various sites in different geological conditions is highlighted.

Shallow Landslides Physically Based Susceptibility Assessment Improvement Using InSAR. Case Study: Carpathian and Subcarpathian Prahova Valley, Romania

A multi-temporal satellite radar interferometry technique is used for deriving the actual surface displacement patterns in a slope environment in Romania, in order to validate and improve a landslide susceptibility map. The probability the occurrence of future events is established using a deterministic approach based on a classical one-dimension infinite slope stability model. The most important geotechnical parameters for slope failure in the proposed study area are cohesion, unit weight and friction angle, and the triggering factor is a rapid rise in groundwater table under wetting conditions. Employing a susceptibility analysis using the physically based model under completely saturated conditions proved to be the most suitable scenario for identifying unstable areas. The kinematic characteristics are assessed by the Small BAseline Subsets (SBAS) interferometry technique applied to C-band synthetic aperture radar (SAR) Sentinel-1 imagery. The analysis was carried out mainly for inhabited areas which present a better backscatter return. The validation revealed that more than 22% of the active landslides identified by InSAR were predicted as unstable areas by the infinite slope model. We propose a refinement of the susceptibility map using the InSAR results for unravelling the danger of the worst-case scenario.

Hydrological control of soil thickness spatial variability on the initiation of rainfall-induced shallow landslides using a three-dimensional model

Thickness and stratigraphic settings of soils covering slopes potentially control susceptibility to initiation of rainfall-induced shallow landslides due to their local effect on slope hydrological response. Notwithstanding the relevance of the assessment of hazard to shallow landsliding at a distributed scale by approaches based on a coupled modelling of slope hydrological response and slope stability, the spatial variability of soil thickness and stratigraphic settings are factors poorly considered in the literature. Under these premises, this paper advances the well-known case study of rainfall-induced shallow landslides involving ash-fall pyroclastic soils covering the peri-Vesuvian mountains (Campania, southern Italy). In such a unique geomorphological setting, the soil covering is formed by alternating loose ash-fall pyroclastic deposits and paleosols, with high contrasts in hydraulic conductivity and total thickness decreasing as the slope angle increases, thus leading to the establishment of lateral flow and an increase of pore water pressure in localised sectors of the slope where soil horizon thickness is less. In particular, we investigate the effects, on hillslope hydrological regime and slope stability, of irregular bedrock topography, spatial variability of soil thickness and vertical hydraulic heterogeneity of soil horizons, by using a coupled three-dimensional hydrological and a probabilistic infinite slope stability model. The modelling is applied on a sample mountain catchment, located on Sarno Mountains (Campania, southern Italy), and calibrated using physics-based rainfall thresholds derived from the literature. The results obtained under five simulated constant rainfall intensities (2.5, 5, 10, 20 and 40 mm h−1) show an increase of soil pressure head and major failure probability corresponding to stratigraphic and morphological discontinuities, where a soil thickness reduction occurs. The outcomes obtained from modelling match the hypothesis of the formation of lateral throughflow due to the effect of intense rainfall, which leads to the increase of soil water pressure head and water content, up to values of near-saturation, in narrow zones of the slope, such as those of downslope reduction of total soil thickness and pinching out of soil horizons. The approach proposed can be conceived as a further advance in the comprehension of slope hydrological processes at a detailed scale and their effects on slope stability under given rainfall and antecedent soil hydrological conditions, therefore in predicting the most susceptible areas to initiation of rainfall-induced shallow landslides and the related I-D rainfall thresholds. Results obtained demonstrate the occurrence of a slope hydrological response depending on the spatial variability of soil thickness and leading to focus slope instability in specific slope sectors. The approach proposed is conceived to be potentially exportable to other slope environments for which a spatial modelling of soil thickness would be possible.

Mapping method of rainfall-induced landslide hazards by infiltration and slope stability analysis

By utilizing the Green-Ampt infiltration equation and the infinite slope stability model, a method for analyzing shallow slope failures caused by rainfall is developed. With rainfall intensity, soil characteristics, and topography, the modified Green-Ampt infiltration equation is used to estimate the rainfall infiltration capacity and depth of infiltration in a given slope. Assigning the calculated depth of infiltration as the depth of slip surface, the factor of safety of the slope is obtained through the infinite slope stability model. A time-series visualization map of the space-time varying factor of safety is generated when the method is implemented with the aid of Geographic Information System (GIS) software. The model is applied and validated with the landslides that occurred during the October 2019 Typhoon Hagibis in Marumori, Japan. The model results show good agreement with the reported time and depths of failure, and the analysis of the spatial distribution of predicted failures yielded receiver operating characteristic-area under the curve (ROC-AUC) value of 0.90. The applicability of the model can be extended for post-analysis, real-time, or projected assessment of slope stability, depending on the nature of input rainfall data (e.g., historical, real-time, forecast, hypothetical).

Infinite slope stability model and steady-state hydrology-based shallow landslide susceptibility evaluations: The Guneysu catchment area (Rize, Turkey)

The main purpose of this study is to investigate shallow landslide susceptibility by considering the infinite slope stability model and steady-state hydrological conditions. The prediction performance of the Stability Index Mapping (SINMAP) carried out by considering the mechanical and hydrological parameters and soil thickness values for different residual soils derived from different geological formations was evaluated. For this purpose, comprehensive geotechnical site investigations were conducted in the Guneysu catchment area located at the east of Rize in the Eastern Black Sea region of Turkey, where shallow landslides are frequently observed within the residual levels developed as a result of decomposition of magmatic rocks. The research was performed in four stages: (i) The general characteristics of the region were examined; (ii) detailed investigations were carried out for the preparation of shallow landslide inventory of the Guneysu catchment area; (iii) to reveal the mechanical and hydrological characteristics of the residual soils, disturb and undisturbed samplings were carried out, and geophysical investigations were performed; (iv) as the last stage, shallow landslide susceptibility was assessed by implementing the SINMAP mathematical model. As a result, the average accuracy value of the models produced to predict shallow landslide initiation in the region was obtained to be 96.7%. Considering the statistics achieved in this research, it is realized that the differentiation of soil material increases the model prediction capacity. Additionally, pre-evaluations of the mechanical and hydrological characteristics of the residual soils also increase the estimation performance.

Modeling hydrologic processes associated with soil saturation and debris flow initiation during the September 2013 storm, Colorado Front Range

Seven days of extreme rainfall during September 2013 produced more than 1100 debris flows in the Colorado Front Range, about 78% of which occurred on south-facing slopes (SFS). Previously published soil moisture (volumetric water content) observations suggest that SFS were wetter than north-facing slopes (NFS) during the event, which contrasts with soil moisture patterns observed during normal conditions. Various causes have been hypothesized for the preferential saturation of SFS, but those hypotheses remain largely untested. Here, we analyze the soil moisture patterns using additional soil moisture observations, determine the hydrologic processes controlling the preferential saturation of SFS, and evaluate the importance of soil moisture in predicting the debris flow initiation sites. Soil moisture patterns are simulated using the Equilibrium Moisture from Topography, Vegetation, and Soil (EMT + VS) model. Five hypotheses are tested that may have influenced the soil moisture reversal including higher rainfall rates, lower interception rates, lower saturated water content, thinner soils, and reduced deep drainage on SFS. The EMT + VS model is coupled with an infinite slope stability model to produce factor of safety maps. The hypotheses are tested by comparing the modeled soil moisture to soil moisture observations and the debris flow initiation sites. The results suggest that differences in interception and deep drainage between SFS and NFS were primarily responsible for producing wetter SFS, but the soil moisture pattern likely played a smaller role than vegetation and slope in determining where debris flows initiated. The final model predicts instability at approximately 72% of the observed debris flow initiation sites.

Multiseasonal probabilistic slope stability analysis of a large area of unsaturated pyroclastic soils

The analysis of slope stability over large areas is a demanding task for several reasons, such as the need for extensive datasets, the uncertainty of collected data, the difficulty of accounting for site-specific factors, and the considerable computation time required due to the size of investigated areas, which can pose major barriers, particularly in civil protection contexts where rapid analysis and forecasts are essential. However, as the identification of zones of higher failure probability is very useful for stakeholders and decision-makers, the scientific community has attempted to improve capabilities to provide physically based assessments. This study combined a transient seepage analysis of an unsaturated-saturated condition with an infinite slope stability model and probabilistic analysis through the use of a high-computing capacity parallelized platform. Both short- and long-term analyses were performed for a study area, and roles of evapotranspiration, vegetation interception, and the root increment of soil strength were considered. A model was first calibrated based on hourly rainfall data recorded over a 4-day event (December 14–17, 1999) causing destructive landslides to compare the results of model simulations to actual landslide events. Then, the calibrated model was applied for a long-term simulation where daily rainfall data recorded over a 4-year period (January 1, 2005–December 31, 2008) were considered to study the behavior of the area in response to a long period of rainfall. The calibration shows that the model can correctly identify higher failure probability within the time range of the observed landslides as well as the extents and locations of zones computed as the most prone ones. The long-term analysis allowed for the identification of a number of days (9) when the slope factor of safety was lower than 1.2 over a significant number of cells. In all of these cases, zones approaching slope instability were concentrated in specific sectors and catchments of the study area. In addition, some subbasins were found to be the most recurrently prone to possible slope instability. Interestingly, the application of the adopted methodology provided clear indications of both weekly and seasonal fluctuations of overall slope stability conditions. Limitations of the present study and future developments are finally discussed.

Modeling the landslide-generated debris flow from formation to propagation and run-out by considering the effect of vegetation

This study aimed to investigate the formation and propagation processes of a landslide-generated debris flow within a small catchment while considering the effects of vegetation. This process is divided into three stages: rainfall infiltration, slope failure, and debris flow routing, according to their different mechanisms. Existing models that involve the effect of vegetation for each stage, including Richards’s model, infinite slope stability model, and the enhanced two-phase debris flow model (Pudasaini 2012), were coupled. The tridiagonal matrix algorithm and finite volume method were applied to solve these equations, respectively. Finally, the approach was tested by application to the 2018 debris flow event in the Yindongzi catchment, China. The results showed that the proposed comprehensive model could effectively describe the behaviors of each stage during the formation and propagation processes of landslide-generated debris flows in vegetated area. The roles of vegetation on each stage, such as root water uptake and root soil reinforcement, were also analyzed by performing several scenarios.

Study on the role of lateral unsaturated flow in triggering slope failure under varying boundary water level conditions

Lateral unsaturated flow was found to contribute little to rainfall-induced shallow landslides, but it can be important when the landslides are triggered under conditions of varying boundary water level. By considering a hillslope with an impermeable bedrock and rising water level at the uphill/downhill boundary, this study explored how lateral unsaturated flow would affect slope stability. Three different Hillslope-Storage Boussinesq models that differ in their treatment of the unsaturated flow were coupled with the same infinite slope stability model to predict and compare the safety factor and instability time. Specific to the situations considered, this study discovered that, despite the inclusion of lateral unsaturated flow effect, the hillslope remains stable when water level at the downhill boundary rises. Under the condition of increasing uphill boundary water level, the consideration of lateral unsaturated flow leads to earlier slope failure for loamy hillslopes with a moderate slope. Also, the lateral unsaturated flow may not induce slope failure for mildly sloping loamy hillslopes and plays an ignorable role when landslides occur fast in very steep hillslopes. By contrast, the lateral unsaturated flow does not affect much the failure of sandy hillslopes. Moreover, when water level at the uphill boundary increases faster, the lateral unsaturated flow exerts a greater influence on initiating slope failure. Further examination shows that intensive rainfall may weaken the effect of lateral unsaturated flow on shallow landslides triggering under the condition of rising uphill boundary water level.

Probabilistic landslide susceptibility analysis in tropical mountainous terrain using the physically based r.slope.stability model

Abstract. Landslides triggered by rainfall are very common phenomena in complex tropical environments such as the Colombian Andes, one of the regions of South America most affected by landslides every year. Currently in Colombia, physically based methods for landslide hazard mapping are mandatory for land use planning in urban areas. In this work, we perform probabilistic analyses with r.slope.stability, a spatially distributed, physically based model for landslide susceptibility analysis, available as an open-source tool coupled to GRASS GIS. This model considers alternatively the infinite slope stability model or the 2.5-D geometry of shallow planar and deep-seated landslides with ellipsoidal or truncated failure surfaces. We test the model in the La Arenosa catchment, northern Colombian Andes. The results are compared to those yielded with the corresponding deterministic analyses and with other physically based models applied in the same catchment. Finally, the model results are evaluated against a landslide inventory using a confusion matrix and receiver operating characteristic (ROC) analysis. The model performs reasonably well, the infinite slope stability model showing a better performance. The outcomes are, however, rather conservative, pointing to possible challenges with regard to the geotechnical and geo-hydraulic parameterization. The results also highlight the importance to perform probabilistic instead of – or in addition to – deterministic slope stability analyses.

A new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USA

Abstract. We developed a new approach for mapping landslide hazards by combining probabilities of landslide impacts derived from a data-driven statistical approach and a physically based model of shallow landsliding. Our statistical approach integrates the influence of seven site attributes (SAs) on observed landslides using a frequency ratio (FR) method. Influential attributes and resulting susceptibility maps depend on the observations of landslides considered: all types of landslides, debris avalanches only, or source areas of debris avalanches. These observational datasets reflect the detection of different landslide processes or components, which relate to different landslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical and physically based probabilities as indices and calculates a joint probability of landsliding at the intersections of probability bins. A ratio of the joint probability and the physically based model bin probability is used as a weight to adjust the original physically based probability at each grid cell given empirical evidence. The resulting integrated probability of landslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentially unstable areas with the proposed integrated model are statistically quantified. We provide multiple landslide hazard maps that land managers can use for planning and decision-making, as well as for educating the public about hazards from landslides in this remote high-relief terrain.

Sensitivities of input parameters for predicting stability of soil slope

The infinite slope stability model is the basis for predicting the slope stability; however, the fundamental theory requires various input parameters. The objective of this study is to suggest a reasonable method for assuming input parameters in difficult measurement areas. The referred values are used to perform the sensitivity analysis, which found the influence degree of each parameter on the output result. Both slope angle and soil depth are shown to be highly affected parameters in the infinite slope stability model. To gather the real values of the slope angle, soil depth, and water table height, field tests are carried out and the remaining values are estimated from laboratory test results. The geostatistical method is applied to predict the distribution of input parameters over the entire study area based on the measured data, and the safety factor in the objective area is calculated. To observe fluctuations in the safety factor, the input parameter values are changed to single values representing the average, maximum, and minimum measured values. Then the contour map, histogram, and error ratios are established using the deduced safety factors. This study suggests considerations needed to determine the input parameters and a reasonable method when assuming factors.

Quantifying the three-dimensional effects of anisotropic soil horizons on hillslope hydrology and stability

Rainfall-induced shallow landslides cause significant damage involving loss of life and property. Many hydrological processes such as rainfall infiltration, soil water dynamics, and slope stability are controlled by unsaturated soil properties, such as unsaturated hydraulic conductivity. Natural soils often exhibit a certain degree of anisotropy in hydraulic conductivity due to stratification and compaction mechanisms in soil formation processes.In this paper we investigate the effect of soil hydraulic conductivity anisotropy (SHCA) on hillslope hydrology and stability using a three-dimensional hydrological model coupled with a probabilistic infinite slope stability model. The model is applied in two independent case studies. The first aims to quantify the combined effect of different anisotropy ratios (lateral/normal saturated hydraulic conductivity) and hillslope morphologies (convex, concave, and planar) on slope stability. Anisotropy ratios are assumed in this case higher than one (1, 2, 10). Results show that increasing the anisotropy ratio (from 1 to 10) anticipates the failure time (from 12 to 9 h after the start of rainfall) and that in concave morphologies the unstable area tends to be wider than planar and convex. The second application aims to simulate the soil moisture dynamic and the probability of failure at different depths (100, 500, and 900 mm) of a stratified volcanic soil, making leverage on the model flexibility to accommodate SHCA. No assumptions are made on the anisotropy ratio in this case study. Our results, based on model parameter calibration and verification against in-situ soil moisture measurements during the year 2009, showed good model performance in simulating the soil moisture dynamic (Kling-Gupta Efficiency higher than 0.78) and confirmed no failure for the simulated year. The promising results support the aspiration that the physically based hydrological model can complement and improve the current predictions of landslide early warning systems.

Modeling regional landslide susceptibility using dynamic soil moisture profiles

A landslide susceptibility mapping study was performed using dynamic hillslope hydrology. The modified infinite slope stability model that directly includes vadose zone soil moisture (SM) was applied at Cleveland Corral, California, US and Krishnabhir, Dhading, Nepal. The variable infiltration capacity (VIC-3L) model simulated vadose zone soil moisture and the wetness index hydrologic model simulated groundwater (GW). The GW model predictions had a 75% NASH-Sutcliffe efficiency when compared to California’s in-situ GW measurements. The model performed best during the wet season. Using predicted GW and VIC-3L vadose zone SM, the developed landslide susceptibility maps showed very good agreement with mapped landslides at each study region. Previous quasi-dynamic model predictions of Nepal’s hazardous areas during extreme rainfall events were enhanced to improve the spatial characterization and provide the timing of hazardous conditions.

A modelling study of rainfall-induced shallow landslide mechanisms under different rainfall characteristics

Rainfall-induced shallow landslide is a common geological hazard around the world that can pose serious threat to both lives and property. Previous studies suggested that rainfall induced shallow landslides always occurred either above the bottom of a downward wetting front in infiltration, or below a rising water table. This paper proposed a different mechanism of shallow landslides in a modelling approach. The comprehensive physics-based Integrated Hydrology Model (InHM) and the infinite slope stability model were employed on a virtual slope to simulate the hydrologic response and estimate the slope stability. Different failure mechanisms with various characteristics were investigated under diverse rainfall scenarios (i.e., various combinations of rainfall depths, durations and temporal patterns). The results showed a novel mechanism of shallow landslides: a significant vertical change in saturated hydrologic conductivity causes the accumulation of infiltrated water, and subsequently leading to an increase pore pressures and landslides in unsaturated soil layer. More importantly, this kind of landslide would bring larger landslide volume even with smaller total rainfall depths. This study expanded our understanding about landslides and had important application in alleviating the loss of lives and property.