Infinite Slope Stability Analysis Research Articles

Improving pixel-based regional landslide susceptibility mapping

Regional landslide susceptibility mapping (LSM) is essential for risk mitigation. While deep learning algorithms are increasingly used in LSM, their extensive parameters and scarce labels (limited landslide records) pose training challenges. In contrast, classical statistical algorithms, with typically fewer parameters, are less likely to overfit, easier to train, and offer greater interpretability. Additionally, integrating physics-based and data-driven approaches can potentially improve LSM. This paper makes several contributions to enhance the practicality, interpretability, and cross-regional generalization ability of regional LSM models: (1) Two new hybrid models, composed of data-driven and physics-based modules, are proposed and compared. Hybrid Model I combines the infinite slope stability analysis (ISSA) with logistic regression, a classical statistical algorithm. Hybrid Model II integrates ISSA with a convolutional neural network, a representative of deep learning techniques. The physics-based module constructs a new explanatory factor with higher nonlinearity and reduces prediction uncertainty caused by incomplete landslide inventory by pre-selecting non-landslide samples. The data-driven module captures the relation between explanatory factors and landslide inventory. (2) A step-wise deletion process is proposed to assess the importance of explanatory factors and identify the minimum necessary factors required to maintain satisfactory model performance. (3) Single-pixel and local-area samples are compared to understand the effect of pixel spatial neighborhood. (4) The impact of nonlinearity in data-driven algorithms on hybrid model performance is explored. Typical landslide-prone regions in the Three Gorges Reservoir, China, are used as the study area. The results show that, in the testing region, by using local-area samples to account for pixel spatial neighborhoods, Hybrid Model I achieves roughly a 4.2% increase in the AUC. Furthermore, models with 30 m resolution land-cover data surpass those using 1000 m resolution data, showing a 5.5% improvement in AUC. The optimal set of explanatory factors includes elevation, land-cover type, and safety factor. These findings reveal the key elements to enhance regional LSM, offering valuable insights for LSM practices.

Stability analysis of heterogeneous infinite slopes under rainfall-infiltration by means of an improved Green-Ampt model

Rainfall infiltration analysis has a great significance to the mitigation and risk assessment of rainfall-induced landslides. The original Green-Ampt (GA) model ignored the fact that a transitional layer exists in infiltration regions of soils under the rainfall permeation, therefore it cannot effectively analyze the rainfall-infiltrated heterogeneous slope considering the spatial variability of saturated hydraulic conductivity (ks). In this paper, an improved GA model is proposed for the rainfall-infiltration analysis of heterogeneous slopes. Four common slope cases are investigated to validate the effectiveness of the proposed model. An infinite slope model is taken as an illustrative example to investigate the distributions of volumetric water content and slope stability under the rainfall infiltration. The results show that the distributions of volumetric water content and factors of safety (Fs) obtained from the proposed model are in very good agreement with the numerical results of Richards equation. In contrast, the modified GA model obtains biased distributions of volumetric water content and smaller Fs for the same cases. The results show that the proposed GA model can accurately identify the location of critical slip surface of the slope, and as such it provides an efficient method for risk control analysis of slopes susceptible to landslide.

Influence of Rainfall Pattern on Wetness Index for Infinite Slope Stability Analysis

Landslides are one of the riskiest disasters combining excessive rainfall and unstable slope that a wetness index can quantify. The wetness index generated by water infiltration considering the rainfall pattern such as cumulated rainfall, rainfall duration and rainfall intensity should be estimated for the slope stability analysis. Even though the infiltration capacity of soils has been largely focused to evaluate the slope stability, the temporal patterns of rainfall have commonly been ignored or assumed as a steady state for the prediction of the slope failure in the previous studies. Thus, this study focuses more on evaluating the influence of various rainfall patterns on the slope stability, and compares it with an actual landslide incident that occurred in 2011, in Korea. The factor of safety (FS) considering the time-dependent wetness index variation is used to determine the slope stability. For the various rainfall designs, the uniform rainfall distribution, Yen and Chow, Mononobe, alternating block and second quartile Huff models are adopted. Thereafter, the FS variations from five models are compared with an actual landslide incident in Seoul, Korea. Among the rainfall designs, the models that consider the abrupt rainfall intensity capture the landslide time with an FS < 1. Therefore, the appropriate adoption of a rainfall distribution model should be highlighted for landslide prediction.

Combining portable cone penetration test and electrical resistivity tomography to assess residual risks after shallow landslides: a case at the Hokkaido Eastern Iburi earthquake in 2018 in Japan

Landscapes disturbed by shallow landslides present several residual risks. For example, residual soils on sliding surfaces may lead to the re-occurrence of shallow landslides, and landslide deposits on valley floors may introduce multiple hazards associated with river blocking or landslide damming. Despite such risks, few studies have investigated the residual risks following shallow landslides, and thus, no methodology has been established for assessing such risks. In this study, we combined portable cone penetration test (PCPT) and electrical resistivity tomography (ERT) to investigate the post-event risks associated with a landslide scar resulting from the 2018 Hokkaido Eastern Iburi earthquake (HEIE) in Japan. The multi-point PCPT identified the interface between a weak volcanic soil layer and underlying weathered sedimentary rocks. This interface exhibited an abrupt spatial change in resistivity, ranging from 20 to 100 Ωm. The thickness of the residual soil layer was 0.3–3.2 m and that of the landslide deposit exceeded 2.0 m. An infinite-slope stability analysis was performed to predict the re-occurrence of shallow landslides due to a lower intensity earthquake than that of HEIE in this region. Considering the area affected by the HEIE and the physical properties of soil layers, our findings imply a widespread risk of re-occurrence of shallow landslides over an area of 20 km × 20 km. Although the areal coverage of the combined ERT/PCPT method needs to be extended, it is effective for assessing the residual risks associated with shallow landslides.

On the seismic response and earthquake-triggered failures of subaqueous slopes in Swiss lakes

SUMMARY Seismically triggered subaqueous mass movements in lakes may generate tsunamis that can cause significant damage on the shore. In this study, we assess the seismic response and stability of subaqueous slopes in Swiss lakes based on recorded seismological data, historical and geological information and geotechnical surveys. We performed seismic investigations at multiple locations in Lake Lucerne using Ocean Bottom Seismometers (OBS). For these locations, we derived ground-motion amplification functions from local and regional earthquakes and horizontal-to-vertical spectral ratios (H/V) from the earthquake and ambient vibration recordings. The results show (1) very high amplification levels, often exceeding values of 50–100 in the frequency range between 1 and 10 Hz, (2) the fundamental frequency of resonance in the range of 0.5–3.5 Hz and (3) laterally variable site response even for closely located stations. We sought also the signatures of non-linear site response in the H/V curves or ground-motion amplification functions but found only weak indicative effects and no clear evidence. This is most likely due to the low levels of ground motion recorded during the OBS campaigns. We conducted back analyses of historical earthquakes in Switzerland with available documental and/or geological evidence of induced (tsunamigenic) subaqueous slope failures in Swiss lakes. The data set of historical events was complemented with a selection of instrumentally recorded earthquakes in Switzerland. For the analyses, we selected multiple sites in Swiss lakes which failed in the past or are prone to failure in the future. We modelled the ground motion at these locations assuming Swiss standard reference rock conditions (vs30 = 1105 m s−1). The modelled ground motion intensity measures (IM) included peak ground acceleration (PGA), peak ground velocity (PGV) and pseudospectral acceleration (PSA) at 0.3, 1 and 2 s. We estimated the minimum ground motion and macroseismic intensity at reference rock conditions required to trigger the failures of subaqueous slopes. In addition, we defined a threshold for the seismic triggering of such failures in terms of moment magnitude (Mw) and epicentral distance (Re) as: $$\begin{eqnarray} M_{\rm w}=2.891+1.904\log_{10}(R_e+5.166)\: {\rm for}\: R_e\ge 3.7\: {\rm km}. \end{eqnarray}$$ Our results are consistent with previous studies based on worldwide observations. Furthermore, we related the modelled ground motions to the Swiss seismic hazard products and estimated the return period of critical ground shaking responsible for triggering subaqueous slope failures (with potential for tsunami generation) to be in the range of 36–224 yr. Finally, based on previously collected geotechnical data (in situ Cone Penetration Testing and laboratory sediment analysis), we determined the most likely values of the seismic coefficient k to be used with the ground motion IMs modelled at reference rock conditions in infinite slope stability analyses to estimate the factor of safety (FS). For PGA, we found a k = 1; for PGV, k = 2; for PSA0.3s, k = 0.6; for PSA1s, k = 2 and for PSA2s, k = 5.5. These estimates are conservative and affected by the trade-off between the thickness of unconsolidated sediments and the slope angle. Thus, we recommend applying them to slopes with a low-to-moderate gradient (<15°) and sediment thickness of more than 2 m.

A Preliminary Study of the Seepage Hammer Effect and Its Impacts on the Stability of Layered Infinite Slope

A rapid change in the pore water pressure of unsaturated soil due to a wetting front is a crucial factor and may result in instabilities in layered slopes. This study presents preliminary research on such a change, which we define as the seepage hammer effect. Vertical infiltration with multiple soil layers by column test was implemented to investigate the mechanism of the seepage hammer effect and distinguish it from the well-known Lisse effect and reverse Wieringermeer effect. A two-phase flow model was utilized to understand the evolutions of pore water/air pressure and volumetric water content, and its result evolved into a layered infinite slope stability analysis. Thus, the impacts of the seepage hammer effect on slope stability can be analyzed. This study found that the seepage hammer effect was triggered when the wetting front reached the interface of multiple layers and impermeable layers, and the rising speed of pore water pressure was proportional to the air venting capacity of soil. Slope stability analysis showed that the safety factor may decline suddenly because of the seepage hammer effect. Its relationship with the factor of safety and the sliding velocity is proportional. The detection of the seepage hammer effect could be a potential application of the study of fast-moving landslides.

An Analysis of Landslide Risk Using the Change in the Volumetric Water Content Gradient in the Soil Layer Per Unit Time of Effective Cumulative Rainfall

The topographical characteristics of South Korea are coupled with heavy rain and typhoons concentrated from July to September, which take up two-thirds of the country’s annual precipitation, causing substantial damage from slope failures, landslides, debris flows, and other mountain disasters. This study uses the Land-Atmosphere Modeling Package (LAMP) data to study the area, which has been affected by numerous landslides in the past. Specifically, to analyze the likelihood of slope failure, this study simulates the rainfall events in the area at the time of the landslides as well as changes in the volumetric water content in the soil layer and uses the changes in the volumetric water content per unit time, which are affected by the effective cumulative rainfall within the soil layer. To that end, this study assesses the risk of landslides based on how rainwater infiltration in the saturation depth changes the saturation depth ratio and compares the results with the landslide spots in the past. Moreover, this study analyzes the landslide risk by applying the saturation depth ratio (Ht) to an infinite slope stability analysis model. The landslide threshold proposed in this study was obtained by analyzing the rainfall events that caused the landslides in the study area using the LAMP model. It can then be concluded that, when compared with the spatial information on the previous landslides, if the change in the volumetric water content per unit time during the first and second rainfall events is 0.7, a landslide may occur. These results indicated that the landslide risk increases the volumetric water content in the soil layer, along with the congruence between past landslide risk points and spatial landslide risks.

Post‐Wildfire Stability of Unsaturated Hillslopes Against Rainfall‐Triggered Landslides

AbstractWildfire records demonstrate worsening patterns coupled with the spread to higher altitudes in several regions, raising the risk of post‐wildfire ground failures. This study investigates the post‐wildfire stability of unsaturated hillslopes against rainfall‐triggered shallow landslides. We developed a new physics‐based analytical framework incorporating wildfire‐induced changes in soil properties and near‐surface processes affecting the hillslope stability. A coupled hydromechanical infiltration model is integrated into an infinite slope stability analysis to simulate temporal changes in the depth profiles of soil water content, pressure head, and the resulting factor of safety (F.S.) of a vegetated slope. We consider the antecedent conditions of soil and vegetation cover, including the recovery phase after the fire, wildfire‐induced alterations in transpiration, and time‐varying infiltration rates. The model is verified against numerical simulations and employed in parametric studies evaluating the effects of wildfire severity and rainfall intensity‐duration. For the cases examined, it was shown that wildfire could reduce the F.S. of slopes by 25%. As a case study, the model successfully captured shallow rainfall‐triggered landslides that occurred in the Las Lomas watershed in California, USA, in 2019, 3 years after the Fish Fire burned the area. The proposed model uses measurable hillslope and wildfire characteristics and can be employed to evaluate the risk of shallow landslides in wildfire‐prone areas.

경기도 광주지역의 극한강우 사상을 고려한 산사태위험도 분석

South Korea is featured by the rugged topography that is composed of mountains about 68% of the country and the weather that rainfall is mostly concentrated during the summer. These topographic and meteorological features have caused disasters such as landslide and avalanche from mountains every year. Especially, urban expansion caused urban boundaries to get closer to steep slopes of mountains and residents are seriously exposed to disasters such as landslides so appropriate measures should be required. We, however, are facing the limitations in prevention and mitigation of landslide disasters due to the complexity of the causes of landslides like human factors as well as natural ones. To reduce the limitations, we generated of a hazard map by landslide for Gwangju City, Gyeonggi-do with an assumption of an extreme rainfall situation based on the infinite slope stability analysis model. To derive the landslide hazard map, we collected soil samples from the places where landslides actually occurred and constructed physical data by experiments and derived a landslide hazard map based on 5 rainfall scenarios. The accuracy of the result was evaluated by comparing the reference of the landslide hazard maps published by Korean Ministry of Forest.

Stability analysis of unsaturated slopes under elevated temperatures

Several natural and man-made phenomena (e.g., droughts, wildfires, shallow geothermal technologies) can subject unsaturated slopes to elevated temperatures. However, the impact of temperature on the stability of unsaturated slopes is not well understood. This study aims to examine the stability of unsaturated intact slopes under elevated temperatures. An analytical framework is developed to calculate the factor of safety (FOS) of unsaturated slopes under steady fluid flow conditions at various temperatures. The theoretical basis of the framework is built upon the concept that, within the temperatures range investigated, the influence of temperature on the soil's shear strength is primarily attributed to thermal induced changes in apparent cohesion stemming from matric suction. Temperature dependency of apparent cohesion is quantified by employing temperature-dependent soil-water retention curve (SWRC) and effective stress models, which are then integrated into an infinite slope stability analysis of unsaturated soils under steady flow. A saturation-dependent thermal conductivity is used to obtain the temperature profile versus depth. The formulations are used to determine FOS for intact slopes with different hypothetical soils including sand, silt, and clay at surface temperatures of 25, 40, and 55 °C under different steady flow rates. Results show that the effective stress, shear strength, and FOS increase by increasing temperature from 25 °C to 55 °C. Results reveal that the effect of temperature on the stability of clayey and silty slopes can be considerable. The proposed models are validated against two sets of laboratory-measured data from the literature. The presented model provides a simple and effective method for site-specific and regional-scale stability analyses of unsaturated slopes under different thermal and seepage conditions.

Landslide Susceptibility Assessment Using the Scoops3D Model in a Tropical Mountainous Terrain

Many physically-based distributed models study the landslide occurrence using an infinite slope stability analysis, simulating a planar failure, which is not usually applicable to rotational failures and deep landslides. Recently, some three-dimensional distributed physically-based models have been developed that have been applied in different parts of the world. In this research, the Scoops3D model is implemented for a landslide susceptibility analysis in a tropical mountainous terrain of the Colombian Andes (Medellín, Colombia). In addition to identifying the areas susceptible to the occurrence of rotational landslides, the results of the safety factor are analyzed with the areas of associated critical failure surfaces to provide an interpretation and explanation of the simulation results. This is to have a better understanding of how the model works and to facilitate its implementation in landslide hazard assessment. The Scoops3D physicallybased model can be a very useful tool for mass movement risk management projects.

A Landslide Monitoring System for Natural Terrain in Korea: Development and Application in Hazard Evaluations.

This study describes the development of a landslide monitoring system for the purpose of reducing damages caused by landslides in natural terrain. The system was developed to analyze the effects of landslide-inducing rainfall and the behavior of slopes through 12 monitoring stations that are distributed across eight national parks in Korea. Several sensors and a data acquisition equipment to monitor landslide were installed in each station. The composition of the system and its operating program were designed to efficiently manage the sizeable amounts of real-time monitoring data that are collected from the various stations. To test the potential of the developed system for reliable landslide hazard evaluations, data measured over a five-year period by the two monitoring stations in Jirisan National Park were analyzed. Subsequently, the suction stress of the soil over the monitoring period was calculated by applying laboratory test result of the geotechnical and unsaturated soil properties in the analysis domain area. The infinite slope stability analysis combined with an effective stress concept based on the suction stress was applied to calculate the factor of safety. This method also enabled the temporal and quantitative evaluation of slope stability in natural terrain. In addition, based on the monitoring and slope stability analysis results, an analysis for the spatial classification of landslide hazards was conducted. The analysis results quantitatively and statistically demonstrated that 98% of historical landslide initiation areas were classified as high hazard levels.

Improving Spatial Landslide Prediction with 3D Slope Stability Analysis and Genetic Algorithm Optimization: Application to the Oltrepò Pavese

In this study, we compare infinite slope and the three-dimensional stability analysis performed by SCOOPS 3D (software to analyze three-dimensional slope stability throughout a digital landscape). SCOOPS 3D is a model proposed by the U. S. Geological Survey (USGS), the potentialities of which have still not been investigated sufficiently. The comparison between infinite slope and 3D slope stability analysis is carried out using the same hydrological analysis, which is performed with TRIGRS (transient rainfall infiltration and grid-based regional slope-stability model)—another model proposed by USGS. The SCOOPS 3D model requires definition of a series of numerical parameters that can have a significant impact on its own performance, for a given set of physical properties. In the study, we calibrate these numerical parameters through a multi-objective optimization based on genetic algorithms to maximize the model predictability performance in terms of statistics of the receiver operating characteristics (ROC) confusion matrix. This comparison is carried out through an application on a real case study, a catchment in the Oltrepò Pavese (Italy), in which the areas of triggered landslides were accurately monitored during an extreme rainfall on 27–28 April 2009. Results show that the SCOOPS 3D model performs better than the 1D infinite slope stability analysis, as the ROC True Skill Statistic increases from 0.09 to 0.37. In comparison to other studies, we find the 1D model performs worse, likely for the availability of less detailed geological data. On the other side, for the 3D model we find even better results than the two other studies present to date in the scientific literature. This is to be attributed to the optimization process we proposed, which allows to have a greater gain of performance passing from the 1D to the 3D simulation, in comparison to the above-mentioned studies, where no optimization has been applied. Thus, our study contributes to improving the performances of landslide models, which still remain subject to many uncertainty factors.

A GIS tool for infinite slope stability analysis (GIS-TISSA)

Landslides are one of the most common and a destructive natural hazard in mountainous terrain and thus evaluating their potential locations and the conditions under which they may occur is crucial for their hazard assessment. Shallow landslide occurrence in soil and regolith covered slopes are often modeled using the infinite slope model, which characterizes the slope stability in terms of a factor of safety (FS) value. Different approaches have been followed to also assess and propagate uncertainty through such models. Haneberg (2004) introduced the use of the First Order Second Moment (FOSM) method to propagate input uncertainty through the infinite slope model, further developing the model and implementing it in the PISA-m software package (Haneberg, 2007). Here we present an ArcPy implementation of PISA-m algorithms, which can be run from ESRI ArcMap in an entirely consistent georeferenced framework, and which we call “GIS Tool for Infinite Slope Stability Analysis” (GIS-TISSA). Users can select between different input options, e.g., following a similar input style as for PISA-m, i.e., using an ASCII.csv parameters input file, or providing each input parameter as a raster or constant value, through the program graphic user interface. Analysis outputs can include FS mean and standard deviation estimates, the probability of failure (FS < 1), and a reliability index (RI) calculation for FS. Following the same seismic analysis approach as in PISA-m, the Newmark acceleration can also be done, for which raster files of the mean, standard deviation, probability of exceedance, and RI are also generated. Verification of the code is done by replicating the results obtained with the PISA-m code for different input options, within a 10−5 relative error. Monte Carlo modeling is also applied to validate GIS-TISSA outputs, showing a good overall correspondence. A case study was performed for Kannur district, Kerala, India, where an extensive landslide database for the year 2018 was available. 81.19% of the actual landslides fell in zones identified by the model as unstable. GIS-TISSA provides a user-friendly interface, particularly for those users familiar with ESRI ArcMap, that is fully embedded in a GIS framework and which can then be used for further analysis without having to change software platforms and do data conversions. The ArcPy toolbox is provided as a .pyt file as an appendix as well as hosted at the weblink: https://pages.mtu.edu/~toommen/GeoHazard.html.

An improved Chebyshev semi-iterative method for simulating rainfall infiltration in unsaturated soils and its application to shallow landslides

A Chebyshev semi-iterative method (CSIM) with preconditioner (P-CSIM) is proposed to simulate numerically unsteady flow in unsaturated soils. An exponential function was used to linearize Richards’ equation, which was discretized using a finite difference method to obtain the linear equations. For layered soils, the numerical discretization takes into account the continuity of the pressure head at the interface. Conventional iterative approaches, including the Jacobi and the Gauss–Seidel iterative methods, require more iterations to obtain numerical solutions. The CSIM incurs more computational cost per iteration. The improved P-CSIM by comparison solves the linear equations in fewer iterations, with higher computational efficiency, and better robustness. The results indicate that the proposed P-CSIM provides good computational acceleration; specifically, at least 50% more than the CSIM and the Gauss–Seidel and Jacobi iterative methods. To simulate shallow landslides, the stability analysis of infinite slopes was developed to incorporate the time-varying pressure head and soil–water characteristic curves of unsaturated soils. The results of the examples indicate that the solver is able also to represent the increase of pressure head which may lead to a landslide. As a result, the proposed method with high computational efficiency can be developed to effectively analyze rainfall-induced shallow landslides in unsaturated soils.

A two-stage probabilistic approach for the risk assessment of submarine landslides induced by gas hydrate exploitation

In this paper, a two-stage risk assessment approach for gas hydrate exploitation is presented. In the first stage, a probabilistic analysis method is used to evaluate the failure probability of submarine landslide due to hydrate exploitation. The excess pore pressure due to hydrate exploitation is evaluated using a proposed maximum excess pore pressure model, which can consider the equilibrium of pressure and temperature for hydrates during decomposition. An infinite slope stability analysis and Monte Carlo simulations are then used to evaluate the failure probability of the slope with consideration of the generated excess pore pressure. In the second stage, a Bayesian network model to estimate the mortality rate of platform workers is proposed based on the logical sequence of events. The proposed approach is easy to implement and provides an efficient approach for quantitative assessment of human risk. Application of the proposed approach to a potential hydrate exploitation area, the Shenhu area in the South China Sea, is presented. The probabilistic analyses reveal that the production temperature T1 and the slope angle β have significant influences on the failure probability. Analysis of the human risk suggests that the key factors affecting the mortality rate are the distance of the platform to landslide and the equipment time for the workers to equip with lifejackets.

Physically Based Estimation of Rainfall Thresholds Triggering Shallow Landslides in Volcanic Slopes of Southern Italy

On the 4th and 5th of March 2005, about 100 rainfall-induced landslides occurred along volcanic slopes of Camaldoli Hill in Naples, Italy. These started as soil slips in the upper substratum of incoherent and welded volcaniclastic deposits, then evolved downslope according to debris avalanche and debris flow mechanisms. This specific case of slope instability on complex volcaniclastic deposits remains poorly characterized and understood, although similar shallow landsliding phenomena have largely been studied in other peri-volcanic areas of the Campania region underlain by carbonate bedrock. Considering the landslide hazard in this urbanized area, this study focused on quantitatively advancing the understanding of the predisposing factors and hydrological conditions contributing to the initial landslide triggering. Borehole drilling, trial pits, dynamic penetrometer tests, topographic surveys, and infiltration tests were conducted on a slope sector of Camaldoli Hill to develop a geological framework model. Undisturbed soil samples were collected for laboratory testing to further characterize hydraulic and geotechnical properties of the soil units identified. In situ soil pressure head monitoring probes were also installed. A numerical model of two-dimensional variably saturated subsurface water flow was parameterized for the monitored hillslope using field and laboratory data. Based on the observed soil pressure head dynamics, the model was calibrated by adjusting the evapotranspiration parameters. This physically based hydrologic model was combined with an infinite-slope stability analysis to reconstruct the critical unsaturated/saturated conditions leading to slope failure. This coupled hydromechanical numerical model was then used to determine intensity–duration (I-D) thresholds for landslide initiation over a range of plausible rainfall intensities and topographic slope angles for the region. The proposed approach can be conceived as a practicable method for defining a warning criterion in urbanized areas threatened by rainfall-induced shallow landslides, given the unavailability of a consistent inventory of past landslide events that prevents a rigorous empirical analysis.

Analysis of Landslide Risk Distribution Pattern under Extreme Precipitation

This study analyzed the landslide risk in Ulsan, Korea using infinite slope stability analysis considering rainfall infiltration in the soil layer. The parameters used in the analysis were obtained by geographic information system (GIS) and field survey using the following parameter values: a cohesion of 30.84 kPa, unit weight of 1.46 t/m3, specific gravity of 2.65, effective soil depth of 0.41 m, and internal friction of 27.15°. The rainfall intensity was set to last for 60 min at a 10-year frequency of 57.8 mm/h, 50-year frequency of 78.5 mm/h, 100-year frequency of 87.3 mm/h, and 500-year frequency of 107.5 mm/h. The minimum safety factor for the landslide risk was set at 1.3, according to the slope design criterion of construction slope announced by Korea's Ministry of Land, Infrastructure, and Transport. The safety factors with the values of 0-1.3 have been classified into four grades based on the saturation depth ratio varying with the rainfall intensity. The higher the rainfall intensity, the higher the percentage of the first grade (very dangerous) area. For verification, the landslide risk area proposed in this study was compared with the ‘Landslide Risk Map’ provided by Korea Forest Service. It is expected that high accuracy could be achieved in future by increasing the field survey data. Keywords: Infinite Slope Stability Analysis, Rainfall Infiltration, Landslide, Wetting Front

Investigation of the Influence of Rainfall Runoff on Shallow Landslides in Unsaturated Soil Using a Mathematical Model

Infiltration and groundwater have been widely considered as the main factors that cause shallow landslides; however, the effect of runoff has received less attention. In this study, an in-house physical-process-based shallow landslide model is developed to demonstrate the influence of runoff. The model is controlled by coupling the shallow water equation (dynamic) and Richards’ equation. An infinite slope stability analysis is applied to evaluate the possibility of regional landslides. A real, small catchment topography is adopted as a demonstration example. The simulation illustrates the variations of runoff and the factor of safety (FS) during a storm. The results indicate that, after the surface becomes saturated, the FS may keep varying due to the increasing pressure head, which is caused by increasing surface water depth. This phenomenon most likely occurs downstream where the slopes easily accumulate water. The depth of the surface water may also be a factor of slope failure. Therefore, it is essential to increase the accuracy of calculating the runoff depth when assessing regional shallow landslides.

Model test study on the hydrological mechanisms and early warning thresholds for loess fill slope failure induced by rainfall

Under rainfall conditions, the characteristics of hydraulic changes related to the failure evolution of fill slopes are critical to the early warning of slope failure. In this study, a series of model tests are carried out on loess fill slopes with different slope types. The matric suction, volumetric moisture content, pore water pressure and deformation of the slope are monitored in real time during the rainfall process. Meanwhile the development of cracks and the failure modes of the slope are analyzed, and then the early warning strategy of fill slope failure induced by rainfall is studied. The results show that loess landslides induced by rainfall exhibit a hysteresis. However, the volumetric water content and the matrix suction respond earlier than the pore water pressure. The slope failure is produced when the volumetric water content and the matrix suction are respectively at their maximum and minimum values. The evolution mechanism of cracks on the slope starts when tensile cracks are first generated near the leading edge surface and then extend backwards. In the next stage, shear fracture is produced near the flanking of the slope and finally, the trailing edge produces a transfixion tensile crack from the top to toe of the fill slope, which not only provides the advantage of an infiltration channel to control the hydrological process, but also evolves into the trailing edge boundary of each failure of fill slope. With the increase of rainfall duration, the filling slope presents different failure characteristics, revealing the hydraulic behavior of a partially saturated slope. In addition, combined with the infinite slope stability analysis in Mohr–Coulomb soil, the matrix suction and volumetric water content thresholds of the fill slopes with different slope angle are determined. The early warning threshold model for rainfall induced slope instability is proposed and a new framework of early warning is provided.