Infinite Slope Stability Research Articles

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.

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.

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.

Strengths and Infinite Slope Stability of Unsaturated Soils

Strengths and Infinite Slope Stability of Unsaturated Soils

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.

Exploring extreme rainfall-triggered landslides using 3D unsaturated flow, antecedent moisture and spatially distributed soil depth

The susceptibility to shallow landslides is affected by several factors. Rainfall intensity, soil thickness distribution, and antecedent moisture conditions are components that influence the spatio-temporal prediction of landslides at the watershed scale. Yet, the combined impact of these factors on the susceptibility to landslides has been overlooked. The purpose of this paper is to investigate landslides triggered by extreme precipitation in the Tijuca Massif, Rio de Janeiro, southeastern Brazil. Our approach couples a 3D variably saturated flow solver with the infinite slope stability method to calculate the statistical distributions of the safety factor and the pore pressure at the soil–bedrock interface. Numerical simulations were performed for 6 scenarios considering 1-year spin-up time for soil moisture and different spatially distributed soil depths. The results show that during extreme precipitation events, soil depth and initial moisture conditions may not have much influence on the safety factor, as the intensity and duration of rainfall will be the triggering agents. Comparison of simulated unstable zones and field data from mapped landslide scars further supported this conclusion. We conclude that simple soil depth models are feasible options for regional studies of landslide susceptibility. Our findings are relevant to understanding shallow landslides induced by extreme rainfall in Rio de Janeiro and other regions with similar geological and climate settings.

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.

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%.

Analytical Analysis of Infinite Heterogeneous Slope Stability considering Suction Influence

Soil heterogeneity in an infinite unsaturated slope increases the difficulty of analysing its stability. A common method of modelling the spatial variability in the slope stability analysis is to use random fields together with Monte Carlo simulation, but this requires an impressive amount of computational efforts. To reduce the computing time, this paper develops an analytical approach to study the stability of infinite heterogeneous unsaturated slopes. The analytical method provides a newly time-efficient way of analysing such kinds of slopes. It has been used to investigate the stability of four different kinds of unsaturated soil slopes. Meanwhile, the influences of the correlation between the strength parameters and the autocorrelation length of the strength parameters are investigated. The analysed results show that the suction has influences on the distribution of the FOS for both homogeneous slopes and heterogeneous slopes. In addition, the correlation coefficient between the strength parameters and the autocorrelation length of the strength parameters affects the mean and standard deviation of FOS for homogeneous slopes and the probability of failure for heterogeneous slopes.

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.

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.

Reliability analysis of infinite slopes with linearly increasing mean undrained strength

The infinite slope stability problem receives much interest in geotechnical engineering, as it can provide an initial assessment on the mechanics of shallow landslides. It is well known that natural soils exhibit spatial variability, with properties varying from point to point, and a trend of strength changing with depth. This paper will use a random field method to investigate the reliability of undrained infinite slopes with linearly increasing mean strength. An algorithm generating 1D non-stationary random fields of undrained strength will be introduced. Infinite slopes subjected to both static and pseudo-seismic loadings are considered. The paper reviews the influence of non-stationarity of undrained strength on the reliability and failure mechanisms of infinite slopes.

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.

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.