Infinite Slope Research Articles

Stability of long uniform slopes in cohesionless soils with seepage parallel to slope surface

A method is employed in this paper for the computation of earth pressures mobilized by landslides in cohesionless soil slopes against retention systems. For calculation purposes, the water table is taken to be parallel to the slope and at a depth zw. Steady seepage is assumed to be taking place in a direction parallel to the slope. End effects are taken into account. In the upper part of the slope, the soil is considered to be in a Rankine active state of equilibrium and a Rankine passive state of equilibrium is assumed to reign in the lower part of the slope. The infinite slope concept is applied to the central part of the slope. The theory shows that the slip surfaces below the water table are curved, not straight lines.The theoretical procedure developed in the present paper was applied to the analysis of an initially unstable long slope that failed in spite of the presence of a shear pile wall made up of a row of closely spaced 1m-diameter bored piles. The retaining system was designed based on the Rankine active state of equilibrium, using a factor of safety of about 1.7. It is shown that, as the shear pile wall was located in the lower part of the slope, it was subjected to a much greater force, compatible with a Rankine passive state of equilibrium, corresponding to a factor of safety of about 0.9. As a result, the shear pile wall was doomed to fail.

Probabilistic stability analysis of small-angle marine slopes considering hydrate decomposition and seismic excitation

The submarine massive mud transports of several seas around the world, including the Shenhu Sea, are thought to relate with hydrate decomposition, which occur even at small gradients. This article investigates the stability and reliability of marine slopes considering three factors related to hydrate decomposition and earthquake, namely decrease in sediment strength, increase in excess pore pressure, and activation by external seismic force. Taking the SH2 hole, implemented by the first Chinese offshore hydrate drilling mission (GMGS-1), as an example, the impacts of three factors mentioned above on marine slopes stability are analyzed with infinite slope theory. In addition, the space distribution of physical and mechanical parameters in hydrate deposits is under consideration. The cohesion, friction angle and buoyant unit weight in a non-stationary random field are treated as spatial random variables, where the means of the first two increase linearly with depth. Variation characteristics of the failure probability for various slope angles are analyzed under different scenarios. The outcomes reveal that the safety factor of the slopes at 30% potential for damage is around 1.25 within a given variant characterization. The proposed integrated stability and reliability analysis can effectively provide early warning for collapse of marine hydrate-bearing slopes.

Approach to stationarity for the KPZ fixed point with boundaries

Current fluctuations for the one-dimensional totally asymmetric exclusion process (TASEP) connected to reservoirs of particles, and their large scale limit to the KPZ fixed point in finite volume, are studied using exact methods. Focusing on the maximal current phase for TASEP, corresponding to infinite boundary slopes for the KPZ height field, we obtain for general initial condition an exact expression for the late time correction to stationarity, involving extreme value statistics of Brownian paths. In the special cases of stationary and narrow wedge initial conditions, a combination of Bethe ansatz and numerical conjectures alternatively provide fully explicit exact expressions.

An Analytical Insight Into Stability Analysis of Unsaturated Multi‐Layered Slopes Subjected to Rainfall Infiltration

ABSTRACTSlopes in nature usually present layered characteristics, and its stability is susceptible to rainfall events. Considering that current analytical solutions are only suited to simulate the rainfall infiltration of double‐layered infinite unsaturated slopes, an analytical procedure is hence proposed in this study to tackle the consideration of multiple layers. The variable separation method and transfer matrix method are combined to derive the analytical solution of pore water pressure (PWP) for simulating rainfall infiltration in layered infinite unsaturated slopes. After having validated the proposed model and analytical solutions by comparing with existing literature and numerical simulation, the closed‐form solution of PWP is incorporated into the limit equilibrium for assessing slope stability. A three‐layer slope is selected as an example for further discussion. PWP distribution and factor of safety are calculated, considering the effects of saturated hydraulic conductivity and thickness of the upper layer, intensity of antecedent and subsequent rainfall, and varied soil unit weight along the depth. The slope stability subjected to rainfall effects is consistent with the variation of PWP. The proposed analytical solutions provide a simple and practical avenue for computing PWP distribution and evaluating the stability of multi‐layered slopes under rainfall conditions, which can also serve as a benchmark for numerical solutions.

Shallow-landslide stability evaluation in loess areas according to the Revised Infinite Slope Model: a case study of the 7.25 Tianshui sliding-flow landslide events of 2013 in the southwest of the Loess Plateau, China

Abstract. The occurrence of shallow loess landslides induced by prolonged heavy rainfall is prevalent in loess-dominated regions, often leading to property damage, human casualties, and sediment pollution. Developing an accurate prediction model for shallow landslides in loess areas is crucial for effective landslide mitigation. In 2013, prolonged heavy rains from 19–25 July triggered mass sliding-flow loess landslides in Tianshui, China. Landslide data, along with the characteristics of the sliding-flow loess landslides, were obtained through extensive field investigations and remote sensing interpretations. The sliding-flow loess landslide event demonstrated clustering, high density, small areas, and long travel distance. The depth of the sliding surface is correlated with the saturated layer resulting from rainfall infiltration; it is typically less than 2 m deep and negatively correlated with slope steepness. Based on the common characteristics of shallow loess landslides, the mechanisms involved in the sliding-flow landslide are proposed. The Revised Infinite Slope Model (RISM) was introduced using an equal differential unit method to address deficiencies when the safety factor remains constant or increases with increasing slope greater than 40°, as calculated using the Taylor slope infinite model. The relationship between the critical depth and the slope of the shallow loess landslide was determined. The intensity–duration (I–D) prediction curve of the rainfall-induced shallow loess landslides for different slopes was constructed and combined with the characteristics of rainfall infiltration for use in forecasting regional shallow loess landslides. Additionally, the influence of loess strength on the shallow loess landslide stability was analyzed. The shallow loess landslide stability responds to slope and cohesion but is not sensitive to the internal friction angle.

Influence of 3D subsurface flow on slope stability for unsaturated soils

The occurrence of rainfall-induced slope failures has become more frequent due to the effect of climate change. Hence, various studies have been conducted to analyse the effect of rainfall infiltration on slope stability. Physically-based hydrological models have been commonly used with slope stability models such as the infinite slope model to develop slope susceptibility maps. However, a combination of three-dimensional (3D) water balance model with 3D limit equilibrium method (LEM) has not been commonly used. Hence, in this study, a water balance model, GEOtop was used to investigate the influence of subsurface flow in unsaturated soil under extreme rainfall conditions on regional slope stability in 3D directions. The results from the GEOtop model were used as inputs for 3D LEM slope stability analysis performed using the Scoops3D software to obtain the factor of safety (FOS) map for the region. Four slopes within the region were then selected to be modelled in the two-dimensional (2D) seepage and slope stability analyses, SEEP/W and SLOPE/W. Results from the detailed study showed that the pore-water pressures (PWPs) from the 3D water balance analyses were found to be higher than the 2D seepage analyses. Under similar PWP conditions, the FOS from the 2D slope stability analysis was observed to be lower than the 3D analysis for two out of the four slopes. However, the combined 3D water balance and slope stability analyses produced lower FOS compared to the 2D seepage and slope stability analyses due to the higher PWPs in the 3D water balance analyses. Therefore, this study highlights the importance of considering the 3D subsurface flow in unsaturated soil given that it has a significant influence on the FOS of slopes.

Infiltration, runoff, and slope stability behaviors of infinite slope with macropores based on an improved Green-Ampt model

Infiltration, runoff, and slope stability behaviors of infinite slope with macropores based on an improved Green-Ampt model

A comparative study of slope stability analysis via Geo5 using IoT framework

In mountainous regions, landslides pose significant and frequent threats, causing extensive damage due to their destructive nature and frequency, therefore determining their likely occurrence sites and environmental factors is essential for hazard assessment. The infinite slope approach characterizes slope stability using a factor of safety (FOS) to assess the likelihood of slope failure and is frequently used to estimate the occurrence of shallow landslides on soil and regolith-covered slopes. Various methods have been used to evaluate and spread uncertainty across such models. Slope failure is a significant geological occurrence brought on by topography and weather, which result in a variety of ground movements. Engineers must plan and implement measures to mitigate hazards, safeguarding both lives and property from potential risks and dangers by using an adequate stabilizing solution. Technology and software advancements have made it simpler than ever to handle challenging issues that used to require a lot of time in every profession. Over the past decade, software utilization in civil engineering has surged. GEO 5 is a versatile program gaining prominence, aiding in the resolution of diverse geotechnical challenges. Through the installation of IoT cameras in various sand and clay areas along the bank of the Mahandi River in Odisha, we have gathered the data necessary to develop the region in this case. a select selection of which we have chosen for our research. In this study, slope stability-related modules have been carefully examined and used for the analysis of slope stability. Using the GEO5 program, the geometry of the issues was established, and the study took into account several stability optimization techniques. Additionally, the cost factor of various reinforcing techniques was calculated and contrasted.

Numerical Simulation of Rainfall-Induced Erosion on Infiltration and Slope Stability

In slopes where a mixture of coarse and fine particles is present, the infiltration of rainfall can cause the migration of fine particles. This migration alters the hydraulic properties of the soil and has implications for slope stability. In this study, the slope under investigation is a tailings dam composed of loosely consolidated soil with a wide particle size distribution. Due to rainfall infiltration, fine particles tend to migrate within the voids of the coarse particle framework, leading to changes in hydraulic properties and inducing slope instability. The classical internal erosion constitutive model, known as the Cividini and Gioda erosion criterion, is commonly used to predict the behavior and effects of fine particle erosion in geotechnical engineering. However, certain parameters in this erosion criterion equation, such as long-term density, are challenging to obtain through experiments. To investigate the coupled evolution of seepage and erosion within landfill slopes under the influence of rainfall infiltration and to understand the mechanisms of slope instability, this research assumes the erosion of fine particle suspension and adopts the Worman and Olafsdottir erosion criterion to establish a coupled model of unsaturated seepage and internal erosion. The developed model simulates the coupled response of seepage and erosion in unsaturated landfill slopes under three different rainfall intensities. It is then combined with the infinite slope model to quantitatively analyze the impact of fine particle migration on soil permeability and slope stability. The numerical simulations provide the following findings: The Worman and Olafsdottir erosion criterion, unlike the Cividini and Gioda erosion criterion, only requires the determination of the soil’s gradation curve to estimate the erosion rate. Internal erosion primarily occurs within the leading edge of moisture penetration, accelerating the advancement of the wetting front and reducing slope stability. When the rainfall intensity is lower than the saturated permeability coefficient, the influence of internal erosion can be disregarded. However, under rainfall intensities equal to or greater than the saturated permeability coefficient, considering internal erosion results in a difference in the depth of the wetting front of up to 34.2 cm after 6 h in the R2 scenario. The safety factor without considering internal erosion is 1.12, whereas considering internal erosion yields safety factors between 1.08 and 1.09. In the R3 scenario, the difference in the depth of the wetting front reaches 53.8 cm after 6 h, with a safety factor of 1.12 without considering internal erosion and safety factors between 1.06 and 1.07 when considering internal erosion.

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.

Long-term “memory” of extraordinary climatic seasons in the hysteretic seepage of an unsaturated infinite slope

This paper presents a study of the hydraulic response of an infinite unsaturated slope exposed to a perturbation of the ordinary seasonal climatic cycle. The ground flow is modelled via a simplified one-dimensional finite difference scheme by decomposing the two-dimensional slope seepage into antisymmetric and symmetric parts. The numerical scheme incorporates two distinct hysteretic and non-hysteretic soil water retention laws, whose parameters have been selected after a preliminary sensitivity analysis. Results indicate that, in the hysteretic case, the “memory” of the perturbation takes a long time to fade, and the ordinary soil saturation cycle is only restored after several years of normal weather. Instead, in the non-hysteretic case, the recovery of the ordinary saturation regime is almost immediate after the perturbation. In contrast with the markedly different predictions of degree of saturation, both hysteretic and non-hysteretic slope models predict virtually identical evolutions of negative pore water pressures, with an almost immediate restoration of the ordinary cycle after the perturbation.

A closed-form criterion to identify high-mobility flowslides

This paper derives a closed-form criterion to assess the risk of flowslide runout in loose frictional soil. The derivations rely on a recently proposed framework to simulate pre- and post-failure motion in infinite slopes. An analytical solution of the coupled differential equations capturing flowslide hydromechanics is obtained by specifying them for a perfectly plastic constitutive law. This result enables a comprehensive examination of the factors that control whether the landslide motion, once triggered, autonomously comes to rest (self-regulating behaviour with low mobility) or continues to propagate (self-feeding behaviour with high mobility). It is found that the time history of motion is regulated by non-dimensional property groups reflecting the timescale of excess pore pressure dissipation and the inertial properties of the liquefied zone, which are in turn governed by material (e.g. hydraulic conductivity, dilation coefficient, elastic moduli) and slope properties (e.g. thickness, inclination). The solution is used to build charts identifying the critical ranges of soil properties and triggering factors that differentiate between high-mobility and low-mobility flowslides. Most importantly, it is shown that the fate of flowslide motions is predicted by a critical ratio expressed in terms of excess pore pressure and flow velocity, here defined as the factor of mobility, FM, with values above 1 indicating a self-feeding runout.

Modelling antecedent soil hydrological conditions to improve the prediction of landslide susceptibility in typhoon-prone regions

Most regional landslide susceptibility models do not consider the evolving soil hydrological conditions leading up to a multiple occurrence regional landslide event. This results in inaccurate predictions due to the non-linear behaviour of the terrain. To address this, we have developed a simple and efficient model that incorporates the mid-term evolution of soil hydrological conditions. The model combines a water balance model and a geotechnical model based on infinite slope theory. The analysis of 561 high-intensity rainfall events in a typhoon-prone region of the Philippines revealed that the percolation of water during the 5-month wet season is crucial in determining landslide susceptibility. Consequently, high-intensity rainfall events at the start of the wet season are less likely to trigger landslides, while later events are more hazardous. We analysed the change in landslide susceptibility during the 2018 rainy season by comparing the probability of failure (PoF) before and after three high-intensity rainfall events (July, August and September). Only the event in September caused a significant increase in the probability of failure (PoF). The model showed an accuracy of 0.63, with stable cells better represented than unstable cells. The antecedent hydrological conditions on the lower soil layers are responsible for changes in landslide susceptibility. Our findings support the hypothesis that new approaches to developing hydro-meteorological thresholds for landslide early warning systems should be evaluated, especially in regions with strong seasonality.

Wet-to-dry transition description in the mixture of working fluids

The organic rankine cycle performance and some similar processes depend on many factors. One of them is the category of the working fluid, influencing the performance through the phase/phases during and at the end of the expansion process. Droplet formation for wet fluids and superheated for dry fluids motivated the researchers to seek isentropic working fluids, where expansion could proceed and terminate in a saturated vapour state. The shape of the T-s diagram is a material property; it cannot be changed for real pure fluids, but small jumps can be initiated by replacing one working fluid with a chemically very similar one, like Propane (a wet one) with Butane (a dry one). Our study presents a much smoother transition, using mixed working fluids prepared from chemically similar materials to obtain almost ideal zeotropic mixtures. The main point of our study is to show the wet-to-dry transition for mixtures and prove or disprove the existence of compositions where the fluid can show T-s diagram resembling the ones for ideal isentropic working fluids. For this purpose, Propane was mixed with other alkanes, such as Butane, Pentane, and Hexane, in various compositions, and the thermophysical properties of fluids were calculated by using the REFPROP software program. Wet-to-dry transitions were shown for the Propane/Hexane mixture at (0.6584 + 0.3416 mass fraction), while (0.5823 + 0.4177 mass fraction) and (0.6436 + 0.3564 mass fraction) was the transition mixture for Propane/Butane and Propane/Pentane respectively. Consequently, when exceeding the mentioned composition range, the fluids switch from wet to dry without forming a composition showing ideal isentropic properties. Therefore, isentropic working fluid (showing an infinite slope for the saturated vapour branch in a finite, nonzero temperature range) was not found during this transition.

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 of Ficus virens-Reinforced Slopes Considering Mechanical and/or Hydrological Effects

Vegetation reinforcement for slopes has been recognized as an environment-friendly measure and has been widely adopted in engineering practice. However, the stability analysis of vegetation reinforcement for slopes has mainly been discussed for an infinite slope and common grass and scrub plant species. This study proposes a procedure for analyzing the stability of a finite slope reinforced with Ficus virens under transpiration and rainfall conditions. A simplified empirical model for characterizing root cohesion and triaxial testing is utilized to quantify the mechanical effect of roots on rooted soil shear strength. A numerical modeling technique with COMSOL Multiphysics is used to investigate the hydrological effect of roots. The combination of these two effects forms an expression for the unsaturated shear strength of rooted soils. The stability of a vegetated soil slope is then investigated in terms of safety factors and failure mechanisms, with/without considering rainfall. The results show that the stability solutions without consideration of the roots’ mechanical and/or hydrological effects are overly conservative. The hydrological contribution to slope stability could also be partially preserved under short-term rainfall, and as rainfall continues, the hydrological effect is weakened, while the mechanical reinforcement is assumed to be unchanged. In the meantime, the hydrological contribution to slope stability is susceptible to atmospheric conditions, which indicates a favorable effect on water uptake and an adverse consequence for water infiltration.

An Infinite Slope Model Considering Unloading Joints for Spatial Evaluation of Coseismic Landslide Hazards Triggered by a Reverse Seismogenic Fault: A Case Study of the 2013 Lushan Earthquake

Coseismic landslides pose a significant threat to the sustainability of both the natural environment and the socioeconomic fabric of society. This escalation in earthquake frequency has driven a growing interest in regional-scale assessment techniques for these landslides. The widely adopted infinite slope model, introduced by Newmark, is commonly utilized to assess coseismic landslide hazards. However, this conventional model falls short of capturing the influence of rock mass structure on slope stability. A novel methodology was previously introduced, considering the roughness of potential slide surfaces on the inner slope, offering a fresh perspective on coseismic landslide hazard mapping. In this paper, the proposed method is recalibrated using new datasets from the 2013 Lushan earthquake. The datasets encompass geological units, peak ground acceleration (PGA), and a high-resolution digital elevation model (DEM), rasterized at a grid spacing of 30 m. They are integrated within an infinite slope model, employing Newmark’s permanent deformation analysis. This integration enables the estimation of coseismic displacement in each grid area resulting from the 2013 Lushan earthquake. To validate the model, the simulated displacements are compared with the inventory of landslides triggered by the Lushan earthquake, allowing the derivation of a confidence level function that correlates predicted displacement with the spatial variation of coseismic landslides. Ultimately, a hazard map of coseismic landslides is generated based on the values of the certainty factor. The analysis of the area under the curve is utilized to illustrate the improved effectiveness of the proposed method. Comparative studies with the 2014 Ludian earthquake reveal that the coseismic landslides triggered by the 2013 Lushan earthquake predominantly manifest as shallow rock falls and slides. Brittle coseismic fractures are often associated with reverse seismogenic faults, while complaint coseismic fractures are more prevalent in strike–slip seismogenic faults. The mapping procedure stands as a valuable tool for predicting seismic hazard zones, providing essential insights for decision-making in infrastructure development and post-earthquake construction endeavors.

Rapid Earthquake Damage Assessment and Education to Improve Earthquake Response Efficiency and Community Resilience

Southeastern Europe faces a significant earthquake threat, endangering lives, property, and infrastructure thus jeopardizing sustainable development. The development of a Rapid Earthquake Damage Assessment System (REDAS) designed to deliver crucial earthquake damage information for scenario planning, real-time response, and bolstering public awareness and preparedness is presented. In doing so, REDAS enhances community resilience and safeguards sustainability. REDAS comprises a Rapid Earthquake Damage Assessment platform (REDA.p), a smartphone application, and an Educational Hub (Edu.Hub). REDA.p provides both scenario-based and near real-time seismic damage evaluation of structures, gas pipelines, and geotechnical failures, based on harmonized Ground Motion Prediction Equations and a comprehensive building taxonomy scheme covering the area under investigation. To assess regional landslide hazards, the Infinite Slope Model and a statistics-based model have been implemented, alongside a statistical model for liquefaction probability assessment. Validated against historical data, REDA.p integrates real-time input from key earthquake monitoring networks in the region, covering cross-border areas as well, while in designated urban zones, the system is enhanced by real-time data from a dense earthquake monitoring network deployed in selected school buildings. The smartphone app and Edu.Hub disseminate critical information, guidelines, and tools to improve public prevention, preparedness, and response capacities, thereby enhancing societal resilience.

Estimation of site-specific multivariate probability distribution of soil properties using a mixed sampling technique

Estimation of multivariate probability density function (PDF) of soil properties based on limited site investigation data plays an important role in data driven-based geotechnical engineering analysis and design. However, this estimation is often intractable because the site-specific investigation data generally are multivariate, uncertain and unique, sparse, incomplete, sometimes corrupt and spatially variable. The estimation is more challenging when the uncertainties in model parameters of the distribution (i.e., mean, standard deviations and scale of fluctuation of soil properties) are taken into consideration. To address these difficulties, this study proposed a mixed sampling technique by combing the Gibbs sampler and transitional Markov Chain Monte Carlo sampler to effectively estimate the multivariate probability density function of soil properties. The proposed method is demonstrated through a virtual site example while the effect of statistical uncertainty in the scale of fluctuation on reliability analyses is illustrated in an infinite slope example. It is shown that the proposed method can not only handle the complex features of site investigation data but also effectively quantify the statistical uncertainties of the mean values, standard deviations and scale of fluctuation of the investigated soil properties. Ignoring the statistical uncertainties of scale of fluctuation can affect the estimation of mean and standard deviations of the soil parameters. When considering the statistical uncertainty of scale of fluctuation, the 95% confidence intervals for the profiles of the soil properties can rationally cover the actual soil data at the unobserved points. Ignoring the statistical uncertainty of scale of fluctuation can lead to the underestimation of the probability of failure of the infinite slope.