In the loess tableland, gully slope instability induces severe soil erosion and land degradation, yet the synergistic effects of dominant vegetation under varying restoration modes combined with dynamic rainfall regimes and topographic variations on gully slope stabilization mechanisms remain inadequately quantified. Therefore, the dominant vegetation species under natural (NR) and artificial restoration (AR) was chosen as the object. Through field sampling, root-soil complex mechanical experiments, and numerical simulations, the protection effect of dominant vegetation under different restoration modes combination with rainfall and topographic variations was investigated. The result revealed significant differences in basic soil physical properties, root morphological characteristics, root and root-soil complex mechanical properties among five dominant vegetated plots under the different restoration modes (P < 0.05). The soil properties in the Scop plot under AR were slightly better than those in the other plots. The roots in the Spp plot developed better under NR. The shear strength of Lespedeza bicolor Turcz. was the highest under NR. The tensile strength of Digitaria sanguinalis (L.) Scop. was greatest under AR. The tensile force and tensile strength of single roots exhibited a significant positive linear correlation and a significant negative exponential correlation, with root diameter, respectively (P < 0.01). For the unstable gully slopes (F-s < 1.0), maximum displacement occurred at the slope foot, where tensile shear failure dominated, while the interior experienced compressive yielding. The grey relational analysis identified rainfall intensity as the primary destabilizing factor, followed by dominant vegetation species, slope height, and slope gradient. Notably, when rainfall intensity reaches or exceeds 0.06 m/h, or when slope height exceeds 20 m combined with long-duration rainfall, the regulatory impacts of dominant vegetation under different restoration modes on the gully slope stability are substantially diminished and become negligible. This study provides a theoretical basis for gully slope protection and ecological environmental construction in loess tableland.

In the dynamic response analysis of slopes, the displacement of sliding surfaces is an important indicator for assessing stability. However, due to the uniform dynamic parameters of the Newmark slide block method, it is difficult to accurately analyze the displacements of large-scale slopes. To address this issue, the spatial distribution characteristics of dynamic parameters need to be considered to accurately analyze the stability of slopes. Under the combined action of rainfall and reservoir water level change, the Shiliushubao old landslide in the Three Gorges Reservoir area remains stable. To investigate the seismic stability of slopes, simulated seismic waves were employed. Firstly, the dynamic triaxial test, designed with cyclic loading, was employed to investigate the variation rules of the dynamic parameters of slope soil, and to establish a functional relationship. Then, the stochastic seismic motion model was used to generate artificially seismic waves in the Three Gorges Reservoir Area. Finally, to assess the stability of the old landslide, finite element software, GeoStudio 2018 was used to obtain the spatial distribution characteristics of the dynamic parameters and to calculate the permanent displacements of the reservoir bank slope by inputting random ground motion loads and dynamic characteristic functions. It is demonstrated that under the most unfavorable working conditions of heavy rainfall and the earthquake in the specific region, the permanent displacement of the Shiliushubao old landslide will be less than the critical permanent displacement, the old landslide is not to experience instability again.

Antislide piles are currently applied widely in slope reinforcement engineering, but investigation of the stability of slopes stabilized with this measure under the action of mainshock-aftershock (Ms-As) sequences is very limited. In this study, the probability density evolution method (PDEM) and the Newmark method is adopted to evaluate the reliability of slope reinforced by antislide piles subjected to Ms-As sequences considering the spatial variability of material parameters. Firstly, stochastic Ms-As sequences are generated by combining a physical function model, the Copula function, and the narrowband harmonic group superposition method. In addition, the spectral representation method is taken to generate the random field and the parameters are assigned to the numerical model. Then, the Newmark method is applied to batch-calculate the permanent displacement (Disp) of the slope caused by the Ms-As sequences. The effects of pile position, pile length, and coefficient of variation of cohesion and friction angle (COVC and COVF) on the average value of Disp are discussed. Finally, based on the PDEM, the seismic reliability of the slope strengthened by antislide piles subjected to the Ms-As sequences are obtained. The research results indicate that with the COV increases, the average value of Disp of the slope shows a gradual tendency to increase, and the average value is more sensitive to COVC. Compared with the unreinforced slope, the Disp of the slope strengthened by antislide piles is reduced. The cumulative damage caused by the aftershock and the risk of failure can be significantly reduced by setting a reasonable antislide pile.

The present work introduces an analytical framework based on the limit-equilibrium method for the determination of the local factor of safety (FS) and global factor of safety (FSG), and local displacements along the critical slip surface using the Morgenstern-Price (MP) method of slices. This proposed work computes displacements along the critical slip surface in addition to a single FSG. The unsaturated shear strength models, in conjunction with the soil-water characteristic curve (SWCC), are considered. The MP-based equilibrium equations to determine FSG are utilized as an objective function in the metaheuristic search algorithm of particle swarm optimization to determine the critical center, critical radius, and minimum FSG for unsaturated finite slopes. It is recommended to use a particle size of 75 and conduct 50 iterations for optimal results. The effects of SWCC fitting parameters on the critical slip surface, FSG, point FS, and point displacements are also investigated. Two distinct benchmark slope scenarios with and without negative pore water considerations are utilized in the current study. This approach enables a detailed investigation into the influence of various unsaturated soil parameters, such as af (related to the air-entry value), nf (related to the slope of the SWCC), and mf (related to the residual water content), as well as constitutive model parameters including the linear shear modulus (G) and the fitting parameter (rho). The maximum displacement occurs at the slope's top crest. Under benchmark conditions, the first scenario shows a reduction in point displacement by 3.30%, 1.98%, and 10.23% for SWCC-1, SWCC-2, and SWCC-3, respectively. However, in the second scenario with SWCC-3, the critical slip surface's position changes, affecting local displacements. This results in an increase of 32.72% (i.e., from 21.45 to 28.47 mm) in point displacement at the top when comparing SWCC-3 with no SWCC consideration. The current study advocates that the effect of fitting parameters of the SWCC should be used to better understand the local FS and displacement, because the critical slip surface is contingent on the values of the SWCC. Ignoring SWCC parameters can lead to an underestimation of slope displacement, because they significantly influence the critical slip surface position and displacement magnitude. Their inclusion is essential for accurately assessing slope stability and preventing errors in displacement prediction.

Fibre reinforcement technology has been widely adopted in soil improvement due to its cost-effectiveness, simplicity, and environmental benefits. In many fibre reinforcement projects, the soil is often in an unsaturated state. However, the numerical simulation mechanisms of fibre-reinforced unsaturated soils remain poorly understood. In this study, a Vangenuchten (VG) model considering fibre incorporating fibres was proposed based on the original VG model. This model considering fibre accurately describes the soil water characteristic curve (SWCC) of fibre-reinforced sand (FRS), as verified by water-holding characteristics tests. Then, unsaturated triaxial tests confirmed the applicability of an unsaturated soil elastoplastic constitutive model and a fully coupled soil-water-air finite element-finite difference (FE-FD) method for simulating the mechanical behaviour of unsaturated FRS. Finally, using the SWCC parameters derived from the VG model considering fibres and mechanical parameters from saturated triaxial tests, slope models were established to analyse the stability of both unreinforced and fibre-reinforced slopes. The results show that the interweaving action of fibres within the soil enhances its strength, reduce permeability, and decreases both saturation and pore water pressure, ultimately increasing slope stability. This study provides valuable insights into the SWCC characteristics and the numerical calculation of FRS under unsaturated conditions.

The presence of desiccation cracks can affect rainfall-induced slope stability through both hydraulic and mechanical ways. Despite the valuable insights gained from physical tests in literature, there still lacks understanding how crack characteristics impact water flow dynamics and slope stability, especially considering the coexistence of vegetation. In this study, new analytical solutions were derived for calculating pore-water pressure and slope stability for an infinite unsaturated slope with cracks and vegetation. Both enhanced infiltration from water-filled cracks and water uptake by plant roots are considered. Using the newly developed solutions, two series of parametric analyses were carried out to improve understanding of the factors affecting crack water infiltration and hence the stability of vegetated slope. The calculated results show that slope failure at shallow depths is governed by the surface crack ratio, whereas deeper failures typically occur with greater crack depths. The surface crack ratio primarily influences the hydraulic response at shallow depths not exceeding 1.5 m, hence affecting the factor of safety for slip surfaces within the crack zone. Moreover, increasing the crack-to-root depth ratio from 0.5 to 1.5 results in a 25% reduction in suction at 1.5 m, threatening slope safety in deeper depth after 10-year rainfall.

This paper presents a method for analyzing slope stability in anisotropic and heterogeneous clay using a strength reduction finite element method (SRFEM) integrated with the level set method (LSM). Anisotropy refers to the inherent anisotropy in the clay's strength, while heterogeneity describes the spatial variability in strength parameters. The static LSM uses a zero level set function to model heterogeneous clay slopes. The method is validated through undrained slope stability analyses on different types of anisotropic clay and heterogeneous fields, showing its effectiveness in modeling anisotropic shear strength and capturing the characteristics of heterogeneous regions. The results indicate that the proposed method accurately predicts factors of safety and slip surfaces across various soil conditions, accounting for both anisotropic and heterogeneous characteristics.

In this paper a three-dimensional agro-hydrological model for shallow landslides' prediction is presented. The model is an extension of the CRITERIA-3D free-source model for crop development and soil hydrology, developed by the Hydrometeorological service of the Regional Agency for Environmental prevention and Energy of EmiliaRomagna region (Arpae-simc). The soil-water balance is computed through the coupling of surface and subsurface flows in multi-layered soils over areas topographically characterized by Digital Elevation Model (DEM). The rainfall infiltration process is simulated through a three-dimensional version of Richards' equation. Surface runoff, lateral drainage, capillarity rise, soil evaporation and plant transpiration contribute to the computation of the soil hydrology on an hourly basis. The model accepts meteorological hourly records as input data and outputs can be obtained for any time step at any selected depth of the soil profile. Among the outputs, volumetric water content, soil-water potential and the factor of safety of the slope can be selected. The validation of the proposed model has been carried out considering a test slope in Montue` (northern Italy), where a shallow landslide occurred in 2014 a few meters away from a meteorological and soil moisture measurement station. The paper shows the accuracy of the model in predicting the landslide occurrence in response to rainfall both in time and space. Although there are some model limitations, at the slope scale the model results are highly accurate with respect to field data even when the spatial resolution of the Digital Elevation Model is reduced.

Soil-rock mixtures (SRM) from mine overburden form heterogeneous dump slopes, whose stability relies on their shear strength properties. This study investigates the shear strength properties and deformation characteristics of SRM in both in-situ and laboratory conditions. Total twelve in-situ tests were conducted on SRM samples with a newly developed large scale direct shear apparatus (60 cm x 60 cm x 30 cm). The in-situ moist density and moisture content of SRM are determined. Particle size distribution is performed to characterize the SRM in laboratory. The bottom bench has the highest cohesion (64 kPa) due to high compaction over time while the other benches have consistent cohesion values (25 kPa to33 kPa). The laboratory estimated cohesion values are high compared to in-situ condition. It is further observed that for in-situ samples, the moist density notably affects the cohesion of SRM, with cohesion decreasing by 3 to 5 % for every 1 % increase in moist density. At in-situ condition, internal friction angles are found to be 1.5 to 1.7 times compared to laboratory values which is due to the presence of the bigger sized particles in the SRM. The outcomes of the research are very informative and useful for geotechnical engineers for slope designing and numerical modeling purpose.

Understanding slope stability is crucial for effective risk management and prevention of slides. Some deterministic approaches based on limit-equilibrium and numerical methods have been proposed for the assessment of the safety factor (SF) for a given soil slope. However, for risk analyses of slides of earth dams, a range of SFs is required due to uncertainties associated with soil strength properties as well as slope geometry. Recently, several studies have demonstrated the efficiency of artificial neural network (ANN) models in predicting the SF of natural and artificial slopes. Nevertheless, such techniques operate as black-box models, prioritizing predictive accuracy without suitable interpretability. Alternatively, multivariate polynomial regression (MVR) models offer a pragmatic interpretability strategy by combining the analysis of variance with a response surface methodology. This approach overcomes the difficulties associated with the interpretability of the black-box models, but results in limited accuracy when the relationship between independent and dependent variables is highly nonlinear. In this study, two models for a quick assessment of slope SF in earth dams are proposed considering the MVR and the ANN models. Initially, a synthetic dataset was generated considering different soil properties and slope geometries. Then, both models were evaluated and compared using unseen data. The results are also discussed from a geotechnical point of view, showing the impact of each input parameter on the assessment of the SF. Finally, the accuracy of both models was measured and compared using a real-case database. The obtained accuracy was 78% for the ANN model and 72% for the MVR one, demonstrating a great performance for both proposed models. The efficacy of the ANN model was also observed through its capacity to reduce false negatives (a stable prediction when it is not), resulting in a model more favorable to safety assessment.