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The numerical simulation and slope stability prediction are the focus of slope disaster research. Recently, machine learning models are commonly used in the slope stability prediction. However, these machine learning models have some problems, such as poor nonlinear performance, local optimum and incomplete factors feature extraction. These issues can affect the accuracy of slope stability prediction. Therefore, a deep learning algorithm called Long short-term memory (LSTM) has been innovatively proposed to predict slope stability. Taking the Ganzhou City in China as the study area, the landslide inventory and their characteristics of geotechnical parameters, slope height and slope angle are analyzed. Based on these characteristics, typical soil slopes are constructed using the Geo-Studio software. Five control factors affecting slope stability, including slope height, slope angle, internal friction angle, cohesion and volumetric weight, are selected to form different slope and construct model input variables. Then, the limit equilibrium method is used to calculate the stability coefficients of these typical soil slopes under different control factors. Each slope stability coefficient and its corresponding control factors is a slope sample. As a result, a total of 2160 training samples and 450 testing samples are constructed. These sample sets are imported into LSTM for modelling and compared with the support vector machine (SVM), random forest (RF) and convolutional neural network (CNN). The results show that the LSTM overcomes the problem that the commonly used machine learning models have difficulty extracting global features. Furthermore, LSTM has a better prediction performance for slope stability compared to SVM, RF and CNN models.

Infiltration of irrigation water is an important factor affecting the stability of loess slopes. In this study, based on the Green-Ampt infiltration model. We analysed the cumulative effect of drip irrigation on the stability of loess slope through an indoor cumulative drip-irrigation infiltration test with a single-point source, which was combined with the Geo-Studio finite-element software. Our results show that: (1) infiltration of drip irrigation in loess slopes has an obvious cumulative phenomenon. The depth of infiltration and volumetric water content of underlying soil increase with increasing cumulative number of drip irrigation; (2) the infiltration time calculated by the classical and improved Green-Ampt infiltration models is more in line with the experimental results, with errors ranging from 4 to 11%. (3) Short-term 3-day drip irrigation creates a layer of infiltration area on the slope surface. The safety coefficient of the slope body is reduced by 0.01, which has less impact on the slope. Long-term 3-year drip irrigation increased the volumetric water content of the entire slope, and decreased the safety coefficient by 0.91, which had a greater impact on the slope. Our results have important scientific significance slope-disaster warnings, and prevention in loess areas.

This paper aimed to study the soil–water characteristics and stability evolution law of rainfall-induced landslide. Taking the two landslide events in Siwan village as an example, the formation conditions of the disaster and landslide characteristics were analyzed. Additionally, the deformation characteristics and destruction mechanisms of landslides were discussed in-depth. The soil–water characteristics and hydraulic conductivity of the landslides were analyzed based on TRIM experiment results. Geo-Studio numerical software was further used for typical sections to analyze the stability of the evolution of the landslide events under rainfall conditions. The results showed that (1) The soil–water characteristic curve (SWCC) inversely varies with water content volume, and the sliding body has lower saturated water content and matrix suction than the sliding zone. The hydraulic conductivity function (HCF) increases with water content volume, and the sliding body has higher hydraulic conductivity (0.43 m/d) than the sliding zone (0.03 m/d). (2) Rainfall is the primary cause of landslides, and there is a hysteretic effect. Heavy rainfall will inevitably accelerate the formation of landslides in the analysis of the deformation characteristics and destruction mechanisms of rainfall-induced landslides. (3) Compared with the engineering analogy of the Fredlund and Xing (FX) model, the Van Genuchten–Mualem (VGM) model of the soil–water characteristics test based on the TRIM experimental system can better reflect the actual field situation. The numerical simulation method based on the TRIM experiments of the soil–water characteristics test is scientifically sound and reliable for the stability evolution of overburden rainfall-induced landslides.

Yunnan Province of China is located in the southwest frontier, with high altitude, fragile geological environment, uneven spatial and temporal distribution of rainfall, and more localized rainfall and landslide geological hazards caused by rainfall are extremely common. Therefore, based on saturated–unsaturated seepage theory, it is of great engineering significance to deeply study the change law of internal seepage of slopes under different rainfall conditions and the influence of dynamic seepage on slope stability. In this paper, based on the saturated–unsaturated seepage theory, the soil–water characteristic curve and unsaturated permeability coefficient prediction model are determined, and GEO-Studio finite element software is used to explore the changes of seepage field, stress field, displacement field, and stability coefficient of the slope under different rainfall conditions from the perspectives of seepage mechanics and rock mechanics, and to reveal the changes of unsaturated soil The mechanical response mechanism of unsaturated soil slopes in the process of dynamic seepage and the influence of seepage on the stability of slopes. The results show that: (1) the volumetric water content and saturation of the shallow soil will increase rapidly when the unsaturated soil slope is affected by rainfall, and the pore water pressure, maximum shear stress, and total displacement in the corresponding area will increase with the increase of rainfall time; (2) the stability of the slope is closely related to the rainfall time, and the longer the rainfall time, the lower the stability coefficient. At the same time, it provides theoretical support for the study of similar landslide mechanisms and prevention engineering.

This research work was carried out using Geo-Slope software programmes, i.e., to compute the infiltration and slope stability analysis of the Grindeho dam using SEEP/W and SLOPE/W. Embankment dam failure may occur due to different reasons, such as structural instability, hydraulic conditions, seepage through the dam body and foundation. The determination of the factor of safety for the dam slope stability and quantify the amount of seepage through the dam, under different cases of operations, is vital to ascertain the dam overall safety. In this research, Finite Element modelling is used through Geo-Studio software to simulate slope stability and seepage analysis of the embankment dam. Three distinct operational cases are considered for the dam analysis: end of construction before filling the reservoir, after/full reservoir condition, and rapid reservoir condition drawdown. Four separate methods of analysis were used to verify the stability of the slope embankment: Morgenstern-Price, Bishop, Janbu, and Spencer. The requirements of the Benchmark Safety Legislation (US Army of Corps Engineers and British Dam Society) are observed. The simulation results of the upstream and downstream side of the dam section have a direct effect on the factor of safety, the outcome of the stability analysis performed showed that all sections of the dam are safe within the specified range of factors of safety for the potential all loading and operation cases. But all the slip surfaces move through the section of the dam shell, which shows that this zone is the weaker zone and requires spatial attention. The simulation results obtained from the SEEP/W program revealed that 15,291.5 m 3 /year and 22,818.56 m 3 /year amount of seepage loss is present in the Grindeho dam during the drawdown case and full reservoir case, respectively.

Medapalli Open Cast Project (MOCP) owned by M/s Singareni Collieries Company Limited (SCCL), Andhra Pradesh, India where “Highwall mining” is practiced lies in the immediate vicinity of a large perennial river, ‘Godavari’. The mine and river, which are only 140–150 m apart, an artificially constructed embankment, built above highest flood level, restricts the water leakages into the mine. A need to know seepages that may occur at active working faces of MOCP highwall mining faces, referred here as web holes/web cuts, is realized and this seepage modeling study is undertaken. Since the coal mine has “Barakar formations” which, in general, has watery field conditions, there exists an enhanced possibility of seepage or water inflow into the mine pit. For this reason also this predictive assessment study of seepage modeling became essential. The quantitative estimation of water is done by conceptualized model of mine which was based on the sub-surface geology and hydrological set up of the area. SEEP/W module of ‘Geostudio’ software is used for prediction, estimation and assessment of water flux, inflow and recharges quantities as it is capable to consider the saturated/unsaturated flow conditions for the encountered unconfined aquifers. In the modeling exercise, we used ‘steady state’ and ‘transient state’ conditions to determine the water quantities of the seepage faces at pit walls/web holes. The estimation so done for this coal mine is compared and verified by another popular “Ground water flow and contaminant transport and river modeling software” namely, MODFLOW. Briefly and concisely, this study concludes that the water seepage from river to mine pit is very less and hence it has no adverse effect on the web holes and web pillars of highwall mining faces. The results of this study had helped mine management in taking decision about (a) uninterrupted operation of ‘highwall miner’ at the coal extraction faces, (b) safe extraction of the locked in coal between river and mine, (c) developing and designing safe work places for both man and machinery, (d) achieving targeted coal production as per production schedule, (e) effective drainage and utilization of mine water as per the action plan of mine. Thus, on account of seepage water any harm/damage to already deployed, ‘highwall miner’ is very remote and the coal wining operation at MOCP is safe. The mine planning can be done easily using estimated water quantities and mine faces can be kept dry during maximum period in a year.