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The large deformation and strong rheological characteristics of the underground rock body under complex geological conditions have led to the failure of the support system and even the instability of tunnels from time to time. Based on the theory of groundwater seepage, the elastic solution of the mechanical model of the tunnel anchorage support system under seepage is solved, which reveals the influence of seepage on the peripheral rock and the support parameters of the anchorage support system; the viscoelastic solution is solved according to the corresponding principle of elasticity-viscoelasticity, which analyses the influence of seepage on the rheological process of the anchorage support system; and the model is simulated with the help of finite element software, which analyses the agreement and discrepancy of the numerical solution and the theoretical solution. The results show that the analytical and numerical solutions are basically consistent. This study can provide important guidance for controlling long-term stability of water-rich tunnel rocks., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

In the present study, three machine learning methods were applied for predicting seepage flow through embankment dams, namely (i) support vector regression (SVR), relevance vector machine (RVM), and Gaussian process regression (GPR). The three models were developed using seepage flow (Q: L/mn) and piezometer level (Z:m) measured at several piezometers placed in the corps body of the dam. The proposed models were calibrated and validated using a separate subset. Models evaluation and comparison was successfully achieved using various performances metrics, i.e., coefficient of correlation (R), Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), and mean absolute error (MAE). Experimental results showed that the proposed models are a good alternative to the in situ measured and contributed significantly in overcoming the case of missing measured seepage flow. The best performances were obtained using the RVM model with R and NSE values of ≈0.909 and ≈0.823, followed by the GPR model with R and NSE values of ≈0.891 and ≈0.767, while the SVR model was ranked as the poorest one exhibiting R and NSE values of ≈0.780 and ≈0.600, respectively. While, a growing number of investigations have focused on testing machine learning in terms of their feasibilities to accurately describe seepage flow, as well as providing important support to our understanding of the factors affecting its fluctuation, the present work was demonstrated that the combination of a wide range of variables can help in simulating seepage flow, and enhance their sensitivity which has help in developing new algorithms., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Snowmelt erosion is an important way of soil loss in Chinese Mollisol region. However, little is known about the effects of seepage flow and soil thaw depth on hillslope snowmelt runoff erosion. An indoor simulated experiment was conducted to analyze the impacts of seepage flow and soil thaw depth on hillslope snowmelt erosion. There were two snowmelt flow rates (1 and 4 L·min -1 ), two soil thaw depths (5 and 10 cm), and two near-surface hydrological conditions (with and without seepage flow). The results showed that hillslope runoff depth and soil erosion amount in the treatment with seepage flow were 1.1 to 1.2 times and 1.3 to 1.9 times of those in the treatment without seepage flow, respectively. Under two snowmelt flow rates, when soil thaw depth increased from 5 cm to 10 cm, hillslope runoff depth and soil erosion amount increased by 10.0% to 13.5% and 15.4% to 37.1% in the treatment without seepage flow, respectively. In the treatment with seepage flow, when soil thaw depth shifted from 5 cm to 10 cm, hillslope runoff depth increased by 6.5% to 8.5%, and soil erosion amount remained stable. Moreover, hillslope rill development was comprehensively influenced by seepage flow, soil thaw depth, and snowmelt flow rate, with rill erosion amount occupying more than 72% of hillslope snowmelt erosion amount. Compared with the treatment without seepage flow, flow velocity and shear stress under the treatment with seepage flow increased by 20.3% to 23.2% and 37.0% to 51.3%, respectively; but Darcy-Weisbach friction coefficient reduced by 9.0% to 21.4%, which caused an increase of hillslope snowmelt erosion. In addition, seepage flow enhanced rill development, which caused rill erosion amount to increase by 43.6% to 69.9% compared with the treatment without seepage flow, and it further resulted in the increase of hillslope snowmelt erosion amount. The main reason for soil thaw depth enhancing hillslope snowmelt erosion amount under the treatment without seepage flow was that both sloping runoff erosivity and erodible materials increased with increasing soil thaw depth. Furthermore, soil thaw depth had a significant impact on hillslope rill morphology development under the treatment with seepage flow. Rill widening process was dominated when soil thaw depth was 5 cm, whereas rill incision process was dominant when soil thaw depth was 10 cm. This study could improve the understanding of hillslope snowmelt erosion mechanism in Chinese Mollisol region and provide theoretical guidance for the development of water erosion model.

Numerical study is carried out to analyse the behaviour of cut off walls in sandy soil, under constant differential pressure head, by varying its location from upstream end to downstream end. The deformation and bending moment in cut off wall are at their lowest magnitude when the cut off wall is positioned at upstream end. The cut off wall is subjected to second lowest deformation, when it is positioned at downstream end. The maximum deformation occurs, when the cut off wall is positioned at 0.60 times the total width of diversion dam from upstream end. The seepage rate in the diversion dam is highest when the cut off wall is positioned at centre of the diversion dam. The seepage rate in the diversion dam is having direct relation with the maximum displacement and maximum bending moment. The seepage force found to be more predominant than the pressure gradient and active pore pressure variations in deforming the cut off walls of diversion dams.