To address the problem of adjacent pipeline deformation induced by underground excavation of metro stations, it is indicated by existing studies that soil strength decreases under unloading conditions. However, in engineering practice, little consideration is given to the influence of the actual excavation-induced unloading conditions on the strength properties of soils, by which an overestimation of soil strength and an underestimation of pipeline deformation may be caused. Taking underground excavation project of Yunnan Road Station on Nanjing Metro Line 5 as a case study, the actual stress–strain characteristics of the soils surrounding various types of pipelines were considered, and corresponding unloading stress path triaxial tests were designed, from which strength parameters that could faithfully reflect the soil unloading state were obtained. Based on the ABAQUS finite element platform, a zone-specific and stepwise dynamic assignment method for soil parameters was adopted, a three-dimensional numerical model that realistically captured soil unloading during the excavation process was established, and the influence of underground excavation on pipeline deformation was analyzed. The results showed that overlying pipelines were primarily affected by vertical unloading of the soil, and the settlement curve characterized by larger settlement in the middle and smaller settlement at the ends. Laterally passing pipelines were mainly influenced by lateral unloading of the excavation, and more pronounced differential settlement was observed. On this basis, the effects of factors including excavation sequence, pipeline burial depth and pipeline-station separation distance were further investigated, and the corresponding engineering control measures for pipeline deformation were proposed.

Local scour at the bottom of bridge piers further affects the stability of ice jams. In this study, the experimental study on the influence of local scour on the stability of ice jams at the pier was carried out, and the test conditions of different initial flow rates, different initial water depths and different pier diameters were selected to explore the influence of different factors on the stability of ice jams. The stresses and strains of ice jams near bridge piers under the influence of local scour were further discussed, and the discriminative equation for the stability state of ice jams was derived. Through the experimental data, the stability discrimination equation of ice jams under the influence of local scour at the pier was verified, and the results of ice jams stability discrimination equation are in good agreement with the experimental data. The study of the influence of local scour on the stability of ice jams at bridge piers can provide a theoretical basis and support for further exploration of the evolution of ice jams at bridge piers.

Inter-basin water diversion projects have profoundly altered the thermal boundary conditions of source reservoirs, reshaping the spatial redistribution of heat and the seasonal dynamics of heat storage and release. Efficiently utilizing the thermal potential of reservoirs can help mitigate winter freezing risks in long-distance water conveyance systems across high-latitude regions. Using the Danjiangkou Reservoir, the headwater source of the South-to-North Water Diversion Middle Route Project, as a case study, this study employs a three-dimensional EFDC hydrodynamic-thermal coupled model to simulate the spatiotemporal evolution of winter thermal conditions. The model performance was evaluated against observed temperature records, showing good agreement and high reliability, with RMSE = 0.53 degrees C and NSE = 0.97. On this basis, the analysis focuses on the inter-reservoir heat budget differences between the main (Han) and tributary (Dan) reservoirs, heat transfer processes, and the response of the Taocha headwork intake temperature under different operational scenarios, with the objective of developing a dual-objective "water-heat" regulation strategy. Results show that due to its riverine morphology, upstream cascade inflows, and elevated inflow temperatures, the Han reservoir exhibits strong heat-retention capacity, maintaining winter heat content about 20.5 & times; 1013 kJ higher than the Dan reservoir, continuously supplying compensatory heat. Winter heat transfer is driven by intake-induced hydrodynamics, with stratification intensity determining transport pathways and flow processes regulating compensatory fluxes. Heat-transfer efficiency is jointly constrained by water level and stratification: under low-level conditions, the unit-intake temperature-rise coefficient (epsilon) reaches 0.6 degrees C (100 m3 s-1)-1, declining to 0.4 degrees C (100 m3 s-1)-1 at high levels. The combined influence of intake discharge and water level controls both the process and magnitude of winter heat transfer. A coordinated operational framework-high water level for heat storage, high intake discharge for enhanced transfer, and low outflow for reduced heat loss-is proposed. Under this strategy, the Taocha headwork intake temperature increases by about 1.1 degrees C, demonstrating the reservoir's significant winter heat-supply potential. The findings reveal the dual role of source reservoirs in cold seasons as both water and heat sources, providing a scientific basis for winter thermal regulation and safe operation of inter-basin water diversion projects in cold regions.

Riverbank erosion is a common phenomenon in alluvial rivers and often leads to hydrogeological hazards such as bank collapse and soil loss. Compared with open-channel flow conditions, the mechanisms of bank erosion during ice-covered periods are more complex. Therefore, investigating riverbank slope stability under ice-covered conditions is essential for bank protection, riverbed evolution analysis, and river regulation in ice-affected rivers. In the present study, based on soil mechanics theory, a stability equation for cohesive riverbanks under ice-covered channel conditions is established. Key parameters are investigated, including the critical bank height ratio, riverbed scour depth, and lateral erosion distance under varying ice-cover thicknesses and stress conditions during the initial and stable freeze-up periods. The established equation is verified using river width data derived from satellite imagery and is applied to the Inner Mongolia reach of the Yellow River, yielding good agreement with observations. The results indicate that, compared with open-channel flow conditions, the presence of ice cover significantly intensifies riverbank erosion. Furthermore, during ice-covered periods, riverbank and riverbed scouring is more severe in the downstream section than in the upstream section of the Inner Mongolia Reach. Taking the Toudaoguai cross section as an example, under an ice cover thickness of 0.6 m and an ice stress of 50 kPa, the initial critical bank height ratio increases by 22.1%, the riverbed scour depth by 364.2%, and the river width by 332.6%. The results of this study provide a useful reference for river hydrological management in cold regions.

The occurrence of ice jams in rivers in cold regions during winter complicates the local scour process around spur dikes. In this study, laboratory experiments were conducted to investigate the effects of flow Froude number, ice-water flow ratio, the ratio of spur dike length to flume width, sediment median particle size, and other factors on the maximum scour depth around spur dikes, as well as the thickness distribution of ice jams around different spur dike configurations. The maximum scour depth around spur dikes under open flow and sheet-ice cover conditions was compared. The experimental results indicate that, compared with open flow conditions, the maximum scour depth around spur dikes under sheet-ice cover increases by 10-30%, while under ice jam conditions, it increases significantly by 150-200%. Under ice jam conditions, the maximum scour depth around spur dikes is positively correlated with the ice-water flow ratio and flow velocity, and negatively correlated with the median sediment particle size. Under open flow conditions, the maximum scour depth around spur dikes increases with an increasing ratio of spur dike length to flume width. In contrast, under ice jam conditions, the maximum scour depth initially decreases and then increases as the ratio of spur dike length to flume width increases. During the upstream progression of an ice jam, a critical flow Froude number exists at the (cross-section) CS where the spur dike is located, which is primarily influenced by the ratio of spur dike length to flume width, the ice-water flow ratio, flow velocity, and water depth.

In cold-region rivers, the formation of ice cover during winter markedly modifies the hydraulic conditions, leading to enhanced local scour around in-stream infrastructures such as bridge piers. To analyze the flow characteristics and maximum local scour depth around the pier under both open-channel and ice-covered conditions with varying roughness, both experimental methods and numerical simulations were employed in this study. The findings reveal that, under rough ice-covered flow conditions, the interaction of elevated bed shear stress and intensified turbulent kinetic energy contributes to an increased maximum scour depth around the pier. Under identical approaching flow conditions, when the ratio of ice cover roughness to bed roughness increases to 1.9, the increase in maximum local scour depth around the pier becomes less pronounced owing to the enhanced energy dissipation caused by the rough ice cover. A numerical model for local scour around the pier under open-channel flow and ice-covered flow conditions was developed by integrating the RNG k − ε turbulence model with the Meyer-Peter sediment transport equation. A new formula was developed to estimate the maximum local scour depth around bridge piers considering various ice cover roughness conditions. Comparison with existing formulas demonstrates that the proposed formula achieves the highest accuracy, offering a useful reference for the design of bridge foundations in ice-affected regions.

In cold regions, bridge piers in rivers can alter flow characteristics and influence the formation and evolution of ice jams, complicating the local scour around the piers and the distribution of ice jam thickness. This study, based on experiments conducted in an S-shaped flume, examines how the flow Froude number and the ice-water discharge ratio affect the local scour depth around tandem double piers and the ice jam thickness. The results reveal that, while a positive correlation exists between the flow Froude number and the scour depth under both open flow and ice-covered flow conditions, the relationship between the scour depth and the flow Froude number under ice-jammed flow conditions is considerably more complex. Due to the influence of the ice jam on scour depth, there exists a critical Froude number at which the relationship between the flow Froude number and scour depth changes. The results indicate that when the flow Froude number is below the critical value, the ice jam thickness decreases slightly, while the scour depth shows a positive correlation with the flow Froude number. When the flow Froude number reaches the critical Froude number, the scour depth peaks. When the flow Froude number exceeds the critical value, the ice jam thickness decreases significantly, and the scour depth becomes negatively correlated with the flow Froude number. Additionally, when the flow Froude number remains constant, an increase in the ice-water discharge ratio leads to a rise in ice jam thickness, which in turn causes the scour depth to increase.

River ice formation during the winter period is a common phenomenon for most rivers in the northern hemisphere. The combined effect of hydraulic, thermodynamic, and geometric boundary conditions results in a highly complex system when compared to open channel conditions, particularly in regard to ice cover and ice jams. These differences have a considerable impact on the evolution of river morphology, sediment transport, and the stability of hydraulic structures. The presence of ice cover and ice jam results in an increase in river channel roughness, which in turn changes the velocity and shear stress distribution in the riverbed. The present review summarizes the current state-of-the-art research on river ice, including field observation, experimental study, and numerical simulation. Finally, the review concludes with an overview of the current state of research in the field, accompanied by an analysis of the challenges that remain and suggestions for future research directions.

Ice jams, which are prevalent in rivers of cold regions, can escalate into severe flooding disasters. Understanding variations in ice jam thickness is crucial, generating significant scholarly interest in developing accurate computational methods. Current models primarily rely on mechanical equilibrium equations to estimate ice jam thickness, representing a significant advancement in theoretical research. However, these models often overlook critical factors such as the cohesion of ice jams and the distribution of equilibrium stress across the river’s width, which can undermine their accuracy. This study introduces an enhanced model that incorporates these aspects, thereby improving the mathematical rigor. Validated against empirical data from natural rivers, the proposed model demonstrates strong agreement with observed values. This research not only refines the theoretical framework for calculating ice jam thickness but also improves the prediction and management of ice jam evolution and related disasters in cold regions.

In winter, ice cover or ice jams frequently form in rivers in cold regions, causing the flow to shift from open flow to ice-covered flow. As the ice jam thickness changes, the maximum flow velocity beneath it shifts further toward the channel bed, potentially intensifying erosion of the riverbed and damaging hydraulic structures. On the other side, the formation of ice cover or jams can raise upstream water levels, and in severe cases, may lead to flooding. Therefore, to predict water levels and mitigate potential flooding, accurately calculating ice jam thickness is crucial. Currently, formulas for calculating ice jam thickness are derived from the mechanical equilibrium equation of ice jams. These formulas often simplify the river channel to a rectangular section. In this study, a new approach to calculating ice jam thickness is proposed by coupling the water flow energy equation with the mechanical equilibrium equation of ice jams. The calculation formula of the ice jam thickness is verified using the measured data from the long-distance water conveyance channel of the middle route of the South-to-North Water Diversion Project from 2019 to 2020. The calculation result using this proposed formula shows strong agreement with the measured data, which provides a new method for the calculation and simulation analysis of the ice jam thickness in channels in winter.

Accurate prediction of structural displacements in hydropower stations is essential for the safety and long-term stability of large-scale water-related infrastructure. To address this challenge, this study proposes an AI-assisted monitoring framework that integrates Convolutional Neural Networks (CNNs) for spatial feature extraction with Gated Recurrent Units (GRUs) for temporal sequence modeling. The framework leverages long-sequence prototype monitoring data, including reservoir level, temperature, and displacement, to capture complex spatiotemporal interactions between environmental conditions and dam behavior. A parameter optimization strategy is further incorporated to refine the model’s architecture and hyperparameters. Experimental evaluations on real-world hydropower station datasets demonstrate that the proposed CNN–GRU model outperforms conventional statistical and machine learning methods, achieving an average determination coefficient of R2 = 0.9582 with substantially reduced prediction errors (RMSE = 4.1121, MAE = 3.1786, MAPE = 3.1061). Both qualitative and quantitative analyses confirm that CNN–GRU not only provides stable predictions across multiple monitoring points but also effectively captures sudden deformation fluctuations. These results underscore the potential of the proposed AI-assisted framework as a robust and reliable tool for intelligent monitoring, safety assessment, and early warning in large-scale hydropower facilities.

Through laboratory experiments in an S-shaped channel, this study analyzes how the flow Froude number, the ratio of ice-to-flow rate, pier spacing-diameter ratio, and bed material median grain size influence scour depth around side-by-side double piers under ice-jammed flow conditions. Unlike the development of a scour hole around a bridge pier in a straight channel, where the scour depth increases with the flow Froude number under ice-covered conditions, this study reveals that in an S-shaped channel, scour depth increases with the flow Froude number near the convex bank pier and decreases near the concave bank counterpart. Irrespective of ice conditions, a higher ratio of pier spacing-diameter correlates with augmented scour depth at the convex bank and diminished scour at the concave bank. As the ice-to-flow rate ratio increases, the ice jam thickness in the S-shaped channel also increases, leading to a significant decrease in the flow area and resulting in deeper scour holes around the piers. Equations have been developed to calculate the maximum scour depth around side-by-side double piers positioned in an S-shaped channel with ice-jammed flow.

In winter, rivers in cold regions often experience flood disasters resulted from ice jams or ice dams. Investigations of the variation of ice jam thickness and water level during an ice jammed period are not only a practical need for ice prevention to avoid disaster and plan water resource, but also essential for the development of any mathematical model for predicting the evolution of ice jam. So far, some equations based on the energy equation have been proposed to describe the relationship between ice jam thickness and water level. However, in the derivation of these equations, the local head loss coefficient at the ice jam head and the riverbed slope factor were neglected. Obviously, those reported equations cannot be used to preciously describe the flow energy equation with ice jams and accurately calculate the ice jam thickness and water level. In the present study, a more comprehensive theoretical model for hydraulic calculation of ice jam thickness has been derived by considering important and essential factors including riverbed slope and local head loss coefficient at the ice jam head. Furthermore, based on the data collected from laboratory experiments of ice jam accumulation, the local head loss coefficient at the ice jam head has been calculated, and the empirical equation for calculating the local head loss coefficient has been established by considering flow Froude number and the ratio of ice discharge to flow discharge. The results of this study not only provide a new reference for calculating ice jam thickness and water level, but also present a theoretical basis for accurate CFD simulation of ice jams.

Local scour often causes pier instability; however, the characteristics and mechanism of downflow, representing one of the crucial flow structures, are still unclear. In this paper, the interaction between the downflow and the horseshoe vortex system and the role of the downflow under clear-water local scour conditions are discussed, based on the stress distribution obtained via experiments and simulations. In the present experiment, more accurate data are measured by installing suitable sensors on 3D-printed models that reproduce the scour hole conditions at various times. The obtained results reveal that the downflow exhibits a strong interaction with the horseshoe vortex system. From the perspective of flow structures, the flow structures collide and rub against each other, which weakens the effect of the downflow. From the perspective of energy transfer, the horseshoe vortex system absorbs the energy carried by the downflow to develop and reduce the energy introduced into the sediment. In addition, shear stress is a crucial factor in maintaining a high tangent slope. When the shear stress is down to a minimum and is stable, the tangent slope rises with the growth of the pressure stress, which means that the downflow is able to promote scour depth development.

In winter, the water transfer channel of the Middle Route of South-to-North Water Transfer Project (MR-StNWTP) in China always encounters ice problems. The preciously simulation and prediction of water temperature is essential for analyzing the ice condition, which is important for the safety control of the water transfer channel in winter. Due to the difference of specific heat between water and air, when the air temperature rises and falls dramatically, the range of change of water temperature is relatively small and has a lag, which often affects the accuracy of simulation and prediction of water temperature based on air temperature. In the present study, a new approach for simulating and predicting water temperature in water transfer channels in winter has been proposed. By coupling the neural network theory to equations describing water temperature, a model has been developed for predicting water temperature. The temperature data of prototype observations in winter are preprocessed through the wavelet decomposition and noise reduction. Then, the wavelet soft threshold denoising method is used to eliminate the fluctuation of certain temperature data of prototype observations, and the corresponding water temperature is calculated afterward. Compared to calculation results using both general neural network and multiple regression approaches, the calculation results using the proposed model agree well with those of prototype measurements and can effectively improve the accuracy of prediction of water temperature.

The stability of bridge foundations is affected by local scour, and the formation of ice jams exacerbates local scour around bridge piers. These processes, particularly the evolution of ice jams and local scour around piers, are more complex in curved sections than in straight sections. This study, based on experiments in an S-shaped channel, investigates how various factors—the flow Froude number, ice–water discharge rate, median particle diameter, pier spacing, and pier diameter—affect the maximum local scour depth around double piers in tandem and the distribution of ice jam thickness. The results indicate that under ice-jammed flow conditions, the maximum local scour depth around double piers in tandem is positively correlated with the ice–water discharge rate, pier spacing, and pier diameter and negatively correlated with median particle diameter. The maximum local scour depth is positively correlated with the flow Froude number when it ranges from 0.1 to 0.114, peaking at 0.114. Above this value, the correlation becomes negative. In curved channels, the arrangement of double piers in tandem substantially influences ice jam thickness distribution, with increases in pier diameter and spacing directly correlating with greater ice jam thickness at each cross-section. Furthermore, ice jam thickness is responsive to flow conditions, escalating with higher ice–water discharge rates and decreasing flow Froude numbers.

In view of operation characteristics of concrete dams in cold regions, comprehensively considering the impact of overwintering layer, cold wave and freeze-thaw and the representativeness of various evaluation indexes with in-situ monitoring data, an evaluation index system affecting the structural behavior of concrete dams in cold regions is constructed. Based on typical small probability method and analytic hierarchy process, the unequal interval division method of evaluation index grade is proposed. Based on game theory, a combined subjective and objective weighting method of evaluation indexes is established. In order to solve the problem of fuzziness and randomness of evaluation indexes, an improved interval intuitionistic fuzzy set method is adopted for a comprehensive evaluation method for structural behavior of concrete dams in cold regions. The effectiveness of the proposed method is verified by practical engineering application.

This study divided the total storage potential in a natural channel into the ice production volume and the water storage capacity volume. Thermal factors, hydraulic processes, topography, and ice formation were selected to derive a discriminant equation for freeze-up and break-up conditions in the Inner Mongolia Reach of the Yellow River. The trends observed from data for the freeze-up dates, break-up dates, and total frozen days from 2017 to 2020 conform to the principle that the river is gradually frozen from the downstream to the upstream and later thawed from the upstream to the downstream. The number of frozen days in the downstream is greater than in the upstream. Results indicate that freeze-up typically occurs when the proportion of ice in the channel is relatively high. Higher temperatures and greater discharges are required to facilitate the break-up of the river when the equilibrium ice thickness is greater. This study can provide a theoretical basis and framework for establishing an accurate freeze-up and break-up forecast model to prevent and mitigate ice-induced disasters.

Ice jam, a unique hydrological phenomenon of rivers in cold regions, is a major cause of ice flooding. There are many different kinds of damage that can result from ice jams: e.g., blockage of the water flow, rising water levels that can flood farmland and dwellings, damage to hydraulic structures, and interruptions to shipping. The formation of an ice jam is influenced by various factors associated with different fields of study. The accumulation of an ice jam is thus a complex process worth investigating. However, previous studies seldom take account of ice discharge factors. This study carries out 29 tests on the accumulation of an ice jam, and discovers four kinds of phenomena: inlet ice that fails to submerge (case 1); thickening ice from upstream to downstream (case 2); thickening ice from downstream to upstream (case 3); and failure to form an ice jam (case 4). Two typical examples are used to detail cases 2 and 3. The authors suggest differentiating between the two cases using the longitudinal boundary line running through the point of the Froude number (Fr) = 0.119. Furthermore, the authors analyze the phenomena that make it difficult for an ice jam to form and suggest using the critical discriminant line to distinguish between cases 3 and 4. Combined with the longitudinal boundary line, a partition result diagram of the different accumulation features of ice jams is presented to differentiate between the four modes of accumulation of ice jams.

This study proposes a novel nonlinear model updating approach based on an improved generative adversarial network (GAN). In the improved GAN, a convolutional neural network (CNN) surrogate model is added to the discriminator network to enhance the capability of the GAN to learn the complex mapping relationship between vibration responses and nonlinear model parameters. To avoid the gradient disappearance present in the traditional GAN, a combined objective function is added to the improved GAN model. In the network training process, the instantaneous amplitudes of the decomposed accelerations are extracted as input samples and the nonlinear model parameters are defined as the GAN output. When the improved GAN is trained, the trained network model is capable of estimating the nonlinear model parameters based on measured instantaneous acceleration amplitudes. To confirm the feasibility of the improved GAN for structural nonlinear model updating, a steel-concrete hybrid bridge tower subjected to seismic excitation is numerically simulated and the effects of different numbers of data points and noise levels are studied. Furthermore, the identification accuracy of the improved GAN is compared with the updated results. For experimental applications, the shake table test of a scaled steel-concrete hybrid bridge tower subjected to seismic excitations is employed to confirm the effectiveness of the proposed nonlinear model updating method. Both numerical and experimental results demonstrate that the improved GAN model is reliable and effective for the nonlinear model updating of structures subjected to seismic excitation.