Sediment Model Research Articles

Sediment Simulation Using Multi Layer Perceptron (MLP), Co-Active Neuro-Fuzzy Inference System (CANFIS) and Multiple Linear Regression Tecniques (MLR) for Hurdag Watershed

Sediment modeling plays a crucial role in sustainable water resources planning, development, and management. Techniques like the Multilayer Perceptron (MLP), Co-active Neuro-Fuzzy Inference System (CANFIS), and Multiple Linear Regression (MLR) have proven effective for sediment modeling and forecasting. This study aimed to develop and assess the applicability of MLP, CANFIS, and MLR models by training and testing them during the monsoon season (June to September) for the Hurdag watershed in the Damodar-Barakar basin, located in Hazaribagh district, Jharkhand, India. Daily rainfall, runoff (or streamflow), and sediment concentration data from 1997 to 2006 were used, with the data split into two sets: training set (1997–2004) and a testing set (2005–2006). The analysis was conducted using NeuroSolution 5.0 software and Microsoft Excel for performance evaluation indices. The best input combinations for sediment yield simulation were identified, and 10 optimal models were selected from 31 different input combinations. These input combinations were applied to the network for training using the back propagation algorithm for MLP and Gaussian and generalized bell membership functions for CANFIS models. Multiple networks were trained individually, with the most accurate predictions during testing being chosen as the best models. The models’ performance was evaluated using statistical indices such as root mean squared error (RMSE), coefficient of efficiency (CE), and correlation coefficient (r). The results showed that MLP and CANFIS models performed best in predicting sediment concentration for the Hurdag watershed, whereas MLR models showed poor performance for the given dataset. Specifically, sediment concentration for the current day could be modeled using current day rainfall and runoff data (MLP-7), while runoff could be simulated using the previous day's rainfall data (MLP-2).

Holocene aeolian-fluvial interactions patterns and their response to climate changes in the Paiku Co basin, Southern Tibetan Plateau

Aeolian-fluvial processes are crucial in shaping landforms. Despite the advancements in understanding the sedimentary processes of aeolian-fluvial interactions, the sedimentary patterns of these interactions are complex in spatiotemporal scale, and the records of Holocene small-scale aeolian-fluvial interaction sedimentary is insufficient, especially in the Tibetan Plateau region. Therefore, this study focuses on analyzing the sedimentary patterns of aeolian-fluvial interactions and their response to climate change in the Paiku Co basin of the southern Tibetan Plateau (TP). Through the examination of aeolian-fluvial sequences, Optically Stimulated Luminescence (OSL) dating is utilized to establish a chronological framework. Furthermore, proxy indices are explored to identify potential sediment models and their reactions to climate change. The findings indicate that fluvial activity predominated during a relatively warm and wet period around 5.1–4.6 ka, while thicker aeolian sands accumulated extensively during 4.6–4.1 ka as the climate transitioned to cold and dry conditions. On a millennial scale, the aeolian-fluvial interaction sedimentation is characterized by alternating deposition of clay layers and medium to fine sand. This sedimentation pattern is predominantly influenced by climate change. Overall, the findings shed light on the complex coupling between aeolian and fluvial processes in response to past climate changes, which has important implications for understanding the landscape evolution and environmental changes in this sensitive high-altitude region.

Kernel-Based Versus Tree-Based Data-Driven Models: On Applying Suspended Sediment Load Estimation

River sediment load estimation poses a critical challenge for water engineers due to its complex and nonlinear hydrological processes. This study assessed the amount of suspended sediment at the Bagh-e-Kalayeh hydrometric station on the Alamut River in the Qazvin province of Iran using two hydrological and meteorological variables, including discharge and rainfall, by considering three scenarios (discharge, discharge + monthly rainfall, and discharge + monthly rainfall + daily rainfall). For modeling, kernel-based data-driven methods, including Gaussian process regression (GPR) and support vector regression (SVR), and tree models, including the M5 tree, random forest (RF), random tree (RT), extra trees, reduced error pruning tree (REPT), and multi-search methods, were used. The results showed that the best performance was achieved by the SVR, with r = 0.948, Wilmot index = 0.965, and RMSE = 0.011 in the first scenario (only discharge). Discharge had the most significant impact on sediment estimation compared to rainfall. It was determined that the suspended sediment load in the Alamut River can be successfully estimated by the SVR method, where only the discharge was used as the input parameter. Additionally, the results indicated that given its characteristics and inherent features, the multi-search method can be used as a complementary approach in sediment modeling, especially in situations where the data volume is not extensive.

A meshless model for three-dimensional direct numerical simulation of local scour around cylinder bridge foundation

A meshless local scour model for cylinder bridge foundation based on the smoothed particle hydrodynamics (SPH) method is proposed in this paper. Differing from the traditional Eulerian mesh model used for monopile local scour, it overcomes the high requirements of mesh quality and density for capturing large deformations at the fluid interface. Unlike the transient sediment erosion SPH model used for dam-break, sediment flushing, and water jet, the meshless approach is innovatively applied to the continuous simulation of bridge local scour under steady flow conditions. The present SPH model is established based on the SPH multi-phase fluid model, integrating a classical fluid model combined with numerical stabilization algorithms to govern water particle motion and a sediment model from Zhang et al. (2024) to govern sediment evolution, and tests a new scheme for boundary treatment in the model based on DualSPHysics. Furthermore, a novel scour visualization method that aims at extracting both visible and actual bed surfaces from discrete particles is proposed. The model is validated through comparison with rigid bed and live bed experiments, demonstrating favorable agreement in terms of flow and scour simulation. Importantly, the model results reveal a discrepancy between the elevation of the post-scour visible bed surface derived from the conventional Eulerian mesh model and experimental data, compared to the actual bed surface unaffected by water flow erosion. This indicates the necessity for incorporating a safety margin in foundation design when utilizing experimental results to determine the maximum scour depth.

Research on the shear stress and microscopic deformation mechanism of deep sea sediments under the action of tracked miner

The traction force of the tracked miner is primarily determined by the shear characteristics of deep-sea sediments. The influence of different parameters on the shear characteristics of deep-sea sediments and the particles change law of the soil–track interface are discussed. By constructing the relationship between the particles horizontal displacement and residual shear strength, a novel shear rheological damage model of deep-sea sediments considering the influence of grounding pressure is proposed, and the microscopic mechanism of shear displacement of deep-sea sediments is explained. The results show that the peak shear strength and residual shear strength increase significantly with the increase of grounding pressure, track length, grouser height and shear speed. Moreover, the particles within the soil–track interface move along the lower right of the vehicle operating direction during the shearing process under different working conditions, the change of particle spacing shows a non-linear trend, and a quantitative equation for the horizontal deformation of soil–track interface under the experimental conditions is constructed. Additionally, the new shear model has a high level of accuracy in fitting with the experimental data, the internal particle migration changes on the soil–track interface can be divided into four characteristics: compaction, failure, deformation and translation.

Response of tenuous clay-polysaccharide flocs to hydrodynamic shearing

The response of suspended tenuous clay-polysaccharide flocs to hydrodynamic shearing was investigated in the laboratory via particle size analyses to understand the molecular-scale interactions between clay minerals and polysaccharides and their hydrodynamic behavior such as size kinetics, re-flocculation/breakdown, and shear strengths of the hybrid flocs. While the studied suspensions had a fixed clay concentration of 0.4 g/L, an array of other parameters was varied to reflect the complexity of clay-polysaccharide systems, including four types of clay minerals with varying layer charges and swellability (i.e., kaolinite, illite, and sodium- (Na-) and calcium- (Ca-) montmorillonites), two exopolymers of dissimilar polarities (i.e., xanthan and guar), six polysaccharide (P) to clay (C) weight ratios (i.e., P/C = 0, 1, 2, 5, 10, and 20 wt%), and three hydrodynamic shearing rates of 187, 429, and 1,100 1/s (i.e., corresponding to laminar, transitional, and turbulent flows, respectively). Results show that the clay-polysaccharide floc sizes are sensitive to the shear stress and also vary with different clay-polysaccharide systems. Four discrete particle groups were identified by statistical analyses, consisting of primary particle (PP), flocculi (FL), microfloc (MiF), and macrofloc (MaF), which exhibit distinct stabilities to shearing. The MaF is much weaker than MiF and can easily breakdown, as indicated by the decrease in MaF fraction with increasing shearing, while the MiF is the dominant particle group in transitional and turbulent flows. The fractions of PP and FL generally increase with shearing rate. Based on floc survivability in different flow conditions, the MaF’s upper and lower bound shear strengths were estimated to be 0.95 and 0.17 Pa, respectively. The strongest MaF with a maximum shear strength of 0.95 Pa is formed in the clay-guar suspensions at a P/C of 10 wt%. Anionic xanthan only forms flocs with kaolinite with little surface charges, but cannot induce clay-polysaccharide flocs for illite and Ca/Na-montmorillonite with negative surface charges due to electrostatic repulsion. In contrast, neutral guar generates flocs with all 4 clay minerals due to the formation of hydrogen bonds, and MaF compounds usually are absent in turbulent flow (except kaolinite with a small fraction of MaF). These results further demonstrate the essential role of polysaccharide’s polarity in dictating the flocculation dynamics, and, hence, sediment transport behavior. Practical implications of the findings are discussed in terms of the emerging technological applications of clay-polymer systems as well as the transport and modeling of natural aquatic cohesive sediment in biofilm-bearing waters.

Comment on: "Anomalous reflection from a two-layered marine sediment" [J. Acoust. Soc. Am. 155, 1285-1296 (2024)] (L).

Buckingham [(2024). J. Acoust. Soc. Am. 155, 1285-1296] analyzed the dependence of the reflection coefficient on the grazing angle in two-layer marine sediment model. The upper layer in his model consists of a fine-grained material (mud), while seawater and the basement below the mud layer are treated as homogeneous halfspaces. Buckingham's analyses revealed several narrow spikes in this dependence that appeared only in the presence of a sound velocity gradient in the mud layer, a phenomenon he called acoustic glint. His derivation was accomplished for certain specific dependencies of the sound velocity on the depth. Surprisingly, the authors appear to reach the conclusion that for a slightly different vertical sound speed profile in the mud layer the spikes are no longer present in the dependence of the reflection coefficient on the grazing angle. More precisely, the same problem is examined in this letter for the case of an n2-linear layer (often called Airy medium). Acoustic glint effect is therefore very sensitive to the exact parametrization of the mud layer.

Incorporating memory effect into a fractional stochastic diffusion particle tracking model for suspended sediment using Malliavin-Calculus-based fractional Brownian Motion

This study aims to develop a Fractional Stochastic Diffusion Particle Tracking Model (FSDPTM) to illustrate suspended sediment’s long-term dependence (LTD) trajectories immersed in fully developed turbulent flow. Carried by eddies in the open channel, individual suspended sediment behavior exhibits dependence on its past increments. The Fractional Brownian Motion (FBM) is incorporated into the FSDPTM to account for the randomness of turbulent flow and to include the time-dependent increments as a memory effect. Additionally, to enhance the capacity for differentiating FBM, this study introduces Malliavin Calculus, the stochastic calculus of variation, to construct the square -differentiable FBM. For the numerical realizations of square differentiable FBM, the integration of fractional Gaussian white noise and Wiener–Ito Chaos expansion with the Hermite sequence is employed. The FSDPTM offers probabilistic LTD trajectories as solutions to the Ito-type Langevin equation. It also provides particle velocity, acceleration, and ensemble statistics, collectively demonstrating the application of FBM to sediment transport modeling. In conclusion, the key feature of the FSDPTM is its ability to translate LTD derived from FBM into the trajectory of suspended sediment particles in fully developed turbulent flow. Additionally, it expands the solutions from non-differentiable to square-differentiable stochastic processes.

Observations of Flocs in an Estuary and Implications for Computation of Settling Velocity

AbstractThe settling velocity (ws) in estuarine environments can impact whether a region is eroding or accreting sediment on the bed, yet determining this rate can be an indirect process requiring a number of assumptions. Accurate determination of ws is especially needed for numerical models to reproduce observed sediment concentrations at the appropriate timescale. We collected information on suspended sediment flocculation at a channel site (13 m deep) and a shallows site (4 m deep) within South San Francisco Estuary, alongside timeseries of flow, wave statistics, turbulent shear, and bottle samples analyzed for both ws and particle size. Using the measurements of floc size and settling velocity, we performed a sensitivity analysis on the unknown parameters in the general explicit formula for settling velocity. The collected particle size distribution data show that multiple classes of flocs are present; these are characterized as flocculi, microflocs, and macroflocs. We show that ws of flocculi is closest to ws for the full distribution. The determined parameter values lead to near‐bed mass‐weighted settling velocities (standard deviation) of 1.18 (0.55) and 0.22 (0.15) mm/s at the channel and shallows sites, respectively. Modeling efforts can use this work to help select an appropriate sediment model and parameter values.

The sources and transport model of deep-sea sediment in the Southwest Sub-basin of the South China Sea

The sources and transport model of deep-sea sediment in the Southwest Sub-basin of the South China Sea

Erosion under drawdown flushing with the SPH method

This study investigates the effects of drawdown flushing in hydraulic structures on sediment transport and morphological changes within and around reservoirs. Utilizing the Smoothed Particle Hydrodynamics (SPH) method, the research focuses on local erosion induced by drawdown flushing and examines the interaction between water and sediment. To validate sediment behavior, we analyzed a granular dam-break model using three rheological models: Herschel-Bulkley (H–B), Bingham, and μ(I). Two drawdown flushing scenarios are explored, considering mobile bed conditions at the reservoir's inlet and outlet. The study area is categorized into three zones: water, sediment, and the interface between water and sediment, with the μ(I) rheological model applied to the sediment portion. Within the interaction zone of sediment and water, the Shields parameter is defined based on Julien's relations to determine the yield stress of sediments. This value is then incorporated into the H–B model for sediment in this specific zone. Additionally, the drag force is introduced into the momentum equation within this zone. The study's findings are rigorously validated against existing numerical and experimental studies, affirming the credibility of the modeling approach. This research provides valuable insights into the complex dynamics of sediment transport during drawdown flushing in hydraulic structures.

An improved analytical model of effective thermal conductivity for hydrate-bearing sediments during elastic-plastic deformation and local thermal stimulation

As one of the crucial thermal properties controlling the dissociation of natural gas hydrate (NGH), effective thermal conductivity (ETC) should be precisely determined to improve the efficiency of NGH exploitation. But so far, most existing analytical ETC models of hydrate-bearing sediments could not accurately characterize the evolution of ETC. In this paper, an improved analytical model is derived for quantitatively revealing physical relations between ETC and various influencing factors during elastic-plastic deformation and local thermal stimulation processes, including hydrate saturation change, complex pore structures evolution, and hydrate occurrence patterns transition. The effectiveness of the proposed model is validated against available experimental data and compared with other existing models, then effects of various critical parameters on ETC are investigated. Results show that the porosity of hydrate-bearing sediments is accurately predicted during both loading and unloading processes, and the calculated ETC values under various conditions (effective stress, hydrate saturation, and temperature) are satisfactory with the test data. Contributions of elastic deformation and plastic deformation to ETC increments are quantitatively obtained. It is noteworthy that this proposed model is significant to reveal the evolution mechanisms of ETC, helping to accurately predict gas production and offer better plans for efficient NGH exploitations.

Simulating liquefaction-induced resuspension flux in a sediment transport model

Wave-induced liquefaction is a geological hazard under the action of cyclic wave load on seabed. Liquefaction influences the suspended sediment concentration (SSC), which is essential for sediment dynamics and marine water quality. Till now, the identification of liquefaction state and the effect of liquefaction on SSC have not been sufficiently accounted for in the sediment model. In this study, we introduced a method for simulating the liquefaction-induced resuspension flux into an ocean model. We then simulated a storm north of the Yellow River Delta, China, and validated the results using observational data, including significant wave heights, water levels, excess pore water pressures, and SSCs. The liquefaction areas were mainly distributed in coastal zones with water depths less than 12 m, and the simulated maximum potential soil liquefaction depth was 1.39 m. The liquefaction-induced SSC was separated from the total SSC of both liquefaction- and shear-induced SSCs by the model, yielding a maximum liquefaction-induced SSC of 1.07 kg·m−3. The simulated maximum proportion of liquefaction-induced SSC was 26.2% in regions with water depths of 6–12 m, with a maximum significant wave height of 3.4 m along the 12 m depth contour. The erosion zone at water depths of 8–12 m was reproduced by the model. Within 52.5 h of the storm, the maximum erosion thickness along the 10 m depth contour was enhanced by 33.9%. The model is applicable in the prediction of liquefaction, and provides a new method to simulate the SSC and seabed erosion influenced by liquefaction. Model results show that liquefaction has significant effects on SSC and seabed erosion in the coastal area with depth of 6–12 m. The validity of this method is confined to certain conditions, including a fully saturated seabed exhibiting homogeneity and isotropic properties, small liquefaction depth, residual liquefaction dominating the development of pore pressures, no influence by structures, and the sediment composed of silt and mud that experiences frequent wave-induced liquefaction.

Modeling soil erosion dynamic processes along hillslopes with vegetation impact across different land uses on the Loess Plateau of China

Developing a process-based soil erosion model that comprehensively considers the effects of vegetation is complex but crucial for evaluating sediment reduction during vegetation restoration. Current understanding of the effect of vegetation on sediment reduction along hillslopes across different land uses is limited. In this paper, we developed a dynamic model of hillslope erosion that integrates the effects of vegetation on soil detachability and hydrodynamics (VED) based on the feedback mechanism between soil detachment and sediment transport. The VED was calibrated and validated with runoff plot data for woodland, grassland, and farmland in the Wuding, Yan, Jing and Wei Rivers of the Loess Plateau in China. Unified baseline parameters and decay coefficients of vegetation were obtained. The model validation results indicated that the coefficient of determination, Nash–Sutcliffe simulation efficiency and relative error ranged from 0.59 to 0.99, 0.56 to 0.90, and −45.99 % to 46.36 %, respectively. The decay coefficients for soil detachment capacity (Φ), sediment transport capacity (Tc), and the sediment reduction effect of vegetation exhibited the following order: woodland > grassland > farmland. Compared with VED, existing process-based soil erosion models failed to effectively characterize the influence of vegetation on Φ and Tc on the Loess Plateau, with differences of several orders of magnitude. The individual contributions of runoff, soil detachability, and hydrodynamics with vegetation impact on sediment yield were quantified by VED. The contribution rates of vegetation to sediment reduction decreased gradually with increasing slope length because the soil detachment capacity of bare slopes exceeded that of vegetated slopes, resulting in a faster increase in sediment yield. The contribution rates of vegetation to sediment reduction for woodland, grassland, and farmland with 20 %–60 % vegetation covers were 66.75 %–99.95 %, 57.43 %–99.63 %, and 27.91 %–88.63 % in the boundary conditions of this study, respectively. The results reveal the potential for integrating VED into other distributed watershed hydrological and sediment models to assess the effects of vegetation restoration on sediment reduction at a watershed scale.

Evaluating the comprehensive flood impact assessment on the head reach of the Chiniot dam project

The major sources of surface water available to Pakistan are perennial flows of the River Indus and its tributaries i.e. Jhelum and Chenab Rivers. The creation of a reservoir of 0.9 MAF Capacity will cause the water level to rise and reduction in flow velocity on the Chenab River upstream of Chiniot Bridge. Consequently, it will cause sediment deposition which would further increase the water level due to the raised river bed level by deposited sediments. To study this storage, the reservoir has been modelled in HEC-RAS software to assess pre-dam and post-dam scenarios to simulate different conditions of river flow for water surface profile and sediment delta modelling of the reservoir reach, using historical daily water and sediment flows (1985–2022). The results of flood routing showed that the reservoir has attenuated the peak flood volume with safe releases at downstream side with proper operation of spillway gates. The average sediment inflow in the reservoir is worked out to be 38.4 metric tons. The results of sediment modelling and reservoir flood management indicated that after every 05 years of normal reservoir operation, reservoir flushing is recommended. Without sediment flushing, the river bed would be further raised beyond 189.0 m due to incoming sediment, resulting in further rise of water level up to 192.8 m which is the existing crest level of upstream training works of Talibwala Motorway Bridge.

Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations

Suspended sediment concentration (SSC) is a crucial indicator for aquatic ecosystems and reservoir management but is challenging to predict at large scales. It is unclear whether SSC is predictable using macroscopic environmental attributes and forcings. This study tested the feasibility of deep-network-based models to predict daily SSC at basin outlets given only basin-averaged forcings, readily-available physiographic attributes, and streamflow (from observation or model). We trained long short-term memory (LSTM) deep networks both separately for each of the 377 sites across the conterminous United States (CONUS) (termed “local models”), and on all the sites collectively (Whole-CONUS). The Whole-CONUS and local models presented median coefficient of determination (R2) values of 0.63 and 0.52, respectively. This comparison agrees with previously acknowledged “data synergy” effects for LSTM models, where more data from more sites can help improve predictions overall. Furthermore, the continental-scale analysis provided a wealth of insights about SSC patterns. Both local and Whole-CONUS models tended to be more successful where SSC-streamflow correlations (Rs-q) were high − typically in the humid Eastern US − and with lower SSC. Low Rs-q basins were often found in the arid Southwest with higher SSC. The highly-nonlinear SSC-streamflow relationships seem related to seasonality, basin size, and heterogeneity of land cover and rainfall within the basins, suggesting these basins need to be simulated at higher spatial resolution and may require additional inputs related to SSC induced by seasonality. The Whole-CONUS model also performed well for spatial extrapolation (basins not included in the training dataset, median R2 = 0.55), supporting large-scale modeling efforts. These state-of-the-art results using only minimal inputs suggest data-driven approaches can exploit the natural coevolution of sediment processes and the environment to support sediment modeling.

Reducing Sedimentation in Catchment Areas as Part of the Revitalization Efforts at Batujai Reservoir in Central Lombok

This research discusses efforts to revitalize the Batujai Reservoir in Central Lombok with a focus on sedimentation problems. Batujai Reservoir has a strategic role in meeting water needs in the surrounding area, but faces serious challenges due to significant sedimentation. In addition to assessing the effects of these changes on the reservoir's benefits�such as irrigation, flood control, and electricity production�this study intends to examine the effects of land use changes in the Dodokan Sub-Watershed Catchment Area (DTA) on the features and volume of sedimentation entering the reservoir. In addition, this study attempts to develop suggestions for efficient sedimentation management plans in order to increase the Batujai Reservoir's service life. Research methods include primary and secondary data collection, sedimentation modeling using the Water and Tillage/Sediment Delivery Model (WATEM/SEDEM), to evaluate the impact of sediment control structures such as check dams. Research variables include catchment area, population, annual rainfall, average daily evaporation, mainstay surface water availability, land surface erosion rate, sediment volume deposited in the reservoir, effective age of the Batujai Reservoir, and changes in land use in the Dodokan Sub-watershed. The results of this research will provide a better understanding of the main sources of sedimentation in the Batujai Reservoir and the impact of land use changes on the reservoir. It is hoped that the recommendations for sedimentation management strategies resulting from this research will help maintain reservoir storage capacity, which is important for meeting various water needs in the region.

Mesh-free SPH modelling of sediment scouring and flushing considering grains transport and transformation

Sediment scour numerical simulation plays a critical role in the design of water-resistant foundation engineering, and this paper addresses a significant gap in most related studies, which often overlook the transformation of sediment and struggle to identify the actual riverbed obscured by yielding bed and suspended load. To tackle this challenge, a comprehensive sediment model based on the meshless Smoothed Particle Hydrodynamics (SPH) method was developed. Firstly, to enhance computational efficiency and mitigate the high cost of Fluid-Solid Interaction (FSI) between water and sediments, cohesionless sediment grains were modelled as non-Newtonian fluids, with yield strength determined according to a combined strength criterion. Subsequently, sediment transformation and identification were determined based on sediment particle velocity and shear stress, with the seepage force driving yield sediment particle motion at the interface. The effectiveness of this comprehensive sediment model was validated through comparison with three scour experiments. The results show better agreement between the model and experimental data, with a root-mean-square error of less than 2.17% in scour morphology simulation and successful identification of the actual post-scouring bed surface in each case. However, the free surface simulation in this model still exhibits slight error, with a root-mean-square error of less than 8.35%.

Analysis of the thermo-hydro-mechanical coupled dynamic response of sediments under eccentric driving of deep-sea mining vehicle

This study establishes a coupled thermo-hydro-mechanical dynamic model(THMD) for saturated porous sediments under the eccentric motion of a deep-sea mining vehicle, considering the characteristics of deep-sea sediments. We applied the method of complex Fourier series expansion to simplify the coupled equations into ordinary differential equations and obtained the complex Fourier series expansion forms of various physical quantities of sediments during the eccentric movement of the mining vehicle. The undetermined constants are determined based on boundary conditions, yielding a series representation of the solution for THMD of deep-sea sediments. Subsequently, the solution was utilized to investigate the influence of mining vehicle parameters on the dynamic response of deep-sea sediments. This study demonstrates that the vertical displacement, vertical stress, and excess pore water pressure of sediments increase as the speed of the mining vehicle increases. Furthermore, the vertical displacement, vertical stress, and excess pore water pressure increase with the increment of load amplitude, and the differences in the curves at different eccentricities gradually become larger as the load amplitude increases. The proposed model can be applied to geotechnical engineering problems in saturated porous foundations, providing a necessary theoretical basis and analytical approach.

Establishment of critical non-depositing velocity prediction model for sediment in drip irrigation laterals based on PSO-SVM

Accurately determining the critical non-depositing velocity for sediment (CNDVS) in drip irrigation laterals is essential to address issues of sediment deposition and clogging in drip irrigation pipes caused by the use of muddy water. This paper focuses on three main factors: the percentage of intermediate-sized sediment particles (P), pipe diameter (D), and sediment concentration (S), all of which significantly influence the CNDVS in drip irrigation laterals. To predict the CNDVS, a comprehensive gradient test was developed and the Particle Swarm Optimization-Support Vector Machine (PSO-SVM) algorithm was applied to establish a response surface for predicting the CNDVS. Additionally, the PSO algorithm optimized the penalty parameter (C), loss parameter (ε), and kernel parameter (δ) in the SVM, resulting in a prediction model for the CNDVS. The proposed model was trained and tested using experimental data, and its prediction performance and accuracy were compared with the regression fitting model. The results indicate that within a specific range, the CNDVS increases with higher values of the three factors. The PSO-SVM model, with optimal parameters combination values of C = 486.37, ε = 0.04, and δ = 68.49, provided the most prediction accurate. Compared with the regression fitting model, the PSO-SVM model has the smaller values of Mean Absolute Error (MAE) = 0.0049, Root Mean Square Error (RMSE) = 0.0057, and Percent Bias (PBIAS) = 0.0004, and the larger value of Nash–Sutcliffe Efficiency (NSE) = 0.9874, Willmott index (WI) = 0.9401, and Coefficient of Determination (R2) = 0.9875. These results demonstrate that the PSO-SVM model established in this study exhibits high prediction performance and accuracy. The findings of this research can serve as a foundation for developing optimal operating and flushing flow velocity within the laterals in muddy water drip irrigation systems.