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Previous studies have demonstrated that vegetation‐generated turbulence can enhance erosion rate and reduce the velocity threshold for erosion of non‐cohesive sediment. This study considered whether vegetation‐generated turbulence had a similar influence on natural cohesive sediment. Cores were collected from a black mangrove forest with aboveground biomass and exposed to stepwise increases in velocity. Erosion was recorded through suspended sediment concentration. For the same velocity, cores with pneumatophores had elevated turbulent kinetic energy compared to bare cores without pneumatophores. However, the vegetation‐generated turbulence did not increase bed stress or the rate of resuspension, relative to bare cores. It was hypothesized that the short time‐scale fluctuations associated with vegetation‐generated turbulence were not of sufficient duration to break cohesion between grains, explaining why elevated levels of turbulence associated with the pneumatophores had no impact on the erosion threshold or rate. Plain Language Summary Mangrove habitat grows by retaining sediment. To restore these systems, it is necessary to understand how vegetation influences the transport and retention of sediment. This study used sediment cores collected from the interior of a mangrove forest to study how the aboveground roots, called pneumatophores, influence hydrodynamic conditions and sediment transport, and in particular the onset and rate of sediment erosion. Individual pneumatophores generate eddies that enhance turbulence, compared to conditions without pneumatophores. In sandy soil, vegetation‐generated turbulence can enhance erosion. However, in this study, vegetation‐generated turbulence did not increase the rate of erosion for natural cohesive (muddy) sediment, suggesting that the mangrove forest interior has naturally greater resistance to erosion and sediment loss. Key Points For the same velocity, cores with pneumatophores had higher turbulent kinetic energy (TKE) compared to cores without pneumatophores Unlike sands, the inception of erosion and erosion rates for cohesive sediment were better predicted by bed shear stress than by TKE Modelers should parameterize erosion within vegetation differently for cohesive and non‐cohesive sediment

Net deposition in estuaries is often linked to the estuarine turbidity maximum zones, in which fine, cohesive sediments accumulate due to residual transport by the estuarine circulation and tidal asymmetries. Sediments deposit in fairways or harbours, which creates high maintenance dredging costs and the need for better prediction of dredging hotspots with process-based numerical models. In this paper, a new efficient modelling approach is presented which enables the simulation of the ETM formation, its seasonal dynamics and the local sedimentation. A 3D baroclinic large-scale estuary model with a characteristic sediment fraction with simplified sediment transport properties is used with realistic boundary conditions, but without initial sediment distribution. This approach is referred to as supply-limited, regarding the ETM formation by residual transport. A dynamic equilibrium between residual sediment import from the open boundaries, accumulation and local sedimentation establishes in the model. This is achieved by combining the large-scale supply-limited model with an extended bed exchange formulation (2-Layer-Concept). A model of the Weser estuary is used as case study to reproduce and analyse the ETM formation and the resulting sedimentation simulated with this approach. The results are compared with the equivalent sediment concentration of turbidity measurements and dredging volumes.

The assessment of chloride salt release from sediments is important for environmental and water resource protection. However, the reliability of computational models for chloride salt release flux from cohesive sediment beds is limited because the models do not consider the fluidization and fine particle characteristics of cohesive sediment beds. In this study, 398 experiments were conducted to investigate the chloride salt release flux of cohesive sediment beds that had been fluidized to various degrees. The degree of fluidization was reflected by the magnitude of sediment yield stress. The authors found that sediment yield stress is a relevant and critical indicator of chloride salt release flux. The lower the yield stress, the higher the chloride salt release flux. The content and size of fine particles in cohesive sediment beds were indicated by the magnitude of surface coefficient of fine particles. The chloride salt release flux decreases with the surface coefficient of fine particles, and increases with temperature and the salinity difference between the cohesive sediment bed and the overlying water column. An empirical formula was proposed to calculate the chloride salt release flux from a cohesive sediment bed in quiescent water. The findings of this study provide valuable insights into the assessment and management of water salinization.

In this study, we investigate how changes in the vertical distribution of suspended sediment affect continuous suspended sediment flux measurements at a location in the San Francisco Estuary. Current methods for measuring continuous suspended sediment flux estimates relate continuous estimates of suspended-sediment concentration (SSC) measured at-a-point (SSC pt ) to discrete cross-section measurements of depth-averaged, velocity-weighted SSC (SSC xs ). Regressions that compute SSC xs from continuous estimates of SSC pt require that the slope between SSC pt and SSC xs , controlled by the vertical distribution of SSC, is fixed. However, in tidal systems with suspended cohesive sediment, factors that control the vertical SSC profile—vertical turbulent mixing and downward settling of suspended sediment mediated by flocculation of cohesive sediment—constantly vary through each tide and may exhibit systematic differences between flood and ebb tides (tidal asymmetries in water velocity or particle size). We account for changes in the vertical SSC profile on estimates of SSC xs using time series of the Rouse number of the Rouse-Vanoni-Ippen equation combined with optical turbidity measurements, a surrogate for SSC pt , to predict SSC xs from 2009 to 2011 and 2013. Time series of the Rouse number were estimated by fitting the Rouse-Vanoni-Ippen equation to SSC estimated from optical-turbidity measurements taken at two elevations in the water column. When accounting for changes in the vertical SSC profile, changes in not only the magnitude but also the direction of cumulative sediment-flux measurements were observed. For example, at a mid-depth sensor, sediment flux estimates changed from - 319 kt (± 65 kt, negative indicating net seaward transport) to 482 kt (± 140 kt, positive indicating net landward transport) for 2009–2011 and from - 388 kt (± 140 kt) to 1869 kt (± 406 kt) for 2013–2016. At the study location, estimation of SSC xs solely from SSC pt resulted in sediment flux values that were underestimates on flood tides and overestimates on ebb tides. This asymmetry is driven by covariance between water velocity and particle settling velocity (W s ) with larger W s on flood compared to ebb tides. Results of this study indicate that suspendedsediment-flux measurements estimated from point estimates of SSC may be biased if systematic changes in the vertical distribution of SSC are unaccounted for.

For the first time a comprehensive analysis for steady and unsteady flow conditions was performed of timedependent scour processes in non-cohesive sediment downstream of a Type A piano key weir. The evolution and progression of scour of large-scale laboratory experiments were interpreted using an empirical approach and adapting a theoretical model based on the phenomenological theory of turbulence developed elsewhere. The results were within 30% of experimental with the R-squared values of 0.972 for the theoretical model and 0.993 for a calibrated empirical model. Results of this study demonstrate consistent scour evolution kinetics between steady and unsteady flow cases, although in the latter, the maximum scour features were smaller than their steady-state counterparts. This study highlights the novelty of integrating experimental and theoretical frameworks to validate and enhance the design of complex hydraulic structures. Quantitative findings confirm the robustness of first principles-based approaches, offering practical insights and design parameters critical for addressing scour challenges in non-cohesive sediment environments.

PurposeThe critical shear stress of cohesive and mixed cohesive/non-cohesive sediments is affected by multiple interacting physical, chemical and biological parameters. There are various mathematical approaches in the scientific literature for computing critical shear stress. However, processes that influence sediment stability are still not fully understood, and available formulas differ considerably. These discrepancies in the literature arise from random system behaviour (natural variability of the sediments), different definitions of the critical shear stress, different measurement techniques and different model frameworks (scope of the parameters, undisturbed versus artificial sediment samples). While analytical approaches fail to address the involved uncertainties, fuzzy logic-based models integrate uncertainty and imprecision.Materials and methodsWith this in mind, a data-driven neuro-fuzzy model (ANFIS) was used to determine the critical shear stress based on sediment characteristics such as wet bulk density and grain size distribution. In order to select model predictors systematically, an automated stepwise regression algorithm was applied. The database for this analysis consisted of 447 measurements of the critical shear stress originating from 64 undisturbed sediment samples.Results and discussionThe study identified clay content as the primarily controlling variable for erosion resistance. Depending on the characteristics of the sampling location, the bulk density was also selected as a model predictor. In comparison to analytical models that are available in the scientific literature, the fuzzy model achieved higher correlation coefficients between measured and predicted data.ConclusionsThe neuro-fuzzy-model includes uncertainties of input variables and their interactions directly. Thus, it provides a reliable method for the prediction of erosion thresholds of cohesive/non-cohesive mixtures. It was also shown that this approach requires fewer measured variables as well as fewer assumptions than the models it was compared to.

The linear formulation for erosion E = M(τb−τc), often applied in engineering applications, has two properties, which do not always comply with field and laboratory observations, they are as follows: (1) The erosion rate is zero below the critical bed shear stress τc and increases linearly with bed shear stress τb, when exceeding the critical bed shear stress; incipient motion (τb ≃ τc) is poorly represented. (2) The erosion rate is constant in time for constant values of M and τc, whereas observations often suggest time dependency. In this paper we analyze the process of incipient motion and time dependency by using a stochastic forcing (bed shear stress) and a stochastic bed strength (critical bed shear stress). It is well known that the bed shear stress is not constant but varies due to turbulence. This stochastic nature of the turbulent motion is accounted for by a probability density distribution for the bed shear stress, which is based on the formulation of Hofland and Battjes (2006). This distribution is implemented in the linear erosion formulation. An analytical solution for the erosion rate is obtained, which only depends on the mean bed shear stress. A parametrization is made for efficient application in numerical models. The sediment in the bed is considered to be nonuniform. Therefore, it is subdivided into several classes, distinguished by the critical bed shear stress and not necessarily by the grain size. The variability of the critical bed shear stress is treated in a discritized way. Sediment balance equations are solved for each class. Considering different classes, the total erosion rate becomes time dependent, as the erosion depends on the availability of sediment. The model is applied to two annular flume data sets, Jacobs (2009) and Amos et al. (1992a). The results show that with a proper choice of the required parameters, the time dependence of the erosion rate and the concentration can be reproduced. We conclude that the occurrence of incipient motion can be explained from a stochastic forcing. Time‐varying erosion rates can be explained from a stochastic bed strength distribution or from a vertical gradient in bed strength. The latter is, however, not likely and not measurable in the top layers of dense consolidated cohesive sediment beds.

Thermal conductivity is one of the key parameters for estimating low-temperature geothermal potential. In addition to field techniques, it can be determined based on physical parameters of the sediment measured in the laboratory. Following the methodology for cohesive and non-cohesive sample preparation, laboratory measurements were carried out on 30 samples of sediments. Density, porosity and water content of samples were measured and used in thermal conductivity estimation models (TCEM). The bulk thermal conductivity (λb) calculated with six TCEMs was compared with the measured λb to evaluate the predictive capacity of the analytical methods used. The results show that the empirical TCEMs are suitable to predict the λb of the analysed sediment types, with the standard deviation of the residuals (RMSE) ranging from 0.11 to 0.35 Wm−1 K−1. To improve the fit, this study provides a new modified parameterisation of two empirical TCEMs (Kersten and Côté&Konrad model) and, therefore, suggests the most suitable TCEMs for specific sample conditions. The RMSE ranges from 0.11 to 0.29 Wm−1 K−1. Mixing TCEM showed an RMSE of up to 2.00 Wm−1 K−1, meaning they are not suitable for predicting sediment λb. The study provides an insight into the analytical determination of thermal conductivity based on the physical properties of sediments. The results can help to estimate the low-temperature geothermal potential more quickly and easily and promote the sustainable use of this renewable energy source, which has applications in environmental and engineering science.

Harmful heavy metals (HHMs) in marine sediments pose significant ecological and human health risks. This research developed a novel one-dimensional mathematical model to investigate the desorption rates and background concentrations (Cbg) of HHMs in cohesive sediments of coastal environments, using Cartagena Bay (CB), Colombia, as a reference for estuarine systems. The model integrates mass balance and molecular diffusion equations incorporating porosity and tortuosity. Both the particulate and dissolved phases of HHMs were considered. Numerical experiments were conducted over 28 years with a daily time step, simulating four primary hydrodynamic processes: molecular diffusion, desorption, sedimentation, and turbulent water exchange. The spatiotemporal evolution of  Cbg provides valuable insights for sediment modeling, policy development, and advancing the understanding of HHM pollution in sediments. Results of the model align closely with empirical data from CB, demonstrating its applicability not only to local conditions but also to similar contaminated areas through a generalized approach. This model can be used as a reliable computational tool for managing coastal environments.

The quantification of the erodibility of cohesive sediments is fundamental for an advanced understanding of estuarine sediment transport processes. In this study, the surface erosion threshold τ c for cohesive sediments collected from two sites in the area of the Port of Hamburg in the River Elbe is investigated in laboratory experiments. An improved closed microcosm system (C-GEMS) is used for the erosion experiments, which allows the accumulation of suspended sediment concentration (SSC) over an experimental run. A total of 34 erosion experiments has been conducted with homogenized samples and bulk densities between 1050 kg/m³ and 1250 kg/m³. The covered range of bulk densities is seen to represent the values commonly exhibited by freshly deposited cohesive sediments. Two approaches to derive τ c based on the erosion rate ( ε -method) and the SSC (SSC-method) were elaborated and compared. For both approaches, only one parameter has to be set in order to facilitate transferability to other devices. The results show a better performance of the SSC-method in terms of lower uncertainties, especially at the upper application limits of the utilized C-GEMS. The application of the SSC method yields values for τ c between 0.037 N/m² and 0.305 N/m², continuously increasing with bulk density. Repetition tests proved the repeatability of the experimental procedure and utilized methods to derive τ c . The derived data for τ c is used to fit two mathematical models: i) a highly empirical model relating τ c to dry bulk density and ii) a recently proposed model relating τ c to the physical properties of the sediment-mixture. While the derived parameters for the first model vary widely for the two sampling sites, the fit-parameter for the latter model is virtually independent of the investigated site, suggesting the superiority of this approach.