Prediction Of Sediment Transport Research Articles

Integrated hydrological and hydraulic modeling for predicting sediment transport in hydraulic road structure design: the case of oued ait ourir, high atlas, Morocco

Integrated hydrological and hydraulic modeling for predicting sediment transport in hydraulic road structure design: the case of oued ait ourir, high atlas, Morocco

Advp Measurements Of Flow Over Low-Angle Bedforms In A Laboratory Flume Setup

In many coastal and estuarine environments, bedforms develop due to the complex interactions between hydrodynamics, sediment transport and morphology which affect hydro-morphodynamic processes at various spatio-temporal scales. Furthermore, bedforms are considered main drivers of flow resistance via turbulence and affect near bottom processes such as bed roughness, bottom shear stress and turbulent structures. A detailed study and characterisation of flow over bedforms is therefore significant to many fundamental and engineering applications such as sediment transport calculation and prediction, channel managements, or burial of submarine cables. Asymmetric dunes with an angle-of-repose (30°) lee side have been well studied (Best, 2005; Venditti, 2013). They are representative of dunes commonly found in laboratory flumes and small rivers. Over such bedforms, flow is characterised by a permanent flow separation zone and intense turbulence over their lee side. Recently, it was shown that bedforms in large rivers are mainly low- to intermediate-angle dunes (mean lee side ca. 5-20°) having their steepest slope located close to the trough (Cisneros et al., 2020). Over such low- and intermediate-angle river dunes, flow separation is inexistent or intermittent and only little turbulence is generated (e.g. Kwoll et al., 2016; Lefebvre and Cisneros, 2023). Estuarine bedforms also possess mostly low- to intermediate-angle mean lee slopes between 5° and 20° (Dalrymple and Rhodes, 1995; Lefebvre et al., 2021). However, contrary to river bedforms, estuarine bedforms usually have a sharp pointed crest with the steepest slope situated near the crest and a relatively flat trough (Aliotta and Perillo, 1987; Lefebvre et al., 2021). It is not clear yet how much flow properties vary between high-angle flat-crested dunes and low-angle sharp-crested dunes. In particular, it is unknown whether a permanent or an intermittent flow separation can be observed over some segments of the lee side. Furthermore, the relation between the reversing tidal flow and natural estuarine morphology is not well understood yet. In this study, laboratory flume experiments will be conducted to measure the mean flow and turbulence over estuarine bedforms. Previous experiments performed by Carstensen and Holzwarth (2023) demonstrated the potential of high-resolution measurements over a large-scale estuarine dune in a laboratory flume. Building on this, experiments will be carried out over a fixed concrete low- and intermediate- angle estuarine bedform field. The results from this study can be used to characterise in detail the flow dynamics over estuarine bedforms.

Turbulence Intermittency Effects on the Initiation Threshold of Sediment Motion in Natural Waters

AbstractThe initiation threshold of sediment motion, a key component in quantifying sediment transport, has potential link to intermittent turbulence bursts. Here, we elaborated in situ experiments on coastal sea bottom covered with cohesive sediments, to obtain intermittency parameters. The variable “waiting time” between turbulence bursts was utilized to capture the occurrence of sediment initiation events in natural waters. A relationship between waiting time and shear stress reveals the different intermittency features of sediment flux time series before and after reaching the threshold, which can be used to determine the initiation threshold of sediment motion. Multi‐site results demonstrate the limitations of traditional empirical formulae for fine‐grained sediments, where cohesiveness becomes more pronounced as grain size decreases and the deviation can reach 600%. The empirical formula was modified using grain size, and the modified calculations were in good agreement with observed values, which will greatly assist in sediment transport and geomorphology model predictions.

Review of the Quantification of Aeolian Sediment Transport in Coastal Areas

Coastal dunes, formed and shaped by aeolian sediment transport, play a crucial role in ecosystem services and act as natural flood and coastal erosion defenses. This paper delves into theoretical equations and numerical models predicting sediment transport. Numerical models like cellular automata, XBeach-DUNA, the coastal dune model, and others are analyzed for their ability to simulate dune morphology, erosion processes, and vegetation impacts accurately. Evaluated are field observation and measurement techniques, such as sand traps, impact sensors, and optical sensors, for their precision in quantifying aeolian dynamics. Further examined is the effectiveness of vegetation and fencing in dune stabilization, noting species-specific responses and the influence of fence design on sediment accumulation. These tools offer insights into optimizing aeolian sediment management for coastal protection. By conducting a systematic review and connecting theoretical, empirical, and modeling findings, this study highlights the complex challenge of measuring and managing aeolian sediment transport and proposes integrated strategies for enhancing coastal dune resilience against the backdrop of climate change and erosion. This study’s objectives to bridge gaps in current understanding are met, highlighting the need for a multidisciplinary approach to coastal dune management and conservation, especially combining wind- and wave-driven processes.

An examination of point-particle Lagrangian simulations for assessing time-resolved hydroacoustic particle flux measurements in sediment-laden flows.

Accurate modelling and prediction of sediment transport in aquatic environments is essential for sustainable coastal and riverine management. Current capabilities rely on physical process-based numerical models and fine-scale sediment flux measurements. High-resolution hydroacoustic instrumentation has emerged as a promising tool for such measurements. However, challenges arise due to the inherent complexity of ultrasound scattering processes. This study introduces a numerical modelling using a point-particle approach to simulate the echoes backscattered by such instrumentation in sediment-laden flow conditions. The model considers geometric, statistical, particle cloud, and flow-induced effects on sediment velocity, concentration, and flux estimates using an acoustic concentration and velocity profiler as a reference. The model performance is assessed here under unidirectional constant flow conditions in terms of velocity, concentration, and time-resolved sediment flux estimates for a large range of the particles' advection speed and sampled volume sizes. Application to the estimation of the measurement accuracy of sediment flux in these flows is also considered, with a final error on the flux seen to be partially controlled by the residence time of particles within the sampled volumes. The proposed model provides insights into scattering processes and offers a tool for investigating robust sediment flux estimation techniques in various flow conditions.

Sustainable Watershed Management: Assessing the Impact of Data Precision on Sediment Transport in the Oostanaula Creek Watershed, Tennessee

This study applies the WaTEM/SEDEM model, a watershed-scale model based on the Universal Soil Loss Equation (USLE), to enhance sustainable watershed management by identifying high-erosion-risk areas for targeted mitigation at various scales. It focuses on identifying potential errors in using statewide or worldwide land use data layers derived from remote-sensing algorithms and inaccuracies in the spatial distribution of cropland and soil types resulting in misinterpretation of sediment yields. These model limitations emphasize the need for field validation and precise input data, particularly stream data, to improve the reliability of these models. The study examines hydrologic rainfall-runoff processes in Tennessee’s 182 km2 Oostanaula catchment using various data sources, including the National Land Cover Database (NLCD), the European Space Agency WorldCover dataset (ESA), and manual field surveys. Three modeling scenarios were evaluated, with and without stream topology corrections, using the WaTEM/SEDEM model. It details the global data used, the methodology of the field survey, the simulation and validation of data, and the critical point identification. Significant discrepancies in long-term sediment transport predictions were found, depending on the land use data source. This study addresses watershed model validity and potential errors and recommendations for the use of globally available data.

Reinvestigating the Kinetic Model for the Suspended Sediment Concentration in an Open Channel Flow

The prediction of sediment transport, related to different environmental and engineering problems, requires accurate mathematical models. Most available mathematical models for the concentrations of suspended sediments are based on the classical advection diffusion equation, which remains not efficient enough to describe the complete behavior related to sediment–water two-phase flows and the feedback between the turbulent unsteady flow and suspended sediments. The aim of this paper is to reinvestigate the kinetic model for turbulent two-phase flows, which accounts for both sediment–turbulence interactions and sediment–sediment collisions. The present study provides a detailed and rigorous derivation of the kinetic model equations, clarifications about the mathematical approach and more details about the main assumptions. An explicit link between the kinetic model and the classical advection diffusion equation is provided. Concentration profiles for suspended sediments in open channel flows show that the kinetic model is able to describe the near-bed behavior for coarse sediments.

Prediction of sediment transport due to detached breakwater

This research intends to predict the pattern and accumulation of sediment transport before and after being built the detached breakwater. This research was conducted on Matras, Penyak, and Pasir Padi shorelines which are located in Bangka Island-Indonesia. Based on the previous research, few empirical methods are used for analyzing the shore response due to the breakwater for fulfilling the erosion and sedimentation in the shoreline. However, there has not been more research that analyzed the effect of breakwater itself on the pattern and accumulation of sediment transport (the formation of tombolo and salient) that happens in the shorelines based on the parameters of structure, physical condition, and characteristics of sediment. The research methodology consists of collecting data, measurement on the field, and Citra satellite observation without and with breakwater. The result is hoped can support the modelling of the distance among breakwaters and the effective formulation of the distance among breakwaters.

Nearshore wave buoy data from southeastern Australia for coastal research and management

Wind wave observations in shallow coastal waters are essential for calibrating, validating, and improving numerical wave models to predict sediment transport, shoreline change, and coastal hazards such as beach erosion and oceanic inundation. Although ocean buoys and satellites provide near-global coverage of deep-water wave conditions, shallow-water wave observations remain sparse and often inaccessible. Nearshore wave conditions may vary considerably alongshore due to coastline orientation and shape, bathymetry and islands. We present a growing dataset of in-situ wave buoy observations from shallow waters (<35 m) in southeast Australia that comprises over 7,000 days of measurements at 20 locations. The moored buoys measured wave conditions continuously for several months to multiple years, capturing ambient and storm conditions in diverse settings, including coastal hazard risk sites. The dataset includes tabulated time series of spectral and time-domain parameters describing wave height, period and direction at half-hourly temporal resolution. Buoy displacement and wave spectra data are also available for advanced applications. Summary plots and tables describing wave conditions measured at each location are provided.

Using Field Measurements Across Land Cover Types to Evaluate Albedo‐Based Wind Friction Velocity and Estimate Sediment Transport

AbstractThe soil surface wind friction velocity (us*) is an essential parameter for predicting sediment transport on rough surfaces. However, this parameter is difficult and time‐consuming to obtain over large areas due to its spatiotemporal heterogeneity. The albedo‐based approach calibrates normalized shadow retrieved from any source of albedo data with laboratory measurements of aerodynamic properties. This enables direct and cross‐scale us* retrieval but has not been evaluated against field measurements for different cover types. We evaluated the approach's performance using wind friction velocity (u*) measurements from ultrasonic anemometers. We retrieved coincident field pyranometer and satellite albedo at 48 sites that were spread over approximately 1,800 km on the Inner Mongolia Plateau, including grassland, artificial shrubland, open shrubland, and gobi land. For all cover types, u* estimates from ultrasonic anemometers were close to the albedo‐based results approach. Our results confirm and extend the findings that the approach works across scales from lab to field measurements and permits large‐area assessments using satellite albedo. We compared the seasonal sediment transport across the region calculated from albedo‐based us* with results from an exemplar traditional transport model (QT) driven by u* with aerodynamic roughness length varying with land cover type and fixed over time. The traditional model could not account for spatiotemporal variation in roughness elements and considerably over‐estimated sediment transport, particularly in partially vegetated and gravel‐covered central and western parts of the Inner Mongolia Plateau. The albedo‐based sediment transport (QA) estimates will enable dynamic monitoring of the interaction between wind and surface roughness to support Earth System models.

Predicting marine and aeolian contributions to the Sand Engine’s evolution using coupled modelling

Quantitative predictions of marine and aeolian sediment transport in the nearshore–beach–dune system are important for designing Nature-Based Solutions (NBS) in coastal environments. To quantify the impact of the marine-aeolian interactions on shaping NBS, we present a framework coupling three existing process-based models: Delft3D Flexible Mesh, SWAN and AeoLiS. This framework facilitates the continuous exchange of bed levels, water levels and wave properties between numerical models focussing on the aeolian and marine domain. The coupled model is used to simulate the morphodynamic evolution of the Sand Engine mega-nourishment. Results display good agreement with the observed aeolian and marine volumetric developments, showing similar marine-driven erosion from the main peninsula and aeolian-driven infilling of the dune lake. To estimate the magnitude of the interactions between aeolian and marine processes, a comparison between the simulated morphological development by the coupled and stand-alone models was made. This comparison shows that aeolian sediment transport to the foredune, i.e. 214,000 m3 over 5 years, extracts sediment from the marine domain. As a result, the alongshore redistribution of sediment from the main peninsula by marine-driven processes decreased by 70,000 m3, representing 1.7% of the total marine-driven dispersion. From the aeolian perspective, marine-driven deposition and erosion reshape the cross-shore profile, controlling the supply-limited aeolian sediment transport and the magnitude of sediment deposition in the foredunes. In the region with persistent accretion along the Sand Engine’s southern flank, a higher than average foredune deposition was predicted due to morphological development of the region where sediment is picked up by aeolian transport. Including these marine processes in the coupled model resulted in an increase of 1.3% in foredune growth in year 1 and up to 6.7% in year 5 along this accretive section. At the northern flank, where the developing lagoon and tidal channel provided increased shelter to the supratidal beach, predicted foredune deposition reduced up to −11.5% over the evaluation period. Our findings show that both aeolian and marine transports impact reshaping the nourished sand, where developments in one domain affect the other. The study findings echo that the interplay between aeolian- and marine-driven morphodynamics could play a relevant role when predicting sandy NBS.

The effect of compound channel shape for local scouring and flow dynamics using NaysCUBE-3D RANS at Downstream Tukad Unda River Bali Province

The prediction of sediment transport and flow dynamics are important issues in channel design as the local scouring has an important effect on the shape of the channel, especially on the compound channel. Tukad Unda River in Bali has river section in the form of compound channel. It consists of two sections with different dimension, the main channel and the flood plain. These dimensional differences cause two different flows. Transformation of flow velocity and turbulence cause movement of sediment transport, generates a complex 3D flow structure in the boundary of main channel and floodplain. This study uses morphology data in Tukad Unda River and simulated by using NaysCUBE. NaysCUBE is a three-dimensional numerical modeling which use the Reynold Average Navier Stoke equation (3D RANS model). The result in this study shows the different pattern of flow dynamics and local scouring in the boundary between main channel and floodplain as the concrete block located in that boundary compare to the nature compound channel. In the 40-minute simulation, the nature compound channel represented significant deformation of the river bed in the interface area, with a decrease in elevation of 0.01 meters higher than the compound channel with concrete blocks. while the increase in elevation in the main channel is around 0.09 meters lower than the compound channel with concrete blocks. Application of concrete blocks can be useful to reduce local scour at the interface as the impact of compound channel flow characteristics.

Characteristics and interactions of fluctuation velocities, saltation mass flux, and temperature in the atmospheric surface layer

The essence of wind-blown sand movement is a particle movement system driven by high Reynolds number wall turbulence in the atmospheric surface layer (ASL). Understanding this phenomenon is crucial as the law and mechanism of sand movement have not been effectively revealed at present. In this study, we utilize the high-frequency time series data from the Oceano site, a renowned location for such studies, which includes streamwise wind velocity (u), wall-normal wind velocity (w), temperature (T), and total saltation mass flux (q) to delve deeper into wind-blown sand movement. The results indicate a positive correlation between T and w. Interestingly, this correlation not only escalates with height but also intensifies with the increase of the stratification stability parameters (z/L). Sand influences the intensity ratio of each quadrant to Reynolds stress without altering the time ratio. Both the ejection and sweep processes correlate well with z/L. Similarly, q also exhibits a good correlation with z/L. The buoyancy's impact on the low-frequency fluctuations of q might be through its effect on the low-frequency fluctuations of w, enhancing the sand transport capacity of w. This discovery holds profound implications for the study of two-phase flow in ASL and the precise prediction of surface sediment transport.

Enhancing sediment transport predictions through machine learning-based multi-scenario regression models

Machine learning is one effective way of increasing the accuracy of sediment transport models. Machine learning captures patterns in the sequence of both structured and unstructured data and uses it for forecasting. In this research, the different regression models were train to forecast sediment data using 8 years of measured sediment data collected in Sg. Linggui suspended sediment station. Data from different scenarios were used where each scenario indicates the number of lags. Seven regression models, namely, Linear Regression, Regression Trees, Support Vector Machines, Gaussian Process Regression, Kernel Approximation, Ensemble of Trees, and Neural Network were trained using the data and compared. The trained models were evaluated using Root Mean Square Error (RMSE) and Coefficient of Determination (R2). The best-performing models from two different types of regression models were chosen and they were tested using the test data to find the Relative Percentage Error (RPE) of the predicted data. The Exponential Gaussian Process Regression model performs much better than the other models in terms of RMSE and R2 values. When the exponential models from all 3 scenarios are compared, scenario 3 seems to have a better-performing model but only by a very small margin, after using testing data, the result shows scenario 3 has less RPE compared to other models. Hence, it can be deduced that the exponential gaussian process regression model from scenario 3 is the best-performing model overall in terms of RSME, R2, and RPE.

Rainfall characteristics of sediment connectivity activation from plot to watershed scales on the Loess Plateau

Sediment connectivity is a fundamental concept for understanding sediment dynamics within watersheds, serving as a crucial component in watershed management and soil and water conservation. However, quantifying sediment connectivity remains a challenging task due to its complexity and the difficulties associated with direct measurements of sediment flux at multiple temporal and spatial scales. Our research aims to address this challenge by monitoring functional sediment connectivity at various scales using two key indicators: sediment yield and sediment marks. Sediment yield is monitored at slope plots, slope-channel cascades, and watershed outlets, while sediment marks provide additional insight into functional sediment connectivity along the sediment transport path, particularly in slope-channel cascades and channels following rainfall events. To record sediment marks, we used wooden sticks wrapped with clean gauze as an alternative to assessing functional connectivity. Our results revealed that the activation of sediment connectivity was influenced by rainfall amount, intensity, and type, with the highest activation observed at the slope plot, followed by the outlet of the slope-channel cascade and the watershed outlet. Notably, strong sediment connectivity at slope plots, slope-channel cascades, and main channels exhibits a weak correlation with sediment connectivity at the watershed outlet. In upper contribution areas with lower vegetation coverage and higher human disturbance, rainfall amount and I60 values associated with sediment connectivity activation tend to be lower. Furthermore, our research indicates that medium-duration and moderate-intensity rainfall events have a more significant impact on sediment connectivity at slope plots, while rainfall types characterized by longer durations, lower intensity, and larger amounts have a more pronounced effect on sediment transport paths. This suggests that the identification of sediment connectivity switch nodes can be achieved by considering both rainfall characteristics and underlying surface features. Looking ahead, future research can leverage long-term observations and data-driven models to explore rainfall thresholds for sediment connectivity at various scales, ultimately improving sediment transport prediction within watersheds.

Prediction modeling of coastal sediment transport using accelerated smooth particle hydrodynamics approach

A GPU-accelerated 3D smooth particle hydrodynamics (SPH) scheme is developed and applied to a coastal multi-phase liquid-sediment interaction and sediment transport. The SPH scheme's meshless design and the sediment's particle structure enable the modeling of the waves' interactions with the sediment particles beyond the limitation of the mesh-based methods. A Newtonian constitutive model is used to model the liquid phase, and the sediment transport is formulated based on the Herschel-Bulkley-Papanastasiou (HBP) model. The yield characteristics of the sediment phase are estimated using the Drucker-Prager yield criterion. Due to the parallelization of the solution on graphics processing units, the 3D SPH scheme's performance, which uses millions of particles, is improved. Good correlations were observed in the SPH predictions and experimental measurements, with a maximum difference of 4.85 %. The validated scheme is applied to formulate forecasting models for the coastline sediment transport. It is found that erosion and scouring are expected at the coastline region inclined to the direction of the sea waves, with a predicted mass erosion of about 60e3 kg in four years. The wave's velocity is also established to be directly proportional to the sediment transport. The proposed multi-phase SPH methodology is proven effective for sediment transport prediction.

Comparison of Artificial Intelligence (AI) Based Models for Sediment Transport Prediction Using SWOT and Statistical Analyses

The dynamics involved in sediment scour are complicated to create a general empirical optimization algorithm to offer reliable sediment load estimation. The existing study was conducted to analyse the architectures of assorted artificial intelligence (AI) based model to forecast suspended sediment load in fluvial system. An in-depth study on traditional approach including Artificial Neural Network (ANN), Adaptive NeuroFuzzy Inference System (ANFIS), and Genetic Programming (GP) was carried out. The goal of this study is to evaluate the performance of AI-based models from various research using SWOT and statistical analyses. Three statistical measures of model prediction accuracy including coefficient of correlation (R), root mean square error (RMSE), and mean absolute error (MAE) were used. The results revealed that the SVM and ANFIS models outperformed the other soft computing and conventional models. It is concluded that the SVM and ANFIS models are preferred and may be successfully used to estimate the suspended sediment concentration for the research area.

The importance of grain‐related shear velocity in predicting multi‐monthly dune growth

AbstractThis study assesses the accuracy of the aeolian transport model proposed by van Rijn and Strypsteen in 2020 in predicting sediment transport rates for dune growth, with a focus on the importance of grain‐related shear velocity. A 9‐month dataset of local and regional wind characteristics and dune growth from a new artificial dune with planted marram grass in an environment with minor supply limitations was analysed. The study site is located in Oosteroever, Belgium. The results revealed that utilizing local measured overall shear velocities resulted in significant overprediction of dune volume changes. Incorporating sub‐models for grain‐related bed roughness and shear velocity improved the predictions of dune growth drastically with high statistical results (r2 = 0.98 and RMSE = 0.64 m3/m). The primary driver contributing to dune growth at the study site was due to oblique onshore moderate winds of 10 m/s, as revealed from a frequency‐magnitude analysis. The model could be used with either local wind measurements or regional data transformed to local beach conditions. The study highlights the importance of considering grain‐related shear velocity in future studies to improve the prediction of sand transport rates and enhance our understanding of dune evolution.

A SIMPLE LABORATORY CALIBRATION METHOD FOR MITIGATING SEAWATER EFFECTS ON SOIL MOISTURE SENSORS

The importance of moisture content for sediment dynamics in coastal environments is well documented, particularly in reference to aeolian sediment transport (Davidson-Arnott, 2005). Tidally-induced changes in moisture content in partially saturated environments, such as beaches, cause significant changes in surface shear strength through the development of suction stresses, which can affect erodibility (Sassa and Watabe, 2007). Thus, the accurate measurement of moisture content in these environments is important for determination of strength properties and for predicting sediment transport. Most moisture sensors work by measuring dielectric permittivity, the ability to carry electric charge, of the substrate, which is proportional to the moisture content. However, most moisture sensors are not calibrated for seawater, which has a higher dielectric permittivity than freshwater, causing overestimation of the moisture content. Therefore, the goal of this study is to develop and demonstrate a laboratory calibration scheme to account for this overestimation, and thus to allow for more accurate measurements of moisture content in coastal environments.

CROSS-SHORE BEACH PROFILE SIMULATION IN THE SWASH ZONE OF NARRABEEN-COLLAROY BEACH

Sediment transport and, consequently, the beach profile changes in the swash zone are important to the overall sediment budget and beach profile evolution because the hydrodynamic condition in this zone is complex. One of the swash zone morphodynamic difficulties is estimating the beach profile accretion and erosion above the mean water level. Although there have been considerable studies and investigations into the swash zone morphodynamic, numerical models for predicting sediment transport rate and beach profile changes are limited. Therefore, this study examined a morphodynamic numerical model to predict beach profile evolution in the swash zone using a nearshore beach profile dataset measured at the Narrabeen-Collaroy beach, Australia.