On the mechanisms of the saltating motion of bedload

Saltation of sediment particles is an important pattern of bedload transport.Based on force analysis for sediment particles,a Lagrangian model was proposed for the saltating motion of bedload in river flows,which was then solved with numerical method.Simulation results on the saltating trajectories neglecting particle rotation and turbulence effects compare fairly well with experimental observations.The mean values of the saltation parameters (saltation height,length and velocity) also agree well with the previous experimental data.Based on the numerical results,regression equations for the dimensionless saltation height,length and velocity were presented.Using the numerically achieved characteristics of the sediment saltation,we also obtained mathematical expression for the sediment transport rate.The studies in this paper are significant for its contribution to mechanism of the bedload motion and the computation of sediment transport rate.     

AN ANALYTICAL SOLUTION FOR CALCULATING THE INITIATION OF SEDIMENT MOTION

This paper presents an analytical solution for calculating the initiation of sediment motion and the risk of river bed movement. It thus deals with a fundamental problem in sediment transport, for which no complete analytical solution has yet been found. The analytical solution presented here is based on forces acting on a single grain in state of initiation of sediment motion. The previous procedures for calculating the initiation of sediment motion are complemented by an innovative combination of optical surface measurement technology for determining geometrical parameters and their statistical derivation as well as a novel approach for determining the turbulence effects of velocity fluctuations. This two aspects and the comparison of the solution functions presented here with the well known data and functions of different authors mainly differ the presented solution model for calculating the initiation of sediment motion from previous approaches. The defined values of required geometrical parameters are based on hydraulically laboratory tests with spheres. With this limitations the derivated solution functions permit the calculation of the effective critical transport parameters of a single grain, the calculation of averaged critical parameters for describing the state of initiation of sediment motion on the river bed, the calculation of the probability density of the effective critical velocity as well as the calculation of the risk of river bed movement. The main advantage of the presented model is the closed analytical solution from the equilibrium of forces on a single grain to the solution functions describing the initiation of sediment motion.     

Significance of particle interaction to the modelling of cohesive sediment transport in rivers

Aggregation processes of fine sediments have rarely been integrated in numerical simulations of cohesive sediment transport in riverine systems. These processes, however, can significantly alter the hydrodynamic characteristics of suspended particulate matter (SPM), modifying the particle settling velocity, which is one of the most important parameters in modelling suspended sediment dynamics. The present paper presents data from field measurements and an approach to integrate particle aggregation in a hydrodynamic sediment transport model. The aggregation term used represents the interaction of multiple sediment classes (fractions) with corresponding multiple deposition behaviour. The k–ε–turbulence model was used to calculate the coefficient of vertical turbulent mixing needed for the two‐dimensional vertical‐plane simulations. The model has been applied to transport and deposition of tracer particles and natural SPM in a lake‐outlet lowland river (Spree River, Germany). The results of simulations were evaluated by comparison with field data obtained for two levels of river discharge. Experimental data for both discharge levels showed that under the prevailing uniform hydraulic conditions along the river reach, the settling velocity distribution did not change significantly downstream, whereas the amount of SPM declined. It was also shown that higher flow velocities (higher fluid shear) resulted in higher proportions of fast settling SPM fractions. We conclude that in accordance with the respective prevailing turbulence structures, typical aggregation mechanisms occur that continuously generate similar distribution patterns, including particles that settle toward the river bed and thus mainly contribute to the observed decline in the total SPM concentration. In order to determine time‐scales of aggregation and related mass fluxes between the settling velocity fractions, results of model simulations were fitted to experimental data for total SPM concentration and of settling velocity frequency distributions. The comparison with simulations for the case of non‐interacting fractions clearly demonstrated the practical significance of particle interaction for a more realistic modelling of cohesive sediment and contaminant transport. Copyright © 2004 John Wiley & Sons, Ltd.     

Computational modeling of flow and sediment transport and deposition in meandering rivers

A computational modeling analysis of the flow and sediment transport, and deposition in meandering-river models was performed. The Reynolds stress transport model of the FLUENT^TM code was used for evaluating the river flow characteristics, including the mean velocity field and the Reynolds stress components. The simulation results were compared with the available experimental data of the river model and discussed. The Lagrangian tracking of individual particles was performed, and the transport and deposition of particles of various sizes in the meandering river were analyzed. Particular attention was given to the sedimentation patterns of different size particles in the river-bend model. The flow patterns in a physical river were also studied. A Froude number based scale ratio of 1:100 was used, and the flow patterns in the physical and river models are compared. The result shows that the mean-flow quantities exhibit dynamic similarity, but the turbulence parameters of the physical river are different from the model. More strikingly, the particle sedimentation features in the physical and river models do not obey the expected similarity scaling.     

Parsimonious sediment transport equations based on Bagnold's stream power approach

It is increasingly recognized that effective river management requires a catchment scale approach. Sediment transport processes are relevant to a number of river functions but quantifying sediment fluxes at network scales is hampered by the difficulty of measuring the variables required for most sediment transport equations (e.g. shear stress, velocity, and flow depth). We develop new bedload and total load sediment transport equations based on specific stream power. These equations use data that are relatively easy to collect or estimate throughout stream networks using remote sensing and other available data: slope, discharge, channel width, and grain size. The new equations are parsimonious yet have similar accuracy to other, more established, alternatives. We further confirm previous findings that the dimensionless critical specific stream power for incipient particle motion is generally consistent across datasets, and that the uncertainty in this parameter has only a minor impact on calculated sediment transport rates. Finally, we test the new bedload transport equation by applying it in a simple channel incision model. Our model results are in close agreement to flume observations and can predict incision rates more accurately than a more complicated morphodynamic model. These new sediment transport equations are well suited for use at stream network scales, allowing quantification of this important process for river management applications. Copyright © 2017 John Wiley & Sons, Ltd.     

Muskingum equation based downstream sediment flow simulation models for a river system

Applications of sediment transport and water flow characteristics based sediment transport simulation models for a river system are presented in this study. An existing water–sediment model and a new sediment–water model are used to formulate the simulation models representing water and sediment movement in a river system. The sediment–water model parameters account for water flow characteristics embodying sediment transport properties of a section. The models are revised formulations of the multiple water inflows model describing water movement through a river system as given by the Muskingum principle. The models are applied to a river system in Mississippi River basin to estimate downstream sediment concentration, sediment discharge, and water discharge. River system and the river section parameters are estimated using a revised and the original multiple water inflows models by applying the genetic algorithm. The models estimate downstream sediment transport rates on the basis of upstream sediment/water flow rates to a system. Model performance is evaluated by using standard statistical criteria;downstream water discharge resulting from the original multiple water inflows model using the estimated river system parameters indicate that the revised models satisfactorily describe water movement through a river system. Results obtained in the study demonstrate the applicability of the sediment transport and water flow characteristics-based simulation models in predicting downstream sediment transport and water flow rates in a river system.     

Modelling-based assessment of suspended sediment dynamics in a hypertidal estuarine channel

We investigate the dynamics of suspended sediment transport in a hypertidal estuarine channel which displays a vertically sheared exchange flow. We apply a three-dimensional process-based model coupling hydrodynamics, turbulence and sediment transport to the Dee Estuary, in the north-west region of the UK. The numerical model is used to reproduce observations of suspended sediment and to assess physical processes responsible for the observed suspended sediment concentration patterns. The study period focuses on a calm period during which wave-current interactions can reasonably be neglected. Good agreement between model and observations has been obtained. A series of numerical experiments aim to isolate specific processes and confirm that the suspended sediment dynamics result primarily from advection of a longitudinal gradient in concentration during our study period, combined with resuspension and vertical exchange processes. Horizontal advection of sediment presents a strong semi-diurnal variability, while vertical exchange processes (including time-varying settling as a proxy for flocculation) exhibit a quarter-diurnal variability. Sediment input from the river is found to have very little importance, and spatial gradients in suspended concentration are generated by spatial heterogeneity in bed sediment characteristics and spatial variations in turbulence and bed shear stress.     

Sensitivity of simulated flow fields and bathymetries in meandering channels to the choice of a morphodynamic model

Morphodynamic models are used by river practitioners and scientists to simulate geomorphic change in natural and artificial river channels. It has long been recognized that these models are sensitive to the choice of parameter values, and proper calibration is now common practice. This paper investigates the less recognized impact of the choice of the model itself. All morphodynamic models purport to simulate the same flow and sediment dynamics, often relying on the same governing equations. Yet in solving these equations, the models have different underlying assumptions, for example regarding spatial discretization, turbulence, sediment inflow, lateral friction, and bed load transport. These differences are not always considered by the average model user, who might expect similar predictions from calibrated models. Here, a series of numerical simulations in meandering channels was undertaken to test whether six morphodynamic codes (BASEMENT, CCHE‐2D, NAYS, SSIIM‐1, TELEMAC‐2D and TELEMAC‐3D) would yield significantly different equilibrium bathymetries if subjected to identical, initial flow conditions. We found that, despite producing moderately similar velocity patterns on a fixed‐flat bed (regression coefficient r of 0.77 ± 0.20), the codes disagree substantially with respect to simulated bathymetries (r = 0.49 ± 0.31). We relate these discrepancies to differences in the codes' assumptions. Results were configuration specific, i.e. codes that perform well for a given channel configuration do not necessarily perform well with higher or lower sinuosity configurations. Finally, limited correlation is found between accuracy and code complexity; the inclusion of algorithms that explicitly account for the effects of local bed slope and channel curvature effects on transport magnitude and direction does not guarantee accuracy. The range of solutions obtained from the evaluated codes emphasizes the need for carefully considering the choice of code. We recommend the creation of a central repository providing universal validation cases and documentation of recognized fluvial codes in commonly studied fluvial settings. Copyright © 2016 John Wiley & Sons, Ltd.     

Modelling mean annual sediment yield using a distributed approach

In this paper a spatially distributed model for the calculation of sediment delivery to river channels is presented (SEDEM: SEdiment DElivery Model). The model consists of two components: (1) the calculation of a spatial pattern of mean annual soil erosion rates in the catchment using a RUSLE (Revised Soil Erosion Equation) approach; and (2) the routing of the eroded sediment to the river channel network taking into account the transport capacity of each spatial unit. If the amount of routed sediment exceeds the local transport capacity, sediment deposition occurs. An existing dataset on sediment yield for 24 catchments in central Belgium was used to calibrate the transport capacity parameters of the model. A validation of the model results shows that the sediment yield for small and medium sized catchments (10–5000 ha) can be predicted with an average accuracy of 41 per cent. The predicted sediment yield values with SEDEM are significantly more accurate than the predictions using a lumped regression model. Moreover a spatially distributed approach allows simulation of the effect of different land use scenarios and soil conservation techniques. Copyright © 2001 John Wiley & Sons, Ltd.     

A statistical riverine litter propagation model.

A statistical riverine litter propagation (RLP) model based on importance sampling Monte Carlo (ISMC) simulation was developed in order to predict the frequency distribution of certain litter types in river reaches. The model was preliminarily calibrated for plastic sheeting by a pilot study conducted on the River Taff, Wales (UK). Litter movement was predominantly controlled by reach characteristics, such as vegetation overhang and water-course obstructions. These affects were modeled in the simulations, by utilizing geometric distributions of river reaches in the time domain. The proposed model satisfactorily simulated the dosing experiments performed at the River Taff. It was concluded from the preliminary calibrations that, the RLP model can be efficiently utilized to portray litter propagation at any arbitrarily selected river site, provided that the stream flows and reach characteristics are calibrated by representative probability distributions of similar sections. Therefore, the RLP model can be considered as a new statistical technique that can predict litter propagation in river sections.     

Evaluating the effect of land use changes on soil erosion and sediment yield using a grid‐based distributed modelling approach

Processes of soil erosion and sediment transport are strongly influenced by land use changes so the modelling of land use changes is important with respect to the simulation of soil degradation and its on‐site and off‐site consequences. The reliability of simulation results from erosion models is circumscribed by considerable spatial variation in many parameters. However, most of the currently widely used erosion models at the mesoscale are semidistributed, which leads to difficulties in incorporating a high degree of spatial information, especially land use information, so that the effects of land use changes on soil erosion have hitherto not been investigated in detail using these models. In this article, a grid‐based distributed erosion and sediment transport model is introduced, which simulates the spatial pattern of erosion and deposition rates and sediment transport processes in river channels. In this model, land use affects soil erosion through altering soil loss and influencing sediment delivery. Simulated soil erosion for events recorded in 1989 and 1996 in the Lushi basin in China was analyzed by comparing it with historical land use maps. The results indicated that even relatively minor land use changes had a significant effect on regional soil erosion rates and sediment transport to rivers. The average erosion rate increased from 1989 to 1996, after the transformation of forest to farmland. The results of the study suggest that the proposed soil erosion model can be applied in similar river basins. Copyright © 2011 John Wiley & Sons, Ltd.     

Does an upper limit to river water temperature apply in all places?

There remains continued use of non‐linear, logistic regression models for predicting water temperature from air temperature. A dominant feature of these non‐linear models is an upper bound on river water temperature. This upper bound is often attributed to a large increase in evaporative cooling at high air temperatures, but the exact conditions under which such an increase may occur have not been thoroughly explored. To better understand the appropriateness of the non‐linear model for predicting river water temperatures, it is essential to understand the physical basis for the upper bound and when it should and should not be included in the statistical model. This paper applies and validates an energy balance model against 8 river systems spread across different climate regions of the United States. The energy balance model is then used to develop a diagram relating vapour pressure deficit and air temperature to water temperature. With knowledge of present or future vapour pressure deficit (difference between saturation and actual vapour content in the atmosphere) conditions in a given climate, the diagram can be used to predict the likelihood of an upper bound in the air–water temperature relationship. This investigation offers a fundamental physical explanation of the most appropriate form of statistical models that should be used for predicting future water temperature from air temperature in different geographic regions with different climate conditions. In general, climatic regions that have only a slight increase in vapour pressure deficit with increasing air temperature (typically humid regions) would not be expected to have an upper bound. Conversely, climatic regions in which vapour pressure deficit sharply increases with increasing air temperature (typically arid regions) would be expected to have an upper bound.     

Suspended sediment yield modeling in Mahanadi River,India by multi-objective optimization hybridizing artificial intelligence algorithms

River sediment produced through weathering is one of the principal landscape modification processes on earth.Rivers are an integral part of the hydrologic cycle and are the major geologic agents that erode the continents and transport water and sediments to the oceans.Estimation of suspended sediment yield is always a key parameter for planning and management of any river system.It is always challenging to model sediment yield using traditional mathematical models because they are incapable of handling the complex non-linearity and non-stationarity.The suspended sediment modeling of the river depends on the number of factors such as rock type,relief,rainfall,temperature,water discharge and catchment area.In this study,we proposed a hybrid genetic algorithm-based multi-objective optimization with artificial neural network(GA-MOO-ANN)with automated parameter tuning model using these factors to estimate the suspended sediment yield in the entire Mahanadi River basin.The model was validated by comparing statistically with other models,and it appeared that the GA-MOO-ANN model has the lowest root mean squared error(0.009)and highest coefficient of correlation(0.885)values among all comparative models(traditional neural network,multiple linear regression,and sediment rating curve)for all stations.It was also observed that the proposed model is the least biased(0.001)model.Thus,the proposed GA-MOOANN is the most capable model,compared to other studied models,for estimating the suspended sediment yield in the entire Mahanadi river basin,India.The results also suggested that the proposed GA-MOO-ANN model is unable to estimate suspended sediment yield satisfactorily at gauge stations having very small catchment areas whereas performing satisfactorily on locations having moderate to the large catchment area.The models provide the best result at Tikarapara,the gauge station location in the extreme downstream,having the largest catchment area.     

A model for the generation of simultaneous daily discharges of two rivers at their point of confluence

A geomorphological study at the confluence of the Danube and the Isar in Bavaria required long series of daily discharges in both rivers. A model that generates simultaneous correlated streamflows in both rivers was developed and tested. The model is a modified shot noise model, first developed by Treiber (1975) for a single river, that was adapted to two rivers. It generates correlated pulses of events that produce flow for each river, and these pulses are then convoluted with a river specific systems function. The model, after being calibrated for the two rivers on the basis of 85 years of records, yields artificial series of discharges, in which the statistical properties of the historical records are reproduced. The performance of the model was tested with 20 generated series each 100 years long.     

A model for the generation of simultaneous daily discharges of two rivers at their point of confluence

A geomorphological study at the confluence of the Danube and the Isar in Bavaria required long series of daily discharges in both rivers. A model that generates simultaneous correlated streamflows in both rivers was developed and tested. The model is a modified shot noise model, first developed by Treiber (1975) for a single river, that was adapted to two rivers. It generates correlated pulses of events that produce flow for each river, and these pulses are then convoluted with a river specific systems function. The model, after being calibrated for the two rivers on the basis of 85 years of records, yields artificial series of discharges, in which the statistical properties of the historical records are reproduced. The performance of the model was tested with 20 generated series each 100 years long.     

Development of spatial regression models for predicting summer river temperatures from landscape characteristics: Implications for land and fisheries management

There is increasing demand for models that can accurately predict river temperature at the large spatial scales appropriate to river management. This paper combined summer water temperature data from a strategically designed, quality controlled network of 25 sites, with recently developed flexible spatial regression models, to understand and predict river temperature across a 3,000 km² river catchment. Minimum, mean and maximum temperatures were modelled as a function of nine potential landscape covariates that represented proxies for heat and water exchange processes. Generalised additive models were used to allow for flexible responses. Spatial structure in the river network data (local spatial variation) was accounted for by including river network smoothers. Minimum and mean temperatures decreased with increasing elevation, riparian woodland and channel gradient. Maximum temperatures increased with channel width. There was greater between‐river and between‐reach variability in all temperature metrics in lower‐order rivers indicating that increased monitoring effort should be focussed at these smaller scales. The combination of strategic network design and recently developed spatial statistical approaches employed in this study have not been used in previous studies of river temperature. The resulting catchment scale temperature models provide a valuable quantitative tool for understanding and predicting river temperature variability at the catchment scales relevant to land use planning and fisheries management and provide a template for future studies.     

Siltation by sediment-induced density currents

This paper describes the results of numerical experiments with a three-dimensional hydrodynamic and mud transport model in which sediment–fluid interaction is taken into account through the effects of hindered settling, buoyancy destruction in the turbulence k– model and sediment-induced barocline pressure gradients in the momentum equations. The model was applied to a schematic case representing a coastal area with a tidal river, navigation channel and harbour basin, and a real-world case, viz. Rotterdam harbour area in The Netherlands. The results show that the sediment transport into the harbour area, and subsequent siltation rates, increase by a factor 3 to 5 due to the sediment–fluid interaction. It is shown that the larger contribution stems from an increase in vertical gradients in suspended sediment.Responsible Editor: Jens Kappenberg     

River flow modelling: comparison of performance and evaluation of uncertainty using data-driven models and conceptual hydrological model

Hydrological and statistical models are playing an increasing role in hydrological forecasting, particularly for river basins with data of different temporal scales. In this study, statistical models, e.g. artificial neural networks, adaptive network-based fuzzy inference system, genetic programming, least squares support vector machine, multiple linear regression, were developed, based on parametric optimization methods such as particle swarm optimization (PSO), genetic algorithm (GA), and data-preprocessing techniques such as wavelet decomposition (WD) for river flow modelling using daily streamflow data from four hydrological stations for a period of 1954–2009. These models were used for 1-, 3- and 5-day streamflow forecasting and the better model was used for uncertainty evaluation using bootstrap resampling method. Meanwhile, a simple conceptual hydrological model GR4J was used to evaluate parametric uncertainty based on generalized likelihood uncertainty estimation method. Results indicated that: (1) GA and PSO did not help improve the forecast performance of the model. However, the hybrid model with WD significantly improved the forecast performance; (2) the hybrid model with WD as a data preprocessing procedure can clarify hydrological effects of water reservoirs and can capture peak high/low flow changes; (3) Forecast accuracy of data-driven models is significantly influenced by the availability of streamflow data. More human interferences from the upper to the lower East River basin can help to introduce greater uncertainty in streamflow forecasts; (4) The structure of GR4J may introduce larger parametric uncertainty at the Longchuan station than at the Boluo station in the East river basin. This study provides a theoretical background for data-driven model-based streamflow forecasting and a comprehensive view about data and parametric uncertainty in data-scarce river basins.     

On the importance of river hydrodynamics in simulating groundwater levels and baseflows

Research to date affirmed the key role of stream–aquifer interactions in integrated water resources management. The importance of river hydrodynamics on the spatial and temporal behaviour of groundwater was, however, not yet fully investigated. In contrast to the common approach where topography-based estimates of riverbed elevation may lead to inappropriate discretization and constant river stages, this study couples a fully hydrodynamic and one-dimensional river model to a two-dimensional catchment hydrological model. The surface and subsurface runoff, groundwater, and river components are integrated into a single modelling framework. The coupled model was applied to a medium sized catchment in Belgium with three model setups, in which the level of detail of representation of river hydrodynamics varies. Further model iterations were carried out for the most exhaustive setup to assess the importance of the bi-directional interactions between model components. Results show that higher details of river hydrodynamics help to improve the simulation of time-averaged groundwater levels. However, the impacts were not that clear for the time-varying groundwater levels. Moreover, visual and statistical model performance evaluation indicates a strong enhancement of the coupled models compared to the output from the hydrological model with respect to river discharge observations at catchment outlet and at internal stations. It also reveals the impact of river hydrodynamics on groundwater discharges when the most detailed setting delivered the highest performance among the three coupled models.