Modelling of resuspension due to fish activity:Mathematical modeling and annular flume experiments

A spatially averaged numerical model was developed to describe the erosion of cohesive sediment. Together with known empirical relations, the model comprises a new formulation for resuspension due to fish activity. Experiments on erosion of natural sediments in the annular flume at Aachen University are used for model calibration. Empirical coefficients were evaluated with genetic algorithms to achieve the best agreement between the model results and the experimental data. The presented model shows sufficient flexibility to account for various sediment properties, including different sediment sources, natural and artificial contaminants, presence or absence of aquatic organisms, and results in an average coefficient of determination, R2 = 90.5% between the model results and the experimental data. Model validation allows it to be assumed that different contaminants affect bed properties differently. Fish activity plays an essential role in correct resuspension prediction. Further sediment erosion experiments with carefully chosen conditions will allow a more comprehensive model evaluation. The presented model is intended to serve as a building block in the development of a hydraulic-sediment-biota model within the W3-Hydro: Water Quality Event Detection for Urban Water Security and Urban Water Management Based on Hydrotoxicological Investigations project that aims to improve the knowledge concerning bioavailability, transport, fate, and effects of contaminants on the aquatic environment.     

Using ADV backscatter strength for measuring suspended cohesive sediment concentration

Laboratory experiments were conducted at two institutes to reveal the relationship between acoustic backscatter strength and suspended sediment concentration (SSC). In total, three acoustic Doppler velocimeters (ADVs) with different frequencies (5, 10 and 16 MHz) were tested. Two different commercial clays and one natural sediment from Clay Bank site in the York River were checked for acoustic responses. The SSCs of selected sediments were artificially changed between a selected low and a high value in tap or de-ion water. Each ADV showed quite different backscatter responses depending on the sediment type and SSC. Not all devices had a good linear relationship between backscatter strength and SSC. Within a limited range of SSC, however, the backscatter strength can be well correlated with the SSC. Compared with optical backscattering sensor (OBS), the fluctuation of ADV backscatter signals was too noisy to be directly converted to the instantaneous changes of SSC due to high amplification ratio and small sampling volume. For the more accurate signal conversion for finding the fluctuation of SSC, the ensemble average should be applied to increase the signal-to-noise ratio. There are unexpected responses for the averaged backscatter wave strength: (1) high signals from small particles but low signals from large particles; and (2) two linear segments in calibration slope. These phenomena would be most likely caused by the different gain setting built in ADVs. The different acoustic responses to flocculation might also contribute somewhat if flocs are tightly packed. This study suggests that an ADV could be a useful instrument to estimate suspended cohesive sediment concentration and its fluctuation if the above concerns are clarified.     

Non-equilibrium concentration profile formulas of suspended sediment and their preliminary applications

The vertical concentration profiles in non-equilibrium sediment transport processes generally deviate from the equilibrium concentration distribution of suspended sediment. The non-equilibrium concentration profile formulas currently available are those of Han and Brown, respectively. However, the complexity of these formulas limits their use in practical calculations. To improve the usefulness of these formulas, the unknown parameters in Han’s formula are reduced from three to two, and the thre...     

Vertical profiles of fluid velocity and suspended sediment concentration in nearshore

Based on the power function of velocity and the friction velocity,a velocity profile is obtained.By solving the Schmidt’s diffusion equation,an equilibrium suspended sediment concentration profile is further deduced.The profiles of velocity and suspended sediment concentration agree well with the field data,and the profile of suspended sediment concentration avoids the unreasonableness of the classical Rouse profile such as a zero value at the water surface.According to these profiles,an expression which is easy to use for calculating the suspended sediment transport rate is derived.     

Dimensionless critical shear stress evaluation from flume experiments using different gravel beds

Flume experiments were conducted using four different gravel beds (D₅₀ + 12–39 mm) and a range of marked particles (10–65 mm). The shear stresses were evaluated from friction velocities, when initial movement of marked particles occurred. Two kinds of equations were produced: first for the threshold of initial movement, and second for generalized movement. Equations of the type 0_c + a(D_i/D₅₀)^b, as proposed by Andrews (1983) are applicable even if the material is relatively well sorted. However, the values of a and b are lower (respectively 0·050 and -0·70) for initial movement. Generalized movement requires a higher shear stress (a + 0·068 and b + -0·80). D₉₀ of the bed material and y₀ (the bed roughness parameter) were also used as reference values in place of D₅₀. They produced lower values than in natural streams, mainly owing to the fact that the material used in the flume is better sorted: clusters are less well developed and the bed roughness is lower.     

Velocity profiles and bed shear stress over various bed configurations in a river bend

Vertical velocity profiles measured over various bed configurations (plane beds, ripples, and dunes) in. the meandering River South Esk, Glen Clova, Scotland are presented on semilogarithmic paper. Local bed shear stress and roughness height are calculated from the lowermost parts of the profiles using the Karman-Prandtl law of the wall; these parameters, and the geometrical properties of the profiles, are related to the various bed configurations. A graphical model is used to identify profiles developed on specific regions of dune geometry, in order to discriminate those profiles that define bed shear effective in transporting sediment over dunes. An assessment is made of the errors involved in estimating local mean velocity from extrapolating the law of the wall to the water surface. A Darcy-Weisbach friction coefficient is related to bed configuration and local stream power.     

A study of suspended sediment concentration in Yangshan deep-water port in Shanghai,China

Suspended sediment concentration (SSC) plays an important role in the estuarine environment.Its spatial or temporal variations in coastal zones and estuaries indicate that sediments are suspended,trans...     

Use of Large-Eddy Simulation for the bed shear stress estimation over a dune

Environmental flows are generally characterized by complex bed morphology and high current speeds. Such configurations favor the formation of vortex structures that strongly affect hydrody-namics and sediment transport. Large-Eddy Simulation (LES) enables investigation of the dynam-ics of the largest turbulence scales and, thanks to enhanced calculation resources, has now become applicable for simulating environmental flows. In this paper, a LES approach is developed in a CFD code (TELEMAC-3D), which was originally developed to simulate free surface flows using RANS methods. The present developments involve implementing subgrid models, boundary con-ditions and numerical schemes suitable for LES. The LES version of TELEMAC-3D was validated by comparing results on the model with experimental data for flow past a cylinder. Then, the model was applied to a test case representing flow over dunes. After validating the hydrodynamics, the model was used to assess the bottom shear stress, using both a RANS and a LES approach. Com-parison highlighted the potential contribution of LES to investigating the hydrodynamic forces acting on the bottom.     

Artificial neural network simulation for prediction of suspended sediment concentration in the River Ramganga,Ganges Basin,India

The relation between the water discharge (Q) and suspended sediment concentration (SSC) of the River Ramganga at Bareilly, Uttar Pradesh, in the Himalayas, has been modeled using Artificial Neural Networks (ANNs). The current study validates the practical capability and usefulness of this tool for simulating complex nonlinear, real world, river system processes in the Himalayan scenario. The modeling approach is based on the time series data collected from January to December (2008-2010) for Q and SSC. Three ANNs (T1-T3) with different network configurations have been developed and trained using the Levenberg Marquardt Back Propagation Algorithm in the Matlab routines. Networks were optimized using the enumeration technique, and, finally, the best network is used to predict the SSC values for the year 2011. The values thus obtained through the ANN model are compared with the observed values of SSC. The coefficient of determination (R2), for the optimal network was found to be 0.99. The study not only provides insight into ANN modeling in the Himalayan river scenario, but it also focuses on the importance of understanding a river basin and the factors that affect the SSC, before attempting to model it. Despite the temporal variations in the study area, it is possible to model and successfully predict the SSC values with very simplistic ANN models.     

Modeling depth-averaged velocity and bed shear stress in compound channels with emergent and submerged vegetation

This paper presents an approach to modeling the depth-averaged velocity and bed shear stress in compound channels with emergent and submerged vegetation. The depth-averaged equation of vegetated compound channel flow is given by considering the drag force and the blockage effect of vegetation, based on the Shiono and Knight method (1991) [40]. The analytical solution to the transverse variation of depth-averaged velocity is presented, including the effects of bed friction, lateral momentum transfer, secondary flows and drag force due to vegetation. The model is then applied to compound channels with completely vegetated floodplains and with one-line vegetation along the floodplain edge. The modeled results agree well with the available experimental data, indicating that the proposed model is capable of accurately predicting the lateral distributions of depth-averaged velocity and bed shear stress in vegetated compound channels with secondary flows. The secondary flow parameter and dimensionless eddy viscosity are also discussed and analyzed. The study shows that the sign of the secondary flow parameter is determined by the rotational direction of secondary current cells and its value is dependent on the flow depth. In the application of the model, ignoring the secondary flow leads to a large computational error, especially in the non-vegetated main channel.     

Using velocimeter signal to noise ratio as a surrogate measure of suspended mud concentration

This study examines the relationship between suspended sediment concentration (SSC) and the signal to noise ratio (SNR) recorded by a 6 MHz Nortek Vector velocimeter in a laboratory water tank using four different synthetic and natural mud mixtures and different combinations of the user-set Vector parameters transmit power level and velocity range. For concentrations less than 1500 mg/l (1.5 g/l), a region of linearity between the logarithm of concentration and time-average SNR was found for all sediment types and transmitter power level settings. Within this concentration range, the experimental data was used to develop calibrated equations of the form, log(SSC)=c₁SNR+c₂; R² values for all calibrated equations were greater than 0.98, suggesting that properly calibrated relations can yield accurate time-averaged SSC measurements using Vector measured SNR. An analysis of the general calibration equation indicated that the predicted SSC values are sensitive to changes in the coefficient values for c₁ and c₂. Even small (10%) deviations in coefficient values resulted in 20%-65% changes in the predicted SSC. Variation in c₁ and c₂ values among all four mud mixtures were significant enough that the calibrated equations could not be used interchangeably. This was true even among three samples that had similar particle-size distributions. Translation of raw 32 Hz SNR data to 32 Hz SSC time series produced excessively large variation in the SSC time series. Several smoothing and filtering schemes were examined to reduce the magnitude of these fluctuations to more reasonable levels. Of the methods tested, a two-sided moving average functioned best at removing fine-scale variation while retaining larger-scale trends. A 96-point (3 Hz) averaging window brought 98.6% of the Vector estimated SSC time series values to within ±10% of the time-average physical samples. Impacts of turbulent kinetic energy and sampling volume size on instrument recorded SNR were also empirically examined.     

A comparison of instrumental dewatering methods for the separation and concentration of suspended sediment for subsequent trace element analysis

A comparison involving both field and laboratory trials was performed to evaluate the utility of two continuous-flow centrifuges and a tangential-flow filtration system for dewatering suspended sediments for subsequent trace element analysis. Although recovery efficiencies for the various devices differ, the analytical results from the separated suspended sediments indicate that any of the tested units can be used effectively and precisely for dewatering. Further, the three devices appear to concentrate and dewater suspended sediments in such a manner as to be equivalent to that which could be obtained by in-line filtration. Only the tangential-flow filtration system appears capable of providing both a dewatered sediment sample and a potentially usable effluent, which can be analysed for dissolved trace elements. The continuous-flow centrifuges can process whole water at an influent feed rate of 41 per minute; however, when suspended sediment concentrations are low (<30mg^?1), when small volumes of whole water are to be processed (30 to 401), or when suspended sediment mean grain size is very fine (<10 μm), influent feed rates of 21 per minute may be more efficient. Tangential-flow filtration can be used to process samples at the rate of 11 per minute.     

Linear spectral unmixing algorithm for modelling suspended sediment concentration of flash floods,upper Tekeze River,Ethiopia

Flash floods are the highest sediment transporting agent,but are inaccessible for in-situ sampling and have rarely been analyzed by remote sensing technology.Laboratory and field experiments were done to develop linear spectral unmixing(LSU) remote sensing model and evaluate its performance in simulating the suspended sediment concentration(SSC) in flash floods.The models were developed from continuous monitoring in the laboratory and the onsite spectral signature of river bed sediment deposits and flash floods in the Tekeze River and in its tributary,the Tsirare River.The Pearson correlation coefficient was used to determine the variability of correlations between reflectance and SSCs.The coefficient of determination(R2) and root mean square of error(RMSE) were used to evaluate the performance of the generated models.The results found that the Pearson correlation coefficient between SSCs and reflectance varied based on the level of the SSCs,geological colors,and grain sizes.The performance of the LSU model and empirical remote sensing approaches were computed to be R2=0.92,and RMSE=±0.76 g/1 in the Tsirare River and R2=0.91,and RMSE=±0.73 g/1 in the Tekeze River and R2=0.81,RMSE=±2.65 g/l in the Tsirare river and R2=0.76,RMSE=±10.87 g/l in the Tekeze River,respectively.Hence,the LSU approach of remote sensing was found to be relatively accurate in monitoring and modeling the variability of SSCs that could be applied to the upper Tekeze River basin.     

Experimental investigation on local shear stress and turbulence intensities over a rough non-uniform bed with and without sediment using 2D particle image velocimetry

The current work focuses on locally resolving velocities,turbulence,and shear stresses over a rough bed with locally non-uniform character.A nonporous subsurface layer and fixed interfacial sublayer of gravel and sand were water-worked to a nature-like bed form and additionally sealed in a hydraulic flume.Two-dimensional Particle Image Velocimetry(2 D-PIV) was applied in the vertical plane of the experimental flume axis.Runs with clear water and weak sediment transport were done under slightly supercritical flow to ensure sediment transport conditions without formation of considerable sediment deposits or dunes.The study design included analyzing the double-averaged flow parameters of the entire measurement domain and investigating the flow development at 14 consecutive vertical subsections.Local geometrical variabilities as well the presence of sediment were mainly reflected in the vertical velocity component.Whereas the vertical velocity decreased over the entire depth in presence of sediment transport,the streamwise velocity profile was reduced only within the interfacial sublayer.In the region with decelerating flow conditions,however,the streamwise velocity profile systematically increased along the entire depth extent.The increase in the main velocity(reduction of flow resistance)correlated with a decrease of the turbulent shear and main normal stresses.Therefore,effects of rough bed smoothening and drag force reduction were experimentally documented within the interfacial sublayer due to mobile sediment.Moreover,the current study leads to the conclusion that in nonuniform flows the maximum Reynolds stress values are a better predictor for the bed shear stress than the linearly extrapolated Reynolds stress profile.This is an important finding because,in natural flows,uniform conditions are rare.     

Capacitive sensing technique for silt suspended sediment concentration monitoring

Automated, real-time, and continuous techniques for monitoring suspended sediment concentration in rivers and reservoirs can play an important role in the improvement of the quantity and quality of sediment data, and are valuable to the management of water environment, water conservancy, hazard prevention, and water resources. Research in the monitoring techniques has examined the possibility of using the characteristics of dielectric constants for detecting soil moisture and concentration of air-water two-phase flow, based on the fact that dielectric constants of sediment, air and water are different. A capacitance sensor was developed to monitor the silt suspended sediment concentration (SSSC) in a recent study, following the principle that as SSSC increases in the sediment-water mixture, the apparent dielectric constant of the water sample also increases and therefore the capacitance detected by the sensing system also increases. It is demonstrated that the variations in the concentration of silt sediment correlates positively with the variations in observed capacitance in a linear fashion, and correlates negatively with voltage outputs but also in a linear fashion. The correlation coefficients reached above 0.98. The overall errors in estimated concentrations range between 0.26% and 2.91%. Elements in the capacitance sensor system such as the frequencies of the signal generating system, areas of the electrode plates, and effects of sample temperature have also been evaluated. The results illustrated that the capacitance sensor techniques can be applied to monitoring SSSC automatically and continuously. Also, the range of SSSC in the experiment reached 200 kg/m³; therefore, the application of this technique in practical SSSC monitoring is worthy of further research.     

Response of nephelometric turbidity to hydrodynamic particle size of fine suspended sediment

Turbidity is used as a surrogate for suspended sediment concentration (SSC), and as a regulatory tool for indicating land use disturbance and environmental protection. Turbidity relates linearly to suspended material, however, can show non-linear responses to particulate organic matter (POM), concomitant with changes in particle size distribution (PSD). In the paper the influence of ultra-fine particulate matter (UFPM) on specific turbidity and its association with POM in suspended sediment are shown for alpine rivers in the Southern Alps of New Zealand. The approach was two-fold: a field-based investigation of the relations between SSC, POM, and turbidity sampled during event flow; and experimental work on hydrodynamic particle size effects on SSC, POM, PSD, and turbidity. Specific turbidity changes over event flow and are sensitive to increasing proportional amounts of sand, UFPM, and POM in suspension. Furthermore, the UFPM is the size fraction (<6 μm) where POM increases. The implications of the current study are that the slopes of turbidity-SSC relations are undesirable in locations that may be dominated by cyclic release of POM or distinct pulses of fine-grained material. At locations where the turbidity-SSC slopes approximate 2, the POM proportion is usually <10% of the total suspended load. However, when turbidity-SSC slopes are <1 this is likely caused by high amounts of side-scatter from UFPM concomitant with higher proportions of POM. Thus, the use of turbidity as a proxy for determining SSC may have serious consequences for the measurement of representative suspended sediment data, particularly in locations where POM may be a significant contributor to overall suspended load.     

Modelling suspended sediment concentration using artificial neural networks for Gangotri glacier

The dynamics of suspended sediment involves inherent non‐linearity and complexity because of existence of both spatial variability of the basin characteristics and temporal climatic patterns. This complexity, therefore, leads to inaccurate prediction by the conventional sediment rating curve (SRC) and other empirical methods. Over past few decades, artificial neural networks (ANNs) have emerged as one of the advanced modelling techniques capable of addressing inherent non‐linearity in the hydrological processes. In the present study, feed‐forward back propagation (FFBP) algorithm of ANNs is used to model stage–discharge–suspended sediment relationship for ablation season (May–September) for melt runoff released from Gangotri glacier, one of the largest glaciers in Himalaya. The simulations have been carried out on primary data of suspended sediment concentration (SSC) discharge and stage for ablation season of 11‐year period (1999–2009). Combinations of different input vectors (viz. stage, discharge and SSC) for present and previous days are considered for development of the ANN models and examining the effects of input vectors. Further, based on model performance indices for training and testing phase, a suitable modelling approach with appropriate model input structure is suggested. The conventional SRC method is also used for modelling discharge–sediment relationship and performance of developed models is evaluated by statistical indices, namely; root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R²). Statistically, the performance of ANN‐based models is found to be superior as compared to SRC method in terms of the selected performance indices in simulating the daily SSC. The study reveals suitability of ANN approach for simulation and estimation of daily SSC in glacier melt runoff and, therefore, opens new avenues of research for application of hybrid soft computing models in glacier hydrology. Copyright © 2015 John Wiley & Sons, Ltd.