An evaluation of sediment rating curves for estimating suspended sediment concentrations for subsequent flux calculations

In the absence of actual suspended sediment concentration (SSC) measurements, hydrologists have used sediment rating (sediment transport) curves to estimate (predict) SSCs for subsequent flux calculations. Various evaluations of the sediment rating‐curve method were made using data from long‐term, daily sediment‐measuring sites within large (>1 000 000 km²), medium (<1 000 000 to >1000 km²), and small (<1000 km²) river basins in the USA and Europe relative to the estimation of suspended sediment fluxes. The evaluations address such issues as the accuracy of flux estimations for various levels of temporal resolution as well as the impact of sampling frequency on the magnitude of flux estimation errors. The sediment rating‐curve method tends to underpredict high, and overpredict low SSCs. As such, the range of errors associated with concomitant flux estimates for relatively short time‐frames (e.g. daily, weekly) are likely to be substantially larger than those associated with longer time‐frames (e.g. quarterly, annually) because the over‐ and underpredictions do not have sufficient time to balance each other. Hence, when error limits must be kept under ±20%, temporal resolution probably should be limited to quarterly or greater. The evaluations indicate that over periods of 20 or more years, errors of <1% can be achieved using a single sediment rating curve based on data spanning the entire period. However, somewhat better estimates for the entire period, and markedly better annual estimates within the period, can be obtained if individual annual sediment rating curves are used instead. Relatively accurate (errors <±20%) annual suspended sediment fluxes can be obtained from hydrologically based monthly measurements/samples. For 5‐year periods or longer, similar results can be obtained from measurements/samples collected once every 2 months. In either case, hydrologically based sampling, as opposed to calendar‐based sampling is likely to limit the magnitude of flux estimation errors. Published in 2003 John Wiley & Sons, Ltd.     

Application of soft-computing techniques in forecasting sediment load and concentration

ABSTRACT

This paper investigates conventional and soft-computing methods for the estimation of suspended sediment concentration (SSC) and load (SSL) in rivers. Frequently used methods of sediment rate curve (SRC) and multi-nonlinear regression, and soft-computing methods of multi-layer perceptron, multi-linear regression and adaptive neuro-fuzzy inference system are implemented using various hydrological and hydraulic parameters for the Little Kickapoo Creek Watershed, Illinois, USA. All methods performed equally well in the estimation of SSL, without any noticeable outperformance from any from the methods. However, the application of soft-computing methods decreased SSC estimation errors considerably as compared to the results of SRC. The results are significant in the way they reconcile traditionally used hydrological parameters into the soft-computing methods. Overall, soft-computing methods are recommended for the estimation of SSC in rivers because of their reasonably better performance and ease of implementation.     

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.     

Estimation of suspended sediment concentration and yield using linear models,random forests and quantile regression forests

For sediment yield estimation, intermittent measurements of suspended sediment concentration (SSC) have to be interpolated to derive a continuous sedigraph. Traditionally, sediment rating curves (SRCs) based on univariate linear regression of discharge and SSC (or the logarithms thereof) are used but alternative approaches (e.g. fuzzy logic, artificial neural networks, etc.) exist. This paper presents a comparison of the applicability of traditional SRCs, generalized linear models (GLMs) and non‐parametric regression using Random Forests (RF) and Quantile Regression Forests (QRF) applied to a dataset of SSC obtained for four subcatchments (0·08, 41, 145 and 445 km²) in the Central Spanish Pyrenees. The observed SSCs are highly variable and range over six orders of magnitude. For these data, traditional SRCs performed inadequately due to the over‐simplification of relating SSC solely to discharge. Instead, the multitude of acting processes required more flexibility to model these nonlinear relationships. Thus, alternative advanced machine learning techniques that have been successfully applied in other disciplines were tested. GLMs provide the option of including other relevant process variables (e.g. rainfall intensities and temporal information) but require the selection of the most appropriate predictors. For the given datasets, the investigated variable selection methods produced inconsistent results. All proposed GLMs showed an inferior performance, whereas RF and QRF proved to be very robust and performed favourably for reproducing sediment dynamics. QRF additionally provides estimates on the accuracy of the predictions and thus allows the assessment of uncertainties in the estimated sediment yield that is not commonly found in other methods. The capabilities of RF and QRF concerning the interpretation of predictor effects are also outlined. Copyright © 2008 John Wiley & Sons, Ltd.     

Real-time prediction of the peak suspended sediment concentration and sediment yield of the Lao-Nung River during storms

Based on rainfall erosion of soil and suspended sediment transport in storm events, a method is proposed to predict peak suspended sediment concentration and suspended sediment yield in watersheds based on rainfall characteristics prior to peak rainfall intensity. The rainfall characteristics factors that dominate peak suspended sediment concentration C_p are rainfall erosion factor R_ef, first peak rainfall intensity of area-average rainfall i_p1 and antecedent precipitation index I_ap; the rainfall characteristics factors that dominate suspended sediment yield Y_ss in storm events are total rainfall P, suspended sediment yield factor R_sf and antecedent precipitation index I_ap. This research focuses on watersheds in Liau-Kwei observation station along Lao-Nung River in southern Taiwan as the research object, and adopts the PSED-model to simulate the discharge hydrograph, suspended sediment concentration hydrograph and suspended sediment yield in 11 storm events for analysis. The analytical results show that there is a good correlation between the above-mentioned rainfall characteristics factors and C_p as well as Y_ss, thus enabling C_p and Y_ss to be predicted by using Expressions (13) and (14). These two expressions are utilized to predict C_p and Y_ss of Typhoon Morakot in 2009, and the results are compared with those from simulation by using the PSED-model. The result of comparison shows there is a good capability in predicting. For the watersheds where it is necessary to predict C_p and Y_ss of a storm event for the benefit of effective operation of water resource facilities, the aforesaid rainfall characteristics factors can be utilized to establish applicable models for prediction.     

Evaluating suspended sediment and turbidity reduction projects in a glacially conditioned catchment through dynamic regression and fluvial process-based modelling

Elevated turbidity (T_n) and suspended sediment concentrations (SSC) during and following flood events can degrade water supply quality and aquatic ecosystem integrity. Streams draining glacially conditioned mountainous terrain, such as those in the Catskill Mountains of New York State, are particularly susceptible to high levels of T_n and SSC sourced from erosional contact with glacial-related sediment. This study forwards a novel approach to evaluate the effectiveness of stream restoration best management practices (BMPs) meant to reduce stream T_n and SSC, and demonstrates the approach within the Stony Clove sub-basin of the Catskills, a water supply source for New York City. The proposed approach is designed to isolate BMP effects from natural trends in T_n and SSC caused by trends in discharge and shifts in average T_n or SSC per unit discharge (Q) following large flood events. We develop Dynamic Linear Models (DLMs) to quantify how T_n-Q and SSC-Q relationships change over time at monitoring stations upstream and downstream of BMPs within the Stony Clove and in three other sub-basins without BMPs, providing observational evidence of BMP effectiveness. A process-based model, the River Erosion Model, is then developed to simulate natural, hydrology-driven SSC-Q dynamics in the Stony Clove sub-basin (absent of BMP effects). We use DLMs to compare the modelled and observed SSC-Q dynamics and isolate the influence of the BMPs. Results suggest that observed reductions in SSC and T_n in the Stony Clove sub-basin have been driven by a combination of declining streamflow and the installed BMPs, confirming the utility of the BMPs for the monitored hydrologic conditions.     

Estimation of suspended sediment concentration in the Saint John River using rating curves and a machine learning approach

ABSTRACT

Sedimentation in navigable waterways and harbours is of concern for many water and port managers. One potential source of variability in sedimentation is the annual sediment load of the river that empties in the harbour. The main objective of this study was to use some of the regularly monitored hydro-meteorological variables to compare estimates of hourly suspended sediment concentration in the Saint John River using a sediment rating curve and a model tree (M5?) with different combinations of predictors. Estimated suspended sediment concentrations were multiplied by measured flows to estimate suspended sediment loads. Best results were obtained using M5? with four predictors, returning an R² of 0.72 on calibration data and an R² of 0.46 on validation data. Total load was underestimated by 1.41% for the calibration period and overestimated by 2.38% for the validation period. Overall, the model tree approach is suggested for its relative ease of implementation and constant performance.

EDITOR M.C. Acreman; ASSOCIATE EDITOR B. Touaibia     

Suspended sediment concentration and the ripple–dune transition

Flume experiments were conducted in order to monitor changes in flow turbulence intensity and suspended sediment concentration at seven stages across the ripple–dune transition and at three different positions above the bed surface. Three‐dimensional velocity measurements were obtained using an acoustic Doppler velocimeter (ADV). Suspended sediment concentration (SSC) was monitored indirectly using ADV signal amplitude. Although limited to time‐averaged parameters, the analysis reveals that SSC varies significantly with stage across the transition and with sampling height. The statistical analysis also reveals an apparent uniformity of suspended sediment concentration with height above the bed in the lower half of the flow depth at the critical stage in the transition from ripples to dunes. This is also the stage at which turbulence intensity is maximized. Statistically significant correlations were also observed between suspended sediment concentrations and root‐mean‐square values of vertical velocity fluctuations. These correlations reflect the various levels of shear‐layer activity and the distinct turbulent flow regions across the transition. Conversely, time‐averaged values of Reynolds shear stress exhibit a very weak relationship with suspended sediment concentrations. Copyright © 2004 John Wiley & Sons, Ltd.     

The effects of sample scheduling and sample numbers on estimates of the annual fluxes of suspended sediment in fluvial systems

Since the 1970s, there has been both continuing and growing interest in developing accurate estimates of the annual fluvial transport (fluxes and loads) of suspended sediment and sediment‐associated chemical constituents. This study provides an evaluation of the effects of manual sample numbers (from 4 to 12 year^?1) and sample scheduling (random‐based, calendar‐based and hydrology‐based) on the precision, bias and accuracy of annual suspended sediment flux estimates. The evaluation is based on data from selected US Geological Survey daily suspended sediment stations in the USA and covers basins ranging in area from just over 900 km² to nearly 2 million km² and annual suspended sediment fluxes ranging from about 4 Kt year^?1 to about 200 Mt year^?1. The results appear to indicate that there is a scale effect for random‐based and calendar‐based sampling schemes, with larger sample numbers required as basin size decreases. All the sampling schemes evaluated display some level of positive (overestimates) or negative (underestimates) bias. The study further indicates that hydrology‐based sampling schemes are likely to generate the most accurate annual suspended sediment flux estimates with the fewest number of samples, regardless of basin size. This type of scheme seems most appropriate when the determination of suspended sediment concentrations, sediment‐associated chemical concentrations, annual suspended sediment and annual suspended sediment‐associated chemical fluxes only represent a few of the parameters of interest in multidisciplinary, multiparameter monitoring programmes. The results are just as applicable to the calibration of autosamplers/suspended sediment surrogates currently used to measure/estimate suspended sediment concentrations and ultimately, annual suspended sediment fluxes, because manual samples are required to adjust the sample data/measurements generated by these techniques so that they provide depth‐integrated and cross‐sectionally representative data. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.     

Using sediment rating parameters to evaluate the changes in sediment transport regimes in the middle Yellow River basin,China

This study analyses the changes in sediment transport regimes in the middle Yellow River basin (MYRB) using sediment rating parameters. Daily streamflow and suspended sediment concentration data were collected at 35 hydrological stations from the 1950s to 2016, which can be divided into three periods based on the type and intensity of human activities: the base stage before 1970, the restraining stage from 1971 to 1989, and the restoration stage after 2002. Data within each period were fitted by log‐linear sediment rating curves and the sediment rating parameters were utilized to analyse the spatial and temporal variations in sediment transport regimes. The results show that sediment rating parameters are indicative of sediment transport regimes. In the base stage and the restraining stage, the hydrological stations can be categorized into four groups based on their locations on the rating parameter plot. The stations with small drainage basins were characterized by the highest sediment transport regime, followed by those located in the coarse‐particle zone, the loess zone, and the mountainous/forest zone. In the restoration stage, the difference in sediment transport regimes between different geomorphic zones became less distinguishable than in previous stages. During the transition from the base stage to the restraining stage, sediment rating parameters showed no significant changes in sediment transport regimes in all four geomorphic groups. During the transition from the restraining stage to the restoration stage, significant changes were observed in the coarse‐particle zone and the mountain/forest zone, indicating that the revegetation programme and large reservoirs imposed a stronger influence on sediment transport regimes in these two zones than in the rest of the MYRB. This study provides theoretical support for evaluating sediment transport regimes with sediment rating parameters.     

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.     

Time‐varying suspended sediment‐discharge rating curves to estimate climate impacts on fluvial sediment transport

This study presents time‐varying suspended sediment‐discharge rating curves to model suspended‐sediment concentrations (SSCs) under alternative climate scenarios. The proposed models account for hysteresis at multiple time scales, with particular attention given to systematic shifts in sediment transport following large floods (long‐term hysteresis). A series of nested formulations are tested to evaluate the elements embedded in the proposed models in a case study watershed that supplies drinking water to New York City. To maximize available data for model development, a dynamic regression model is used to estimate SSC based on denser records of turbidity, where the parameters of this regression are allowed to vary over time to account for potential changes in the turbidity‐SSC relationship. After validating the proposed rating curves, we compare simulations of SSC among a subset of models in a climate change impact assessment using an ensemble of flow simulations generated using a stochastic weather generator and hydrologic model. We also examine SSC estimates under synthetic floods generated using a peaks‐over‐threshold model. Our results indicate that estimates of extreme SSC under new climate and hydrologic scenarios can vary widely depending on the selected model and may be significantly underestimated if long‐term hysteresis is ignored when simulating impacts under sequences of large storm event. Based on the climate change scenarios explored here, average annual maximum SSC could increase by as much as 2.45 times over historical values.     

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.     

Application of Hausdorff fractal derivative to the determination of the vertical sediment concentration distribution

The Rouse formula and its variants have been widely used to calculate the steady-state vertical concentration distribution for suspended sediment in steady sediment-laden flows, where the diffusive flux is assumed to be Fickian. Turbulent flow, however, exhibits fractal properties, leading to non-Fickian diffusive flux for sediment particles. To characterize non-Fickian dynamics of suspended sediment, the current study proposes a Hausdorff fractal derivative based advection-dispersion equation(H...     

考虑采砂影响的鄱阳湖丰水期悬浮泥沙浓度模拟

针对受采砂活动影响显著的鄱阳湖高浑浊水体,结合数值模拟和遥感技术,利用已有的鄱阳湖采砂区遥感监测结果,在构建的鄱阳湖水动力-悬浮泥沙输移模型中添加泥沙点源,对2011年7月1-31日采砂影响下的鄱阳湖丰水期悬浮泥沙浓度进行数值模拟.利用悬浮泥沙浓度实测数据和MODIS影像反演结果对模拟结果的有效验证表明,考虑采砂影响后,悬浮泥沙浓度模拟值与实测值具有强相关关系,确定性系数为0.831,均方根误差为15.5 mg/L,悬浮泥沙浓度空间分布趋势与遥感反演结果基本一致.模拟结果显示,采砂活动对鄱阳湖南部主湖区、河流入湖口影响较小,其主要影响由南向北,经棠荫以西和松门山岛以北航道、入江水道延伸到湖口区域,是鄱阳湖北湖区高浑浊水体形成的重要原因.     

Understanding the effect of catchment characteristics on suspended sediment dynamics during flood events

Hysteresis in the relationship between suspended sediment concentration and flow during run-off events is commonly used to inform on sediment sources and hydrological pathways. Less attention, however, has been paid to comparing the water and sediment hydrographs, which provide a more direct appreciation of in-event sediment dynamics and their relationship with the upstream catchment characteristics. The aim of this study is to better understand the catchment and hydrological controls on the phasing of water and sediment discharges during events and, in particular, to explore what controls sediment concentrations late on event recessions. Continuous records of flow and turbidity data (calibrated to suspended sediment concentration) were collected from 17 catchments across New Zealand for this purpose. Relationships between event sediment yield and peak flow showed, as anticipated, higher event sediment loads were generated in pasture compared with forested catchments and were also higher from catchments in more erodible terrain. One novel result was that these differences were greater during smaller, more frequent events, whereas the loads from larger flood events tended to converge between pasture and forest catchments. Another novel result was that event sediment load tends to be evenly split between rising and falling stages of the hydrograph in pasture catchments, but forested catchments yield more of their event loads on flood recessions, probably because of delayed erosion or more sediment sources remote from the channel network. Land cover, distance of the sediment sources from the monitoring site, and size of the catchments control sediment concentrations late on event recession. Pasture-dominated and more erodible catchments show longer sediment recessions and therefore stay dirtier for longer time periods. In addition, the size of previous flood events appeared to control the extent of sediment exhaustion after the flood peaks in some catchments.     

Present-day sediment dynamics of the Sanaga catchment (Cameroon): from the total suspended sediment (TSS) to erosion balance

ABSTRACT

Total suspended sediment (TSS) data for 1960–1970 and from recent investigations (1990–2000) are used to evaluate the variability in sediment yield of the Sanaga catchment (Cameroon) and the equivalent rates of erosion. At the annual and seasonal time scales, total suspended sediment concentrations for the Mbam sub-catchment are three to four times higher than for the Sanaga basin, reflecting the higher sensitivity of the former to erosion. Classical clockwise hysteresis loops are observed in both sub-catchments, despite a significant increase in human-induced catchment changes. At the multi-year time frame (over a 40-year period), it appears that the second half of the 1990s is marked by a downward trend in TSS. This shift is due to the control infrastructures (river impoundments and ponds) installed in certain parts of the whole catchment, combined with a drop in annual rainfall and river discharge.

Editor Z.W. Kundzewicz; Associate editor not assigned     

Factors controlling variations in suspended sediment concentration for single-valued sediment rating curves,Fraser River,British Columbia,Canada

Functional (regression) and cause-and-effect analytical methods were employed in the investigation of factors controlling single-value sediment–discharge relationships for individual hydrological events in the Fraser River Basin. Of 1025 hydrological events identified in the 97 years of the 9-stations discharge record monitored by the Water Survey of Canada (1960–1988), 49 were associated with linear, non-linear (concave and convex) sediment rating curves. Analysis revealed that time of events offered a partial explanation for the occurrence of single-valued curves because events occurring in isolation or in quick succession did not always produce single-valued curves owing to variations in hydrograph characteristics and temporal and spatial peak attenuation factors. Hydrologically, linear and non-linear sediment rating curves were distinguished by the influence of preceding discharge or antecedent moisture, which tends to generate quick or delayed runoff, thereby causing rapid or slow increases in sediment concentration in concert with discharge changes. Hydraulically, linear curves were shown to be controlled by rates of stream bed scour (rising stage) similar to those for channel filling (falling stage); concave curves by rates of scouring (rising stage) similar to those of filling but different from those of rescouring (falling stage); and convex curves by rates of filling and scouring (rising stage) different from those of filling and rescouring (falling stages), all in relation to the timing of the exceedance of the threshold discharge for stream bed scour. Meteorologically, bed scour and fill approximately coincided with the timing of precipitation, if any, on the rising and/or falling stages under subzero (T≤0 °C), low (1≤T≤9 °C) and moderate (10≤T≤19 °C) temperature conditions. It is concluded that a combination of temporal, spatial, hydrological, hydraulic and meteorological factors control variations in sediment concentration during single hydrological events on the Fraser River in a complex fashion. Multivariate analysis of these factors should greatly improve prediction of sediment transport in the Fraser River Basin. © 1998 John Wiley & Sons, Ltd.     

Pumped rainfall simulators: the impact of rain pulses on sediment concentration and size

Many pumped rainfall simulators used in soil erosion studies use pulsed rain to control the rainfall intensity. We examined the effect of the rain pulsing on sediment concentration and size using three different pulse cycles with the same rainfall intensity. There was considerable variation in sediment concentration through the pulse cycle: the highest concentration was up to four times that of the lowest concentration. Furthermore, the particle size distribution also varied: the peak median particle size was double the lowest median particle size. The magnitude of differences in sediment concentration and particle size were greater the longer the pulse cycle and these dynamics will vary between rainfall simulators and studies. We suggest the impact of the pulsing on sediment is significant and should be investigated prior to experimentation so that sampling periods are designed to avoid bias introduced by fine temporal scale sediment dynamics. Copyright © 2009 John Wiley & Sons, Ltd.     

Response of river channel patterns to the spatially varying suspended sediment concentrations

River channel pattern transformation is dealt with in a broad background of suspended sediment concentration, varying from low, medium, high to hyperconcentration. Based on data from about 100 alluvial rivers in China, suspended sediment transport rate has been plotted against mean annual water discharge, showing that all points can be divided into four belts by three straight lines, as stable braided pattern, meandering pattern with ordinary sediment concentrations, wandering braided pattern, and meandering pattern with hyperconcentration of sediment. This picture of channel pattern transformation can be well explained by the law of the water flow's energy expenditure varying with its sediment concentration. The energy expenditure increases with sediment concentration, reaching a maximum, then declines. Rivers falling in different ranges of sediment concentrations adjust their own energy expenditure in different manners, leading to occurrence of different channel patterns. Project supported by the National Natural Science Foundation of China (Grant No. 49671011).