Sediment Rating Curves Research Articles

ASSESSING SUSPENDED SEDIMENT YIELD IN THE SAF SAF GAUGED CATCHMENT, NORTHEASTERN ALGERIA

Many studies on sediment transport have been carried out on Algerian rivers but few studies have been undertaken in catchments of the Northeast of Algeria. The scarcity or discontinuity on sediment transport measurements reduces knowledge about soil loss. In some cases, researchers find often difficulties to apply the most suitable methods to estimate sediment load. The present work represents an assessment of suspended sediment yield from the Saf Saf catchment (322 km2) over 39 years. Long-term annual suspended sediment loads are estimated using non-linear power model, developed on mean discharge class technique as a sediment rating curve. There is a challenge to estimate suspended sediment load in the Saf Saf catchment, which is distinguished by rapid discharge variation. A second aim is to examine monthly and annual variations in discharge, suspended concentration, rainfall and load in this river and to find causes for these variations. The results show that the mean annual sediment yield is equal to 477 T km-2 yr-1 during the study period. Moreover, the long term variability analysis of sediment load seems to be very high from year to year depending on climatic conditions. The analysis of annual sediment load shows a decreasing trend along 39 years, mainly from 1997. Most sediment loads are transported during the winter season, which represents 78% of the total sediment load. The understanding of sediment transport relationships gained from this study should provide a good starting point for researchers and policymakers to begin addressing sediment issues within the catchment.

Suspended sediment load prediction using non-dominated sorting genetic algorithm II

Awareness of suspended sediment load (SSL) and its continuous monitoring plays an important role in soil erosion studies and watershed management. Despite the common use of the conventional model of the sediment rating curve (SRC) and the methods proposed to correct it, the results of this model are still not sufficiently accurate. In this study, in order to increase the efficiency of SRC model, a multi-objective optimization approach is proposed using the Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm. The instantaneous flow discharge and SSL data from the Ramian hydrometric station on the Ghorichay River, Iran are used as a case study. In the first part of the study, using self-organizing map (SOM), an unsupervised artificial neural network, the data were clustered and classified as two homogeneous groups as 70% and 30% for use in calibration and evaluation of SRC models, respectively. In the second part of the study, two different groups of SRC model comprised of conventional SRC models and optimized models (single and multi-objective optimization algorithms) were extracted from calibration data set and their performance was evaluated. The comparative analysis of the results revealed that the optimal SRC model achieved through NSGA-II algorithm was superior to the SRC models in the daily SSL estimation for the data used in this study. Given that the use of the SRC model is common, the proposed model in this study can increase the efficiency of this regression model.

The role of sediment rating curve development methodology on river load modeling.

The study aims to evaluate the performance of four sediment rating curve development methods, namely (i) simple rating curve, (ii) different ratings for the dry and wet season of the year, (iii) different ratings for the rising and falling limb of the runoff hydrograph, and (iv) broken line interpolation that uses different exponents for two discharge classes at the outlet of the Venetikos River catchment, located at Western Macedonia, Northern Greece. The goal is to provide guidance on the selection of the most appropriate one for the estimation of sediment discharge (yield) at this gauging site (basin), as well as to properly assess such values. The necessary field measurements (discharge, sediment discharge, discharge-sediment discharge pairs) were conducted by the Greek Public Power Corporation. The performance of each method was evaluated by executing a statistical analysis (1965-1982), using as benchmark the observed mean monthly sediment discharge values. The broken line interpolation method performed best, not only by meeting the desired criteria of most statistical indicators used but also by being overall superior to all other methods. Thus, henceforward is to be treated as the representative rating curve development method for the specific site. Finally, an attempt was made to evaluate the estimated (and observed) sediment yield values against the ones attributed by four empirical equations, yet with relatively poor results.

The Use of Sediment Rating Curve under its Limitations to Estimate the Suspended Load

The Use of Sediment Rating Curve under its Limitations to Estimate the Suspended Load

Sediment Dynamics and Rating Curve Development on River Osun, South-Western Nigeria

Sediment Dynamics and Rating Curve Development on River Osun, South-Western Nigeria

Empirical and analytical methods to characterize the efficiency of floods to move sediment in a small semi-arid basin

Abstract. Over a long multi-year period, flood events can be classified according to their effectiveness in moving sediments. Efficiency depends both on the magnitude and frequency with which events occur. The effective (or dominant) discharge is the water discharge which corresponds to the maximum sediment supply. If its calculation is well documented in temperate or humid climates and large basins, it is much more difficult in small and semi-arid basins in which short floods with high sediment supplies occur. Using the example of 31 years of measurements in the Wadi Sebdou (north-west Algeria), this paper compares the two main statistical approaches to calculate the effective discharge (the empirical method based on histograms of sediment supply by discharge classes and an analytical calculation based on a hydrological probability distribution and on a sediment rating curve) to a very simple proxy: the half-load discharge, i.e. the flow rate corresponding to 50 % of the cumulative sediment yield. Three types of discharge subdivisions were tested. In the empirical approach, two subdivisions provided effective discharge close to the half-load discharge. Analytical solutions based on log-normal and log-Gumbel probability distributions were assessed but they highly underestimated the effective discharge, whatever the subdivision used to adjust the flow frequency distribution. Furthermore, annual series of maximum discharge and half-load discharge enabled the return period of hydrological years with discharge higher than the effective discharge (around 2 years) to be inferred and showed that more than half of the yearly sediment supply is carried by flows higher than the effective discharge only every 7 hydrological years. This study was the first to adapt the analytical approach in a semi-arid basin and to show the potentiality and limits of each method in a such climate.

A multi-technique approach for evaluating sand dynamics in a complex engineered piedmont river system

A multi-technique approach is proposed to study sand dynamics in an engineered piedmont river. Only a few studies focused on such systems and innovative methodological protocols still need to be designed to better understand sand transport in piedmont rivers where bedload dynamics has been largely modified with nowadays a residual sand transport on a fixed gravel matrix. The proposed methodology is based on an analysis of bathymetry and turbidity measurements and on modelling, including the development of sediment rating curves and 2D numerical modelling, and using sediment budgeting for cross-validation. Its application to the Isère-Rhône confluence (France) provided some insights of sand fluxes in this complex river system where few sediment flux data are available. Indeed, a substantial amount of sand sporadically reaches the downstream part of the Isère River because of the presence of a series of dams, and jeopardizes navigation and flood management at the confluence. Based on the analysis of the 2015 flushing event, it was found that the sediment transport capacity was reached during the event whereas sand supply can be considered as null when dam bottom gates are closed. Suspended load of sand was prevailing downstream of the last dam but quickly settled down at the confluence. The sand deposit was eventually evacuated from the confluence during the small floods occurring after the flushing event with a minimum discharge of approximately 500 m3/s in the Isère River and 1000 m3/s in the headrace canal of the Rhône River. The presented methodology can be transferred to other sites with similar issues.

Reservoir Sediment Inflow Prediction using Integrated Rainfall-Runoff and Discharge–Sediment model

Reservoir sedimentation adversely affects both operation and safety of dam. It is important for reservoir manager and operator to predict the incoming sediment inflow into a reservoir to develop sustainable sediment management plan. Continuous sediment monitoring is preferred to estimate total sediment load but it is labor intensive and costly. To cope with these limitations, total sediment inflow into a reservoir is predicted by coupling the runoff from hydrological model and sediment rating curves derived from field sampling dataset. In this research, MIKE NAM rainfall runoff model is used to simulate runoff in Cameron Highlands’ catchment, using hydrological data from 1999 to 2012. This model is calibrated and validated using the flow data of Sg Bertam. Field sampling is conducted to measure the Total Suspended Solids (TSS), Bed Load and grab samples at major rivers namely Sg Telom, Sg Habu, Sg Ringlet and Sg Bertam. Sediment rating curves using power function are used to describe the relationship between the total sediment load and discharge. Using this concept, annual total sediment inflow into Ringlet Reservoir from 1999 to 2012 is estimated in the range of 100,000 m3/year to 270,000 m3/year, agreeable to the survey records previously.

A performance evaluation of neuro-fuzzy and regression methods in estimation of sediment load of selective rivers

Sediment rating curves (SRCs) have been recognized as the most popular method for estimating sediment in the hydrology of river sediments and in watersheds. In this regard, in order to compare and correct estimation methods of river sediment load, estimated rates of several univariate types of SRCs and a multivariate type of SRCs (MSRCs) were studied using the neuro-fuzzy and tree regression models in five selective hydrometric stations of different climatic zones of Iran and with various indexes of the accuracy (AI) and the precision (PI). The results of the data analysis showed that the mean of the AI of neuro-fuzzy and tree regression models in selective stations is 151 and 536%, respectively, which shows the low efficiency compared with SRCs. Also according to the results, the best rate of the AI of the MSRCs belongs to the Glink station with the rate of 1.12. Also, the average value of the AI of MSRCs is 1.15 which is an acceptable amount of the other considered various methods.

Orbitally forced glacio-eustatic origin of third-order sequences and parasequences in the Middle Permian Maokou Formation, South China

Abstract Astronomical forcing on the development of depositional sequences has been of particular interest to researchers in recent years. To investigate the forming mechanism of depositional sequences in the Middle Permian Maokou Formation, outcrop sequence stratigraphic analysis and cyclostratigraphic analysis were conducted on one outcrop section and one drilling well in South China. Up to ninety-two meter-scale 6th-order parasequences, thirty-one 5th-order parasequences, eight 4th-order parasequences and two 3rd-order sequences were recognized based on vertical facies changes and stratal stacking patterns. Astronomical cycles (i.e., eccentricity, obliquity and precession) were detected by spectral analysis. An ∼3.1 Myr temporal framework and a high-resolution sedimentation rate curve were constructed by cyclostratigraphic analysis. The similar ratios of average thickness for the high-frequency sequences and the spectral periodicities suggest an astronomical forcing origin for the parasequences. The 4th-, 5th-, and 6th-order high-frequency parasequences correlate well with long eccentricity, short eccentricity and obliquity cycles, respectively. The durations of local and global 3rd-order sea-level sequences match the s4-s3 obliquity modulation cycles. Our results suggest that tectonic and autocyclic processes did not exert a major influence on the development of depositional sequences and that in the Middle Permian Maokou Formation the development of 3rd-order sequences and 4th-, 5th- and 6th-order parasequences was controlled by orbitally-driven glacio-eustatic sea-level changes. The coevolution trends in obliquity power, sea-level change and sedimentation rate hold important implications for stratigraphic correlation and sequence stratigraphic subdivision on a regional scale.

Performance evaluation of correction coefficients to optimize sediment rating curves on the basis of the Karkheh dam reservoir hydrography, west Iran

The prediction of useful lifetime of a dam is estimated through accurate estimate of river sediments which mostly depend on sediment rating curve. Over the past decades, various methods have been developed by investigators. With respect to the importance of this issue, in the present study, the best discharge-sediment relationship for Jelogir hydrometric station located at the upstream of Karkheh reservoir dam is presented. In the first step, sediment rating curves in annual, seasonal, monthly, wet and dry, and middle of the classes linear ways and applying 3 correction coefficients that include Smearing, FAO, and QMILE were obtained; then, their performance was evaluated. Comparison of these results with data obtained from hydrographical operation of Karkheh dam reservoir showed that the optimal equation of discharge-sediment at this hydrometric station follows annual linear sediment rating curve with QMILE correction coefficient. According to the results, annual method has estimated sediment volume less than the actual volume, about 98.7% of the actual sediment, while other evaluated methods have showed sediment volume more than the actual one, and among correction coefficients, the application of QMILE correction coefficient is more reasonable than other coefficients.

Application of sediment rating curves to evaluate efficiency of EPM and MPSIAC using RS and GIS

Erosion potential method (EPM) and Modified Pacific Southwest Interagency Committee (MPSIAC) are two empirical models for estimating soil erosion and sediment delivery. These models use a relatively simple formulation, but they are still applied in various areas with different environmental conditions. However, evaluation of their efficiency is challenging. Accordingly, the main purpose of this study is investigating the performance of EPM and MPSIAC in estimating soil erosion and sediment yield using sediment rating curve (SRC) methods. Talar watershed in Iran was selected as the study area and suspended sediment load (SSL) of two Shirgah–Talar and Valikbon stations were used to assess the output of the models. Remote sensing and geographic information system were utilized in implementing the models. The estimated sediment yield values by the models were evaluated using the results of least square error regression and quantile regression (QR) SRC methods. Then, sediment yield values were obtained from 20-year discharge data (1992–2011). Despite the high uncertainty of QR results, the annual sediment delivery values of the models were achieved in an acceptable range. The most likely (with a probability of 0.5) average annual SSL values were between 713 × 103 and 840 × 103 ton for Shirgah–Talar station. Those values for Valikbon station were between 3142 × 101 and 3702 × 101. Moreover, the estimated average sediment yield in Shirgah–Talar station using MPSIAC and EPM were 591392 and 514054 ton/year, respectively. Those values for Valikbon station were 51881 and 27449 ton/year. Then, the results proved the better performance of MPSIAC in estimating SSL in the study area compared with EPM.

Simulation of suspended sediment based on gamma test, heuristic, and regression-based techniques

In the present study, four different heuristic techniques viz. multi-layer perceptron (MLP), radial basis function (RBF), self-organizing maps (SOM), and co-active neuro-fuzzy inference system (CANFIS) with hyperbolic tangent and sigmoid transfer functions and two regression-based techniques, i.e., multiple linear regression (MLR) and sediment-rating curve (SRC), were used for suspended sediment modeling. Gamma test (GT), correlation function (CF), M test, and trail–error procedure were applied for estimation of appropriate input variables as well as training data length. The results of the GT and CF suggested the five input variables (Qt, Qt−1, Qt−2, St−1, and St−2, where Qt−1 and St−1 indicate the discharge and sediment values of one previous day) as the best combination. The optimal training data length (75% of total data) was estimated by M test and trail–error procedure for development of the applied models. The MLP with sigmoid transfer function (M-2) performed better than the all other models. The results of sensitivity analysis indicated that the present-day discharge (Qt), 1-day lag discharge (Qt−1) and 1-day lag suspended sediment (St−1) are the most influenced parameters in modeling current day suspended sediment (St).

Sub-Bankfull Flow Frequency versus Magnitude of Flood Events in Outlining Effective Discharges. Case Study: Trotuș River (Romania)

Effective discharge, which represents the flow, or range of flows, that transport the most sediment over the long-term, was determined based on the mean daily flow discharge and mean daily suspended sediment discharge recorded between 1994 and 2014 at four gauging stations along the Trotuș River. This study proposes an efficient method for the estimation of effective discharge based on observed values of the suspended sediment load. By employing this method the suspended sediment load is no longer either under- or overestimated as in the cases when the assessment is based on sediment rating curves. The assessment on effective discharge was performed at two distinct levels: for the entire data series during the investigated time spans and, subsequently, for flows less than the bankfull discharge. The effectiveness curves of the suspended sediment transport characteristics revealed highly multimodal characteristics with many peaks, indicating ample ranges for the effective discharges. The main effective discharge corresponded to large flood events, which are typical for the upper end of the discharge range, whereas the secondary effective discharges corresponded to sub-bankfull flows, which are more frequent. The changes that occurred in the channel bed are reflected by the temporal variations in the effective discharge.

Response of Sediment Load to Hydrological Change in the Upstream Part of the Lancang-Mekong River over the Past 50 Years

Sediment load and its response to the variations of the hydrological elements are important for the healthy utilization of a river. In this study, the response of sediment load to hydrological change was explored in the upstream part of the Lancang-Mekong River, a major transboundary river originating from the Tibetan Plateau and running through China, over the past 50 years. A sediment rating curve for the Jiuzhou Station was developed based on the available SSC-Q (suspended sediment concentration (SSC) and flow) data and trends in annual precipitation, runoff, peak flow (PF), low flow (LF), maximum water level (MWL), and sediment load were analyzed from 1957 to 2006. The correlation analysis method and Random Forest (RF) were adopted to qualitatively and quantitatively quantify the contribution of each hydrological element to the sediment load change. Results indicated that both the runoff and sediment load showed a significantly upward trend, especially after 1979, at the 95% confidence level. The sediment load had significantly positive correlations with runoff, PF, and MWL at the 99% confidence level, respectively. In particular, the sediment load had the largest significant positive correlation with runoff since 1980. Runoff had the largest variable importance to the sediment load change, followed by PF, MWL, precipitation, and LF. The increasing trend in the sediment load was mainly attributed to the increase of runoff in the upstream part of the Lancang-Mekong River since the mid-1980s.

Suspended sediment yield estimation using genetic algorithm-based artificial intelligence models: case study of Mahanadi River, India

ABSTRACTThe estimation of sediment yield is important in design, planning and management of river systems. Unfortunately, its accurate estimation using traditional methods is difficult as it involves various complex processes and variables. This investigation deals with a hybrid approach which comprises genetic algorithm-based artificial intelligence (GA-AI) models for the prediction of sediment yield in the Mahanadi River basin, India. Artificial neural network (ANN) and support vector machine (SVM) models are developed for sediment yield prediction, where all parameters associated with the models are optimized using genetic algorithms simultaneously. Water discharge, rainfall and temperature are used as input to develop the GA-AI models. The performance of the GA-AI models is compared to that of traditional AI models (ANN and SVM), multiple linear regression (MLR) and sediment rating curve (SRC) method for evaluating the predictive capability of the models. The results suggest that GA-AI models exhibit better performance than other models.

Evaluating spatial variation of suspended sediment rating curves in the middle Yellow River basin, China

AbstractAbstractThe suspended sediment load in the middle Yellow River basin (YRB) cannot be well predicted by capacity‐based transport formulas because a large fraction of suspended sediment load is composed of wash load. This study evaluated the spatial variations of sediment rating curves (SRCs) in the middle YRB. Both power and linear SRCs were used to fit daily flow and suspended sediment concentration (SSC) historical data at 49 gauging stations throughout the middle YRB. The spatial variation in regression coefficients was investigated, and the relationship between regression coefficients and the physical characteristics of watersheds was discussed. The results indicate that SRC regression coefficients vary with drainage area and basin slope, but their responses to these parameters are remarkably different in watersheds with different underlying surfaces, which indicates the significance of sediment availability, erodibility, and grain size distribution. For power SRCs representing sediment transport in unsaturated flows, the regression coefficients are more closely correlated with the drainage area in loess regions and with the basin slope in rock mountain regions. For linear SRCs representing sediment transport in saturated flows, saturated SSCs vary with coarse (particle size > 0.05 mm) and fine (particle size < 0.01 mm) fractions in suspended sediment. The maximum saturated SSC among the different gauging stations is associated with the optimal grain size composition of suspended sediment, which has been proposed for loess regions in previous studies. This study provides theoretical support for estimating the regression parameters for sediment transport modelling, especially in ungauged basins.

Hydrometeorological assessments and suspended sediment delivery from a central Himalayan glacier in the upper Ganga basin

Integrated hydrometeorological investigations are not frequently available at a regional scale over a longer time period, especially near the terminus of Indian Himalayan glaciers. An integrated approach to the collection of hydrological data has major advantages for understanding the runoff generation mechanisms at basin scale, particularly when coupled with meteorological observations. The current study involves time series analysis of hydrometeorological records collected near the terminus of the Chorabari Glacier, for four consecutive ablation seasons (June–Sept.) 2009–2012. The analysis shows that variation in rainfall was higher (cv = 0.9) at the same elevation over proximal sites, while the intensity of extreme rainfall events was 121–160 mm/d. The diurnal temperature range (DTR) has a tendency to reduce over the ablation season because of the onset of the Indian Summer Monsoon (ISM) and then further increases during the ISM withdrawal indicating humid-temperate conditions. The peak discharge (Qpeak) was found to be higher during July and August. Snow and glacier melt contributed 76% of the total suspended sediment transport during peak ISM months (July and August) reflecting seasonal evolution of the hydrologic conduits. The results indicate that Karakoram and western Himalayan glaciers produce comparatively low sediment yield compared to central Himalayan glaciers. The hydrological variations are depicted through flow duration curves (FDC) for meltwater discharge and sediment load. The flow corresponding to Q50, Q75, and Q90 (where Qx is the discharge that is exceeded x percent of the time referred to as % dependability) are 4.2, 3.7, and 2.8 m3/s; and the corresponding dependability for suspended sediment loads (SSLs) are 409.0, 266.0, and 157.2 t/d, respectively. The daily SSL and discharge (Q) from 2009 to 2012 were used to develop a sediment rating curve (SSL = 39.55 × Q1.588, R2 = 0.8). Multiple regressions are used to determine the impacts of meteorological parameters on glacier melt. The meteorological conditions, hydrological characteristics, and suspended sediment delivery for the Chorabari Glacier provide insight on meltwater generation processes and sediment transport patterns during the ISM season.

Quantifying suspended sediment dynamics in mega deltas using remote sensing data: A case study of the Mekong floodplains

Temporal and spatial concentrations of suspended sediment in floodplains are difficult to quantify because in situ measurements can be logistically complex, time consuming and costly. In this research, satellite imagery with long temporal and large spatial coverage (Landsat TM/ETM+) was used to complement in situ suspended sediment measurements to reflect sediment dynamics in a large (70,000 km2) floodplain. Instead of using a single spectral band from Landsat, a Principal Component Analysis was applied to obtain uncorrelated reflectance values for five bands of Landsat TM/ETM+. Significant correlations between the scores of the 1st principal component and the values of continuously gauged suspended sediment concentration, shown via high coefficients of determination of sediment rating curves (R2 ranging from 0.66 to 0.92), permit the application of satellite images to quantify spatial and temporal sediment variation in the Mekong floodplains. Estimated suspended sediment maps show that hydraulic regimes at Chaktomuk (Cambodia), where the Mekong, Bassac, and Tonle Sap rivers diverge, determine the amount of seasonal sediment supplies to the Mekong Delta. The development of flood prevention systems to allow for three rice crops a year in the Vietnam Mekong Delta significantly reduces localized flooding, but also prevents sediment (source of nutrients) from entering fields. A direct consequence of this is the need to apply more artificial fertilizers to boost agricultural productivity, which may trigger environmental problems. Overall, remote sensing is shown to be an effective tool to understand temporal and spatial sediment dynamics in large floodplains.

A comparison of artificial intelligence models for the estimation of daily suspended sediment load: a case study on the Telar and Kasilian rivers in Iran

Abstract The estimation of the suspended sediment load in rivers is one of the main issues in hydraulic engineering. Different traditional methods such as the sediment rating curve (SRC) can be used to estimate the suspended sediment load of rivers. The main problem with this method is its low accuracy and uncertainty. In this study, the ability of three intelligence models namely: gene expression programming (GEP), artificial neural networks (ANN) and adaptive neuro fuzzy inference system (ANFIS) were compared with the SRC method. The daily flow discharge and sediment discharge at two hydrometric stations of the Kasilian and Telar rivers in the period of 1964–2014 were used to develop intelligence models. The performance of these methods indicated that all intelligence models give reliable results in the estimation of the suspended sediment load and their performance was better than the SRC method. Moreover, results showed that the GEP model with a high coefficient of determination (R2) and a low mean absolute error (MAE) was better than both the ANN and ANFIS models for the estimation of daily suspended sediment load of the two sub-basins of the Kasilian and Telar rivers.