Sediment Rating Curve and Sediment Concentration Estimation for Mahanadi River

2021 ◽  
pp. 95-104
Author(s):  
Pratik Acharya ◽  
Tushar Kumar Nath ◽  
Ram Babu Nimma
Keyword(s):  
Sediment Concentration ◽  
Rating Curve ◽  
Sediment Rating Curve ◽  
Mahanadi River ◽  
Concentration Estimation

Impact of Chelicorophium curvispinum on the concentration-discharge response of suspended sediment in the Rhine River

2021 ◽  
Author(s):  
Marcel van der Perk
Keyword(s):  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Sudden Increase ◽  
Rhine River ◽  
Rating Curve ◽  
Independent Evidence ◽  
Sediment Rating Curve ◽  
Suspended Sediment Concentrations

<p>In an ongoing study to the decline in suspended sediment concentrations and loads in the Rhine river since the mid-1950s, the temporal changes in the power-law sediment rating curve parameters were examined. This revealed that the rating exponent of the rating curve increased substantially between the early and late 1980s. Until the early 1980s, the ratings curves were relatively flat with values of the rating exponent b varying around 0.2. In the mid-1980s, the exponent suddenly increased to a value between 0.4 and 0.6 and since then has remained within this range. This change in the rating exponent was mainly caused by a decrease in suspended sediment concentrations during low discharges. During high discharges, the suspended sediment concentration initially increased during the late 1980s, but this increase was nullified soon afterwards due to the declining trend in suspended sediment concentration.</p><p>The sudden increase of the rating exponent coincided with the period that the Ponto-Caspian <em>Chelicorophium curvispinum</em> (Caspian mud shrimp) invaded the Rhine river basin. This suggests that this suspension-feeder species bears the prime responsibility for this increase, although this hypothesis requires further independent evidence. The sudden increase in the rating exponent does however not manifest itself in the long-term gradual trend of declining suspended sediment concentrations and vice versa. Apparently, the sequestration of sediment by <em>Chelicorophium curvispinum</em> is only temporary: the suspended sediment sequestered during periods of relatively low discharges is likely remobilised again during periods of high discharge. This implies that the invasion of <em>Chelicorophium curvispinum</em> has not played a significant role in the decline of suspended sediment concentrations. The precise reasons for the gradual long-term decline in suspended sediment concentration remain yet unknown.</p>

scholarly journals Suspended Sediment Concentration and Sediment Loading of Bernam River (Perak, Malaysia)

2020 ◽  
Vol 22 (2) ◽  
pp. 1-14
Author(s):  
Sumayyah Aimi Mohd Najib ◽  
Syazwani Aliah ◽  
Husna Nabilah Hamidon
Keyword(s):  
Suspended Sediment Concentration ◽  
Sampling Period ◽  
Sediment Concentration ◽  
High Flow ◽  
Low Flow ◽  
Sediment Loading ◽  
Land Uses ◽  
Rating Curve ◽  
Sediment Rating Curve ◽  
Rain Events

Abstract This paper presents some of our preliminary results on the sediment discharge and load based on weekly sampling starting from Oct 2017 to January 2018. Results show that sediment rating curve of Bernam River was R2 = 0.86 high flow and R2 = 0.5 low flow. Average sediment loading throughout this sampling period is 1,144 t. Land use activity is expected to be the main contribution for the highest sediment concentration during rain events. The amount of annual sediment yield was estimated at 23 t/km2/year and is comparable to other studies having similar land uses in the catchment area.

scholarly journals Classifications of runoff and sediment data to improve the rating curve method

2017 ◽  
Vol 48 ◽  
Author(s):  
Hossein Khaledian ◽  
Homayoun Faghih ◽  
Ata Amini
Keyword(s):  
Suspended Sediment ◽  
River Flow ◽  
Data Classification ◽  
Suspended Sediments ◽  
Sediment Concentration ◽  
Low Flow ◽  
Rating Curve ◽  
Sediment Rating Curve ◽  
Curve Method ◽  
Sediment Data

In this study, data classification method was evaluated to increase accuracy of estimating suspended sediment load. To achieve this objective, suspended sediment in Chehelgazi and Khalifeh-Tarkhan rivers in Kurdistan, Iran, were estimated using Sediment Rating Curve (SRC) method in three different approaches of data classification. At first, measured data were modeled without classification. Then, data based on flow statues were divided into two series as high and low flow. Eventually, based on sediment concentration, the data were divided into low and high sediment concentration. Long-term runoff and sediment data were used to calibrate rating curve model. The estimated values were compared with recorded data and the performances of these models were evaluated using statistical criteria. The results indicated an effective role of data classification to improve estimating sediment transportation by rating curve method. In one of the stations, it was observed that due to classification based on river flow and sediment concentration, model efficiency was increased about 45% and 28%, respectively. Furthermore, in case of improving efficiency of SRC method, classifying data based on flow statues was found to be more effective than sediment concentration. The results of this study can be used to improve the management of the basin by more accurately estimating the amount of suspended sediments transporting in the rivers draining to reservoirs.

scholarly journals A new approach for estimation suspended sediment yield

1999 ◽  
Vol 3 (2) ◽  
pp. 285-294 ◽  
Author(s):  
R. Lidén
Keyword(s):  
Suspended Sediment ◽  
Suspended Sediment Concentration ◽  
Sediment Concentration ◽  
Model Parameters ◽  
Rating Curve ◽  
Sediment Rating Curve ◽  
Daily Series ◽  
Suspended Sediment Concentrations ◽  
Model Equations

Abstract. A semi-distributed conceptual model, HBV-SED, for estimation of total suspended sediment concentration and yield at the outlet of a catchment was developed and tested through a case study. The base of the suspended sediment model is a dynamic hydrological model, which produces daily series of areal runoff and rainfall for each sub-basin as input to the sediment routine. A lumped measure of available sediment is accumulated continuously based on a linear relationship between log-transformed values of rainfall and erosion, while discharge of suspended sediment at the sub-basin outlet is dependent on runoff and amount of stored available sediment. Four model parameter are empirically determined through calibration against observed records of suspended sediment concentration. The model was applied to a 200 km2 catchment with high altitude differences in the tropical parts of Bolivia, where recorded suspended sediment concentrations were available during a two-year period. 10,000 parameter sets were generated through a Monte Carlo procedure to evaluate the parameter sensitivity and interdependence. The predictability of the model was assessed through dividing the data record into a calibration and an independent period for which the model was validated and compared to the sediment rating curve technique. The results showed that the slope coefficients of the log-transformed model equations for accumulation and release were much stronger than the intercept coefficients. Despite and existing interdependence between the model parameters, the HBV-SED model gave clearly better results than the sediment rating curve technique for the validation period, indication that the supply-based approached has a promising future as a tool for basic engineering applications.

scholarly journals Development and Interpretation of New Sediment Rating Curve Considering the Effect of Vegetation Cover for Asian Basins

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Jie Wang ◽  
Hiroshi Ishidaira ◽  
Wenchao Sun ◽  
Shaowei Ning
Keyword(s):  
Suspended Sediment ◽  
Sediment Yield ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Suspended Sediment Concentration ◽  
Hydrological Cycle ◽  
Water Discharge ◽  
Sediment Concentration ◽  
Rating Curve ◽  
Sediment Rating Curve

Suspended sediment concentration of a river can provide very important perspective on erosion or soil loss of one river basin ecosystem. The changes of land use and land cover, such as deforestation or afforestation, affect sediment yield process of a catchment through changing the hydrological cycle of the area. A sediment rating curve can describe the average relation between discharge and suspended sediment concentration for a certain location. However, the sediment load of a river is likely to be undersimulated from water discharge using least squares regression of log-transformed variables and the sediment rating curve does not consider temporal changes of vegetation cover. The Normalized Difference Vegetation Index (NDVI) can well be used to analyze the status of the vegetation cover well. Thus long time monthly NDVI data was used to detect vegetation change in the past 19 years in this study. Then monthly suspended sediment concentration and discharge from 1988 to 2006 in Laichau station were used to develop one new sediment rating curve and were validated in other Asian basins. The new sediment model can describe the relationship among sediment yield, streamflow, and vegetation cover, which can be the basis for soil conservation and sustainable ecosystem management.

Regionalization of sediment rating curve for sediment yield prediction in ungauged catchments

2013 ◽  
Vol 46 (1) ◽  
pp. 26-38 ◽  
Author(s):  
Sokchhay Heng ◽  
Tadashi Suetsugi
Keyword(s):  
Sediment Yield ◽  
Model Performance ◽  
Data Uncertainty ◽  
Spatial Proximity ◽  
Yield Prediction ◽  
Rating Curve ◽  
Ungauged Catchments ◽  
Probability Curve ◽  
Sediment Rating Curve ◽  
Almost All

The main objective of this research is to regionalize the sediment rating curve (SRC) for subsequent sediment yield prediction in ungauged catchments (UCs) in the Lower Mekong Basin. Firstly, a power function-based SRC was fitted for 17 catchments located in different parts of the basin. According to physical characteristics of the fitted SRCs, the sediment amount observed at the catchment outlets is mainly transported by several events. This also indicates that clockwise hysteretic phenomenon of sediment transport is rather important in this basin. Secondly, after discarding two outlier catchments due to data uncertainty, the remaining 15 catchments were accounted for the assessment of model performance in UCs by means of jack-knife procedure. The model regionalization was conducted using spatial proximity approach. As a result of comparative study, the spatial proximity approach based on single donor catchment provides a better regionalization solution than the one based on multiple donor catchments. By considering the ideal alternative, a satisfactory result was obtained in almost all the modeled catchments. Finally, a regional model which is a combination of the 15 locally fitted SRCs was established for use in the basin. The model users can check the probability that the prediction results are satisfactory using the designed probability curve.

scholarly journals Hydroclimatic control on suspended sediment dynamics of a regulated Alpine catchment: a conceptual approach

2018 ◽  
Vol 22 (6) ◽  
pp. 3421-3434 ◽  
Author(s):  
Anna Costa ◽  
Daniela Anghileri ◽  
Peter Molnar
Keyword(s):  
Suspended Sediment ◽  
Sediment Concentration ◽  
Sediment Dynamics ◽  
Time Lags ◽  
Rating Curve ◽  
Conceptual Approach ◽  
Ice Melt ◽  
Alpine Catchments ◽  
Erosive Rainfall ◽  
Hydroclimatic Variables

Abstract. We analyse the control of hydroclimatic factors on suspended sediment concentration (SSC) in Alpine catchments by differentiating among the potential contributions of erosion and suspended sediment transport driven by erosive rainfall, defined as liquid precipitation over snow-free surfaces, ice melt from glacierized areas, and snowmelt on hillslopes. We account for the potential impact of hydropower by intercepting sediment fluxes originated in areas diverted to hydropower reservoirs, and by considering the contribution of hydropower releases to SSC. We obtain the hydroclimatic variables from daily gridded datasets of precipitation and temperature, implementing a degree-day model to simulate spatially distributed snow accumulation and snow–ice melt. We estimate hydropower releases by a conceptual approach with a unique virtual reservoir regulated on the basis of a target-volume function, representing normal reservoir operating conditions throughout a hydrological year. An Iterative Input Selection algorithm is used to identify the variables with the highest predictive power for SSC, their explained variance, and characteristic time lags. On this basis, we develop a hydroclimatic multivariate rating curve (HMRC) which accounts for the contributions of the most relevant hydroclimatic input variables mentioned above. We calibrate the HMRC with a gradient-based nonlinear optimization method and we compare its performance with a traditional discharge-based rating curve. We apply the approach in the upper Rhône Basin, a large Swiss Alpine catchment heavily regulated by hydropower. Our results show that the three hydroclimatic processes – erosive rainfall, ice melt, and snowmelt – are significant predictors of mean daily SSC, while hydropower release does not have a significant explanatory power for SSC. The characteristic time lags of the hydroclimatic variables correspond to the typical flow concentration times of the basin. Despite not including discharge, the HMRC performs better than the traditional rating curve in reproducing SSC seasonality, especially during validation at the daily scale. While erosive rainfall determines the daily variability of SSC and extremes, ice melt generates the highest SSC per unit of runoff and represents the largest contribution to total suspended sediment yield. Finally, we show that the HMRC is capable of simulating climate-driven changes in fine sediment dynamics in Alpine catchments. In fact, HMRC can reproduce the changes in SSC in the past 40 years in the Rhône Basin connected to air temperature rise, even though the simulated changes are more gradual than those observed. The approach presented in this paper, based on the analysis of the hydroclimatic control of suspended sediment concentration, allows the exploration of climate-driven changes in fine sediment dynamics in Alpine catchments. The approach can be applied to any Alpine catchment with a pluvio-glacio-nival hydrological regime and adequate hydroclimatic datasets.

scholarly journals Prediction of sediment load by sediment rating curve and neural network (ANN) in El Kebir catchment, Algeria

2013 ◽  
Vol 122 (5) ◽  
pp. 1303-1312 ◽  
Author(s):  
Z A BOUKHRISSA ◽  
K KHANCHOUL ◽  
Y LE BISSONNAIS ◽  
M TOURKI
Keyword(s):  
Neural Network ◽  
Sediment Load ◽  
Rating Curve ◽  
Sediment Rating Curve

scholarly journals Stormflow and suspended sediment routing through a small detention pond with uncertain discharge rating curves

2018 ◽  
Vol 50 (4) ◽  
pp. 1177-1188 ◽  
Author(s):  
Adam Krajewski ◽  
Kazimierz Banasik ◽  
Anna E. Sikorska
Keyword(s):  
Sediment Concentration ◽  
Rating Curve ◽  
Discharge Time ◽  
Urban Catchment ◽  
Detention Ponds ◽  
Sediment Routing ◽  
Detention Pond ◽  
Huge Impact ◽  
Rating Curves ◽  
The Impact

Abstract Ratings curves are commonly used for computing discharge time series from recorded water stages or for hydrograph and sediment graph routing through detention ponds. Numerous studies have demonstrated that these rating curves are often linked with significant uncertainty. Nevertheless, the uncertainty related to the use of these rating curves in sediment estimates has not been investigated so far. Hence, in this work, we assess the impact of using such uncertain discharge rating curves on the estimation of the pond outflow (discharge, sediment concentration and load) from a small detention pond located in a small urban catchment in Poland. Our results indicate that the uncertainty in rating curves has a huge impact on estimates of discharge and sediment fluxes in the outlet from the reservoir, wherein the uncertainty in the inlet rating curve plays a more important role than the uncertainty in the outlet rating curve. Poorly estimated rating curve(s) may thus lead to serious errors and biased conclusions in the estimates and designs of detention ponds. To reduce this uncertainty, more efforts should be made to construct the rating curves at the pond inlet and to gather more data in extreme conditions.

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