Startseite Sediment transport modelling upstream of Al Kufa Barrage
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Sediment transport modelling upstream of Al Kufa Barrage

  • Zainab Ali Omran ORCID logo EMAIL logo und Nassrin Jassim Hussien Al-mansori ORCID logo
Veröffentlicht/Copyright: 27. Februar 2024
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Abstract

This study estimated the amount of bed sediment load upstream of Kufa Barrage mainly depending on the hydrodynamic conditions, sediment concentration, and hydraulic parameters. Ten cross-sections approximately over 2 km in length in front of the barrage were selected. Velocities and suspended sediment concentrations at 0.2, 0.6, and 0.8 of the water depth at each section were recorded using an ADCP device. A depth-integrated sampling was utilized to examine the collected data from 6th January to 15th October 2022. It was noted that the effective depth-to-width computation methods and the Toffaleti sediment transport function with the Van Rijn fall velocity were the most compatible and appropriate approaches for determining the sediment transport potential in the selected reach. It was also noted that such techniques were better than the previous formulae to predict the total sediment load. The results revealed excellent agreement between the mean sediment discharge obtained using HEC-RAS 6.2, equal to 6.214 kg/s, and the mean sediment discharge obtained from the field measurements, equivalent to 7.142 kg/s.

1 Introduction

River sediment movement is a complicated and challenging process. To manage water resources efficiently, it is essential to understand the types and quantities of sediment delivered by rivers. Because most crucial projects in the study region are located on or close to riverbanks, decision-makers are especially concerned that erosion, transport, and sedimentation processes may impact these projects. To track and predict changes in the areas of the riverbanks, it is therefore necessary to better understand the appropriate equations that can be used to obtain results that are satisfactory for monitoring the processes of erosion, sedimentation, and transport that occur in river paths [15]. Physical modeling and computer simulation are the two fundamental technologies in river engineering studies. Both of them have advantages and disadvantages. Physical modeling is expensive and time-consuming, but it can yield immediately evident results. [68]. Field research, physical modeling, and computational simulation must all be used to solve engineering problems accurately and successfully. A field investigation is the first step in fully identifying the issue [9]. In the literature, there are numerous methods for calculating sediment movement rates. However, no single equation can forecast the transfer of silt at all locations (estuaries, rivers, etc.). However, many formulas, equations, and programs have been developed to calculate sediment transport discharge; however. Omran et al. [10] reviewed the sediment concentration transported in the Iraqi city of Al-Hilla-Diwaniya by the Hilla River. The volume of sediment load in the river section under study was determined using the HEC-RAS version 5.0.0 program. The Yang technique was employed to calculate the transport function, the Ruby method was used to calculate the fall velocity, and the Thomas (Ex5) method was used as a sorting method. Four cross-sections along the river reach (at 0 + 000, 1 + 000, 2 + 000, and 3 + 000) for a length of 100 m for each station were chosen. This project (Hilla-Diwaniya River) is unsuitable for irrigation because the results showed no variation between the four selected stations for recording sediment transport concentration, flow velocity, adequate depth, and effective width. Jassam and Abed [11], morphology and transport of sediment in the Diyala river was analyzed using the HEC-Ras program. The river’s selected length for the current study was 193 km, starting at Diyala Weir and ending at the point where the Tigris River and Diyala River converge. Samples of suspended-load and bed-load have been gathered, and specific cross-sections were surveyed during the fieldwork period, which lasted from June 2020 to August 2020. Between 0.2 and 0.6 m were the results of the invert change from the sediment model’s simulation for the river’s actual condition from 2018 to 2019. In addition, previous investigations into this river revealed that the daily and annual sediment discharges were 227.7 tons per day and 83,531.93 tons per year. The inversion change values in the simulation results for the prescribed timeframe, corresponding to five consecutive flood years, range from −1.25 to 1.4 m. Raising the riverbank level in some areas of the grasp and/or constructing training cross-sections in other areas increased the water’s capacity. Khassaf and Jabber [12] investigated and modeled the sediment transport on the Euphrates River upstream of the Al-Shamia Barrage in Al-Diwaniya, Iraq. Utilizing HEC-RAS version (4.1), in which the Acoustic Doppler Current Profiler (ADCP) device took field measurements. The Enguland-Hansen formula from this model has been proven to be the most accurate compared to field results. The average annual sediment transport load through this formula is around 209,000 tons, whereas the average annual sediment transport load measured in the field is about 140,965 tons. Many studies on sediments using different programs like MIKE, HEC-RAS, and SSIIM were conducted. The novelty of this study is measuring the flow and suspended sediment concentrations and their spatial distribution and characteristics in the study area, which were not measured before, and using the HEC-RAS program to find sediment transport.

2 Study area

Al-Kuffa barrage has been built for irrigation purposes on the Kifil-Shanafiyah branch of the Euphrates River downstream of the Babylon Governorate since 1986. In the middle Euphrates region, the barrage controls the flow for the upstream regulator. The barrage is designed to discharge 1,400 m3/s of floodwater, with an upstream water level of 25.7 m above sea level [13].

2.1 Data field measurements

Ten transect sections used in this study are depicted in Figure 1. The following were among the field measures that involved gathering the information needed to accomplish the study’s goals:

Figure 1 
                  The locations of the cross-sections in the research area as determined by the SAS algorithm.
Figure 1

The locations of the cross-sections in the research area as determined by the SAS algorithm.

Identifying the cross-sections’ locations as well as their coordinates, and then determination of the geometrical characteristics of each section, such as the area of the cross-section, top width, hydraulic radius, etc. Utilizing the ADCP technique to calculate flow rates and water discharge for each cross-section (see Figure 2). Utilizing the Van Veen Grab apparatus to collect samples from the riverbed and for every cross-section, Figure 3. Collecting sediment load samples for each cross-section by using a suspended sampling instrument.

Figure 2 
                  SonTek River Surveyor ADCP.
Figure 2

SonTek River Surveyor ADCP.

Figure 3 
                  Van Veen Grab.
Figure 3

Van Veen Grab.

2.2 Hydraulic measurement

Using ADCP technology, top width, cross-sectional area, discharge, water velocity, and water level were measured for each segment. The field measurements were done from June to September during the season. Version 5.5a of the software and ADCP were utilized for this. As observed in Figure 4.

Figure 4 
                  Cross section no. 1 from Kufa barrage by ADCP device.
Figure 4

Cross section no. 1 from Kufa barrage by ADCP device.

3 Simulation using HEC-RAS model

The unsteady flow simulation was developed for a 2 km length for each 200 m from upstream of the Al-Kuffa barrage using HEC-RAS [Version 6.2]. Figure 5 shows the main window for the software.

Figure 5 
               The main window for HEC-RAS software.
Figure 5

The main window for HEC-RAS software.

To create a study simulation, two specific file types are needed: (1) the stream reach and the river’s cross section are physically described in the geometry file and (2) the flow inputs and reach boundary conditions required for the unsteady flow studies are described in the flow file.

3.1 Data used in HEC-RAS model

Setting parameters and values as inputs is necessary to run the HEC-RAS 6.2 model. These parameters are shown in Table 1 and must be initialized for the model to complete the required simulation [1417].

Table 1

Data of input parameters for running the HEC-RAS 6.2 model

Symbol Description Determination
Geometric file N Manning coefficient (Constant depends on the type of channel and description) (0.035) for straight, full, no rifts or deep pools. From Tables of manning values depending on the type of channel and description
X, Y Station and elevation for each section From field measurements
Cont. Contraction coefficient of flow 0.1 for gradual transitions
Exp. Expansion coefficient of flow 0.3 for gradual transitions
Unsteady file (Quasi- unsteady data) T Temperature (47 From field measurements)
Q (m³/s) Discharge of water From field measurements
T Time step interval s60
Sediment file D Depth of water From field measurements
Bed gradation From experimental measurements
Boundary condition Rating curve from field measurements

3.2. Results of HEC-RAS 6.2 software

The results from the HEC-RAS 6.2 model are split into two sections: the hydrodynamic unit results are in the first section and the sediment transport unit results are in the second section. The degree of convergence between the results and the field measurements was evaluated by contrasting the results, and logical values associated with the coefficient of determination (R²) were discovered. Figure 6 shows the flowchart for the HEC-RAS model.

Figure 6 
                  Flow chart for the HEC-RAS 6.2 model.
Figure 6

Flow chart for the HEC-RAS 6.2 model.

3.2.1 Results of hydrodynamic

In this study, once the unsteady flow data and sediment data had been properly inserted and the “Run” button had been pressed, the program had finished simulating the unsteady flow data. It displayed the results in view/output. In this investigation, flow rates for each section were measured; Figure 7 displays the flow rates for all sections.

Figure 7 
                     Flow rate (m³/s) for all sections.
Figure 7

Flow rate (m³/s) for all sections.

Figure 8 shows the comparison between the model results and the field-measured values of water discharge for the site. It is evident from Figure 9 that there is a good agreement between the model values and the measured values of the average water discharge at the indicated site depending on the coefficient of determination, which reaches (R² = 0.9044).

Figure 8 
                     Field and model water discharge values (m³/s) on a scatter plot.
Figure 8

Field and model water discharge values (m³/s) on a scatter plot.

Figure 9 
                     The relation between field and model values for water discharge.
Figure 9

The relation between field and model values for water discharge.

3.2.2 Results of sediment transport

The most compatible and appropriate methods for determining sediment transport potential in the examined reach are the Toffaleti sediment transport function with the Van Rijn fall velocity and the efficient depth-to-width computation methods. The results of the sediment calculation by HEC-RAS are presented. Figure 10 shows sediment concentration for all sections.

Figure 10 
                     The distribution of sediment discharge at all sections by model.
Figure 10

The distribution of sediment discharge at all sections by model.

Table 2 shows the results from field measurements and model results; Figure 11 shows the comparison between the model results and the field-measured values of sediment discharge for the site; and it is evident from Figure 12 that there is a good agreement between the model values and the measured values of the average sediment discharge at the indicated site depending on the coefficient of determination, which reaches (R 2 = 0.8614).

Table 2

Model and field sediment discharge values

Sediment dis. (kg/s) (model values) Sediment dis. (kg/s) (field values)
5.65 5.70
9.18 10.15
7.91 8.94
6.00 5.73
6.89 8.88
5.34 7.93
4.10 4.77
2.80 2.78
6.91 8.13
7.36 8.41
Figure 11 
                     Field and model sediment discharge values on a scatter plot.
Figure 11

Field and model sediment discharge values on a scatter plot.

Figure 12 
                     The relation between field and model values for sediment discharge.
Figure 12

The relation between field and model values for sediment discharge.

The contribution of suspended sediment concentration for each cross-section can be found from the total suspended sediment concentrations for the study area, as in Figure 13, which illustrates the percentages of sediment from the total suspended sediment concentrations for each cross-section and both field measurements and from the simulated HEC-RAS model.

Figure 13 
                     The percentages of each cross-section from total suspended sediment concentrations, (a) from HEC-RAS and (b) from field measurements.
Figure 13

The percentages of each cross-section from total suspended sediment concentrations, (a) from HEC-RAS and (b) from field measurements.

4 Model verification

To estimate the fluctuations in flow and sediment load using a set of measurements, the verification of hydrodynamic and sediment transport models reflected real-world tests of numerical solutions. The HEC-RAS program was used to confirm the first seven components of the measured sediment discharge. The discrepancy between field measurements and model simulations. The findings are shown in Figure 14 and show a reasonable agreement between observed and estimated data (R² = 0.8789).

Figure 14 
               Verification plot.
Figure 14

Verification plot.

5 Conclusions

By building the numerical model used to represent the study region and analyzing the flow and sediments in it, the current study provided a notion to lessen efforts and time spent in the future making accurate decisions about sediment movement and its effects on the study area. Based on the coefficients of determination (R²), which were 0.9044 and 0.8614, respectively, for average water discharge and sediment discharge, there was a good agreement between the HEC-RAS results and the field observations. The results indicate that the HEC-RAS model has a very high convergence in terms of representing the real reality of the study area through comparison with the changes that occurred in part of it. A good acceptance between the average sediment discharge from HEC-RAS 6.2, which equals 6.214 kg/s, and sediment discharge from field measurements 7.142 kg/s. This amount of sediment affects the efficiency of barrage operations, so to reduce it, operating the barrage with sedimentation in different cases of gate operation to optimize the most suitable case of operation, like middle or terminal gates. The HEC-RAS model has a very high convergence in terms of representing the real reality of the study area through comparison with the changes that occurred in part of it.

  1. Funding information: Authors declare that the manuscriptwas done depending on the personal effort of the author, and there is no funding effort from any side or organization.

  2. Conflict of interest: The authors state no conflict of interest.

  3. Data availability statement: Most datasets generated and analyzed in this study are in this submitted manuscript. The other datasets are available on reasonable request from the corresponding author with the attached information.

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Received: 2023-09-23
Revised: 2023-10-09
Accepted: 2023-10-23
Published Online: 2024-02-27

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Heruntergeladen am 4.11.2025 von https://www.degruyterbrill.com/document/doi/10.1515/eng-2022-0542/html
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