• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.36-36
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• 2023

Sedimentation is a natural process that occurs in all reservoirs. Sedimentation problem reduces the storage capacity of the reservoir and limits its ability to provide water for various uses, such as irrigation, hydropower generation, and flood control. Therefore, predicting reservoir sedimentation is important for ensuring the efficient operation and sedimentation management of a reservoir and . In this study, the HECRAS model was applied to predict longitudinal distribution of deposited sediment in the Pleikrong reservoir to 2050. Different scenarios was considered: (i) no climate change, (ii) climate change (under two emissions scenarios, RCP4.5 and RCP8.5), and (iii) climate change and land use change (followed land use planning of the watershed). The computation results with different scenarios were analyses and compared. The results show that the reservoir reduced storage volume's rate and sedimentation proceed toward to the dam in the case of climate change is faster than in the case of no climate change. Analyses also indicates that following the land used planning could also improve the long-term problem of the reservoir sedimentation. The outcomes of this study will be helpful for a sustainable plan of sediment management for the Pleikrong reservoir.

• Journal of Korean Society on Water Environment
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• v.29 no.6
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• pp.799-807
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• 2013

Reservoir sedimentation is one of the major concerns for sustainable reservoir operation. Since sediment concentration of the rivers in the Himalayan Mountain is very high, a proper sediment management scheme is necessary. This paper presents long-term reservoir sedimentation and sediment flushing based on the gate operation. Focused on the reservoir to be constructed for the Patrind hydropower project in Pakistan, 4 different flushing scenarios were proposed in this study to prevent successive sedimentation. By extending flushing period and by increasing the flushing discharge for 2 times, the flushing rate increases up to 53.2% and 43.6% in proportion to flushing period and discharge, respectively. Based on the simulation presented in this paper, it is expected to establish efficient sediment management plan to increase hydro power generation and sediment flushing simultaneously.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.199-204
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• 2023

Periodic assessment of reservoir capacity is essential for better water resources management and planning for the future water use. Reservoirs and water storage structures raised on the rivers are subjected to sedimentation and he sedimentation is caused by deposition of eroded sediment particles carried by the streams. Knowledge of reservoir sedimentation is important to estimate avaliable storage capacity for optimum reservoir operation and scheduling water release. In recent years, remote sensing and GIS techniques have emerged as an important tool in carrying out reservoir capacity analysis and water management. The reduction in storage capacity as compared to the original capacity at the time of reservoir impounding is indicative of sediment deposition. In this study, the application of GIS and remote sensing techniques were applied to assess the sediment deposition, losses in the reservoir storage and the revised cumulative capacity. Satellite images covering Pyodongdong reservoir were analyzed using Erdas Imagine and ArcGIS softwares.Cumulative capacities at different levels were also calculated and we estimated that the revised live storage was 84.2Mft3 in 2021 and 64.3Mft3 in 2022 while the original capacity was 22.8 and 53.6Mft3 in 2021 and 2022.

• Water for future
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• v.17 no.2
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• pp.107-112
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• 1984

It si presented here that in order to estimate reservoir sedimentation rate through the use of reservoir survey data of 66 irrigation reservoir in 3 major watersheds in this country, the correlation between reservoir sedimentation rate and the following factors; watershed area, trap-efficiency, watershed slope, shape factor of water shed, and reservoir deposition age in two models simple regression model and multiple regression model. Appropriatness of the proposed models have been calibrated from the survey data and as a result, it has been determined that the multiple regression model is much more accurate than the simple regression model. The annual sediment yield is correlated with watershed area and reservoir trap efficiency. It has been found that variation of the annual average sedimentation rate and the annual reservoir capacity loss rate are influenced by the trap efficiency of reservoir.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.1
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• pp.50-58
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• 1993

The sedimentation patterns at a reservoir, important to the reservoir capacity curve were simulated using a depth averaged, two-dimensional sediment transport model, that is capable of depicting velocity distributions and sediment transportation. The Banweol reservoir, whose stage capacity relationships have been surveyed before and after the construction, was selected and the daily inflow rates and stages were simulated using a reservoir operation model(DI-ROM). The applicability of the transport model was tested from the comparisons of simulated sedimentation patterns to the surveyed results. The simulated inflow rates and water level fluctuations at the reservoir during twenty-one years from 1966 to 1986, showed that water levels exceeding 80 percent of the total capacity occurred for 70 percent of the periods and inflow rates less than 5000rn$^3$/day sustained for 54 percent of the spans. Dorminant flow directions were simulated from two streamflow inlets to the dam site. And simulated sediment concentrations were higher near the inlets and lower at the inside of the reservoir. Sediment was deposited heavily near the inlets, and portions of sediments were distributed along the flow paths within the reservoir. The comparisons between the simulation results and the surveyed depositions were partially matched. However, it was not possible to compare two results at the upper parts of the reservoir where dredging was carried out few times for the purpose of reservoir maintenance. This study demonstrates that sedimentation patterns within the reservoir are closely related to incoming sediment and flow rates, water level fluctuations, and flow circulation within the reservoir.

• Magazine of the Korean Society of Agricultural Engineers
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• v.42 no.1
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• pp.73-82
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• 2000

Large quantitive of polllutants are washed into reservoirs during storm events. These polllutants contribute to eutrophication, such as algal blooms and fish kills. This study was conducted for the purpose of assessing the pollutant removal possibilities of sedimentation pool formed by deep dredging of a reservoir inlet. Water quality data were collected in the Masan reservoir, whose inlet has been dredged deep like sedimentation pool. The average concentration of chemical oxygen demand(COD) , toatal nitrogen(T-N) and total phosphrous(T-P) in the deep dredged area were 8.7 ~20.5mg/ι (T-N), 0.17~0.84mg/ι(T-P), which were 4.9%(COD), 29.0%(T-N) and 44.8%(T-P) higher than those of middle part of the reservior. The texture of sediment in the dredged area was silty loam, while that of the middle part was sandy clay loam. Organic matter contents, T-N and T-P of the bottom soil in the dredge area showed higher values than the middle part of the reservoirs. From these results, it was considered thedeep dredged area in the inlet of reservoir might play a key role to settle pollutant particulate. Based on the result of water quality analysis, deep dredging of the reservoir inlet could be assessed to reduce T-N and T-P of the reservoir about 6.5% , 8.3%, respectively. However, the effect of the sedimentation pool would be raised if the settled particles were taken into account in assessing water quality improvement for the reservoir. Accordingly, dredging of a reservoir inlet to make a shape of sedimentation pool is recommended for water quality improvement of reservoir in the stage of dredging plan.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.1 no.1
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• pp.69-76
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• 1981

The predictive equations for reservoir sedimentation rate now in use are extensively reviewed, and the equation of multiple regression type, in which the reservoir sedimentation rate is related with the watershed area and the trap-efficiency, is proposed based on the 113 irrigation reservoir resurvey data. The predictive relation so obtained proved to be a reasonable measure for the estimation of reservoir sedimentation rate. The relationship of sediment yield with the watershed area and with the reservoir trap efficiency is also analyzed. The variations of sedimentation rate and of the annual reservoir capacity loss rate was shown to heavily depend on the trap-efficiency of a reservoir. Besides, the effect of sedimentation on stream channels is confirmed and quantified based on the predictive equation derived in the present study.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.657-662
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• 1999

This study was conducted for the purpose of assessing the pollutant removal possibilities of sedimentation pool formed by deep dredging of a reservir inlet. Water quality data were collected in the Masan reservoir, whose inlet has been dredged deep like sedimentation pool. The average concentration of chemical oxygen demand(COD), total nitrogen(T-N) adnd total phosphorous(T-P) in the deep dredged area were 8.3∼28.4mg/$\ell$ (COD), 2.0∼6.0mg/$\ell$(T-N), 0.17∼1.34mg/$\ell$(T-P), which were 3.3% (COD) , 30.6%(T-N) and 46.4%(T-P) higher than those of middle part of the reservoir. From these results, it was considered the deep dredged area in the inlet of reservoir might play a key role to improve reservoir water quality.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.159-159
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• 2019

In this study, the simulation of sediment deposition at Sangju weir reservoir, South Korea, was carried out using artificial neural networks. The ANNs have typically been used in water resources engineering problems for their robustness and high degree of accuracy. Three basic variables namely turbid water inflow, outflow, and water stage have been used as input variables. It was found that ANNs were able to establish valid relationship between input variables and target variable of sedimentation. The R value was 0.9806, 0.9091, and 0.8758 for training, validation, and testing phase respectively. Comparative analysis was also performed to find optimum structure of ANN for sediment deposition prediction. 3-14-1 network architecture using BR algorithm outperformed all other combinations. It was concluded that ANN possess mapping capabilities for complex, non-linear phenomenon of reservoir sedimentation.

• Journal of Korean Society on Water Environment
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• v.20 no.5
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• pp.473-479
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• 2004

A sedimentation basin (SB) at the inlet of an irrigation reservoir which was constructed using an auxiliary dam was monitored to evaluate its pollutant removal efficiency. Water sampling at three points, i.e., inflow stream, upstream and downstream of the reservoir, were taken 5 times before and after the construction of the SB in 1999 and 2003, respectively. No significant water quality variations in inflow stream were observed during these periods. The COD, T-N, T-P and SS removal efficiencies were 38, 24, 35 and 49%, respectively. The results indicated that those removal efficiencies significantly increased during the rainy season and COD removal efficiency, especially, was higher than others studies. The scale of SB in this study was rational as aspects of pollutant removal efficiency and hydraulic detention time. And it is recommended that SB, at inlet of an reservoir, should be constructed as completely separated structure from reservoir water body and having SAR Index from 0.7% to 1.0%.