• Title/Summary/Keyword: Turbidity modeling

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A Real-time Monitoring and Modeling of Turbidity Flow into a Reservoir (실시간 저수지 탁수 감시 및 예측 모의)

  • Chung, Se-Woong;Ko, Ick-Hwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.1184-1188
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    • 2005
  • The impacts of turbidity flow induced by summer rainfall events on water supply, aquatic ecosystems, and socioeconomics are significant and major concerns in most of reservoirs operations. As a decision support tool, the real-time turbidity flow monitoring and modeling system RTMMS is under development using a laterally integrated two-dimensional (2D) hydrodynamic and water quality model. The objectives of this paper is to present the preliminary field observation results on the characteristics of rainfall-induced turbidity flows and their density flow regimes, and the model performance in replicating the fate and transport of turbidity plume in a reservoir. The rainfall-induced turbidity flows caused significant drop of river water temperature by 5 to $10^{\circ}C$ and resulted in density differences of 1.2 to $2.6kg/m^3$ between inflow water and ambient reservoir water, which consequently led development of density flows such as plunge flow and interflow in the reservoir. The 2D model was set up for the reservoir. and applied to simulate the temperature stratification, density flow regimes, and temporal and spatial turbidity distributions during flood season of 2004 After intensive refinements on grid resolutions , the model showed efficient and satisfactory performance in simulating the observed reservoir thermal stratification and turbidity profiles that all are essentially required to enhance the performance of RTMMS.

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Turbidity Modeling for a Negative Buoyant Density Flow in a Reservoir with Consideration of Multiple Particle Sizes (입자크기 분포를 고려한 부력침강 저수지 밀도류의 탁도 모델링)

  • Chung, Se Woong;Lee, Heung Soo;Jung, Yong Rak
    • Journal of Korean Society on Water Environment
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    • v.24 no.3
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    • pp.365-377
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    • 2008
  • Large artificial dam reservoirs and associated downstream ecosystems are under increased pressure from long-term negative impacts of turbid flood runoff. Despite various emerging issues of reservoir turbidity flow, turbidity modeling studies have been rare due to lack of experimental data that can support scientific interpretation. Modeling suspended sediment (SS) dynamics, and therefore turbidity ($C_T$), requires provision of constitutive relationships ($SS-C_T$) and accounting for deposition of different SS size fractions/types distribution in order to display this complicated dynamic behavior. This study explored the performance of a coupled two-dimensional (2D) hydrodynamic and particle dynamics model that simulates the fate and transport of a turbid density flow in a negatively buoyant density flow regime. Multiple groups of suspended sediment (SS), classified by the particle size and their site-specific $SS-C_T$ relationships, were used for the conversion between field measurements ($C_T$) and model state variables (SS). The 2D model showed, in overall, good performance in reproducing the reservoir thermal structure, flood propagation dynamics and the magnitude and distribution of turbidity in the stratified reservoir. Some significant errors were noticed in the transitional zone due to the inherent lateral averaging assumption of the 2D hydrodynamic model, and in the lacustrine zone possibly due to long-term decay of particulate organic matters induced during flood runoffs.

Uncertainty of Discharge-SS Relationship Used for Turbid Flow Modeling (탁수모델링에 사용하는 유량-SS 관계의 불확실성)

  • Chung, Se-Woong;Lee, Jung-Hyun;Lee, Heung-Soo;Maeng, Seung-Jin
    • Journal of Korea Water Resources Association
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    • v.44 no.12
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    • pp.991-1000
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    • 2011
  • The relationship between discharge (Q) and suspended sediment (SS) concentration often is used for the estimation of inflow SS concentration in reservoir turbidity modeling in the absence of actual measurements. The power function, SS=aQb, is the most commonly used empirical relation to determine the SS load assuming the SS flux is controlled by variations of discharge. However, Q-SS relation typically is site specific and can vary depending on the season of the year. In addition, the relation sometimes shows hysteresis during rising limb and falling limb for an event hydrograph. The objective of this study was to examine the hysteresis of Q-SS relationships through continuous field measurements during flood events at inflow rivers of Yongdam Reservoir and Soyang Reservoir, and to analyze its effect on the bias of SS load estimation. The results confirmed that Q-SS relations display a high degree of scatter and clock-wise hysteresis during flood events, and higher SS concentrations were observed during rising limb than falling limb at the same discharge. The hysteresis caused significant bias and underestimation of SS loading to the reservoirs when the power function is used, which is important consideration in turbidity modeling for the reservoirs. As an alternative of Q-SS relation, turbidity-SS relation is suggested. The turbidity-SS relations showed less variations and dramatically reduced the bias with observed SS loading. Therefore, a real-time monitoring of inflow turbidity is necessary to better estimate of SS influx to the reservoirs and enhance the reliability of reservoir turbidity modeling.

Laterally-Averaged Two-Dimensional Hydrodynamic and Turbidity Modeling for the Downstream of Yongdam Dam (용담댐 하류하천의 횡방향 평균 2차원 수리·탁수모델링)

  • Kim, Yu Kyung;Chung, Se Woong
    • Journal of Korean Society on Water Environment
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    • v.27 no.5
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    • pp.710-718
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    • 2011
  • An integrated water quality management of reservoir and river would be required when the quality of downstream river water is affected by the discharge of upstream dam. In particular, for the control of downstream turbidity during flood events, the integrated modeling of reservoir and river is effective approach. This work was aimed to develop a laterally-averaged two-dimensional hydrodynamic and water quality model (CE-QUAL-W2), by which water quality can be predicted in the downstream of Yongdam dam in conjunction with the reservoir model, and to validate the model under two different hydrological conditions; wet year (2005) and drought year (2010). The model results clearly showed that the simulated data regarding water elevation and suspended solid (SS) concentration are well corresponded with the measured data. In addition, the variation of SS concentration as a function of time was effectively simulated along the river stations with the developed model. Consequently, the developed model can be effectively applied for the integrated water quality management of Yongdam dam and downstream river.

Prediction of Turbidity in Treated Water and the Estimation of the Optimum Feed Concentration of Coagulants in Rapid Mixing Process using an Artificial Neural Network Model (인공신경망 모형을 이용한 급속혼화공정에서 적정 응집제 주입농도 결정 및 응집처리후 탁도의 예측)

  • Jeong, Dong-Hwan;Park, Kyoohong
    • Journal of Korean Society on Water Environment
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    • v.21 no.1
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    • pp.21-28
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    • 2005
  • The training and prediction modeling using an artificial neural network was implemented to predict the turbidity of treated water as well as to estimate the optimized feed concentration of polyaluminium chloride (PACl) in a water treatment plant. The parameters used in the input layers were pH, temperature, turbidity and alkalinity, while those in output layers were PACl and turbidity of treated water. Levenberg-Marquadt method of feedforward back-propagation perceptron in the neural network toolbox of MATLAB program was used in this study. Correlation coefficients of the training data with the measured data were 0.9997 for PACl and 0.6850 for turbidity and those of the testing data with measured data were 0.9140 for PACl and 0.3828 for turbidity, when four parameters at input layer, 12-12 nodes each at both the first and the second hidden layers, and two parameters(PACl and turbidity) at output layer were used. Although the predictability of PACl was improved, compared to that of the previous studies to use the only coagulant dose as output layer, turbidity in treated water could not be predicted well. Acquisition of more data through several years obtained with the advanced on-line measuring system could make the artificial neural network useful and practical in actual water treatment plants.

3D Modeling of Turbid Density Flow Induced into Daecheong Reservoir with ELCOM-CAEDYM (ELCOM-CAEDYM을 이용한 대청댐 유입탁수의 3차원 모델링)

  • Chung, Se-Woong;Lee, Heung-Soo;Ryoo, Jae-Il;Ryu, In-Gu;Oh, Dong-Geun
    • Journal of Korea Water Resources Association
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    • v.41 no.12
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    • pp.1187-1198
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    • 2008
  • Many reservoirs in Korea and their downstream environments are under increased pressure for water utilization and ecosystem management from longer discharge of turbid flood runoff compared to a natural river system. Turbidity($C_T$) is an indirect measurement of water 'cloudiness' and has been widely used as an important indicator of water quality and environmental "health". However, $C_T$ modeling studies have been rare due to lack of experimental data that are necessary for model validation. The objective of this study is to validate a coupled three-dimensional(3D) hydrodynamic and particle dynamics model (ELCOM-CAEDYM) for the simulation of turbid density flows in stratified Daecheong Reservoir using extensive field data. Three different groups of suspended solids (SS) classified by the particle size were used as model state variables, and their site-specific SS-$C_T$ relationships were used for the conversion between field measurements ($C_T$) and state variables (SS). The simulation results were validated by comparing vertical profiles of temperature and turbidity measured at monitoring stations of Haenam(R3) and Dam(R4) in 2004. The model showed good performance in reproducing the reservoir thermal structure and propagation of stream density flow, and the magnitude and distribution of turbidity in the reservoir were consistent with the field data. The 3D model and turbidity modeling framework suggested in this study can be used as a supportive tool for the best management of turbidity flow in other reservoirs that have similar turbidity problems.

Development and Validation of A Decision Support System for the Real-time Monitoring and Management of Reservoir Turbidity Flows: A Case Study for Daecheong Dam (실시간 저수지 탁수 감시 및 관리를 위한 의사결정지원시스템 개발 및 검증: 대청댐 사례)

  • Chung, Se-Woong;Jung, Yong-Rak;Ko, Ick-Hwan;Kim, Nam-Il
    • Journal of Korea Water Resources Association
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    • v.41 no.3
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    • pp.293-303
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    • 2008
  • Reservoir turbidity flows degrade the efficiency and sustainability of water supply system in many countries located in monsoon climate region. A decision support system called RTMMS aimed to assist reservoir operations was developed for the real time monitoring, modeling, and management of turbidity flows induced by flood runoffs in Daecheong reservoir. RTMMS consists of a real time data acquisition module that collects and stores field monitoring data, a data assimilation module that assists pre-processing of model input data, a two dimensional numerical model for the simulation of reservoir hydrodynamics and turbidity, and a post-processor that aids the analysis of simulation results and alternative management scenarios. RTMMS was calibrated using field data obtained during the flood season of 2004, and applied to real-time simulations of flood events occurred on July of 2006 for assessing its predictive capability. The system showed fairly satisfactory performance in reproducing the density flow regimes and fate of turbidity plumes in the reservoir with efficient computation time that is a vital requirement for a real time application. The configurations of RTMMS suggested in this study can be adopted in many reservoirs that have similar turbidity issues for better management of water supply utilities and downstream aquatic ecosystem.

Simulations of Temporal and Spatial Distributions of Rainfall-Induced Turbidity Flow in a Reservoir Using CE-QUAL-W2 (CE-QUAL-W2 모형을 이용한 저수지 탁수의 시공간분포 모의)

  • Chung, Se-Woong;Oh, Jung-Kuk;Ko, Ick-Hwan
    • Journal of Korea Water Resources Association
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    • v.38 no.8 s.157
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    • pp.655-664
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    • 2005
  • A real-time monitoring and modeling system (RTMMS) for rainfall-induced turbidity flow, which is one of the major obstacles for sustainable use of reservoir water resources, is under development. As a prediction model for the RTMMS, a laterally integrated two-dimensional hydrodynamic and water quality model, CE-QUAL-W2 was tested by simulating the temperature stratification, density flow regimes, and temporal and spatial distributions of turbidity in a reservoir. The inflow water temperature and turbidity measured every hour during the flood season of 2004 were used as the boundary conditions. The monitoring data showed that inflow water temperature drop by 5 to $10^{\circ}C$ during rainfall events in summer, and consequently resulted in the development of density flow regimes such as plunge flow and interflow in the reservoir. The model showed relatively satisfactory performance in replicating the water temperature profiles and turbidity distributions, although considerable discrepancies were partially detected between observed and simulated results. The model was either very efficient in computation as the CPU run time to simulate the whole flood season took only 4 minutes with a Pentium 4(CPU 2.0GHz) desktop computer, which is essentially requited for real-time modeling of turbidity plume.

Fuzzy modeling and control for coagulant dosing process in water purification system (상수처리시스템 응집제 주입공정 퍼지 모델링과 제어)

  • 이수범;남의석;이봉국
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.282-285
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    • 1996
  • In the water purification plant, the raw water is promptly purified by injecting chemicals. The amount of chemicals is directly related to water quality such as turbidity, temperature, pH and alkalinity. At present, however, the process of chemical reaction to the turbidity has not been clarified as yet. Since the process of coagulant dosage has no feedback signal, the amount of chemical can not be calculated from water quality data which were sensed from the plant. Accordingly, it has to be judged and determined by Jar-Test data which were made by skilled operators. In this paper, it is concerned to model and control the coagulant dosing process using jar-test results in order to predict optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride). The considering relations to the reaction of coagulation and flocculation, the five independent variables(turbidity, temperature, pH, Alkalinity of the raw water, PAC feed rate) are selected out and they are put into calculation to develope a neural network model and a fuzzy model for coagulant dosing process in water purification system. These model are utilized to predict optimum coagulant dosage which can minimize the water turbidity in flocculator. The efficacy of the proposed control schemes was examined by the field test.

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Characterization of Physical Properties of Turbid Flow in the Daecheong Reservoir Watershed dining Floods (홍수시 대청호 유역에 발생하는 탁수의 물리적 특성)

  • Chung, Se Woong;Lee, Heung Soo;Yoon, Sung Wan;Ye, Lyeong;Lee, Jun Ho;Choo, Chang Oh
    • Journal of Korean Society on Water Environment
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    • v.23 no.6
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    • pp.934-944
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    • 2007
  • Fine suspended solids (SS) induced into a reservoir after flood events play important ecological and water quality roles by presenting persistent turbidity and attenuating light. Thus the origin and physical features must be characterized to understand their transport processes and associated impacts, and for the establishment of watershed based prevention strategies. This study was aimed to characterize the physical properties of the SS sampled from Daecheong Reservoir and its upstream rivers during flood events. Extensive field and laboratory experiments were carried out to identify the turbidity-SS relationships, particle size distributions, settling velocity, and mineral compositions of the SS. Results showed that the turbidity-SS relationships are site-specific depending on the locations and flood events in the system. The turbidity measured within the reservoir was much greater than that measured in the upstream rivers for the same SS value. The effective diameters ($D_{50}$) in the rivers were in the range of $13.3{\sim}54.3{\mu}m$, while those in the reservoir were reduced to $2.5{\sim}14.0{\mu}m$ due to a fast settling of large particles in the rivers. The major minerals consisting of the SS were found to be Illite, Muscovite, Albite, and Quartz both in the rivers and reservoir. Their apparent settling velocities at various locations in the reservoir were in the range of 0.06~0.13 m/day. The research outcome provides a fundamental information for the fine suspended particles that cause persistent turbidity in the reservoir, and can be used as basic parameters for modeling study to search watershed based optimal control measures.