• Journal of Korean Society of Water and Wastewater
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• v.28 no.3
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• pp.277-286
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• 2014

Water discolouration and increased turbidity in the local water service distribution network occurred from hydraulic incidents such as drastic changes of flow and pressure at large consumer. Hydraulic incidents impose extra shear stresses on sediment layers in the network, leading to particle resuspension. Therefore, real time measuring instruments were installed for monitoring the variation of water flow, pressure, turbidity and particulates on a hydrant in front of the inlet point of large apartment complex. In this study, it is attempted to establish a more stable water supply plan and to reduce complaints from customers about water quality in a district metering area. To reduce red or black water, the water flow monitoring and control systems are desperately needed in the point of the larger consumers.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1237-1242
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• 2022

Fugitive dust, which accounts more than 50% of fine dust, is an air pollutant, that is generated by a lot in construction work(29.5%) and the law provides standards for facility installation and measures to control this. However, small-scale construction sites are not subject to management standards, and the law to measure and manage fugitive dust generated from construction sites is insufficient. In this paper, we designed and implemented the method to easily measure and monitor fugitive dust using the digital optical method for turbidity of dust. We presented the method to measure the turbidity of fugitive dust using the digital optical method and measured the actual turbidity of fugitive dust at the construction sites after implementing the fugitive dust measurement system.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.2
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• pp.191-200
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• 2004

DAF process has been designed considering raw water quality characteristics in Korea. Although direct filtration is usually operated, DAF is operated when the freshwater blooms occut or raw water turbidity become high. Pre-sedimentation iS prepared in case when raw water turbidity is very high by rainstorms. A main feature of this plant is that the operation mode can be changed (controlled) based on the characteristics of raw water to optimize the effluent quality and the operation costs. Treatment capacity (surface loading rate) and efficiency of DAF was found to be better than conventional sedimentation process. Moreover, low-density particles (algae and alum flocs) are easily separated while it is difficult to remove in sedimentation. One of the main concerns in adoption of DAF (Dissolved Air-Flotation) process is a high raw water turbidity problem. That is, DAF is not adequate for raw water, which is more turbid than 100NTU. In order to avoid this problem, pre-sedimentation basins are prepared in DAF plant to decrease the turbidity of DAF influent. For simulation of the actual operation, bench and full-scale tests were performed for highly turbid water conditions. Consequently, DAF process coupled with sedimentation is suggested that pre-sedimentation with optimum coagulation prior to DAF would be appropriate.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.517-526
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• 2018

Climate adaptation strategies for water utilities including 16 water treatment plants(WTPs) in Jeju were investigated. Drought, heat wave, and heavy rain were among the most significant climate factors affecting water utilities in Jeju. Heat wave increases water temperature, which in turn increases the concentration of algae, color, and odor materials. Some adaption strategies for the heat wave can be strengthening water monitoring and introducing advanced water treatments. Heavy rain increases raw water turbidity in surface water. The 7 WTPs that take raw water from streams or springs had a maximum turbidity of less than 50 NTU under heavy rain. However, due to concerns of turbidity spike in treated water, some WTPs discontinued intaking raw water when raw water turbidity increased more than 2 NTU. They instead received treated water from other WTPs which took groundwater for water supply. This happens because of the low skills of employees. Thus, there needs to be an increase in operator competency and upgrade of water facilities for the adaption of heavy rain. To improve adaption for the drought, there should be an increase in the capacity of intake facilities of surface water as well as a decrease in water loss. In addition, water consumption per person should be decreased.

• Korean Journal of Ecology and Environment
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• v.41 no.3
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• pp.360-366
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• 2008

The spatial and temporal variations of the high turbid water by a single event of heavy rain (total 299.1 mm and daily maximum 99.4 mm) were studied in Andong Reservoir, which has hypolimnetic discharges. Turbid water entered into the reservoir, was isolated from the bottom at the midreservoir and then passed through the metalimnion as an interflow current in the lacustrine zone. Maximum turbidity was 290 NTU at 16 m depth of the midreservoir, but the initial turbidity showed about 10 NTU in the reservoir before the rainfall. Turbid water in the reservoir affected to increase the withdrawal turbidity from the 3rd day after the rainfall, the maximum turbidity was 129 NTU at 5th day after the rainfall. Turbid water that flew towards the downreservoir distributed within 5 m above the outlet gate of the intake tower, showing the maximum turbidity, and that was decreased in its thickness and concentration by discharging through the intake tower. It has taken 38 days until the turbidity in the withdrawal reduced to 30 NTU, and 87 days to reduce the turbidity to the way when it was before the rainfall, with the correlation coefficient of 0.96 and 0.97, respectively. Turbid water was withdrawn from the reservoir by entraining into the intake tower as a form of the interflow, and not be settled down to the bottom of the reservoir. Therefore, we assessed that the depth of the withdrawal was appropriately positioned in Andong Reservoir, so as to withdraw the turbid water effectively from the reservoir.

• 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.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.107-115
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• 2023

High turbidity in source water can have adverse effects on water treatment plant operations and aquatic ecosystems, necessitating turbidity management. Consequently, research aimed at predicting river turbidity continues. This study developed a multi-class classification model for prediction of turbidity using LightGBM (Light Gradient Boosting Machine), a representative ensemble machine learning algorithm. The model utilized data that was classified into four classes ranging from 1 to 4 based on turbidity, from low to high. The number of input data points used for analysis varied among classes, with 945, 763, 95, and 25 data points for classes 1 to 4, respectively. The developed model exhibited precisions of 0.85, 0.71, 0.26, and 0.30, as well as recalls of 0.82, 0.76, 0.19, and 0.60 for classes 1 to 4, respectively. The model tended to perform less effectively in the minority classes due to the limited data available for these classes. To address data imbalance, the SMOTE (Synthetic Minority Over-sampling Technique) algorithm was applied, resulting in improved model performance. For classes 1 to 4, the Precision and Recall of the improved model were 0.88, 0.71, 0.26, 0.25 and 0.79, 0.76, 0.38, 0.60, respectively. This demonstrated that alleviating data imbalance led to a significant enhancement in Recall of the model. Furthermore, to analyze the impact of differences in input data composition addressing the input data imbalance, input data was constructed with various ratios for each class, and the model performances were compared. The results indicate that an appropriate composition ratio for model input data improves the performance of the machine learning model.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.201-210
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• 2017

This study proposes a numerical model which is able to simulate turbidity currents intruding into a reservoir and resulting sediment depositions. The proposed model is applied to laboratory experiments by Toniolo and Schultz (2005), and propagation of turbidity currents, morphological change, and trap of suspended sediment are simulated. It is simulated that the turbidity current after plunging at the foreset of the model delta, propagates along the bottom. The thickness of the turbidity current increases significantly after being blocked by the dam, and this effect is propagated in the upstream direction. In addition, it is simulated that the foreset moves in the downstream direction due to both the bedload and suspended load and the thickness of the bottom set increases due to the suspended load. It is found that the height of the intake affects the thickness of the turbidity current and the location of the internal hydraulic jump. The impact of the height of the intake on the trap efficiency is not clear in the experimental results, however, overall trap efficiency is predicted quite successfully by the model. Also, sensitivity analysis is carried out, and the results indicates that the particle size affects the trap efficiency most.

• 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.