• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.143-148
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• 2006

There are need to manage the water quality to supply an safety to consumer through pipe and reservoir the drinking water that produced in a clean water reservoir. However, a management of water quality and monitoring in reservoir have never been performed. Recently, the government has enforced standards of water quality. However, we have a inferior technology of water quality as compared with one in USA, Japan, Germany, etc. In case of water quality inspection and analysis equipments, sensor technology is very important to improve the water quality inspection and to develop the analysis equipments. In this paper, we analyze a law and a regulation for management of drinking water quality, and propose the measurement standards of drinking water quality in pH, conductivity, residual chloride, turbidity and water temperature. Then, we analyze electrode sensors that interference within pH, conductivity, residual chloride in interference experiment.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.219-225
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• 2022

5th Assessment Report of the Intergovernmental Panel on Climate Change Weather (AR5) predicts that recent severe hydrological events will affect the quality of water and increase water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed, and solar radiation) were compiled into a representative concentration curve (RC), defined using 8.5. AR5 and future use are calculated based on land use. Semi-distributed emission model Calculate emissions for each target period. Meteorological factors affecting water quality (precipitation, temperature, and flow) were input into a multiple linear regression (MLR) model and an artificial neural network (ANN) to analyze the data. Extensive experimental studies of flow properties have been carried out. In addition, an Acoustic Doppler Velocity (ADV) device was used to monitor the flow of a large open channel connection in a wastewater treatment plant in Ho Chi Minh City. Observations were made along different streams at different locations and at different depths. Analysis of measurement data shows average speed profile, aspect ratio, vertical position Measure, and ratio the vertical to bottom distance for maximum speed and water depth. This result indicates that the transport effect of the compound was considered when preparing the hazard analysis.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.2
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• pp.151-158
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• 2019

Objectives of this study were to identify the hotspot for displacement of the on-line water quality sensors, in order to detect illicit discharge of untreated wastewater. A total of twenty-six water quality parameters were measured in sewer networks of the industrial complex located in Daejeon city as a test-bed site of this study. For the water qualities measured on a daily basis by 2-hour interval, the self-organizing maps(SOMs), one of the artificial neural networks(ANNs), were applied to classify the catchments to the clusters in accordance with patterns of water qualities discharged, and to determine the hotspot for priority sensor allocation in the study. The results revealed that the catchments were classified into four clusters in terms of extent of water qualities, in which the grouping were validated by the Euclidean distance and Davies-Bouldin index. Of the on-line sensors, total organic carbon(TOC) sensor, selected to be suitable for organic pollutants monitoring, would be effective to be allocated in D and a part of E catchments. Pb sensor, of heavy metals, would be suitable to be displaced in A and a part of B catchments.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.44-51
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• 2022

In this study, TOPSIS(Techniques for Order Performance by Similarity to Ieal Solution) was used to evaluate the installation points of water quality monitoring networks in 34 streams of the Nakdong River watershed. The Nakdong River System has been measuring water quality and flow in 195 local streams since 2011. In particular, the 34 key management points are areas with many pollutants and poor water quality, requiring continuous water quality management. For the selection of points requiring management, 10 indicators were selected for evaluation, and the selected indicators were standardized and weighted using the entropy method. As a result of weight calculation, the presence or absence of a nearby measuring network received the greatest weight, and the average water quality and presence of an industrial complex obtained the highest weight. The evaluated data are judged to be the research results necessary for the establishment of a new water quality measurement network in the Nakdong River system and continuous water quality management in tributaries.

• Korean Journal of Ecology and Environment
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• v.37 no.1 s.106
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• pp.106-111
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• 2004

Fecal coliform bacteria is one of the most common cause of water quality impairments in Virginia, USA. Instream concentrations of fecal coliform (FC) bacteria were routinely monitored to assess surface water quality of the Polecat Creek watershed. Median concentration in water samples collected from 1995 to 2000 ranged from 80 cfu/100 mL to t 70 cfu/100 mL, while geometric mean concentrations ranged from 81 cfu/100 mL to 141 cfu/100 mL. The dilution and deposition by Lake Caroline may cause to lower FC concentration at monitoring site QPB, as compared FC concentration at QPD. Higher in-stream FC concentration occurred during the summer period(June-August), and lower concentration typically occurred during the winter period (December-February). This is due to more cattle in streams, and greater survival and regrowth of FC bacteria under warmer condition. The findings of this study can be helpful in planning the water quality monitoring program to avoid the inaccurate assessment of water quality due to the timing of sample collection.

• Journal of Korean Society on Water Environment
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• v.33 no.1
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• pp.78-89
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• 2017

Water quality monitoring network data is being affected continuously due to non-point source pollution arising from agricultural land located on the Gwangsancheon outlet in the Nakdong River basin. In this study, we have performed analysis of water quality monitoring system, water quality pattern using SOM and water quality in the Gwangsancheon for sub-basin located at Gisan-myeon in the Nakdong River basin. We have developed and applied the model to estimate the runoff and non-point source loading. As a result of SOM pattern, the effect of non-point source pollution was the largest in the paddy fields and fields. As a result of the developed model, we found contribution rate and reduction rate for non-point source loading according to change of landuse because the reduction effect of nonpoint pollutants was 20.9% of SS, 9.9% of TN, 21.2% of TP and 8.9% of TOC depending on the landuse change.

• Journal of Korean Society on Water Environment
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• v.39 no.4
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• pp.343-355
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• 2023

After the implementation of the total pollution load control system, the effect of improving river water quality by expanding investments in basic environmental facilities, inducing operational efficiency, and reducing the load of various pollutants was clear. However, since the implementation of the system, the management of non-point pollutants has been neglected; management focused on specific substances (biochemical oxygen demand (BOD) and total phosphorus (T-P)) and lacked specific cause analysis and action plans, failed to establish a relationship between water quality and pollution load, failed to reflect stakeholder demands for river water quality management, and failed to apply technical conditions. Therefore, to overcome the limitations raised and achieve a practical and efficient advanced total pollution system, the current system was partially improved and will continue to be improved. This study analyzed the performance and limitations of the total pollution system and introduced recent improvements and the contents that are being improved. The main contents included reducing emissions and reduction monitoring, using water quality tele-monitoring system (TMS) data and self-measurement data, adding population-inducing facilities, and adjusting regional development projects from 20 to 30 multi-family housing units, currentizing each pollutant source according to the roadmap. If the system is improved in a developmental direction and responds to various changes, it will be a more practical and effective policy.

• Korean Journal of Ecology and Environment
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• v.41 no.spc
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• pp.1-10
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• 2008

We patterned water quality of agricultural reservoirs according to the differences of six physico-chemical environmental factors (TN, TP, DO, BOD, COD, and SS) using four different ordination methods: Principal Components Analysis (PCA), Detrended Correspondence Analysis (DCA), Nonmetric Multidimensional Scaling (NMS), and Isometric Feature Mapping (Isomap). The data set was obtained from the water quality monitoring networks operated by the Ministry of Agriculture and Forestry and the Ministry of Environments. Chlorophyll-${\alpha}$ displayed the highest correlation with COD, followed by TP, BOD, SS, and TN (p<0.01), while negatively correlated with altitude and bank height of the reservoirs (p<0.01). Although four different ordination methods similarly patterned the reservoirs according to the gradient of nutrient concentration, PCA and NMS appeared to be the most efficient methods to pattern water quality of reservoirs based on the explanation power. Considering variable scores in the ordination map, the concentration of nutrients was positively correlated with Chl-${\alpha}$, while negatively correlated with altitude and bank height. These ordination methods may help to pattern agricultural reservoirs according to their water quality characteristics.

• Journal of Environmental Health Sciences
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• v.42 no.4
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• pp.280-292
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• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.

• Membrane and Water Treatment
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• v.10 no.1
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• pp.99-104
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• 2019

In Korea, nonpoint pollutants have a significant effect on rivers' water quality, and they are discharged in very different ways depending on rainfall events. Therefore, preparing an optimal countermeasure against nonpoint pollutants requires much monitoring. The present study was conducted to help prepare a method for installing an automatic nonpoint pollutant measurement system for the cost-effective monitoring of the effect of nonpoint pollutants on rivers. In the present study, monitoring was performed at six sites of a river passing through an urban area with a basin area of $454.3km^2$. The results showed that monitoring could be performed for a relatively long time interval in the upstream and downstream regions, which are mainly comprised of forests, regardless of the rainfall amount. On the contrary, in the urban region, the monitoring had to be performed at a relatively short time interval each time when the rainfall intensity changed. This was because the flow rate was significantly dependent on the rainfall's intensity. The appropriate sites for installing an automatic measurement system were found to be a site before entering the urban region, a site after passing through the urban region, and the end of a river where the effects of nonpoint pollutant sources can be well-decided. The analysis also showed that the monitoring time should be longer for the rainfall events of a higher rainfall class and for the sites closer to the river end. This is because the rainfall runoff has a longer effect on the river. However, the effect of nonpoint pollutant sources was not significantly different between the upstream and the downstream in the cases of rainfall events over 100 mm.