• Environmental Engineering Research
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• v.22 no.1
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• pp.55-60
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• 2017

Provision of safe, accessible, and good water quality in the community is an important step towards reducing various waterborne illnesses. However, improving the quality of water should include spreading awareness to the public regarding the importance of cleaning their household water tanks. The aim of this study was to investigate the microbial quality of water of household water tanks in Dubai. The water samples from household water tanks were collected from forty houses, and a questionnaire was given to the residents to determine the history of the water tanks. The membrane filtration technique was used to quantify heterotrophic and total coliform bacteria on plate count agar and the violet red bile agar respectively. The overall results of this study have shown that 18 out of total 40 household water tanks contained different types of bacteria concentration level beyond local and widely accepted international standards. The overall results of this study indicated that there is a lack of awareness among residents regarding the importance of maintaining proper sanitation and hygiene of the household water tanks.

• Journal of Environmental Impact Assessment
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• v.21 no.4
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• pp.543-552
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• 2012

Namgang mid-watershed is located in downstream of Nakdong river basin. There are many pollution sources arround this area and it's control is important to manage a water quality of Nakdong river. A target year of Namgang mid-watershed water environment management plan is 2013. To predict a water quality at downstream of Namgang, we have investigated and forecasted the pollutant source and it's loading. There are some plan to construction the sewage treatment plants to improve the water quality of Nam river. Those are considered on predicting water quality. As results, it is shown that the population is 343,326 and sewerage supply rate is 79.2% and the livestock is 1,662,000 in Namgang mid-watershed. It is estimated that the population is 333,980, the sewerage supply rate is 86.9% in 2013. The milk cow and cattle were estimated upward and the pigs were downward by 2013. The generated loading of BOD and TP is 75,957 kg/day and 4,311 kg/day, discharged loading is 18,481 kg/day and 988 kg/day respectively in 2006. It were predicted upward the discharged loading of BOD and TP by 4.08% and 6.3% respectively. The results of water quality prediction of Namgang4 site were 2.5 mg/L of BOD and 0.120 mg/L of TP in 2013. It is over the target water quality at that site in 2015 about 25.0% and 9.1% respectively. Consequently, there need another counterplan to reduce the pollutants in that mid-watershed.

• Journal of Korean Society on Water Environment
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• v.20 no.3
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• pp.301-306
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• 2004

The present water quality standards for agricultural were established without considering the effects of water quality on the safety, growth, yield and quality of crops. This study was carried out to investigate the effects of irrigation water quality on the growth, yield, and grain quality of rice, and to acquire basic knowledges to set up water quality standards for irrigation. The field and pot experiments were conducted with irrigation water that was previously adjusted four concentrations (control, 5, 10, 20 mg/L) and six concentrations (control, 5, 10, 15, 20, 30 mg/L) by $NH_4NO_3$ solution and replicated three and four times with randomized block design, respectively. The results of this study showed that the inorganic nutrient of rice plant, rice protein contents and number of panicle tended to increase as the T-N concentration in irrigation water was increased. In addition, grain yield at T-N 10 mg/L and 20mg/L were significantly higher than the control at the field experiment. From the pot experiment at T-N 30 mg/L, the percentage of head rice was slightly lower due to the increase of green kernel and white belly/core kernel.

• The Journal of Engineering Geology
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• v.19 no.3
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• pp.307-311
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• 2009

Agricultural is recognised as being the leading contributor to groundwater. As a consequence, the consumer have to has bear the high expenses of water supplied to be treated. Importantly, the cost of water supplied is a function of the water quality as well as the scale of drinking water treatments. The relationship between the consumer payment and water quality improvement was affected by the scale of drinking water treatments directly. Hence when we achieve the high quality and low cost in the case of groundwater treatment for drinking, it is needed to consider both water quality and plant scale.

• Water Engineering Research
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• v.3 no.2
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• pp.85-92
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• 2002

There has been continuous efforts to manage water resources for the required water quality criterion at river channel in Korea. However, we could obtain the partial improvement only for the point sources such as, waste waters from urban and factory site through the water quality management. Therefore, it is strongly needed that the best management practice throughout the river basin fur water quality management including non-point sources pollutant loads. This problem should be resolved by recognizing the non-point sources pollutant loads from the upstream river basin to the outlet of the basin depends on the landuse and soil type characteristics of the river basin using the computer simulation by a distributed model based on the detailed investigation and application of Geographic Information System (GIS). The purpose of this study is consisted of the three major distributions, which are the investigation of spread non-point sources pollutants throughout the river basin, development of the base maps to represent and interpret the input and outputs of the distributed simulation model, and prediction of non-point sources pollutant loads at the outlet of a up-stream river basin using Agricultural Non-Point Sources Model (AGNPS). For the validation purpose, the Seom-Jin River basin was selected with two flood events in 1998. The results of this application showed that the use of combined a distributed model and an application of GIS was very effective fur the best water resources and quality management practice throughout the river basin

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• Journal of Environmental Science International
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• v.9 no.6
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Journal of Wetlands Research
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• v.1 no.1
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• pp.17-28
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• 1999

The purpose of this study was to analysis water quality monitoring data and to estimate future trends using ARIMA model of time series analysis. Water quality data in Chin yang reservoir were used with monthly monitoring interval during past 7 years. The variations of water quality parameters with periodicity and trend could be estimated by multiplicative ARIMA models and the statistical tests showed a good agreement with the observed data. Therefore, the monthly values of water quality parameters could be forecasted using these models.

• Korean Journal of Ecology and Environment
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• v.43 no.2
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• pp.338-344
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• 2010

The automatic water quality monitoring system (AWQMS) have been installed to immediately response to any pollution incident. It also make it possible to conduct the task efficiently regarding water quality control. The purpose of this study is to enhance reliability by securing accuracy of automatic water quality data through quality assessment (QA) for temperature, pH, dissolved oxygen (DO), electric conductivity (EC), total organic carbon (TOC). The result of comparison between manual and automatic data, relative accuracy of general items (temperature, pH, EC, DO) and TOC were mostly satisfied with guideline (i.e. less than 20%). On the other hand, relative accuracy of DO between sampling site and housing site was somewhat against the guideline. The contamination by attaching algae and microorganism in the pipeline is considered as main cause. After backwashing the pipeline, DO concentration was increased up to 53%. Therefore, pipeline management is recognizable as important thing to secure reliability of water quality data.

• Journal of the East Asian Society of Dietary Life
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• v.8 no.2
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• pp.173-180
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• 1998

This study was conducted to examine the sensory quality, the degree of gelatization, pH, color, texture and moisture content of paeksolgi with omija water extracts added. The results of the analysis were as follows : The moisture contents of Paeksolgi were about 36~39%. The L value of the control group was 83.04 The degree of the colour was (L value: 71.82~86.56), (a value: -1.33~+0.78), (b value : 7.84~9.78). As the amount of omija water extracts was increased. the L and a values increased, but the b value showed a similar value, It was found that the yellowness decreases by increasing the soaking time of each type. The gelatinization of Paeksolgi with omija water extracts added was decreased as the amount of omija was increased. The sensory quality of paeksolgi with 5~7% omija water extracts added showed the most favorable sensory evaluation. In view of color, after taste and overall quality, the D$_2$group of Paeksolgi was preferable to the other paeksolgi groups with omija water extracts added.