• Korean Journal of Environmental Agriculture
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• v.15 no.4
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• pp.506-519
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• 1996

The water quality in the rural areas is degrading due to a variety of causes such as the increase of the urban sewage and industrial wastes, the disposal of solid wastes, the growth of livestock waste, the growth of leisure facilities, the establishment of agricultural industry estates and etc. The water pollutants are scarce while the effluent is increasing from wide scattered sources. The technology specifically designed for the rural wastes water treatment plant needs to be implemented with improvement of agricultural water quality. 1. An integrated management measures against water pollution sources. The prevention of water pollution is the best measures in the environmental pollution. Hence, the most effective measures needs to be against the sources. Small-scale water treatment plants needs to be constructed in each village in the rural areas. As for the industrial effluent, the effluent discharge needs to be strictly monitored. Government subsidy for the establishment of treatment plant for livestock wastes is necessary. 2. The establishment of national-wide network for agricultural water quality. The network for agricultural water quality have been operated to conserve the agricultural water quality, and to develop management policies by the assessment of water pollution in the rural areas. The results of agricultural water quality network indicates that the water quality is degrading not only around urban areas but also in the distant rural areas, and the water quality at the pumping stations and weirs is worse than that of reservoirs. 3. The legal, systematic, and technical approaches for the agricultural water quality management. The actions currently implemented for the improvement of agricultural water quality involve temporary measures such as the improvement of irrigation facilities. These contingency measures are not effective in the long-term, and sometimes bring secondary pollution. Therefore, integrated measures covering the whole water environment such as the flow, quality, river morphology, aquatic ecosystem, and the surrounding environment, need be invented and implemented. Besides, the legal, systematic, and technical frameworks for the management are not fully established so far. The technology for the treatment of rural water pollution should be refined afterwards, and the research for the development of rural waste water treatment plant should be carried out.

• Ecology and Resilient Infrastructure
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• v.5 no.2
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• pp.88-93
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• 2018

In-situ water quality sampling is used for accurate water quality assessment. However, in-situ water quality sampling offers limited samples and requires much time and intensive labors. Remote sensing approach has recently applied for water quality assessment. It has shown the advantage of offering a synoptic view but also more efficient and economical. In this study, we utilized Landsat Imagery to estimate the water quality of the Tamsui River basin, considered as one of the most important rivers located in the north of Taiwan. In order to monitor water quality of Tamsui River basin, a linear regression relation between the value of spectral radiance and four water quality parameters are investigated with 38 water sampling stations. Through the regression model, we could estimate river pollution index (RPI) from the predicted value of four water quality parameters. By using RPI, we can examine the pollution level of Tamsui River. The accuracy of RPI conversion of this study ranged from 32.2% to 68.2%.

• Journal of Korean Society on Water Environment
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• v.28 no.5
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• pp.693-703
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• 2012

Load Duration Curve(LDC) is a useful tool for analyzing water quality characteristics under various stream flow conditions. This study investigated the methods to identify impaired waterbodies in the assessment of water quality goal attainment by using LDC for the management of Total Maximum Daily Loads (TMDLs). Three methods were proposed. Non-typical regime exclusion method is a method to exclude water quality observations in the non-typical extreme flow conditions in order to minimize the influence of non-ordinary water quality. Flow regime weighted average method is a method to calculate weighted mean water quality instead of arithmetic mean in order to consider water characteristics properly on stream flow regime in addition to the effect of Non-typical regime exclusion method. Load exceeded interval comparison method is a method to compare the intervals between the attained and non-attained load duration periods on the LDC. The assessment of water quality goal attainment can be performed more reasonably and precisely considering water quality variations on stream flow conditions by applying these proposed methods.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.737-747
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• 2006

Ministry of Environment (MOE) of Korea has been implementing the water quality management policy to focus on the control of organic matters (BOD and COD) for 28 years since 1978 when the water quality standards had been established. However, the government and the public have begun to recognize the necessity of creating the best water environment for people and aquatic life, and also formulating the various measures of water pollution, Consequently, MOE of Korea is establishing the basic plan of water environment management, with the vision of "Clean Water, Eco River 2015." The major targets of water environment management plan are to maintain ecosystem health and to protect water quality from various hazardous substances in water bodies. In order to achieve the major targets, it is essential to amend the water quality standards, which bring about the systematic management of various pollutants and healthy ecosystem. Introduction of the new techniques of water environment assessment is also prerequisite to maintain sustainable water environment. These can be accomplished under the consideration of following suggestions in environmental quality standards. First, several criteria should be complemented in water quality standards; they include the improvement of the current water quality classification system, the strengthening and supplement of relevant parameters considering human health in the standards, the introduction of biotic indices, and management standards on eutrophication. Secondly, it should be considered to introduce the biological water quality standards using biotic indices and the management standards for sediments. Lastly, it needs to introduce or develop an ecological status classification which could be used in the assessment of the water environment as a whole.

• Water for future
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• v.14 no.3
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• pp.55-66
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• 1981

The theory and practice of water quality scoring and indexing are introduced. The monthly water analysis data are available for six stations long the down-stream Han River whthin the areal boundary of the Special City of Seoul. The data cover the period between 1975 and 1979 inclusive and contain the analytical findings on 37 water constituents including DO, BOD, temperature, total solids and etc. Sic parameters are selected form the 37 items, that, to the judgement of the writer, best reflect the water quality of the Han River. They are; dissolved oxggen saturation, pH, fecal coliform, total solids, BOD and nitrate+ammonia. For each of the six parameters, a subscore function is developed and graphically presented to facilitate the transform of a measurment of the arameter to a subscore on a common score(e.G. 0-100) The score of a sample is calculated as a fuction of the six subscores, using four different approaches; (1) the unweighted arithmetic water quality score, (2) the weighted arithmetic water quality score, (3)the unweighted multiplicative score and (4) the reduced (total) score. Independent of these calculated scores, the experts' score which is calculated by averaging the ratings of water quality experts is obtained and compared with each of the four calculated scores by means of the least square method. The experts' score compares most favorably with the "reduced" score with the correlation coefficient of 0.956 : therefore this method of water quality scoring is adopted to calculate the Han River water quality scores and indices. Water quality index data for Guiri, ukdo, Pokwangdong, Noryangjin, Yongdungpo and Kayang Stations, 1975-1979 are as follow: The overall water quality index data of the Han River between Guiri and Kayang Stations are found; 47.3 in 1976, 48.0 in 1977, 48.5 in 1978 and 54.7 in 1979, indicating the general trend towards water quality improvent in this part of the river, in terms of the increased water quality index by average 1.85 points per year during this period. Finally the optimum sampling frequencies distributed among the six stations, using an equation which takes into account the coefficients of variation of the water quality scores and indices arec calculated.alculated.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.3
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• pp.121-127
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• 2015

The objective of this study is to suggest the water quality criteria of total nitrogen in order to efficiently manage the nutrient pollution in the stream. For this, correlations between water quality parameters were examined using the water quality data collected from the water quality monitoring network in the four rivers between 2003 and 2012. T-N showed positive correlations with T-P (0.636), COD (0.577), BOD (0.574), TOC (0.440), and SS (0.367). The statistical analysis including percentile analysis for the T-N and T-P concentrations was utilized to develop the water quality criteria of T-N. The feasibility of the suggested water quality criteria was evaluated by calculating the achievement rate to water quality target at the representative points in mid-watershed, then the draft water quality standard of T-N was suggested. The suggested water quality standard of T-N in the stream may be used to efficiently control the nutrient pollution in the public water body.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.51-62
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• 2017

Since living environment has improved, waterfront space using and clear water demand have increased. Ministry of Environment (ME) designated polluted reservoir (worse than 4th grade) as a priority management reservoir to improve water quality (better than 3rd grade) accordingly. Minstry of Agriculture, Food and Rural Affairs (MAFRA) aims reservoir water quality 4th not 3rd grade. And water quality of agricultural reservoirs was not a great interest. For this reason, there are very few water quality monitoring data. However after designating as a priority management reservoir, reservoir manager should start water quality and flow monitoring of reservoirs and inflow streams. This process makes it possible setting complex model to accurate prediction of reservoir water quality and volume. Mulwang reservoir designated as a priority management reservoir in September 2014. In this study, BASINS/WinHSPF and EFDC-WASP were used to predict effect of water quality improvement countermeasures in Mulwang reservoir. To improve water quality of Mulwang reservoir, Siheung-si and Korea Rural Community Corporation (KRCC) established water quality improvement countermeasures. However result of simulation adapting these countermeasures cannot achieve 3rd grade. So 4 additional scenarios were adapted and the result satisfied 3rd grade. This study could help to establish water quality improvement countermeasure by using complex modeling.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1387-1391
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• 2007

In this study, water quality prediction that is necessary to water quality forecasting system is performed using 2-D river analysis models RMA-2 and RAM4. RAM4 is suitable to water quality forecasting system cause it is possible to put in the pollutants as a mass type boundary condition. Instant injections of pollutants at Yongdamdaegyo Bridge in Namhangang River are simulated and the behavior of pollutant cloud is observed. The effects of water quality accident to Paldang 2 water intake plants in Paldangho Lake is analyzed with time variation. And extra flow simulation is performed for mitigation of pollution. Several cases of water quality forecasting system at home and abroad are investigated and the direction of water quality forecasting system is presented.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.3
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• pp.112-123
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• 1997

The Anyang stream is one of the Han river in Seoul Metropolitan area. It is 35.1km long, has a basin area of $282.26km^2$ and touches seven cities of Kyounggido and some of Seoul Metropolitan area. The situations of Anyang stream have resulted in severe stream water pollution problems. The purpose of this study were to measure the hydraulic characteristics and water quality, to make the countermeasures to achieve the stream water quality, to suggest the future conditions to improve water quality trough the Hydrodynamic and Water Quality Modal(WASP4). As the result of Anyang stream water quality forecsat, they are follows. Sewerage systems in the watershed of the Anyang stream have to be amended for wrong systemn and constructed in the upstream area of Anyang. The discharge of industrial wastewater has to be throughly controlled from the upstream area of the Anyang stream. Hydrodynamic and Water Quality Model(WASP4) for this study revealed the future water quality of the Anyang stream by computer simulation.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.1
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• pp.1-15
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• 2024

Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.