• 환경영향평가
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• 제17권6호
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• pp.373-380
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• 2008

The Ministry of Environment plans to improve quality of water which is achieved over 85% in rivers and 94% in lakes of the whole country as "Good Water" until 2015. Also, the law of evaluation of water quality and water quality goal were made newly. So, the water quality has evaluated by using new law since 2007. This study evaluated whether "Good Water" and" Water Quality Goal" were achieved or not in 22 middle-sized districts and major 10 lakes of Geum river. The achievement rates of rivers decreased and the achievement rates of lakes mostly were the same for 5 years. In 2007, the achievement rates of "Good Water" were 50% in rivers and 50% in lakes. The achievement rate of "Water Quality Goal" were 59.1% in rivers and 20% in lakes. The water quality in 2007 was evaluated worse than last year in case of rivers. The evaluations of Korea-Comprehensive Water Quality Index(K-CWQI) showed that achievement rates of "Water Quality Goal" were 81.8% in rivers and 0% in lakes. The statistical correlation analysis showed that correlations between BOD and COD were meaningful at the downstream, compared to upstream, generally. In case of lakes, correlations between COD and temperature were meaningful. Also, correlations between COD and Chl-a were meaningful. The Trophic State Index ($TSI_{KO}$) showed that the half of lakes are major over eutrophic status in lakes. These analytical methods such as K-CWQI, $TSI_{KO}$, statistical correlation analysis could be additionally helpful for evaluation of water quality and provide basis data for understanding characteristics of watershed in Geum river.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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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.

• 한국농공학회지
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• 제32권3호
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• pp.116-129
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• 1990

A rational management of water resources in estuary reservoirs necessiates the prediction of water quality. In this study, a multiple box model for the water quality prediction was developed as a tool for the purpose of examining an adequate way to improve and maintain the water quality. Some submodels that are suitable for simulating the mixing behavior of pollutant materials in a lake were considered in this model. The model was appiled for predicting water qualities of Haenam Esturay Reservoir. The result from this study can be summarized as follows : 1.A water quality simulation model that can predict the 10-day mean value of water qualities was developed by adding some submodels that simulate the concentrations of chlorophyll-a, BOD, T-P and T-N to the existing Multiple Box Model representing the mixing and circulating of materials by the hydarulic action. 2.As input data for the model developed, the climatic data including precipitation, solar radiation, temperature, cloudness, wind speed and relative humidity, and the water buget records including the pumping discharge and the releasing discharge by drainage gate were ollected. The hydrologic data for the inflow discharge from the watershed was obtained by simulation with the aid of USDAUL-74/SNUA watershed model. Also the water quality data were measured at streams and the reservoir. 3.As a result of calibration and verification test by using four comonents of water quality such as Chlorophyll-a, BOD, T-P and T-N, it was found that the correlation coefficeints between the observed and the simulated water qualities showed greater than 0.6, therefore the capability of the model to simulate the water quality was proved. 4.The result based on the model application showed that the water quality of the Haenam Estuary Reservoir varies seasonally with the harmonic trend, however the water quality is good in winter and get worse in summer. Also it may be concluded that the current grarde of water quality in the Heanam Esutary Reservoir is ranked as grade 4 suitable only for the agricultutal use.

• 한국물환경학회지
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• 제20권4호
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• pp.313-320
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• 2004

In this study, variable characteristics of drinking water and the influences on underground water reservoirs, rooftop water tanks, and service water pipes in the building were assessed. The influence of underground water reservoir material and water capacity on water quality also were assessed. The results are the following as; First of all, the drinking water passing through underground water reservoirs or service water pipes in the building, averagely metal component concentration more increased from percent of 41.3 to percent of 74.2 totally than other items of water quality. On the other hand, both residual chlorine and total solid highly decreased 65.6 percent and 35.3 percent, respectively. Therefore, it was thought that water quality could be getting worse for microorganism re-growth by residual chlorine reduction, and total solid also could be a cause for extraneous matters accumulated in water reservoir. Secondly, the variations on water quality of each stage for water supply system in the building were higher in water service pipes connected from rooftop water tanks to the tap than in underground water reservoirs. In addition to, among of twelve items on water quality, ten items on water quality except dissolved oxygen and residual chlorine increased. Therefore, it was thought that the influence of water service pipes connected from rooftop water tanks to the tap on water quality were higher than other stages of water supply system in the building. Thirdly, in case of materials of underground water reservoir, it was likely that the variation on water quality by stainless steel and concrete materials got some similar. In case of water capacity, the variations on water quality of underground water reservoirs over $1,000m^3$ higher than those under $1,000m^3$. That reasons was likely that the retention time(49.72 hours averagely) of underground water reservoirs over $1,000m^3$ was two times longer than it of those under $1,000m^3$(23.37 hours). Therefore, it was thought that the influence on water quality by materials were some similar, but in case of water capacity, the influence of underground water reservoirs were higher.

• 한국농공학회지
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• 제43권3호
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• pp.56-65
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• 2001

In interpreting stream water quality data, scientific or statistical mehtods should be employed. Classical parametric statistical methods may not be adopted in analyzing water quality data, due to the violation of normality. In this study, nonparametric statistical methods, such as Kruskal-Wallis test and Mann-Whitney test, were used in comparing water quality data from several monitoring stations. Water quality data used are those collected Bokha watershed, located in Ichon-city, Kyonggi province. Based on the test results, domestic sewage is the major pollution source. A couple of sub-watersheds with a large number of livestock do not show significant differences in water quality parameters. It should be noted that comparison of mean values of water quality parameters is difficult to relate water quality with watershed characteristics. The results also indicate that livestock farming does not significantly affect the water quality.

• 환경영향평가
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• 제15권1호
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• pp.45-52
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• 2006

The purpose of this study is to assess spatiotemporal variation of coastal water quality according to time and location changes. For this we developed numerical marine trophic index base on four water quality components (chlorophyll, suspended solids, dissolved inorganic nitrogen and phosphorus) and applied this index to the water quality data measured in the korean coastal zone for the 7-years period from 1997 to 2003. Water quality data are obtained only at selected sites even though they are potentially available at any location. Therefore, in order to estimate spatial variation of coastal water quality, it is necessary to estimate the unknown values at unsampled locations based on observation data. In this study, we used IDW (Inverse Distance Weighted) method to predict water quality components at unmeasured locations and applied marine trophic index to predicted values obtained by IDW interpolation. The results of this study indicate that marine trophic index and spatial interpolation are useful for understanding spatiotemporal characteristics of coastal water quality.

• 한국물환경학회지
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• 제35권1호
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• pp.55-63
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• 2019

The Four Major Rivers Restoration Project started in 2009 and completed in early 2013 is a large-scale inter-ministry SOC project investing ₩22.2 $10^{12}$ and one of the Project's objectives was to enhance the water-quality grade through recovering the river eco-system and environment. The average concentration and probability distribution of water-quality constituents at given and selected sampling sites are very significant elements for analyzing and controlling the water-quality of rivers or reservoirs effectively. Average concentration can be estimated by point estimator, distribution function of water-quality constituents or Bootstrap method, in which the distribution function estimated with more data in case of insufficient dataset, is applied. Ipo and Gangcheon water-quality monitoring stations in South Han River were selected to compare and analyze the variation of concentration before and after Ipo and Gangcheon Weirs construction, using the whole 4-year's data, from 2005 to 2008 and from 2014 to 2017. Water-quality constituents such as BOD and COD relating to oxygen demanding wastes and TP and Chlorophyll-a relating to the process of nutrient enrichment called eutrophication were also selected. The guidelines for water-quality control and management after weir construction including evaluation of water-quality constituents' variations can be presented by this paper.

• 한국농공학회논문집
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• 제59권3호
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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.

• 한국물환경학회지
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• 제28권6호
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• pp.859-865
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• 2012

It is necessary to evaluate performances hitherto carried out in the management of Total Maximum Daily Loads (TMDLs) and to set up direction so that this system can be improved continuously in the future. This study was investigated load allocation achievement ratio, water quality goal achievement ratio and interrelation between water quality goal and load allocation for the first period (2004~2010). Load allocation achievement and BOD water quality goal achievement ratio were 50% and 73% in Guem River Basin, respectively. The main reason for excess of load allocation and shortfall of water quality goal were unfulfilled reduction plan and pollution sources increment. Therefore, it is necessary to develop enhanced pollution sources prediction method and make a list realizable reduction plan. 63% of the unit watershed was not interrelation between water quality goal and load allocation. The reason why water quality goal and load allocation had not correlation were water quality of upper unit watershed, increment of inflow quantity, effluent water quality of wastewater treatment plant affected the unit watershed, increment of inner productivity by algae, water quality deterioration during the specific period, river management flow, etc.

• 한국환경보건학회지
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• 제31권5호
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• pp.398-403
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• 2005

This study is undertaken to find the optimal method to make the decision on the degree of water pollution by comparison of K-WQI, KOE-WQI that is made for index with the water quality index and water quality environment standard of the Frame Act on Environment Policy as the result of survey for water quality reality on the major point of the Yeongsan river from 2002 to 2004. The water quality of major rivers has some differences depending on seasons. however, under the water quality standard by the $BOD_5$ density, most of rivers displayed the water quality level of $II{\sim}III$ grading, and on K-WQI that is classified by indexing for 10 categories of pH, DO, $BOD_5,\;COD,\;SS,\;T-N,\;NH_3-N,\;NO_{3^-}$ N, T-P, and E-Coli and classified into 5 groups from 100 points to 40 points, they displayed the score distribution of the first grade in water quality for $85{\sim}100$ points to the second grade in water quality for $70{\sim}84$ points. On KOE-WQI that is classified by indexing for 5 categories of pH, DO, $BOD_5$, COD and T-coli and classified into 5 groups from 90 points or above for outstanding and 29 points or below for very bad, and the water quality distribution is made ranged from the first grade in water quality for 90 points or more to the third grade in water quality for $69{\sim}50$ points. In addition, for the contribution of the water quality decline, the Environmental standard has significant dependency on the $BOD_5$ density, with K-WQI contributing in various water quality decline depending on the environment around the river area of $BOD_5,\;T-N,\;NH_3-N,\;NO_3-N,\;T-P$, and E-Coli, and KOE-WQI acting os the factor contributing to lower the water quality decline by $BOD_5$, COD, and T-coli. As such, the current water quality environment standard has high dependency on $BOD_5$ and KOE-WQI excludes some nitrogen and phosphorus that considers the river environment that the grade in water quality is set by some category, and K-WQI reflected well of the ecology environment of rivers with the diversity of the assessment factor as well as to have the low dependency of specific factor to be objective.