• Title/Summary/Keyword: 장래수질

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Estimation of Stream Water Quality Changes Brought by a New Town Development (신도시 개발 후 도시하천의 장래수질 평가)

  • Park, Ji-Young;Lim, Hyun-Man;Yoon, Young-Han;Jung, Jin-Hong;Kim, Weon-Jae
    • Journal of Korean Society of Environmental Engineers
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    • v.36 no.1
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    • pp.58-66
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    • 2014
  • Water pollution problems of urban rivers due to the urbanization and industrialization have been the subject of public attention. In particular, considering the fact that the characteristics of water cycle of each basin change dramatically through the development of new towns, a large number of concerns about future water quality have been raised. However, reasonable measures to predict future water quality quantitatively have not been presented by this moment. In this study, by the linkage of annual unit load generation based on long-term monitoring results of the ministry of environment (MOE) to a semi-distributed rainfall runoff model, SWMM (Storm Water Management Model), we proposed a new methodology to estimate future water quality macroscopically and testified it to verify its applicability for the estimation of future water quality of a small watershed at G new town. As a result of the estimation using Y-EMC (Yearly based Event Mean Concentration), future water quality were simulated as BOD 18.7, T-N 16.1 and T-P 0.85 mg/L respectively which could not achieve the grade III of domestic river life guidance and these criteria could be satisfied by the reduction of domestic wastewater discharge load by over 80%. The results of this study are shown to be utilized for one of basic tools to estimate and manage water quality of urban rivers in the course of new town developments.

Water Quality Model Constitution using Water Quality-Stage Network Data of the Young-san River Basin (영산강 유역의 관측망 자료를 활용한 수질모델 구축)

  • Park, Sung-Chun;Oh, Chang-Ryol;Jin, Young-Hoon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.1338-1342
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    • 2005
  • 최근에 하천수질이 악화되고 물 수요량이 증대됨에 따라 사회적으로 하천의 유지관리문제가 중요시되고 있는 실정이다. 보다 효율적인 수질관리를 위해서 수질모델을 이용하여 장래 수질예측결과를 토대로 수질보전 대책 및 오염원 저감 계획을 수립하여야 하는데, 이러한 수질모델의 구성을 위해서는 장기간의 수질 및 유량측정자료의 구축이 선행되어져야하므로 시간적$\cdot$경제적인 어려움이 따르게 된다. 이에 본 연구에서는 영산강을 대상유역으로 선정하고, 영산강 유역 환경청과 영산강 홍수통제소에서 운영$\cdot$관리하는 관측망 자료인 수질자료와 수위자료를 이용하여 수질모델을 구축하고, 장래 수질예측을 실시하였다. 수질예측결과 영산강은 광주하수종말처리장 방류수의 수질농도가 지대한 영향을 미치는 것으로 판단되어 광주하수종말처리장 처리효율에 따른 수질변화를 모의하였다.

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Water Quality Modeling by the WASP4 Model (WASP4 모형에 의한 수질모델링)

  • 조홍연;전경수;이길성
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.5 no.3
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    • pp.221-231
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    • 1993
  • WASP4. an estuarine or lake water quality model, wat applied to simulate future water qualities at alternative withdrawal sites for capital areas. Simulated water quality constituents were Chlorophyll a, nitrogen cycles, Phosphorus, BOD End DO. A Water budget analysis Using the monthly records of reservoir inflows and outflows between 1986 and 1990 was made to determine seasonally-averaged flowrates at model boundaries. Estimated flowrates were used. together with the seasonal water quality inputs simulated by the QUAL2E model, for the simulation of future water qualities. Sensitivities to the future pollutant inputs and possible future withdrawal alternatives were also analyzed. From simulations or future water qualities it is found that among the candidate withdrawal sites. the one located at the downstream end of the North Han River has the best future water quality in all quality constituents and the one at the downstream end of the South Han River has the worst Possible future withdrawal from the North Han River brings a slight increase or pollutant concentrations at existing withdrawal sites. but the aggravation of water quality is not significant.

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Water Quality Prediction of the Miho Stream Using GIS (GIS를 이용한 미호천의 장래수질예측)

  • Noh, Jun-Woo;Lee, Sang-Jin;Lee, Sang-Uk
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.13-21
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    • 2008
  • This study conducted water quality projection of year 2010 in Miho stream of the Geum river basin by using GIS. Pollutant load data of corresponding tributary of the Miho stream is estimated based on the pollutant load of TMDL zone to simulate water quality of the Miho stream for BOD, TN, and TP. The pollutant load of the urban area such as Bochung and Musim stream basin is relatively high and the wastewater treatment plant of Chunju city directly affects the entire water quality of the target area. As a result, simulation result reveals that water treatment facility needs more refined treatment process for efficient water quality management. Also, to meet the target water quality of the Miho stream water quality simulation estimates the additional dilution flow by increasing irrigation water supplied from the Daechung dam through the Musim stream.

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The prediction of electricity for seawater reverse osmosis process considering future seawater quality (장래 해수수질 변화를 고려한 역삼투압 공정 전력비 예측)

  • Shim, Kyu Dae;Jang, Boo Keun;Choung, Joon Yeon;Baik, Seung Min;Kim, Dong Kyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.243-243
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    • 2020
  • 본 연구는 장래 유입수질 변화로 해수담수화(Desalination) 역삼투압(Seawater Reverse Osmosis) 공정의 전력비 예측 모델을 개발하고 별도의 해수담수화 추가공정이 필요한지 검토하였다. 플랜트 시설은 한번 설치되면 오랜 기간 운영이 되고, 주요 공정의 시설물 변경이 어려우며, 특히 해수담수화 시설의 경우에는 생활용수 및 공업용수를 수요자에 상시 공급함으로서 중간에 추가 시설물을 증설하거나 변경하기가 쉽지 않다. 따라서 해수담수화 시설의 계획 초기부터 현재의 유입수질 및 장래의 수질 변화를 예측하여 해수담수화 공정을 계획하는 것이 필요하다. 금회 검토는 해수온도 및 염분도 변화를 고려하여 서해에 위치한 대산산업단지 해수담수화 시설의 해수담수화 공정 전력비를 예측하였고, 입력 자료(온도 및 염분도)는 국가해양환경정보통합시스템(MEIS, Marine Environment Information System) 22년 과거자료(1997~2018년)를 이용하였다. 개발된 모형에 적용하여, 해수담수화에 필요한 전력비의 변화를 예측할 수 있으며, 이를 바탕으로 해수담수화 시설물 공정계획을 검토할 수 있었다. 금회 연구에서는 장래 수질변화 예측모형의 결과를 기반으로 해수담수화 시설물 공정을 제시하였다는데 의의가 있다.

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Water Quality Modeling of Juam Lake by Fuzzy Simulation Method (퍼지 Simulation 방법에 의한 주암호의 수질모델링)

  • Lee, Yong Woon;Hwang, Yun Ae;Lee, Sung Woo;Chung, Seon Yong;Choi, Jung Wook
    • Journal of Korean Society of Environmental Engineers
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    • v.22 no.3
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    • pp.535-546
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    • 2000
  • Juam lake is a major water resource for the industrial and agricultural activities as well as the resident life of Kwangju and Chonnam area. However, the water quality of the lake is getting worse due to a large quantity of pollutant inflowing to the lake. As a preliminary step in making the countermeasure to achieve the water quality goal of the lake. it is necessary to understand how the water quality of the lake will be in future. Several computer programs can be used to predict the water quality of lake. Each of these programs requires a number of input data such as hydrological and meteorological data. and the quantity of the pollutant inflowed. but some or most of the input data contain uncertainty. which eventually results in the uncertainty of prediction value (future level of water quality). Generally. the uncetainty stems from the lack of information available. the randomness of future situation. and the incomplete knowledge of expert. Thus. the purpose of this study is to present a method for representing the degree of the uncertainty contained in input data by applying fuzzy theory and incorporating it directly into the water quality modeling process. By using the method. the prediction on the future water quality level of Juam lake can be made that is more appropriate and realistic than the one made without taking uncertainty in account.

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Estimation of Reservoir Discharge to Support TMDL Management in the Geum River Basin (금강수계 오염총량관리를 고려한 저수지 방류량산정)

  • Noh Joon-Woo;Kim Soo-Jun;Kim Jeong-Kon;Koh Ick-Hwan
    • Journal of Korea Water Resources Association
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    • v.39 no.7 s.168
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    • pp.627-636
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    • 2006
  • This study estimates adequate discharge to meet the specified target water quality concentration using the pollutant load of the Geum river basin given in TMDL (Total Maximum Daily Load) report. During the 1st phase, BOD is chosen as a target water quality constituent under regulation of the Ministry of Environment in Korea. BOD, TN, and TP loads estimated based on the TMDL and provincial zones were re-distributed for 10 major tributaries, and the remaining areas along the main river are classified as 15 incremental flow areas. Water quality modeling was conducted using Qual2E for the low flow period of a year (i.e. $March{\sim}April$). The results of the model simulation showed that about 30 cms from the Daechung dam would be sufficient to satisfy the target water quality in the Geum river downstream of the Daechung multipurpose Dam.

Analysis of the effect of water quality improvement on Seomgang and South Han river by securing the flow during the dry season (갈수기 유량 확보에 따른 섬강 및 남한강 본류 갈수기 수질 개선 효과 분석)

  • Lee, Seoro;Lee, Gwanjae;Park, Geonwoo;Kim, Jonggun;Lim, Kyoung Jae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.323-323
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    • 2019
  • 최근 충주댐 하류에 위치한 남한강 본류에서는 봄철 지속되는 가뭄으로 인한 유량부족과 인근 주요 유입하천으로부터의 과다한 영양염류 유입으로 갈수기 수질오염 문제가 빈번히 발생하고 있다. 그러나 아직까지 충주댐 하류 남한강 본류 하천을 대상으로 기후변화에 따른 장래 갈수기 수질변화 예측과 상류 유역에서의 유량 확보가 본류 하천 갈수기 수질에 미치는 영향을 정량적으로 분석한 연구는 미흡한 실정이다. 따라서 본 연구에서는 충주댐 하류 남한강 본류 구간과 주요 유입하천을 대상으로 유역 및 수질 모델 연계를 통해 극한 가뭄 사상에 따른 남한강 본류의 장래 갈수기수질 변화를 예측하고, 섬강 유역 내 갈수기 유량 확보 시나리오 적용을 통해 극한 가뭄 사상에서의 섬강 말단 및 남한강 본류 갈수기 수질 개선 효과를 분석하였다. 갈수기 유량 확보 시나리오는 산림 간벌에 따른 증발산량 저감 및 침투량 증진 시나리오로 구성하였다. 시나리오 적용 결과, 섬강 유역에서의 갈수기 평균 유량은 최대 2.19배까지 증가하는 것으로 분석되었으며, 갈수기 수질평균 농도는 최대 BOD5 20.5%, T-N 40.8%, T-P 53.4%까지 개선되는 것으로 나타났다. 또한 섬강 유역에서의 갈수기 유량 확보에 따라 남한강 본류 갈수기 수질 평균 농도는 최대 BOD5 5.22%, T-N 5.42%, T-P 7.69%까지 개선되는 것으로 나타났다. 본 연구의 결과를 통해서 산림 간벌에 따른 기저유량의 확보가 갈수기 하천 수량 및 수질에 긍정적인 영향을 미치는 것을 간접적으로 확인할 수 있었으며, 이는 수량 수질뿐만 아니라 수생태계 건강성 연속성 유지 측면에서 큰 기여를 할 수 있을 것이라 판단된다. 따라서, 섬강 유역 내 갈수기 유량 확보 방안으로 적절 수준의 산림 간벌 대책이 강구되어야 할 것이며, 산림 간벌 이외에 갈수기 유량 확보를 위한 빗물 이용, 공공하수처리시설 방류수 재이용, 우수의 저류 및 침투시설 확충 등 다양한 대책이 검토되어야 할 것으로 판단된다.

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T-N and T-P Simulations in the Downstream of the Han River (한강 하류부에서의 총질소와 총인에 대한 수질모의)

  • 한건연;송재우
    • Water for future
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    • v.28 no.4
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    • pp.137-146
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    • 1995
  • QUAL2E model is applied to predict T-N and T-P concentrations in the downstream of the Han River. Sensitivity analysis shows that the pertinent parameters for T-N and T-P have small effects on the computed concentrations. The computed concentration profiles of T-N and T-P show good agreements with recently measured data. The future tributary loads of T-N and T-P have been estimated to simulate concentrations. The modeling result has been presented under the mean and low flow condition after wastewater treatment in the future.

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Prediction model for electric power consumption of seawater desalination based on machine learning by seawater quality change in future (장래 해수수질 변화에 따른 머신러닝 기반 해수담수 전력비 예측 모형 개발)

  • Shim, Kyudae;Ko, Young-Hee
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1023-1035
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    • 2021
  • The electricity cost of a desalination facility was also predicted and reviewed, which allowed the proposed model to be incorporated into the future design of such facilities. Input data from 2003 to 2014 of the Korea Hydrographic and Oceanographic Agency (KHOA) were used, and the structure of the model was determined using the trial and error method to analyze as well as hyperparameters such as salinity and seawater temperature. The future seawater quality was estimated by optimizing the prediction model based on machine learning. Results indicated that the seawater temperature would be similar to the existing pattern, and salinity showed a gradual decrease in the maximum value from the past measurement data. Therefore, it was reviewed that the electricity cost for seawater desalination decreased by approximately 0.80% and a process configuration was determined to be necessary. This study aimed at establishing a machine-learning-based prediction model to predict future water quality changes, reviewed the impact on the scale of seawater desalination facilities, and suggested alternatives.