• Title/Summary/Keyword: Manage water quality

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Water Quality Modeling using Drone and Spatial Information Technology (드론 공간정보기술을 활용한 수질 모델링)

  • Young-Joo Kim
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.4
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    • pp.236-241
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    • 2023
  • Water quality problems in rivers, lakes, and estuaries have become serious in Korea. In order to overcome eutrophication of freshwater lakes and river basins, systematic management of water quality is necessary. To manage water quality in freshwater lakes and basins, apply hydrological models suitable for the basin and water quality models such as rivers and lakes to reduce water pollution based on the prediction results of these models. Improvement measures must be presented. In order to apply appropriate water pollution improvement measures in the watershed, accurate pollution sources must be identified and pollution loads must be predicted and presented. Based on GIS, the connection between the pollutant database and the hydrological and water quality prediction model will be integrated based on spatial location, making it possible to provide systematic support to improve watershed water quality by comprehensively including the water quality modeling process. In this paper, in order to accurately predict water pollution in freshwater lakes and river basins, a water quality model system is established using GIS-based spatial information to present a comprehensive water quality management method for freshwater lake basins in the future, and to systematically manage pollution sources through water quality modeling. This study was conducted to easily and efficiently operate hydrological and water quality models using automated spatial information.

Assessment of Estuary Reservoir Water Quality According to Upstream Pollutant Management Using Watershed-Reservoir Linkage Model (유역-호소 연계모형을 이용한 상류 오염원 관리에 따른 담수호 수질영향평가)

  • Kim, Seokhyeon;Hwang, Soonho;Kim, Sinae;Lee, Hyunji;Jun, Sang Min;Kang, Moon Seong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.6
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    • pp.1-12
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    • 2022
  • Estuary reservoirs were artificial reservoir with seawalls built at the exit points of rivers. Although many water resources can be saved, it is difficult to manage due to the large influx of pollutants. To manage this, it is necessary to analyze watersheds and reservoirs through accurate modeling. Therefore, in this study, we linked the Hydrological Simulation Program-FORTRAN (HSPF), Environmental Fluid Dynamics Code (EFDC), and Water quality Analysis Simulation Program (WASP) models to simulate the hydrology and water quality of the watershed and the water level and quality of estuary lakes. As a result of applying the linked model in stream, R2 0.7 or more was satisfied for the watershed runoff except for one point. In addition, the water quality satisfies all within 15% of PBIAS. In reservoir, R2 0.72 was satisfied for water level and the water quality was within 15% of T-N and T-P. Through the modeling system, We applied upstream pollutant management scenarios to analyze changes in water quality in estuary reservoirs. Three pollution source management were applied as scenarios, the improvement of effluent water quality from the sewage treatment plant and the livestock waste treatment plant was effective in improving the quality of the reservoir water, while the artificial wetland had little effect. Water quality improvement was confirmed as a measure against upstream pollutants, but it was insufficient to achieve agricultural water quality, so additional reservoir management is required.

The Wate Quality Characterics of Fresh Water Lake by Small-Scale Dairy Farm (소규모 축산농가에 의한 담수호의 수질오염특성)

  • 김선주;이석호
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.727-733
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    • 1999
  • In general ,wastes of livestock are covered 1% in the total wastes in Korea. But, actual pollutant loading rates by an organic material are 18% which will be serious problem in fresh water lake. An aim of this study is analyzing water quality in Bo-Ryeoung fresh water lake which are arounded by a lot of small livestock area, so that look for how to manage water quality of fresh waterlake.

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Rubbish, Stink, and Death: The Historical Evolution, Present State, and Future Direction of Water-Quality Management and Modeling

  • Chapra, Steven C.
    • Environmental Engineering Research
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    • v.16 no.3
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    • pp.113-119
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    • 2011
  • This study traces the origin, evolution, and current state-of-the-art of engineering-oriented water-quality management and modeling. Three attributes of polluted water underlie human concerns for water quality: rubbish (aesthetic impairment), stink (ecosystem impairment), and death (public health impairment). The historical roots of both modern environmental engineering and water-quality modeling are traced to the late nineteenth and early twentieth centuries when European and American engineers worked to control and manage urban wastewater. The subsequent evolution of water-quality modeling can be divided into four stages related to dissolved oxygen (1925-1960), computerization (1960-1970), eutrophication (1970-1977) and toxic substances (1977-1990). Current efforts to integrate these stages into unified holistic frameworks are described. The role of water-quality management and modeling for developing economies is outlined.

An Application of GIS to Water Quality Management (GIS를 이용한 하천수질관리)

  • Yang, Hyung-Jae;Lee, Yoo-Won;Kim, Min
    • Journal of Environmental Impact Assessment
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    • v.3 no.2
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    • pp.25-32
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    • 1994
  • This study was carried out as the Anyang creek water quality management using Geographic Information System (GIS) is the purpose of this pilot project to apply a GIS to environmental management field. Analysis of water quality data has been investigated using GIS with modeling of water quality management for the Anyang creek. The results of this study are summarized as follows: 1. The concentration of Mercury in sediment was increased rapidly nearby A26(Nightsoil Treatment Plant) and maximum was showed at A18 (Imgok bridge). Cadmium was increased rapidly at A35(Chulsan bridge). 2. River water quality management using visible computer system as GIS is effective to make decision for water quality management plan and database of environmental factors should be completed before applying GIS. 3. When water pollution accident is occurred in the river water system, pollutant source can be traced and analysed systematically using GIS to manage pollutants discharged into the river water system.

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Property Analysis of the Water Quality in Mankyeong River (만경강 수질자료 특성분석)

  • Kim, Won-Jang;Jo, Guk-Hyun;Eom, Myung-Chul;Lee, Kwang-Ya
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2002.10a
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    • pp.437-440
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    • 2002
  • By the explosive increase of population and industrialization the security of water resources is required, and water resource pollution problem is emerging as a serious social issue. For the ongoing Saemankeum project, lots of efforts are being put together to manage the water quality of the Saemankeum above a certain level, and it is sure that water quality management problem of main inflows from Mankyung River and Dongjin River is very important. Based upon the water quality data of Mankyung River this report examines its correlative characteristics by water quality sampling point factors and the water pollution resource factors, and subjects to provide elementary data for efficient water quality management of Mankyung River.

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Behavior of Water Quality in Freshwater Lake of Tide Reclaimed Area Using SWMM and WASP5 Models (SWMM과 WASP5모형을 이용한 간척지 담수호의 수질거동 특성 조사)

  • 김선주;김성준;이석호;이준우
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.2
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    • pp.148-160
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    • 2002
  • Lake water quality assessment information is useful to anyone involved in lake management, from lakeshore owners to lake associations. 11 provides lake water quality, which can improve how to manage lake resources and how to measure current conditions. It also provides a knowledge base that can be used to protect and restore lakes. SWMM was applied to simulate the discharge and pollutant loads from Boryeong watershed, and WASP5 was applied to analyze the changes of water quality in Boryeong freshwater lake. In each model, the most suitable parameters were calculated through sensitive analysis and some parameters used default data. Simulated in SWMM and measured discharge showed the accuracy of 88.6%. T-N and T-P exceeds the criteria in the simulation of water quality in Boryeong freshwater lake, and control of pollutant loads in the main stream showed the most effective way. Integrated water quality management system was developed to give convenience in the operation of SWMM and WASP5 and data acquisition.

The Study on the Quality of Natural Mineral Water (먹는 샘물 수질에 관한 연구)

  • Im, HyunChul
    • Journal of the Korean Geophysical Society
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    • v.7 no.1
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    • pp.41-41
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    • 2004
  • 56 samples were analyzed to understand water quality of the natural mineral water of Korea. The geology according to each sample location is grouped into Precambrian metamorphic rocks, Okcheon metamorphic rocks, Jurassic granite, Cretaceous granite, and Jeju volcanic rocks. Average EC and pH values of the water is 150 μS/cm and 7.3, respectively and water type of the water is mainly Ca-Na-HCO3. Fundamentally, there still is no problem for the water quality of the natural mineral water. Nevertheless, nitrate was detected and arsenic and fluoride contents are near the drinking water standards, it is highly necessary to manage the water quality by installment of casing and grouting or by development of another production well.

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Deriving Water Quality Criteria of Total Nitrogen for Nutrient Management in the Stream (하천에서의 영양물질 관리를 위한 총질소 환경기준 설정에 관한 연구)

  • Kim, Hak Kwan;Jeong, Han;Bae, Seung Jong
    • 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.

Application and evaluation for effluent water quality prediction using artificial intelligence model (방류수질 예측을 위한 AI 모델 적용 및 평가)

  • Mincheol Kim;Youngho Park;Kwangtae You;Jongrack Kim
    • 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.