• 제목/요약/키워드: Water quality analyze

검색결과 579건 처리시간 0.026초

Future water quality analysis of the Anseongcheon River basin, Korea under climate change

  • Kim, Deokwhan;Kim, Jungwook;Joo, Hongjun;Han, Daegun;Kim, Hung Soo
    • Membrane and Water Treatment
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    • 제10권1호
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    • pp.1-11
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    • 2019
  • The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) predicted that recent extreme hydrological events would affect water quality and aggravate various forms of water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed and sunlight) were established using the Representative Concentration Pathways (RCP) 8.5 climate change scenario suggested by the AR5 and calculated the future runoff for each target period (Reference:1989-2015; I: 2016-2040; II: 2041-2070; and III: 2071-2099) using the semi-distributed land use-based runoff processes (SLURP) model. Meteorological factors that affect water quality (precipitation, temperature and runoff) were inputted into the multiple linear regression analysis (MLRA) and artificial neural network (ANN) models to analyze water quality data, dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), suspended solids (SS), total nitrogen (T-N) and total phosphorus (T-P). Future water quality prediction of the Anseongcheon River basin shows that DO at Gongdo station in the river will drop by 35% in autumn by the end of the $21^{st}$ century and that BOD, COD and SS will increase by 36%, 20% and 42%, respectively. Analysis revealed that the oxygen demand at Dongyeongyo station will decrease by 17% in summer and BOD, COD and SS will increase by 30%, 12% and 17%, respectively. This study suggests that there is a need to continuously monitor the water quality of the Anseongcheon River basin for long-term management. A more reliable prediction of future water quality will be achieved if various social scenarios and climate data are taken into consideration.

수질자료의 추세분석을 위한 비모수적 통계검정에 관한 연구 (A Study of Non-parametric Statistical Tests to Analyze Trend in Water Quality Data)

  • 이상훈
    • 환경영향평가
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    • 제4권2호
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    • pp.93-103
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    • 1995
  • This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

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경향성 및 패턴 분석을 이용한 낙동강 물금지역의 수질 특성 (Characteristics of Trend and Pattern for Water Quality Monitoring Networks Data using Seasonal-kendall, SOM and RDA on the Mulgeum in the Nakdong River)

  • 안정민;이인정;정강영;김주언;이권철;천세억;류시완
    • 한국환경과학회지
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    • 제25권3호
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    • pp.361-371
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    • 2016
  • Ministry of Environment has been operating water quality monitoring network in order to obtain the basic data for the water environment policies and comprehensively understand the water quality status of public water bodies such as rivers and lakes. The observed water quality data is very important to analyze by applying statistical methods because there are seasonal fluctuations. Typically, monthly water quality data has to analyze that the transition comprise a periodicity since the change has the periodicity according to the change of seasons. In this study, trends, SOM and RDA analysis were performed at the Mulgeum station using water quality data for temperature, BOD, COD, pH, SS, T-N, T-P, Chl-a and Colon-bacterium observed from 1989 to 2013 in the Nakdong River. As a result of trends, SOM and RDA, the Mulgeum station was found that the water quality is improved, but caution is required in order to ensure safe water supply because concentrations in water quality were higher in the early spring(1~3 month) the most.

국내 먹는샘물의 수질특성비교 (Comparison of water quality of domestic natural mineral water)

  • 두용균;김준환;김창수;장덕
    • 환경위생공학
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    • 제15권1호
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    • pp.88-94
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    • 2000
  • The purpose of this study was to analyze and compare the contents of minerals and ionic components in domestic commercial natural mineral waters, and to investigate the relationship between water quality and characteristics of suspended and rocks there of its source. All mineral waters tested in this study met the korean mineral water quality guideline, although chemical components varied widely depending upon the geological characteristics and degree of urbanization of the source area or physical water treatment method. The water quality of commercial bottled water was different from that of source water, especially in cationic components, and showed a tendency to become worse with time elapsed. The water quality on the bottle was also different from the measured quality.

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

  • 김선주;김성준;이석호;이준우
    • 한국농공학회지
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    • 제44권2호
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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.

확률분포를 이용한 남한강 보 건설 전·후 수질변화 분석 (Analysis of Water-Quality Constituents Variations before and after Weir Construction in South Han River using Probability Distribution)

  • 김경섭
    • 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.

수질모형을 이용한 수질오염사고의 모의분석 (Simulation of Water Pollution Accident with Water Quality Model)

  • 최현구;박준형;한건연
    • 환경영향평가
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    • 제23권3호
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    • pp.177-186
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    • 2014
  • Depending on the change of lifestyle and the improvement of people's living standards and rapid industrialization, urbanization of recent, demand for water is increasing rapidly. So emissions of domestic wastewater and various industrial waste water has increased, and water quality is worsening day by day. Therefore, in order to provide a measure against the occurrence of water pollution accident, this study was tried to simulate water pollution accident. This study simulated 2008 Gimcheon phenol accident using 1,2-D model, and analyze scenario for prevent of water pollution accident. Consequently the developed 1-D model presents high reappearance when compared with 2-D model, and has been able to obtain results in a short simulation run time. This study will contribute to the water pollution incident response prediction system and water quality analysis in the future.

여의도 샛강 흐름 정체와 수질악화 원인 분석 (Analysis of the Causes of Flow Stagnation and Water Pollution in Yeouido Saetgang River)

  • 강형식
    • 대한토목학회논문집
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    • 제39권1호
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    • pp.25-32
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    • 2019
  • 도시지역 샛강은 생물이 서식하기 어려운 도심지에 다양한 수변공간을 제공하여 생물다양성에 중요한 역할을 하며, 시민들에게는 휴식 및 체험 공간으로 활용되고 있다. 특히, 여의도 샛강은 국내 최초의 생태공원으로 조성되었으며, 서울 도심 중심에 흐르고 있어 장소적 희소성이 크고 생태적 가치가 매우 높다. 그러나 여의도 샛강은 조성 당시부터 수질 문제가 지속적으로 제기되어 오고 있어, 샛강 환경에 영향을 미치는 요소들과 그 원인에 대한 분석이 필요하다. 이에 본 연구에서는 여의도 샛강 흐름 정체와 수질 악화 원인을 분석하였다. 이를 위해 하천 측량 및 항공사진 분석을 통해 자연적인 물 순환이 어려운 원인에 대해 분석하고 고찰하였다. 한편, 여의도 샛강의 수질 모니터링 결과, 비가 오지 않는 평상시에는 BOD, T-P는 평균 III등급과 IV 등급 수준으로 나타났으며, 강우 시에는 BOD, T-P 모두 V~VI 등급인 것으로 나타났다. 또한 배수분구 분석을 통해 샛강 수질에 영향을 미치는 소유역을 선정하였으며, 결과에 대해 고찰하였다.

BASINS/HSPF 모델을 이용한 화성호 수질보전을 위한 상류 유역 수질개선방안 연구 (Watershed Management Measures for Water Quality Conservation of the Hwaseong Reservoir using BASINS/HSPF Model)

  • 강형식;장재호
    • 한국물환경학회지
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    • 제29권1호
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    • pp.36-44
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    • 2013
  • HSPF model based on BASINS was applied to analyze effects of watershed management measures for water quality conservation in the Hwaseong Reservoir watershed. The model was calibrated against the field measurements of meteorological data, streamflow and water qualities ($BOD_5$, T-N, T-P) at each observatory for 4 years (2007-2010). The water quality characteristics of inflow streams were evaluated. The 4 scenarios for the water quality improvement were applied to inflow streams and critical area from water pollution based on previous researches. The reduction efficiency of point and non-point sources in inflow streams was evaluated with each scenario. The results demonstrate that the expansion of advanced treatment system within wastewater treatment plants (WWTPs) and construction of pond-wetlands would be great effective management measures. In order to satisfactory the target water quality of reservoir, the measures which can control both point source and non-point source pollutants should be implemented in the watershed.

추계학적 비선형 모형을 이용한 달천의 실시간 수질예측 (Real Time Water Quality Forecasting at Dalchun Using Nonlinear Stochastic Model)

  • 연인성;조용진;김건흥
    • 상하수도학회지
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    • 제19권6호
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    • pp.738-748
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    • 2005
  • Considering pollution source is transferred by discharge, it is very important to analyze the correlation between discharge and water quality. And temperature also influent to the water quality. In this paper, it is used water quality data that was measured DO (Dissolved Oxygen), TOC (Total Organic Carbon), TN (Total Nitrogen), TP (Total Phosphorus) at Dalchun real time monitoring stations in Namhan river. These characteristics were analyzed with the water quality of rainy and nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water quality forecasting models were applied. LMNN (Levenberg-Marquardt Neural Network), MDNN (MoDular Neural Network), and ANFIS (Adaptive Neuro-Fuzzy Inference System) models have achieved the highest overall accuracy of TOC data. LMNN and MDNN model which are applied for DO, TN, TP forecasting shows better results than ANFIS. MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. If some data has periodical properties, it seems effective using qualitative data to forecast.