• Title/Summary/Keyword: Water quality characteristics

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확인적 요인모형을 이용한 낙동강 유역의 오염특성 분석 (Analysis of Pollutant Characteristics in Nakdong River using Confirmatory Factor Modeling)

  • 김미아;강태구;이혁;신유나;김경현
    • 한국물환경학회지
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    • 제28권1호
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    • pp.84-93
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    • 2012
  • The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.

Comparative assessment of surface and ground water quality using geoinformatics

  • Giridhar, M.V.S.S.;Mohan, Shyama;Kumar, D. Ajay
    • Advances in environmental research
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    • 제9권3호
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    • pp.151-160
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    • 2020
  • Water quality demonstrates physical, chemical and biological characteristics of water. The quality of surface and groundwater is currently an important concern with population growth and industrialization. Over exploitation of water resources due to demand is causing the deterioration of surface water and ground water. Periodic water quality testing must be carried out to protect our water resources. The present research analyses the spatial variation of surface water and groundwater in and around the lakes of Hyderabad. Twenty-Seven lakes and their neighboring bore water samples are obtained for water quality monitoring. Samples are evaluated for specific physico-chemical parameters such as pH, Total Dissolved Solids (TDS), Cl, SO4, Na, K, Ca, Mg, and Total Hardness (TH). The spatial variation of water quality parameters for the 27 lakes and groundwater were analysed. Correlation and multiple regression analysis were carried out to determine comparative study of lake and ground water. The study found that most of the lakes were polluted and this had an impact on surrounding ground water.

다변량 통계분석을 이용한 낙동강 상수원수의 수질변화 특성 조사 (Evaluation of Water Quality Characteristics in the Nakdong River using Multivariate Analysis)

  • 김경아;김예진;송미정;지기원;유평종;김창원
    • 한국물환경학회지
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    • 제23권6호
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    • pp.814-821
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    • 2007
  • This study was estimated water quality to raw water quality management of the Maeri intake station in the Nakdong River using Multivariate Analysis. The results of Principle Component Analysis was explained up to 76.9% of total water quality by three principle components. The 1st, 2nd was explained 44.7%, 17.9% and third was explained 14.3%. Also, the three factors was derived from Factor Analysis. The 1st factor was estimated as the matabolism and organic matter pattern related to algal growth. The 2nd factor was judged as the pollution of pattern related to the discharge from stream of the Nakdong River and 3rd factor was viewed as the hydrological variation pattern related to particle matter. The results of Cluster Analysis were classified into three groups.

소규모 도시 하천 유역의 수질 특성 연구 (Characteristics Analysis of Water Quality for A Small Stream in Urban Watershed)

  • 곽재원;정종태;김형수;안경수
    • 한국습지학회지
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    • 제10권2호
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    • pp.129-141
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    • 2008
  • 본 연구는 도심지 유역인 경기도 부천 여월동 단지 내 도시하천의 수질 특성을 분석하고 평가하고자 한다. 해당 유역의 하천은 차집관로에 의한 생활하수와 평시 흐름의 차단으로 인하여 매우 적은 유량만이 흐르고 있고, 각종 하수와 오염원의 유입으로 수질 오염 및 악취 발생 등의 문제를 안고 있다. 따라서 본 연구에서는 수질 현황을 파악하고 수질 개선책을 제시하기 위하여 수질 모니터링을 시행하였으며, 해당 유역의 특성과 조사 결과를 이용하여 QUAL2E 모형을 통한 수질 모델링을 구축하고, 이를 이용해 수질특성과 향후 미래 수질을 검토하였다. 검토 결과 주거지역내 소하천의 경우 오염원의 유입에 따라서 수질이 크게 변화하며 비점오염원에 대해서도 불안요소를 포함하고 있는 것으로 나타났다. 본 연구 대상지역의 경우 유지유량 공급과 오염원의 차단이 중요할 것으로 판단된다.

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새만금해역 자동수질모니터링시스템 구축 (Construction of the Automatic Water Quality Monitoring System for the Saemankeum)

  • 김원장;박상현;이형주;이광야
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2002년도 학술발표회 발표논문집
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    • pp.441-444
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    • 2002
  • In recent, industrialization increases the level of pollution load in sea areas, and the inflows of pollutants to public sea areas cause sudden and wide-range of influence to the water quality and the ecosystem. To prepare for these kinds of unpredictable water pollution issues, the necessity is emerging to build an automatic water quality monitoring system, which can monitor and alarm the water quality changes of the subject sea areas. For the ongoing installation plan of the automatic water quality monitoring system around the Saemankeum sea area, this report compares and analyzes its installation conditions as well as the physical and chemical characteristics of the in-situ type and the water-sampling type of the automatic water quality monitoring equipments, and subjects to provide elementary data for the system installation in the Saemankeum.

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팔당수계 주요하천 수질의 시·공간적 특성 (Spatio-temporal Water Quality Characteristics of Major Streams in Pal-dang Watershed)

  • 한미덕;이은주;오조교;김웅수;이창희;남궁은;정욱진
    • 한국물환경학회지
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    • 제25권3호
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    • pp.394-403
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    • 2009
  • A total of 52 sampling sites were selected in the stream network of the upper Paldang watershed (e.g. Kyonan, Gapyeong, Jojong, Chengmi, Bockha, Yanghwa and Heuk streams). Over the time period of April 2007-February 2008, 1820 samples were collected and analyzed for physico-chemical variables of the upper watershed in order to investigate spatio-temporal water quality variation in particular the relationship with land use. Although temporal variations of water quality in each stream were similar and were significantly influenced by flow, spatial variations in each stream varied as physico-chemical characteristics of upper watershed. As a result of regression analysis, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Nitrogen (T-N), and Total phosphorus (T-P) concentration were the most significantly and positively associated with people population density. It is necessary to manage not only water quality but also land use of upper watershed and flow flux.

보령담수호의 수질거동 특성 (Characteristics of Water Quality Behavior in Boryeong Freshwater Lake)

  • 김선주;이석호;이창형
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2001년도 학술발표회 발표논문집
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    • pp.412-416
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    • 2001
  • Among water quality models, WASP5 was applied to Boryeong freshwater lake, as a part of Water Quality Management System. The WASP modeling system is a generalized modeling framework for contaminant fate and transport in surface waters. The simulated result was compaired with actual measurement. So, before and after making freshwater lake were compaired. After this research, the lake may have eutrophication and water quality would be worse after making the lake as freshwater lake. Therefore, to make the freshwater lake better, more appropriate plan is necessary.

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영일만 유입오염부하량과 수질의 시${\cdot}$공간적 변동특성(II) - 유입오염부하량과 수질의 상호거동 - (Spatial and Temporal Variation Characteristics between Water Quality and Pollutant Loads of Yeong-il Bay (II) - Mutual Variation between Inflowing Pollutant Loads and Water Quality -)

  • 윤한삼;이인철;류청로
    • 한국해양공학회지
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    • 제17권5호
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    • pp.32-38
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    • 2003
  • This study investigates the distribution characteristics and relationship of water quality, and analyzes the spatial and temporal variation and distribution of the pollutant loads at Yeong-il Bay. The results of these analysis, the concentrations of nutrient loads (T-N and T-P), both appeared to be at the maximum value in November, while most small values were taken in May for the T-N, and in August for the T-P. For COD, the maximum concentration was in August, which has much precipitation during the same season, T-N was at the mean, and T-P was at the minimum value. Using the cluster analysis to develop the division of the sea basin by the dendrogram, before and after construction of Pohang New-port, the variation characteristics of water quality of Yeong-il Bay were discussed. The in flowing pollutant loads were transported to the landward by the high-density salinity water volume of the bottom layer therefore, it formed nutrient trap or coastal trapping areas of the pollutant load. By this mechanism, it is clear that the water volume with high-density nutrient exists on both sides of the Pohang New-port. Thus, the sea basins increasing concentration of the pollutant load at Yeong-il Bay are most prevalent at Hyeong-san estuary, the Pohang Old, and New-port. To improve water quality of this sea basin, the reduction of these nutrients loads should be the highest priority.

패턴분류 방법 적용에 의한 장성호 수문·수질자료의 특성파악 (Characteristics Detection of Hydrological and Water Quality Data in Jangseong Reservoir by Application of Pattern Classification Method)

  • 박성천;진영훈;노경범;김종오;유호규
    • 한국물환경학회지
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    • 제27권6호
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    • pp.794-803
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    • 2011
  • Self Organizing Map (SOM) was applied for pattern classification of hydrological and water quality data measured at Jangseong Reservoir on a monthly basis. The primary objective of the present study is to understand better data characteristics and relationship between the data. For the purpose, two SOMs were configured by a methodologically systematic approach with appropriate methods for data transformation, determination of map size and side lengths of the map. The SOMs constructed at the respective measurement stations for water quality data (JSD1 and JSD2) commonly classified the respective datasets into five clusters by Davies-Bouldin Index (DBI). The trained SOMs were fine-tuned by Ward's method of a hierarchical cluster analysis. On the one hand, the patterns with high values of standardized reference vectors for hydrological variables revealed the high possibility of eutrophication by TN or TP in the reservoir, in general. On the other hand, the clusters with low values of standardized reference vectors for hydrological variables showed the patterns with high COD concentration. In particular, Clsuter1 at JSD1 and Cluster5 at JSD2 represented the worst condition of water quality with high reference vectors for rainfall and storage in the reservoir. Consequently, SOM is applicable to identify the patterns of potential eutrophication in reservoirs according to the better understanding of data characteristics and their relationship.

DEVELOPMENT OF ARTIFICIAL NEURAL NETWORK MODELS SUPPORTING RESERVOIR OPERATION FOR THE CONTROL OF DOWNSTREAM WATER QUALITY

  • Chung, Se-Woong;Kim, Ju-Hwan
    • Water Engineering Research
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    • 제3권2호
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    • pp.143-153
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    • 2002
  • As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

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