• 제목/요약/키워드: Water Quality Forecasting

검색결과 84건 처리시간 0.026초

하수 차집율에 따른 도시하천의 수질변화 예측 (Forecasting Variations of Water Quality Caused by Intercepting Ratios in a Urban River)

  • 조홍제;김정식;문성준;박재희
    • 상하수도학회지
    • /
    • 제14권2호
    • /
    • pp.181-195
    • /
    • 2000
  • The effect of the intercepting ratios on the water quality improvement was simulated by using Finite Segment Method in a urban river where intercepting sewer under the ground and constructing sewage treatment plant are now being proceeded. To simulate variations of the water quality caused by river flows, rating curve at each gaging station was derived from measurements. Water quality data were from the exiting observations at each key stations from 1990 to 1998, for 1999 and 2000 data we measured in creek and drainage ditch in addition to observation stations. It revealed that increasing the intercepting ratios improved the water quality.

  • PDF

Water Quality Management System at Mok-hyun Stream Watershed Using RS and GIS

  • Lee, In-Soo;Lee, Kyoo-seock
    • 대한원격탐사학회:학술대회논문집
    • /
    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
    • /
    • pp.63-69
    • /
    • 1999
  • The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.

  • PDF

신경망을 이용한 낙동강 유역 홍수기 댐유입량 예측 (Dam Inflow Forecasting for Short Term Flood Based on Neural Networks in Nakdong River Basin)

  • 윤강훈;서봉철;신현석
    • 한국수자원학회논문집
    • /
    • 제37권1호
    • /
    • pp.67-75
    • /
    • 2004
  • 본 연구에서는 홍수시 다목적댐의 효율적 운영을 위하여 상류로부터 유입되는 홍수유입량을 실시간으로 예측하기 위해 역전파 신경망 모형을 사용하여 댐유입량 예측모형(Neural Dam Inflow Forecasting Model; NDIFM)을 개발하였다. NDIFM은 다목적댐에 의한 하류의 홍수조절 비중이 큰 낙동강의 남강댐 유역에 적용하였으며, 입력자료로는 댐유역 평균강우량, 실측 댐유입량, 예측 댐유입량 통을 사용하여 실시간 댐유입량 예측의 가능성을 검토하였다. 실측치와 예측치를 비교ㆍ검토한 결과 제시한 세 가지 모형 중 NDIFM-I이 가장 우수한 결과를 나타내었으며, NDIFM-II 및 NDIFM-III 또한 다양한 예측가능성을 보여주었다. 따라서, 강우-유출의 비선형시스템 모의를 위하여 물리적 매개변수가 복잡한 개념적 모형보다는 양질의 수문관측 자료만 축적된다면 블랙박스 모형인 신경망 모형이 실시간 홍수예측에 효율적으로 활용될 수 있을 것이다.

ARIMA 모형과 인공신경망모형의 BOD예측력 비교 (Comparison of the BOD Forecasting Ability of the ARIMA model and the Artificial Neural Network Model)

  • 정효준;이홍근
    • 한국환경보건학회지
    • /
    • 제28권3호
    • /
    • pp.19-25
    • /
    • 2002
  • In this paper, the water quality forecast was performed on the BOD of the Chungju Dam using the ARIMA model, which is a nonlinear statistics model, and the artificial neural network model. The monthly data of water quality were collected from 1991 to 2000. The most appropriate ARIMA model for Chungju dam was found to be the multiplicative seasonal ARIMA(1,0,1)(1,0,1)$_{12}$, model. While the artificial neural network model, which is used relatively often in recent days, forecasts new data by the strength of a learned matrix like human neurons. The BOD values were forecasted using the back-propagation algorithm of multi-layer perceptrons in this paper. Artificial neural network model was com- posed of two hidden layers and the node number of each hidden layer was designed fifteen. It was demonstrated that the ARIMA model was more appropriate in terms of changes around the overall average, but the artificial neural net-work model was more appropriate in terms of reflecting the minimum and the maximum values.s.

Forecasting of Stream Qualities in Gumho River by Exponential Smoothing at Gumho2 Measurement Point using Monthly Time Series Data

  • Song, Phil-Jun;Lee, Bo-Ra;Kim, Jin-Yong;Kim, Jong-Tae
    • Journal of the Korean Data and Information Science Society
    • /
    • 제18권3호
    • /
    • pp.609-617
    • /
    • 2007
  • The goal of this study is to forecast the trend of stream quality and to suggest some policy alternatives in Gumbo river. It used the five different monthly time series data such as BOD, COD, T-N and EC of the nine of Gumbo River measurement points from Jan. 1998 to Dec. 2006. Water pollution is serious at Gumbo2 and Palgeo stream measurement points. BOD, COD, T-N and EC data are analyzed with the exponential smoothing model and the trend is forecasted until Dec. 2009.

  • PDF

미계측 지점에서의 유출 모의 및 예측 (Runoff Simulation and Forecasting at Ungaged Station)

  • 안상진;최병만;연인성;곽현구
    • 한국수자원학회논문집
    • /
    • 제38권6호
    • /
    • pp.485-494
    • /
    • 2005
  • 유량과 수질의 관계를 분석하는 것은 매우 중요하다. 하천의 실시간적 관리를 위해서는 유량과 수질의 측정이 동일한 지점에서 동시간적으로 이루어져야 보다 효과적이다. 그러나 수질자동측정망 지점과 T/M 수위관측소가 원거리에 위치한 경우들이 있으며, 평창강 수질자동측정망 지점이 그 중 하나이다. 이러한 지점에서는 보다 정확한 유량 산정과 이를 활용한 예측 프로그램이나 시스템이 요구된다. 이번 연구에서는 미계측 지점인 평창강 수질자동측정망 지점에 유량예측 신경망 모형을 적용하고, 적용성을 검토하기 위해 WMS 모형의 모의결과와 비교하였다. WMS 모형은 첨두유량이 작고, 수문곡선이 단조로운 사상에 적합한 것으로 나타났다. 신경망 모형의 유출량 예측값은 비유량과 WMS 모형의 모의값에 근사하였으며, 미계측 지점에서의 유출량 변화성향을 잘 반영하는 것으로 나타났다.

총량규제에 따른 주암호의 장래 수질 예측 (Water Quality Simulation of Juam Reservoir Depend on Total Pollution Loads Control)

  • 장성용;안기선;권영호;한재익
    • 한국환경과학회지
    • /
    • 제19권1호
    • /
    • pp.39-45
    • /
    • 2010
  • When the Juam multipurpose dam which is connected with existing large water supply facilities is finished, water environment is changed from stream to lake. The changed quality of water should be examined. In this study, the result of water quality forecasting is analysed and an effective management plan of water quality is presented. Tn this study, the WASPS model that is a dynamic water quality simulation model was selected to forecast the water quality. This model forecasts movement of change of pollutants. For an application of the model, the subject areas were divided into seventeen sub-areas by considering change temperature depending measuring points and on depth of water. Meteorological data collected by the meteorological observatory and data about quality measured by the Korea Water Resources Development Corporation were used for an operation of the model. As a result of quality examination through quality data and estimated pollutant loading, the water quality environment criterion was grade II and the nutritive condition was measured as meso-graphic grade. In this study, an effective management was planned to improve water quality by reducing pollution load. According to the result of examination, when more than 30% of BOD was reduced it was recorded that the environment standard of water quality was improved to the second grade.

전문가시스템과 GIS를 이용한 저수지 수질 정보시스템 개발 (Development of Water Quality Management System in Reservoirs Using Expert System and GIS)

  • 이주승;고홍석;고남영;조민호
    • 대한공간정보학회지
    • /
    • 제13권1호
    • /
    • pp.71-80
    • /
    • 2005
  • 사회 환경의 급격한 변화에 따라 하천과 호소의 수질이 극도로 오염되면서 그에 따른 수질문제가 해결해야 할 중대한 사안으로 부각되고 있다. 저수지 오염불질의 저감을 위해서는 정확한 저수질 예측이 필요하며 그에 따른 오염물질 저감대책이 수립되어야 한다. 본 연구의 목적은 전문가시스템과 GIS를 도입하여 저수지 수질정보의 관리, 수질 예측과 수질개선 대책 수립을 위한 의사결정을 지원하는 프로토타입의 지능형 지리정보시스템을 개발하는데 있다. 주연구내용은 시스템 분석 및 설계, 지리정보데이터 수집과 데이터베이스 구축, 저수지 수질정보 수집 및 분석, 저수지 수질예측을 위한 GIS, WASPS 및 전문가시스템의 통합 인터페이스 구축이다.

  • PDF

HSPF 유역모델을 이용한 낙동강유역 수질 예측 (Operational Water Quality Forecast for the Nakdong River Basin Using HSPF Watershed Model)

  • 신창민;김경현
    • 한국물환경학회지
    • /
    • 제32권6호
    • /
    • pp.570-581
    • /
    • 2016
  • A watershed model was constructed using the Hydrological Simulation Program Fortran to predict the water quality, especially chlorophyll-a concentraion, at major tributaries of the Nakdong River basin, Korea. The BOD export loads for each land use in HSPF model were estimated at $1.47{\sim}8.64kg/km^2/day$; these values were similar to the domestic monitoring export loads. The T-N and T-P export loads were estimated at $0.618{\sim}3.942kg/km^2/day$ and $0.047{\sim}0.246kg/km^2/day$, slightly less than the domestic monitoring data but within the range of foreign literature values. The model was calibrated at major tributaries for a three-year period (2008 to 2010). The deviation values ranged from -31.5~1.6% of chlorophyll-a, -24.0~2.2% of T-N, and -5.7~34.8% of T-P. The root mean square error (RMSE) ranged from 4.3~44.4 ug/L for chlorophyll-a, -0.6~1.5 mg/L for T-N, and 0.04~0.18 mg/L for T-P, which indicates good calibration results. The operational water quality forecasting results for chlorophyll-a presented in this study were in good agreement with measured data and had an accuracy similar with model calibration results.

수량(水量) 및 수질(水質)을 고려(考慮)한 저수지군(貯水池群)의 종합관리(綜合管理) (Water Quantity and Quality Management Through A Multiple Reservoir System)

  • 고석구;금수삼;이광만;이기종
    • 대한토목학회논문집
    • /
    • 제12권1호
    • /
    • pp.123-130
    • /
    • 1992
  • 수자원의 개발 및 관리 문제에 있어 양적인 문제가 질적인 문제에 우선하여 왔으나 산업화와 생활수준의 향상에 따라 질적인 문제도 양(量)적인 문제만큼 중요하게 되었다. 본 연구에서는 수량과 수질문제를 동시에 고려하면서 수계내의 저수지 시스템을 종합관리하는 방안을 제시하며, 개발된 인(燐) 수지(收支) 모형(模型)에 따라 저수지 수질을 장기예측하는 기법도 제시한다. 개발된 기법은 5개의 저수지 운영을 감안한 한강 유역의 저수지군 관리에 적용하였으며, 적용 결과 수량적인 면과 수질적인 면에 있어 시간과 공간적으로 편기된 수자원을 모든 제약(制約) 조건(條件)을 만족시키면서 활용할 수 있다는 것을 입증하였다.

  • PDF