• 제목/요약/키워드: Water flow forecasting

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실시간 낙동강 흐름 예측을 위한 유역 및 수체모델 결합 적용 연구 (A Study on the Operational Forecasting of the Nakdong River Flow with a Combined Watershed and Waterbody Model)

  • 나은혜;신창민;박란주;김덕길;김경현
    • 한국물환경학회지
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    • 제30권1호
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    • pp.16-24
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    • 2014
  • A combined watershed and receiving waterbody model was developed for operational water flow forecasting of the Nakdong river. The Hydrological Simulation Program Fortran (HSPF) was used for simulating the flow rates at major tributaries. To simulate the flow dynamics in the main stream, a three-dimensional hydrodynamic model, EFDC was used with the inputs derived from the HSPF simulation. The combined models were calibrated and verified using the data measured under different hydrometeological and hydraulic conditions. The model results were generally in good agreement with the field measurements in both calibration and verification. The 7-days forecasting performance of water flows in the Nakdong river was satisfying compared with model calibration results. The forecasting results suggested that the water flow forecasting errors were primarily attributed to the uncertainties of the models, numerical weather prediction, and water release at the hydraulic structures such as upstream dams and weirs. From the results, it is concluded that the combined watershed-waterbody model could successfully simulate the water flows in the Nakdong river. Also, it is suggested that integrating real-time data and information of dam/weir operation plans into model simulation would be essential to improve forecasting reliability.

Low-flow simulation and forecasting for efficient water management: case-study of the Seolmacheon Catchment, Korea

  • Birhanu, Dereje;Kim, Hyeon Jun;Jang, Cheol Hee;ParkYu, Sanghyun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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    • pp.243-243
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    • 2015
  • Low-flow simulation and forecasting is one of the emerging issues in hydrology due to the increasing demand of water in dry periods. Even though low-flow simulation and forecasting remains a difficult issue for hydrologists better simulation and earlier prediction of low flows are crucial for efficient water management. The UN has never stated that South Korea is in a water shortage. However, a recent study by MOLIT indicates that Korea will probably lack water by 4.3 billion m3 in 2020 due to several factors, including land cover and climate change impacts. The two main situations that generate low-flow events are an extended dry period (summer low-flow) and an extended period of low temperature (winter low-flow). This situation demands the hydrologists to concentrate more on low-flow hydrology. Korea's annual average precipitation is about 127.6 billion m3 where runoff into rivers and losses accounts 57% and 43% respectively and from 57% runoff discharge to the ocean is accounts 31% and total water use is about 26%. So, saving 6% of the runoff will solve the water shortage problem mentioned above. The main objective of this study is to present the hydrological modelling approach for low-flow simulation and forecasting using a model that have a capacity to represent the real hydrological behavior of the catchment and to address the water management of summer as well as winter low-flow. Two lumped hydrological models (GR4J and CAT) will be applied to calibrate and simulate the streamflow. The models will be applied to Seolmacheon catchment using daily streamflow data at Jeonjeokbigyo station, and the Nash-Sutcliffe efficiencies will be calculated to check the model performance. The expected result will be summarized in a different ways so as to provide decision makers with the probabilistic forecasts and the associated risks of low flows. Finally, the results will be presented and the capacity of the models to provide useful information for efficient water management practice will be discussed.

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하천유역의 홍수관리 시스템 모델 (Flood-Flow Managenent System Model of River Basin)

  • Lee, Soon-Tak
    • 물과 미래
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    • 제26권4호
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    • pp.117-125
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    • 1993
  • A flood -flow management system model of river basin has been developed in this study. The system model consists of the observation and telemetering system, the rainfall forecasting and data-bank system, the flood runoff simulation system, the dam operation simulation system, the flood forecasting simulation system and the flood warning system. The Multivariate model(MV) and Meterological-factor regression model(FR) for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood-flow management. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, streamflow and other hydrological data during the past flood periods. The flood-flow management system model with SSARR model(FFMM-SR,FFMM-SR(FR) and FFMM-SR(MV)), in which the integrated operation of dams and rainfall forecasting in the basin are considered, is then suggested and applied for flood-flow management and forecasting. The results of the simulations done at the base stations are analysed and were found to be more accurate and effective in the FFMM-SR and FFMM0-SR(MV).

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충주호 상류지역의 유황별 장래수질예측 (Water quality forecasting on upstream of chungju lake by flow duration)

  • 이원호;한양수;연인성;조용진
    • 환경위생공학
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    • 제17권4호
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    • pp.1-9
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    • 2002
  • In order to define about concern with discharge and water-quality, it is calculated drought flow, low flow, normal flow and wet flow in Chungju watershed from flow duration analysis. Water quality modeling study is performed for forecasting at upstream of Chungju lake. It is devided method of modeling into before and after the equipment of environmental treatment institution. And it is estimated the change of water quality. Before the equipment of environmental treatment, BOD concentration is increased from 23000 to 2006 years at all site and decrease on 2012 years. The rate of increasing BOD concentration is showed height between 2000 years and 2003 years most of all site. And after the equipment of environmental treatment, it is showed first grade of BOD water quality in most of sample site beside Jucheon river. The result of water quality modeling using drought flow showed that a lot of pollution occurred. And water quality using wet flow is good, so much discharge make more improve water quality than little discharge.

팔당댐 상류의 수질예보시스템 개발에 관한 연구 (A Study on the Development of Water Quality Forecasting System in Upstream of Paldangdam)

  • 최남정;서일원;김영한;이명은
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2007년도 학술발표회 논문집
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    • pp.1387-1391
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    • 2007
  • In this study, water quality prediction that is necessary to water quality forecasting system is performed using 2-D river analysis models RMA-2 and RAM4. RAM4 is suitable to water quality forecasting system cause it is possible to put in the pollutants as a mass type boundary condition. Instant injections of pollutants at Yongdamdaegyo Bridge in Namhangang River are simulated and the behavior of pollutant cloud is observed. The effects of water quality accident to Paldang 2 water intake plants in Paldangho Lake is analyzed with time variation. And extra flow simulation is performed for mitigation of pollution. Several cases of water quality forecasting system at home and abroad are investigated and the direction of water quality forecasting system is presented.

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유황곡선의 거동특성을 이용한 유역관리모형의 평가 (The Evaluation of Watershed Management Model using Behavioral Characteristics of Flow-duration Curve)

  • 김주철;이상진;신현호;황만하
    • 한국물환경학회지
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    • 제25권4호
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    • pp.573-579
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    • 2009
  • The performance of Rainfall-Runoff Forecasting System (RRFS), the watershed management model for the Geum river basin, is evaluated based on the agreement between the simulated and observed hydrographs and the behavioral characteristics of the flow-duration curves. As a result, the simulated hydrographs are well agreed with the observed ones except high flow discharges. It is inferred that most of the errors in the simulated hydrographs are due to the misestimation of agricultural water use in $2^{nd}$ quarter and the discrepancy of the peak discharges in $3^{rd}$ quarter. It is however judged that RRFS would give the reliable runoff hydrographs from the point of view of continuous model application. And simulated flow-duration curves and flow-duration coefficients are also similar to the observed ones except flood flow region. From the above result it is confirmed that the construction of Yongdam dam improves the state of flow-duration curve at the Gongjoo station.

신경망 모형을 이용한 달천의 수질예측 시스템 구축 (Construction of System for Water Quality Forecasting at Dalchun Using Neural Network Model)

  • 이원호;전계원;김진극;연인성
    • 상하수도학회지
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    • 제21권3호
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    • pp.305-314
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    • 2007
  • Forecasting of water quality variation is not an easy process due to the complicated nature of various water quality factors and their interrelationships. The objective of this study is to test the applicability of neural network models to the forecasting of the water quality at Dalchun station in Han River. Input data is consist of monthly data of concentration of DO, BOD, COD, SS and river flow. And this study selected optimal neural network model through changing the number of hidden layer based on input layer(n) from n to 6n. After neural network theory is applied, the models go through training, calibration and verification. The result shows that the proposed model forecast water quality of high efficiency and developed web-based water quality forecasting system after extend model

영산호 운영을 위한 홍수예보모형의 개발(III) -배수갑문 조절에 의한 홍수파의 전달- (River Flow Forecasting Model for the Youngsan Estuary Reservoir Operation(III) - Pronagation of Flood Wave by Sluice Gate Operations -)

  • 박창언;박승우
    • 한국농공학회지
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    • 제37권2호
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    • pp.13.2-20
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    • 1995
  • An water balance model was formulated to simulate the change in water levels at the estuary reservoir from sluice gate releases and the inflow hydrographs, and an one-di- mensional flood routing model was formulated to simulate temporal and spatial varia- tions of flood hydrographs along the estuarine river. Flow rates through sluice gates were calibrated with data from the estuary dam, and the results were used for a water balance model, which did a good job in predicting the water level fluctuations. The flood routing model which used the results from two hydrologic models and the water balance model simulated hydrographs that were in close agreement with the observed data. The flood forecasting model was found to be applicable to real-time forecasting of water level fluc- tuations with reasonable accuracies.

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유역 유출 예측 시스템 개발 (Development of Rainfall-Runoff forecasting System)

  • 황만하;맹승진;고익환;류소라
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2004년도 학술발표회
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    • pp.709-712
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    • 2004
  • The development of a basin-wide runoff analysis model is to analysis monthly and daily hydrologic runoff components including surface runoff, subsurface runoff, return flow, etc. at key operation station in the targeted basin. h short-term water demand forecasting technology will be developed fatting into account the patterns of municipal, industrial and agricultural water uses. For the development and utilization of runoff analysis model, relevant basin information including historical precipitation and river water stage data, geophysical basin characteristics, and water intake and consumptions needs to be collected and stored into the hydrologic database of Integrated Real-time Water Information System. The well-known SSARR model was selected for the basis of continuous daily runoff model for forecasting short and long-term natural flows.

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단기 물 수요예측 시뮬레이터 개발과 예측 알고리즘 성능평가 (Development of Water Demand Forecasting Simulator and Performance Evaluation)

  • 신강욱;김주환;양재린;홍성택
    • 상하수도학회지
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    • 제25권4호
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    • pp.581-589
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    • 2011
  • Generally, treated water or raw water is transported into storage reservoirs which are receiving facilities of local governments from multi-regional water supply systems. A water supply control and operation center is operated not only to manage the water facilities more economically and efficiently but also to mitigate the shortage of water resources due to the increase in water consumption. To achieve the goal, important information such as the flow-rate in the systems, water levels of storage reservoirs or tanks, and pump-operation schedule should be considered based on the resonable water demand forecasting. However, it is difficult to acquire the pattern of water demand used in local government, since the operating information is not shared between multi-regional and local water systems. The pattern of water demand is irregular and unpredictable. Also, additional changes such as an abrupt accident and frequent changes of electric power rates could occur. Consequently, it is not easy to forecast accurate water demands. Therefore, it is necessary to introduce a short-term water demands forecasting and to develop an application of the forecasting models. In this study, the forecasting simulator for water demand is developed based on mathematical and neural network methods as linear and non-linear models to implement the optimal water demands forecasting. It is shown that MLP(Multi-Layered Perceptron) and ANFIS(Adaptive Neuro-Fuzzy Inference System) can be applied to obtain better forecasting results in multi-regional water supply systems with a large scale and local water supply systems with small or medium scale than conventional methods, respectively.