• Title/Summary/Keyword: Flood management of estuary dam

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Development of Real-Time Forecasting and Management System for the Youngsan Estuary Dam (영산강 하구둑 실시간 홍수예보 및 관리시스템 개발)

  • Kang, Min-Goo;Park, Seung-Woo;Her, Young-Gu;Park, Chang-Eun;Kang, Moon-Sung
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2002.10a
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    • pp.285-288
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    • 2002
  • For real-time flood forecasting and effective control flood at the Youngsan estuary dam, the Flood Forecasting and Control User Interface System II (FFCUS II) has been developed. This paper describes the features and application of FFCUS II. FFCUS II is composed of the database management subsystem, the model subsystem, and the graphic user interface. The database management subsyem collects rainfall data and stream flow data, updates, processes, and searches the data. The model subsystem predicts the inflow hydrograph, the tide, forecasts flood hydrograph, and simulates the release rate from the sluice gates. The graphic user interface subsystem aids the user's decision-making process by displaying the operation results of the database management subsystem and model subsystem.

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Real-Time Flood Forecasting System For the Keum River Estuary Dam(I) -System Development- (금강하구둑 홍수예경보 시스템 개발(I) -시스템의 구성-)

  • 정하우;이남호;김현영;김성준
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.36 no.2
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    • pp.79-87
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    • 1994
  • A real-time flood forecasting system(FLOFS) was developed for the real-time and predictive determination of flood discharges and stages, and to aid in flood management decisions in the Keum River Estuary Dam. The system consists of three subsystems : data subsystem, model subsystem, and user subsystem. The data subsystem controls and manages data transmitted from telemetering systems and simulated by models. The model subsystem combines various techniques for rainfall-runoff modeling, tidal-level forecasting modeling, one-dimensional unsteady flood routing, Kalman filtering, and autoregressivemovingaverage(ARMA) modeling. The user subsystem in a menu-driven and man-machine interface system.

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Investigation and Complementary Measures Establishment for Flood on Tidal Reclaimed Paddy Fields (간척지 논 침수 원인 조사와 방재 대책 수립)

  • Jeong, Ju-Hong;Yoon, Kwang-Sik;Choi, Soo-Myung;Yoon,, Suk-Gun;Go, Young-Bae;Kim, Young-Taek
    • KCID journal
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    • v.17 no.2
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    • pp.105-114
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    • 2010
  • Tidal land reclamation provided water resources and land for agriculture and contributed stable crop production. However, climate change by global warming disrupts the hydrologic circulatory system of the earth resulting in sea level rise and more frequent flood for reclaimed arable land. Recently, Suyu reclaimed paddy field in Jindo-gun experienced prolonged inundation after heavy rainfall and there is a growing risk of flood damage. Onsite survey and flood analysis using GATE_Pro model of Korea Rural Corporation were conducted to investigate causes of flooding. To perform the analysis, input data such as inflow hydrograph, the lowest elevation of paddy field, neap tide level, management level of Gunnae estuary lake at the time of the flood were collected. Flood analysis confirmed that current drainage facilities are not enough to prevent 20year return period flood. The result of analysis showed flooding more than 24hours. Therefore, flood mitigation alternatives such as sluice gate expansion, installation drainage pumping station, refill paddy land, and catch canal were studied. Replacing drainage culvert of Suyu dike to sluice gate and installing drainage pumping station at the Gunne lake were identified as an effective flood control measures. Furthermore, TM/TC (SCADA) system and expert for gate management are required for the better management of drainage for estuary dam and flood mitigation.

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Real-time Upstream Inflow Forecasting for Flood Management of Estuary Dam (담수호 홍수관리를 위한 상류 유입량 실시간 예측)

  • Kang, Min-Goo;Park, Seung-Woo;Kang, Moon-Seong
    • Journal of Korea Water Resources Association
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    • v.38 no.12 s.161
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    • pp.1061-1072
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    • 2005
  • A hydrological grey model is developed to forecast short-term river runoff from the Naju watershed located at upstream of the Youngsan estuary dam in Korea. The runoff of the Naju watershed is measured in real time at the Naju streamflow gauge station, which is a key station for forecasting the upstream inflow and operating the gates of the estuary dam in flood period. The model's governing equation is formulated on the basis of the grey system theory. The model parameters are reparameterized in combination with the grey system parameters and estimated with the annealing-simplex method In conjunction with an objective function, HMLE. To forecast accurately runoff, the fifth order differential equation was adopted as the governing equation of the model in consideration of the statistic values between the observed and forecast runoff. In calibration, RMSE values between the observed and simulated runoff of two and six Hours ahead using the model range from 3.1 to 290.5 $m^{3}/s,\;R^2$ values range from 0.909 to 0.999. In verification, RMSE values range from 26.4 to 147.4 $m^{3}/s,\;R^2$ values range from 0.940 to 0.998, compared to the observed data. In forecasting runoff in real time, the relative error values with lead-time and river stage range from -23.4 to $14.3\%$ and increase as the lead time increases. The results in this study demonstrate that the proposed model can reasonably and efficiently forecast runoff for one to six Hours ahead.

Development of the Automated Irrigation Management System for Paddy Fields (논 물 관리의 자동화시스템 개발)

  • 정하우;이남호;김성준;최진용;김대식
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.36 no.3
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    • pp.67-73
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    • 1994
  • This paper is to validate the proposed models for the real-time forecasting for the Keum river estuary dam such as tidal-level forecasting model, one-dimensional unsteady flood routing model, and Kalman filter models. The tidal-level forecasting model was based on semi-range and phase lag of four tidal constituents. The dynamic wave routing model was based on an implicit finite difference solution of the complete one-dimensional St. Venant equations of unsteady flow. The Kalman filter model was composed of a processing equation and adaptive filtering algorithm. The processng equations are second ordpr autoregressive model and autoregressive moving average model. Simulated results of the models were compared with field data and were reviewed.

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