• Ecology and Resilient Infrastructure
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• v.3 no.4
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• pp.294-301
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• 2016

The underflow type movable weirs were arranged in a multi-stage way at a section of the Chiseong River, a tributary of Geum River, where flooding is observed frequently. The flood control and the movable weir management levels were compared with the occasions of installing the existing weir for analysis. The peak discharge decreased by a maximum of 97% for the underflow type movable weir, and the downstream flood elevation decreased by a maximum of 82%. The amount of storage also increased by a maximum of 463% by the distribution and storage functions of the multi-stage arrangement of the underflow type movable weirs. It is possible to suggest that the management level of each movable weir for the target storage of the reach and the flood reduction level through the relationship among this storage, downstream peak flood elevation, and peak flow.

• Journal of Korea Water Resources Association
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• v.50 no.2
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• pp.111-119
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• 2017

The underflow type movable weirs were arranged in a multi-stage way along a reach at the Chiseong River, where flooding has been observed frequently. With management water level of the movable weirs the control effects of storage and flood were suggested and the control effects were compared with those of existed weir system. The water level for the targeted storage and flood elevation was suggested by building the artificial neural network model. When the underflow type of movable weirs were arranged in a multi-stage way, the peak flood elevation decreased by 68.28% in the downstream compared with the existed weir system, and the total storage of the target section of multi-stage movable weirs increased by 216%. As a result of numerical simulation to build the artificial neural network model, 60%, 20%, and 20% among 216 data were used for the training, validation, and test, respectively. The training result of mean square error was $0.1681m^2$ and the high coefficients of determination were 0.9961, 0.9967, and 0.9943 in the training, validation, and test, respectively. As a result the water level management of each movable weir for the controls of flood elevation in the targeted downstream and targeted storage was suggested by using the artificial neural network.