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A Study on the Development of Water Level Forecasting Model for Flood Forecasting and Warning

  • Crisisonomy
  • Abbr : KRCEM
  • 2010, 6(4), pp.93-104
  • Publisher : Crisis and Emergency Management: Theory and Praxis
  • Research Area : Social Science > Public Policy > Public Policy in general

Jun Kye Won 1

1강원대학교

Candidate

ABSTRACT

Due to recent unusual climate change, flood happen frequently in Korea. Heavy rainfall increase the damage caused by the flooding. It is cause heavy losses of both life and property every year. Flood hazard mitigation measures consist of structural and non-structural mitigation. Most of flood disaster predictions belong to non-structural mitigation. Neural network is proper to solve non-structural problem. Because it is consider only inputs and outputs to construct model. Real-time water level forecasting model was used to construct artificial intelligence neural network. and it was applied to be a highly suitable tool producing a high water level stage forecasting accuracy at Gidae(No.2) of Bocheong stream, which is IHP representative basins. As a result, neural network was proved to be outstanding model for the water level forecasting in the Bocheong stream catchment.

Citation status

* References for papers published after 2023 are currently being built.