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Use of Gauged Water Level and Precipitation Data to Predict Short Term Water Level Changes

  • Crisisonomy
  • Abbr : KRCEM
  • 2014, 10(2), pp.247-264
  • Publisher : Crisis and Emergency Management: Theory and Praxis
  • Research Area : Social Science > Public Policy > Public Policy in general

Seong Joon Byeon 1 이성호 2 Choi Gye Woon 2 정재광 1

1국제도시물정보과학연구원
2인천대학교

Accredited

ABSTRACT

Recently frequent stream flooding and flood disaster due to abnormal climate led to an increased in damage to human life and properties. The most ideal measure is the precise prediction of flood water level. And in the prediction of flood water level, it is important to reduce potential flood damage via approaches from real-time aspect in order to secure sufficient lead time for evacuation and control of citizens and protection of facilities. The Osu Stream Basin which is the first branch of Seomjin River was selected as the subject, where the rainfall and water level data which was obtained by selecting 35 heavy rain events observed between 2006 and 2013 was used. The multiple linear regression models were structured and then parameters were selected from the following 4 methods: in Case 1, hourly data of water level and basin averaged precipitation; in Case 2, 10-minute periodic data of water level and basin averaged precipitaion; in Case 3, hourly data of water level and precipitation gauged 3 different stations and in Case 4, 10-minute periodic data of water level and precipitation gauged 3 different stations were used. According to the results, the precision was slightly reduced as the lead time of prediction, but the 1 hour of predicted lead time showed considerably higher precision, and the prediction results were superior until the 3 hours of predicted lead time. The simulation results showed that data that can be briefly identified may be used to predict the water level of the Osu point of the Osu Stream Basin in real time, and based on the results, the method will be helpful to protect lives and properties of those who live around the area and to reduce damage caused by flooding of the river via securing sufficient lead time for flood forecasting.

Citation status

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