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You are here : eLibrary : IAHR World Congress Proceedings : 32nd Congress - Venice (2007) : THEME B: Data Acquisition and Processing For Scientific Knowledge and Public Awareness. : Flood prediction by applying improved rainfall forecasts using satellite data and neural networks
Flood prediction by applying improved rainfall forecasts using satellite data and neural networks
Author : Gwangseob Kim, Kun-Yeun Han, Hyuk-Joon Choi, Jong Tae Lee
A quantitative rainfall forecasting model was developed using satellite data and neural networks and improved rainfall forecasts were applied to flood analysis. To overcome the geographical limitation of Korean peninsula and to get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took use of satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. The developed rainfall forecast model and flood analysis system were applied to the Nakdong River Basin for the heavy storm period between 6th and 16th of August, 2002. The results demonstrated that the rainfall forecasts of 3 hours lead time showed good agreement with observed data. The inundation aspect of simulation depends on actual levee failure in the same basin. Rainfall forecasts were used for flood amount computation in the target watershed. Also the flood amount in the target watershed was used on boundary condition for flood inundation simulation in protected lowland and a river. The results of simulation are consistent with actuality inundation traces and flood level data of the target watershed. This study provides practical applicability of satellite data in rainfall forecast of extreme events such as heavy rainfall or typhoon. Also this study presented an advanced integrated model of rainfall, runoff, and inundation analysis which can be applicable for flood disaster prevention and mitigation.
File Size : 4,349,582 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 32nd Congress - Venice (2007)
Article : THEME B: Data Acquisition and Processing For Scientific Knowledge and Public Awareness.
Date Published : 01/07/2007
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