| Summary: | 碩士 === 淡江大學 === 水資源及環境工程學系碩士班 === 97 === The typhoon events usually cause downstream flooding in Taiwan. Estimation the flood depths and extent may provide the flood inundation information that will be helpful to deal with some contingencies, then alleviate the risk and losses of the flood disasters. The conventional simulations of flood inundation extent need a huge amount of data and computing time by using a series of numerical models. The study proposes the hybrid models to build the regional flood inundation estimation model. In order to figure out the causes of the flood inundation, the correlation analysis and factor analysis are used to explore the relationship between flood inundation influence factors; then K-means clustering is used to categorize the data points of the different flooding characteristics and to find the control point in each flooding group. The hybrid models are composed of three types of models in each flooding group: a single back-propagation neural network (BPNN) for each control point, the linear regression models for the linear grids and a multi-grid BPNN for the nonlinear grids. Two study areas, Fonshang city, Kaohsiung County, and Yuanlin township, Changhua County, are tested for evaluating the practicability and accuracy of the proposed approach. The results show that the proposed hybrid models can accurately and timely estimate the simulated flood inundation extents and depths.
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