Application of Fuzzy Optimization Model Based on Entropy Weight in Typical Flood Hydrograph Selection

Abstract

In China, design flood computation is generally used by the design flood hydrograph (DFH) method by amplifying the typical flood hydrograph (TFH). TFH selection plays an important role in design flood calculation because the selection result directly affects the final DFH. The traditional method of TFH selection is subjective and varies with designers. So the fuzziness of TFH selection should be considered; the theory of fuzzy pattern recognition is applied in TFH selection to explore a theoretical method. This paper establishes a fuzzy optimization model based on entropy weight to select TFH. The influence indexes reflecting the quality of TFH selection are determined by Pearson correlation test and Spearman’s rho test. A shape parameter, which quantitatively described the shape of the flood hydrograph, is proposed for the first time. The entropy weight method is used to determine the weights of influence indexes and is a better way to avoid subjective influence. The optimal TFH is obtained by the principle of minimum eigenvalue of grades through fuzzy optimization model calculation. The model is applied to Yuecheng Reservoir in the Zhanghe Basin. Results show that No. 520723 flood process is the optimal TFH. Compared with the traditional TFH (1956 TFH), the TFH selected with this model is relatively better to design flood computation.