Climate Change Research ›› 2015, Vol. 11 ›› Issue (1): 15-21.doi: 10.3969/j.issn.1673-1719.2015.01.003

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Spatiotemporal Distribution Features of Extreme Hydrological Events in the Hanjiang River Basin

Yang Wei1, 2, Zhang Liping1, 2, Shan Lijie1, 2, Chen Xinchi1, 2, Yang Yanrong3   

  1. 1 State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;
    2 Hubei Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China; 
    3 Heihe River Bureau, Yellow River Conservancy Commission of the Ministry of Water Resources, Lanzhou 730030, China
  • Received:2014-08-05 Revised:2014-09-30 Online:2015-01-30 Published:2015-01-30

Abstract: The spatial distribution rules of 9 extreme precipitation indices are analyzed based on the daily precipitation data from 15 meteorological stations and the daily runoff data from 3 hydrological stations in the Hanjiang River basin from 1960 to 2012. The generalized extreme value (GEV) model and the Gamma model are selected for the fitting of each station’s extremum samples of maximum 1-day precipitation and maximum 3-day precipitation to single out the best statistical model, and then the precipitation design value with the given recurrence interval is calculated and its spatial distribution rules are analyzed. A joint distribution model of precipitation and flood volume is built based on three Copula functions including the Gumbel, the Clayton and the Frank, and the most appropriate Copula function model is chosen to calculate the design value of the flood volume with the given recurrence interval. The result shows that the GEV model can better simulate the extreme precipitation sequence, and the extreme precipitation in the recurrence interval presents a feature that it is high in the east and low in the west. In comparison with other Copula functions, the Frank Copula function is better to simulate the correlation relationship between the precipitation and the flood volume, and the design value of the flood volume obtained by this function is greater than the design value derived from the fitting of univariate distribution.

Key words: extreme hydrological event, extreme precipitation index, extreme flood, univariate distribution, Copula function

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