地理学报(英文版)

Journal of Geographical Sciences ›› 2012, Vol. 22 ›› Issue (2): 195-208.doi: 10.1007/s11442-012-0921-6

• Climate Change and Hydrology •     Next Articles

Spatio-temporal trend and statistical distribution of extreme precipitation events in Huaihe River Basin during 1960-2009

XIA Jun1, SHE Dunxian1,2, ZHANG Yongyong1, DU Hong3   

  1. 1. Key Laboratory of Water Cycle &|Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101 China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China;
    3. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
  • Received:2011-07-28 Revised:2011-09-19 Online:2012-04-15 Published:2012-04-15
  • Contact: She Dunxian, Ph.D, E-mail: dunxian.she@gmail.com E-mail:dunxian.she@gmail.com
  • About author:Xia Jun, Professor, specialized in hydrology and water resources. E-mail: xiaj@igsnrr.ac.cn
  • Supported by:

    National Basic Research Program of China, No.2010CB428406; National Natural Science Foundation of China, No.41071025

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Abstract:

Based on the daily precipitation data of 27 meteorological stations from 1960 to 2009 in the Huaihe River Basin, spatio-temporal trend and statistical distribution of extreme precipitation events in this area are analyzed. Annual maximum series (AM) and peak over threshold series (POT) are selected to simulate the probability distribution of extreme precipitation. The results show that positive trend of annual maximum precipitation is detected at most of used stations, only a small number of stations are found to depict a negative trend during the past five decades, and none of the positive or negative trend is significant. The maximum precipitation event almost occurred in the flooding period during the 1960s and 1970s. By the L-moments method, the parameters of three extreme distributions, i.e., Generalized extreme value distribution (GEV), Generalized Pareto distribution (GP) and Gamma distribution are estimated. From the results of goodness of fit test and Kolmogorov-Smirnov (K-S) test, AM series can be better fitted by GEV model and POT series can be better fitted by GP model. By the comparison of the precipitation amounts under different return levels, it can be found that the values obtained from POT series are a little larger than the values from AM series, and they can better simulate the observed values in the Huaihe River Basin.

Key words: Huaihe River Basin, extreme precipitation, extreme distribution, L-moments method, Kolmogorov- Smirnov test