Changes in extreme precipitation in the Huang-Huai-Hai River basin of China during 1960-2010

被引:45
|
作者
Zhang, Dong-Dong [1 ]
Yan, Deng-Hua [1 ]
Wang, Yi-Cheng [1 ]
Lu, Fan [1 ]
Wu, Di [1 ]
机构
[1] China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China
关键词
FREQUENCY-ANALYSIS; DAILY RAINFALL; SOUTH-PACIFIC; TRENDS; TEMPERATURE; VARIABILITY; EVENTS; AUSTRALIA; INDEXES; MAXIMUM;
D O I
10.1007/s00704-014-1159-2
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
With the increasing exposure of populations and economy to the natural hazards, it is of vital importance to study the spatiotemporal characteristics of extreme precipitation. Based on daily precipitation at 154 meteorological stations in the Huang-Huai-Hai River basin of China during 1960-2010, the spatial and temporal changes in extreme precipitation were analyzed using twelve indices. The basin was divided into five climate areas using clustering analysis to detect the spatial changes of the extreme indices, and the temporal changes in the probability distributions of the extreme indices were also examined. The results showed that maximum 5-day precipitation, wet days and consecutive wet days decreased significantly while consecutive dry days showed a weak increasing trend. The other precipitation indices had insignificant decreasing trends. The probability distribution functions of simple daily intensity index and consecutive dry days were positively shifted while the rest of the indices were negatively shifted. The temporal changes of extreme indices implied that the frequency of extreme precipitation was decreasing, but the intensity of extreme precipitation was increasing in the Huang-Huai-Hai River basin. The spatial changes in the aspect of precipitation extreme events showed obvious spatial differences between different climate areas. In addition, the series including maximum 1-day precipitation and maximum 5-day precipitation were fitted by generalized extreme-value distribution for risk analysis and the results showed that the generalized extreme-value distribution could fit the series well. The amounts of extreme precipitation for different return periods were calculated and high risk areas for flooding disaster were presented.
引用
收藏
页码:195 / 209
页数:15
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