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投稿时间：2008-06-27 修订日期：2009-02-16
投稿时间：2008-06-27 修订日期：2009-02-16
中文摘要: 建立以Thornthwaite干燥度指数为主、自定义的有效降水指数为辅的干旱综合指数，用1959
—2005年云南省125个气象站资料,分5个时段基于模糊信息分配理论和超越极限概率原理，
对云南干旱风险进行评估。结果表明：云南省每年1—3月出现干旱灾害的风险最大，大部分
地区干旱概率为60%～100%、重旱概率为20%～60%（部分地区甚至达90%）；11—12月干旱风
险次之，大部分地区干旱概率为30%～60%、重旱概率为20%～60%；6—8月云南省基本上没有
出现干旱的风险；9—10月全省各地干旱概率小于5%，重旱的风险基本没有；4—6月上旬约
一半的地区干旱概率为10%～20%、有29%的地区为20%～40%、有21%的地区为40%～80%，重旱
的风险小于5%。
Abstract:By using the conventional meteorological data of 125 stations and dividing 5 dur
ations from 1959 to 2005, the drought risk assessment in Yunnan Province was con
ducted with the fuzzy information theory and over limit probability principle.
The establishment of synthetic drought index was mainly based on the Thornthwait
e drought index and supplemented by self defined effective precipitation index.
The results showed as follows: the most drought risk period is in January to Ma
rch every year; the probability of drought in most area is 60%～100%; the heavy
drought probability is 20%～60% with some area of 90%. The drought risk in Nove
mber
to December is in the second place. The drought probability in most area is 30%
～60%; the heavy drought probability is 20%～60%. There is mostly no drought ris
k in June to August. The drought probability is less than 5% in September to Oct
ober and there is no heavy drought at all. The drought probability is 10%～20% i
n April to the first ten days of June in about half area of Yunnan, 20%～40% in
the area of 29%, 40%～80% in the area of 21% and the heavy drought risk is less
than 5%.
文章编号： 中图分类号： 文献标志码：
基金项目:国家重点基础研究发展计划（国家973项目）（2003CB415101）、中国
气象局新技术推广应用项目(CMATG2006M45)和中国气象局气候变化专项（CCSF 09 4）资
助
引用文本：
彭贵芬,张一平,赵宁坤,2009.基于信息分配理论的云南干旱风险评估[J].气象,35(7):79-86.
Peng Guifen,Zhang Yiping,Zhao Ningkun,2009.Drought Risk Assessment in Yunnan Province on the Basis of Information Distribution Theory[J].Meteor Mon,35(7):79-86.
彭贵芬,张一平,赵宁坤,2009.基于信息分配理论的云南干旱风险评估[J].气象,35(7):79-86.
Peng Guifen,Zhang Yiping,Zhao Ningkun,2009.Drought Risk Assessment in Yunnan Province on the Basis of Information Distribution Theory[J].Meteor Mon,35(7):79-86.