摘要
基于月尺度马尔科夫链模型,系统研究了塔河流域各洪旱状态之间的转移概率、期望停留时间和平均首达时间,在此基础上,预测了未来该流域洪旱灾害状态发生的概率风险。研究表明:(1)塔河流域丰水月和枯水月变化显著,其中,阿拉尔4-9月份枯水发生平均概率最高,大山口枯水发生概率最低;(2)塔河流域10月至次年3月连续枯水频率最高,而开都河流域连续丰水事件发生频率最高,表明该流域有较大的大旱或大涝风险;(3)丰水事件重现期低值主要集中在开都河和阿克苏河,而和田河和叶尔羌河丰水事件重现期较高;(4)塔河流域4-5月份干旱影响较大,加剧了塔河流域的水资源短缺问题。
Based on monthly scaled Markov model this paper studies systematically the transfer probability,expected stay time and average initial arrival time of each flood and drought state in Tarim River Basin and predicts the probabilistic risk of flood and drought of the basin in the future. The results indicate that:( 1) The change is obvious in dry month and wet month in the Tarim River Basin. Occurrence probability is the largest for drought from April to September in the Alaer,while occurrence probability is the lowest for drought in the Dashankou.( 2) Occurrence probability is the largest for consecutive dry events from October to next March in the Tarim River Basins,but Occurrence probability is the largest for consecutive wet events in the Kaidu River Basins.( 3) Lower value of return period of consecutive wet events is mainly in Kaidu River and Aksu River,but the high value of return period is in Hotan River and Yarkand River.( 4) The droughts have the significant impacts on Tahe River Basin from April to May and aggravate the shortage of water resourses.
出处
《自然灾害学报》
CSCD
北大核心
2015年第1期46-54,共9页
Journal of Natural Disasters
基金
新疆维吾尔自治区科技计划项目(201331104)
国家杰出青年科学基金项目(51425903)
中山大学博士研究生创新人才培养资助项目
关键词
概率分布函数
枯水预测
月马尔科夫模型
塔里木河流域
probability distribution function
dryness prediction
monthly Markov chain model
Tarim River Basin
