基于Copula函数的鄱阳湖都昌站枯水多变量频率分析

以鄱阳湖湖区都昌水文站1958—2007年长系列日平均水位资料为基础,采用干旱分析中应用广泛的游程理论进行湖泊枯水的识别,提取枯水历时、平均枯水强度和最大枯水强度作为湖泊枯水特征变量;采用Archimedean Copula函数构造了变量的联合分布,分析了枯水事件出现的概率,计算了枯水事件的联合重现期和条件重现期。结果表明Weibull分布、Logistic分布和GEV分布分别适于作为干旱历时、平均枯水强度和最大枯水程度的边缘分布函数;Clayton Copula函数适于都昌站枯水多变量联合分布的拟合;联合分布考虑了枯水事件多个变量之间的相关性,能提供更多的湖泊枯水特征信息,更能全面揭示湖泊枯水的概率统计特征。

Multivariate Analysis on Low Flow Frequency at Duchang Station in Poyang Lake Using Copula Function

Analysis on low flow features is of practical significance in the management of lake water resources in dry season. According to the theory of runs which is widely used in drought analysis, low flow duration, averaged low flow intensity and maximum low flow intensity were determined as the characteristic variables from the data of averaged daily lake level at Duchang hydrologic station from 1958 to 2007. Weibull, Logistic, and Generalized Extreme Value distributions were used to simulate low flow duration, averaged low flow intensity, and maximum low flow intensity, respectively. Several asymmetric Archimedean copulas were applied to construct three-dimensional joint distributions and the Clayton copula was selected as the best one. The joint probabilities and return periods of low flow variables were calculated and analyzed. It was concluded that the three-dimensional joint distribution could reveal the probability characteristics of low flow more comprehensively in the Poyang Lake.