在变化环境下,对水文时间序列的非一致性研究变得非常重要。经典线性回归模型在传统的水文序列趋势性分析中有广泛的应用,该模型假定水文变量服从正态分布,这与我国现行的水文频率分析计算中推荐选用的皮尔逊Ⅲ型频率分布(简称PⅢ分布)并不相符。提出采用基于PⅢ分布的回归模型对汉口水文站59 a间的年最小月流量序列进行趋势性分析。研究发现基于PⅢ分布的回归模型比基于正态分布的回归模型能更好地揭示水文序列频率分布的时变特征。在此基础上采用灵活性较强的多项式对水文序列的趋势性进行了分析。
Abstract
It is very important to research the inconsistency (or nonstationarity) of hydrological time series under changing circumstance. Classical regression models, which are widely used in traditional hydrological trend analysis, are based on the assumption that the hydrological variables follow the normal distribution. However, this assumption does not consist with the practical findings in China that most hydrological random variables follow the Pearson type III (PⅢ) distribution. In this paper, the regression model based on the assumption of the PⅢ distribution is introduced to analyze the trend of annual minimum monthly runoff series of the Yangtze River at Hankou hydrological station observed over the period of 1952-2010. It is found that the regression model based on the PⅢ distribution is more effective than the regression model based on the normal distribution in fitting the trend of hydrological series. Furthermore, the more flexible polynomial is used to analyze the trend of the hydrological series.
关键词
趋势性分析 /
回归模型 /
正态分布 /
PⅢ分布 /
年最小月流量
Key words
trend analysis /
regression model /
normal distribution /
PⅢ distribution /
annual minimum monthly runoff
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基金
国家自然科学基金重大项目(51190094);国家自然科学基金项目(51079098)
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