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中文摘要：
利用小波分析方法对黄河源区径流数据系列的多尺度变化特征、突变点及变化趋势进行了分析．结果表明：黄河源区年径流量具有8a、15a、22a和36a左右的变化周期，其中8a、36a左右的周期变化最为显著．这些周期变化表明，2007年后流量将呈增加的趋势；1928、1982年和1985年是径流变化趋势重要的转变点．在小波分解的基础上，基于BP神经网络模型构建了黄河源区年径流量的长期动态预报模型，利用该模型对未来10a的流量变化进行了预测，并对其预报结果进行了分析．
英文摘要：
The Yellow River is the maximum water source in Northwest China, especially in the upper reaches above Tangnag, which is called ＂ water tower＂. In the background of global warming, the variation in runoff is responsible for social and eco-nomic sustainable development in the whole Yellow River basin. To assess the long-term run-off changing tendency and characteristics, the complex Morlet continuous wavelet function was applied to analyzing the annual runoff time series in the source regions of Yellow River above Tangnag for the period of 1920--2007. Four major changing periods （8 a, 15 a, 23 a and 36 a） are found. Among them, the period of 36 a is the most noticeable one. By decomposing the long-term runoff time series, the runoff in the upper Yellow River had an increasing tendency before 1985 apparently and has a decreasing tendency after 1985. In order tO find out the future changing tendency of the annual runoff, a combined model is developed by combining wavelet decomposition with artificial neural network. According the stochastic simulation, it is found that the runoff will slightly increase over the next decade, but still has had a significant decrease as a whole since 1956. The results also indicate that the combined model is feasible and efficient.
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