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基于阿克苏河流域1960~2010年的气象、水文观测数据,利用集合经验模态分解(EEMD)方法,对研究期内阿克苏河径流时间序列进行多尺度的分析,并探讨其在不同时间尺度上的振荡模态结构特征及其对气候因子的多尺度响应。结果表明:(1)近50年来,阿克苏河年径流整体上呈现出显著的非线性增加趋势,且其变化在年际尺度上表现出准3 a和准6~7 a的周期性波动,在年代际尺度上表现出准13 a和准25 a的周期性变化;(2)各周期分量的方差贡献率表明,年际振荡在径流长期变化中占据主导地位,年代际尺度在径流变化过程中也起着重要作用。重构的径流年际变化能够较为详细地描述原始径流序列在研究时期内的波动趋势,重构的径流年代际变化则有效揭示了阿克苏河径流在不同年代丰、枯水期交替出现的状态。(3)在年际尺度上径流与气温、降水和潜在蒸发都表现为不显著的正相关关系,而在年代际尺度上,径流量与气温和降水均表现为显著的正相关关系,与潜在蒸发表现为显著的负相关关系,且在年代际尺度上相关性和显著性明显强于年际尺度,表明年代际尺度更适于评价径流对气候波动的响应。结果表明EEMD是一种甄别非线性趋势和尺度循环的有效方法。
Based on the meteorological and hydrological data from 1960 to 2010 in the Aksu River Basin and using the set empirical mode decomposition (EEMD) method, the multi-scale analysis of the runoff time series of the Aksu River during the study period was carried out and the results were discussed on different timescales Oscillatory Modal Structure and Its Multi - scale Response to Climatic Factors. The results show that: (1) The annual runoff of Aksu River shows a significant non-linear trend of increase over the past 50 years, and its variation shows periodic fluctuations of quasi-3 a and quasi-6-7 a on the interannual scale (2) The contribution rate of variance of each periodic component shows that the interannual oscillation dominates in the long-term variation of runoff, and the interdecadal scale in the process of runoff variation Also plays an important role. The reconstructed interannual variation of runoff can describe the trend of fluctuation of original runoff in the study period in detail, and the reconstructed interdecadal variation of runoff effectively reveals the alternation of runoff of Aksu River in different years of abundance and dry season. (3) There was no significant positive correlation between runoff and air temperature, precipitation and potential evaporation on the interannual scale. On the interdecadal scale, there was a significant positive correlation between runoff and air temperature and precipitation, Evaporation showed a significant negative correlation, and the correlation and significance were significantly stronger on interdecadal scales than interannual scales, indicating that decadal scales are more suitable for evaluating the response of runoff to climate fluctuations. The results show that EEMD is an effective way to identify non-linear trends and scale cycles.