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Trends, periodicities and discontinuities of precipitation in the Huangfuchuan Watershed, Loess Plateau, China

机译:黄土高原黄府川流域降水的趋势,周期性和非连续性

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摘要

Longitudinal analyses of hydro-meteorological variables are extremely important for climate studies and water resources planning. Precipitation across the most severely eroded areas of Huangfuchuan Watershed in the Loess Plateau, China was analysed using data from 10 rainfall stations during the period 1954-2010. The ensemble empirical mode decomposition (EEMD), Hurst exponent, and Mann-Kendall methods were utilized to detect periodicities, discontinuities as well as long-term persistence of precipitation. The results show abrupt changes (i.e. discontinuities) in spring during the period 1963-1969 and in 1975, the summer period of 1962 and 1986-1994, the autumn of 1978, and the winter of 1964. These abrupt changes were determined to be statistically significant at the P = 0.05 level. There were inter-annual periods of quasi-3- and quasi-6-year for annual and the four seasons, and decadal periods of quasi-10-, quasi-15-, quasi-25- and quasi-50-year for different seasons. However, periodical features in inter-annual periods were not statistically noticeable. Moreover, Hurst exponent analysis indicated that the current trends of precipitation over the four seasons would continue in the future. The results also indicate that the EEMD method is able to effectively reveal deviations in long-term precipitation series at various timescales and could be utilized for complex analysis of non-stationary and nonlinear signal change. These findings could provide important information for ecological restoration and farming operations across the study region.
机译:水文气象变量的纵向分析对于气候研究和水资源规划极为重要。利用1954-2010年期间10个降雨站的数据,对中国黄土高原皇甫川流域最严重侵蚀地区的降水进行了分析。集合经验模式分解(EEMD),赫斯特指数和曼恩·肯德尔(Mann-Kendall)方法被用于检测降水的周期性,不连续性和长期持续性。结果表明,在1963-1969年的春季和1975年,1962年的夏季和1986-1994年的夏季,1978年的秋天以及1964年的冬天,突变是不连续的。这些突变在统计学上被确定为在P = 0.05水平上具有显着性。年度和四个季节分别有大约3年和大约6年的年际周期,以及不同年份的准10年,准15年,准25年和准50年的十年期。季节。但是,年度间的周期性特征在统计上并不明显。此外,赫斯特(Hurst)指数分析表明,未来四个季节的当前降水趋势将继续。结果还表明,EEMD方法能够有效揭示长期降水序列在各个时间尺度上的偏差,并可用于非平稳和非线性信号变化的复杂分析。这些发现可以为整个研究区域的生态恢复和农业生产提供重要信息。

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