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首页> 外文期刊>River research and applications >Complexity and trends analysis of hydrometeorological time series for a river streamflow: A case study of Songhua River Basin, China
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Complexity and trends analysis of hydrometeorological time series for a river streamflow: A case study of Songhua River Basin, China

机译：河流水文气象时间序列的复杂性和趋势分析-以松花江流域为例

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摘要

In China's national economic growth, an important role is being played by the Songhua River because of the river's abundant resources and natural conditions. Therefore, study of hydrometeorological time series is very important to understand the basin behaviour. This research uses the snow cover data derived from MODIS, streamflow, and meteorological records in the Songhua River Basin to evaluate similarity, complexity, and trends in the snow cover, temperature, precipitation, and streamflow. In this paper, we suggest a new method of ranking the statistics symbolic sequences to examine the degree of similarity (distance measurement) between meteorological stations and compare it with non-parametric correlation methods and also investigate the deviations in the complexity of a hydrometeorological time series. Information-based similarity index and multiscale entropy confirm that the hydrometeorological time series of different stations have self-similarity and abundant complexity. Wavelet entropy is also used to investigate the basin behaviour by taking streamflow records and population. It is found that with the increase in population and urbanization, the complexity values are increased. The results also exhibit that due to increase in urbanization, it affects the hydrological process and nature of environment resulting in complex catchment behaviour. Furthermore, the streamflow trend results displayed significant decline (22.21m(3)/sxyear(-1)) in the Songhua River. The results also indicated that the seasonal snow cover trend has no impact on changes of the streamflow. However, the decline of the streamflow may be influenced by the significant human activity upstream of the Songhua River.
机译：在中国国民经济增长中，松花江由于其丰富的资源和自然条件而发挥着重要作用。因此，研究水文气象时间序列对于了解流域的行为非常重要。本研究使用从松花江流域的MODIS，流量和气象记录得出的积雪数据来评估积雪，温度，降水和流量的相似性，复杂性和趋势。在本文中，我们提出了一种对统计符号序列进行排名的新方法，以检查气象站之间的相似度（距离测量），并将其与非参数相关方法进行比较，并研究水文气象时间序列的复杂性偏差。基于信息的相似度指数和多尺度熵证实了不同台站的水文气象时间序列具有自相似性和复杂性。小波熵还用于通过获取流量记录和总体来研究流域的行为。发现随着人口和城市化的增加，复杂度值也增加。结果还表明，由于城市化进程的加快，它影响了水文过程和环境性质，导致流域行为复杂。此外，松花江水流趋势结果显示显着下降（22.21m（3）/ sxyear（-1））。结果还表明，季节性积雪趋势对流量变化没有影响。然而，水流的下降可能受到松花江上游大量人类活动的影响。

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  • 来源
    《River research and applications》 |2018年第2期|101-111|共11页
  • 作者

    Faiz M. A.; Liu D.; Fu Q.; Qamar M. U.; Dong S.; Khan M. I.; Li T.;

  • 作者单位

    Northeast Agr Univ, Sch Conservancy & Civil Engn, Harbin 150030, Heilongjiang, Peoples R China;

    Northeast Agr Univ, Sch Conservancy & Civil Engn, Harbin 150030, Heilongjiang, Peoples R China;

    Northeast Agr Univ, Sch Conservancy & Civil Engn, Harbin 150030, Heilongjiang, Peoples R China;

    Univ Agr Faisalabad, Dept Irrigat & Drainage, Fac Agr Engn, Faisalabad, Pakistan;

    Hydrol Bur Heilongjiang Prov, Harbin, Heilongjiang, Peoples R China;

    Northeast Agr Univ, Sch Conservancy & Civil Engn, Harbin 150030, Heilongjiang, Peoples R China;

    Northeast Agr Univ, Sch Conservancy & Civil Engn, Harbin 150030, Heilongjiang, Peoples R China;

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  • 正文语种 eng
  • 中图分类
  • 关键词

    IBSI; MSE; MWE; Songhua River Basin; spatio-temporal snow cover trend; water resources management;

    机译：IBSI;MSE;MWE;松花江流域;时空积雪趋势;水资源管理;

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