Determination of variation uncertainty in runoff time series at multi-temporal scales

被引:1
|
作者
Ye, Yan [1 ]
Zhang, Jinping [2 ]
Long, Xunjian [1 ]
Ma, Lihua [1 ]
Ye, Yong [1 ]
机构
[1] Southwest Univ, Coll Resources & Environm, Chongqing 400715, Peoples R China
[2] Zhengzhou Univ, Inst Water Resources & Environm, Zhengzhou 450001, Peoples R China
基金
中国国家自然科学基金;
关键词
empirical mode decomposition; multi-temporal scales; periodic fluctuation; runoff; set pair analysis; EMPIRICAL MODE DECOMPOSITION; RAINFALL; PREDICTION; EMD; SPECTRUM; WAVELET;
D O I
10.2166/wcc.2021.275
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
In order to survey the possible periodic, uncertainty and common features in runoff with multi-temporal scales, the empirical mode decomposition (EMD) method combined with the set pair analysis (SPA) method was applied, with data observed at Zhangjiashan hydrological station. The results showed that the flood season and annual runoff time series consisted of four intrinsic mode function (IMF) components, and the non-flood season time series exhibited three IMF components. Moreover, based on the different coupled set pairs from the time series, the identity, discrepancy, and contrary of different periods at multi-temporal scales were determined by the SPA method. The degree of connection mu between the flood season and annual runoff periods were the highest, with 0.94, 0.77, 0.7 and 0.73, respectively, and the mu between the flood periods and the non-flood periods were the lowest, with 0.66, 0.46, 0.24 and 0.24, respectively. Third, the maximum mu of each SPA appeared in the first mode function. In general, the different extractive periods decomposed by the EMD method reflected the average state of Jinghe River. Results also verified that runoff suffered from seasonal and periodic fluctuations, and fluctuations in the short-term corresponded to the most important variable. Therefore, the conclusions drawn in this study can improve water resources regulation and planning.
引用
收藏
页码:2010 / 2025
页数:16
相关论文
共 50 条
  • [1] Uncertainty analysis and prediction of river runoff with multi-time scales
    Zhang, Jinping
    Zhao, Yong
    Lin, Xiaomin
    [J]. WATER SCIENCE AND TECHNOLOGY-WATER SUPPLY, 2017, 17 (03): : 897 - 906
  • [2] Wavelet-Based Analysis on the Complexity of Hydrologic Series Data under Multi-Temporal Scales
    Sang, Yan-Fang
    Wang, Dong
    Wu, Ji-Chun
    Zhu, Qing-Ping
    Wang, Ling
    [J]. ENTROPY, 2011, 13 (01) : 195 - 210
  • [3] Multi-Temporal Scales Consensus for Weakly Supervised Temporal Action Localization
    Guo, Wenbin
    Yang, Xingming
    Jiang, Zheyuan
    Wu, Kewei
    Xie, Zhao
    [J]. Computer Engineering and Applications, 2023, 59 (10): : 151 - 161
  • [4] Runoff variation and response to precipitation on multi-spatial and temporal scales in the southern Tibetan Plateau
    Jiang, Yao
    Xu, Zongxue
    Xiong, Lvyang
    [J]. JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 2022, 42
  • [5] Analysis of variation characteristics of runoff at multi-time scales under the influence of reservoir
    Yan, B.
    Zhang, X.
    Chen, Y. B.
    Yao, L. Q.
    Huang, F.
    Chen, Q. H.
    Gao, Q. S.
    Zhang, L. G.
    Guo, L. D.
    [J]. 5TH INTERNATIONAL CONFERENCE ON WATER RESOURCE AND ENVIRONMENT (WRE 2019), 2019, 344
  • [6] Complexity analysis of rainfall and runoff time series based on sample entropy in different temporal scales
    Chou, Chien-Ming
    [J]. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2014, 28 (06) : 1401 - 1408
  • [7] Complexity analysis of rainfall and runoff time series based on sample entropy in different temporal scales
    Chien-Ming Chou
    [J]. Stochastic Environmental Research and Risk Assessment, 2014, 28 : 1401 - 1408
  • [8] SAR IMAGE CHANGE DETECTION BY LIKELIHOOD RATIO TEST IN MULTI-TEMPORAL TIME SERIES
    Su, Xin
    Deledalle, Charles-Alban
    Tupin, Florence
    Sun, Hong
    [J]. 2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2013, : 3439 - 3442
  • [9] Joint distributions for multi-temporal series of radar images
    Storvik, B
    Storvik, G
    Fjortoft, R
    [J]. ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 2004, 3 : 186 - 194
  • [10] Analysis of uncertainty in multi-temporal object-based classification
    Loew, Fabian
    Knoefel, Patrick
    Conrad, Christopher
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 105 : 91 - 106