z-logo
open-access-imgOpen Access
Determination of variation uncertainty in runoff time series at multi-temporal scales
Author(s) -
Yan Ye,
Jinping Zhang,
Xunjian Long,
Lihua Ma,
Yong Ye
Publication year - 2021
Publication title -
journal of water and climate change
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.421
H-Index - 22
eISSN - 2408-9354
pISSN - 2040-2244
DOI - 10.2166/wcc.2021.275
Subject(s) - surface runoff , flood myth , environmental science , series (stratigraphy) , mode (computer interface) , hydrology (agriculture) , temporal scales , hilbert–huang transform , time series , climatology , mathematics , statistics , geography , geology , ecology , computer science , paleontology , geotechnical engineering , archaeology , white noise , biology , operating system
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 μ between the flood season and annual runoff periods were the highest, with 0.94, 0.77, 0.7 and 0.73, respectively, and the μ 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 μ 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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom