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

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...

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Autores principales:	Yan Ye, Jinping Zhang, Xunjian Long, Lihua Ma, Yong Ye
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	empirical mode decomposition multi-temporal scales periodic fluctuation runoff set pair analysis Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/5e8c96178c234fd5b8c8073f05aa7982
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spelling	oai:doaj.org-article:5e8c96178c234fd5b8c8073f05aa79822021-11-05T19:02:19ZDetermination of variation uncertainty in runoff time series at multi-temporal scales2040-22442408-935410.2166/wcc.2021.275https://doaj.org/article/5e8c96178c234fd5b8c8073f05aa79822021-08-01T00:00:00Zhttp://jwcc.iwaponline.com/content/12/5/2010https://doaj.org/toc/2040-2244https://doaj.org/toc/2408-9354In 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. HIGHLIGHTS A coupling model of empirical mode decomposition and set pair analysis is proposed.; Mutation and variation of runoff under different time scales is provided.; Trend components and fluctuation features under multi-temporal scales are explored.;Yan YeJinping ZhangXunjian LongLihua MaYong YeIWA Publishingarticleempirical mode decompositionmulti-temporal scalesperiodic fluctuationrunoffset pair analysisEnvironmental technology. Sanitary engineeringTD1-1066Environmental sciencesGE1-350ENJournal of Water and Climate Change, Vol 12, Iss 5, Pp 2010-2025 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	empirical mode decomposition multi-temporal scales periodic fluctuation runoff set pair analysis Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350
spellingShingle	empirical mode decomposition multi-temporal scales periodic fluctuation runoff set pair analysis Environmental technology. Sanitary engineering TD1-1066 Environmental sciences GE1-350 Yan Ye Jinping Zhang Xunjian Long Lihua Ma Yong Ye Determination of variation uncertainty in runoff time series at multi-temporal scales
description	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. HIGHLIGHTS A coupling model of empirical mode decomposition and set pair analysis is proposed.; Mutation and variation of runoff under different time scales is provided.; Trend components and fluctuation features under multi-temporal scales are explored.;
format	article
author	Yan Ye Jinping Zhang Xunjian Long Lihua Ma Yong Ye
author_facet	Yan Ye Jinping Zhang Xunjian Long Lihua Ma Yong Ye
author_sort	Yan Ye
title	Determination of variation uncertainty in runoff time series at multi-temporal scales
title_short	Determination of variation uncertainty in runoff time series at multi-temporal scales
title_full	Determination of variation uncertainty in runoff time series at multi-temporal scales
title_fullStr	Determination of variation uncertainty in runoff time series at multi-temporal scales
title_full_unstemmed	Determination of variation uncertainty in runoff time series at multi-temporal scales
title_sort	determination of variation uncertainty in runoff time series at multi-temporal scales
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/5e8c96178c234fd5b8c8073f05aa7982
work_keys_str_mv	AT yanye determinationofvariationuncertaintyinrunofftimeseriesatmultitemporalscales AT jinpingzhang determinationofvariationuncertaintyinrunofftimeseriesatmultitemporalscales AT xunjianlong determinationofvariationuncertaintyinrunofftimeseriesatmultitemporalscales AT lihuama determinationofvariationuncertaintyinrunofftimeseriesatmultitemporalscales AT yongye determinationofvariationuncertaintyinrunofftimeseriesatmultitemporalscales
_version_	1718444040749318144

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

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