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Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China

Yangzong Cidan, Hongyan Li, Yunqing Xuan Orcid Logo, Hong Sun, Fang You

Sustainability, Volume: 14, Issue: 17, Start page: 10627

Swansea University Author: Yunqing Xuan Orcid Logo

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DOI (Published version): 10.3390/su141710627

Abstract

The Second Songhua River Basin is located at the northern edge of the East Asian monsoonregion in China. The river basin has a large interannual rainfall-runoff variation often associated withfrequent droughts and floods. Therefore, the mid-long-term runoff prediction is of great significance.Accord...

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Published in: Sustainability
ISSN: 2071-1050
Published: MDPI AG 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa60997
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spelling 2022-09-13T13:41:00.5615855 v2 60997 2022-08-31 Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false 2022-08-31 CIVL The Second Songhua River Basin is located at the northern edge of the East Asian monsoonregion in China. The river basin has a large interannual rainfall-runoff variation often associated withfrequent droughts and floods. Therefore, the mid-long-term runoff prediction is of great significance.According to a review of the national and international literature, there are few studies on sunspots inthe prediction of medium- and long-term runoff. In this study, sunspots are selected as the influencingfactors of runoff based on the mechanism of astronomical factors; sensitivity analysis was used toidentify the time delay of sunspots’ influence on runoff and determine the prediction factor (relativenumber of sunspots in January and March). The BP (backpropagation) network is used to identifythe correlation between prediction factors and prediction items (monthly average inflow rate of theFengman Reservoir and the Baishan Reservoir in the flood season), and then the prediction model isconstructed. According to the test results of historical data and the actual forecast results, the forecastis working well, and the accuracy of qualitative forecasting is high. Journal Article Sustainability 14 17 10627 MDPI AG 2071-1050 medium-long-term runoff forecast; sunspots; BP (backpropagation) network; sensitivity analysis; Second Songhua River Basin 26 8 2022 2022-08-26 10.3390/su141710627 COLLEGE NANME Civil Engineering COLLEGE CODE CIVL Swansea University Another institution paid the OA fee This study was supported by key R&D project funding from Jilin Province Science and Technology Department, China, 20200403070SF. 2022-09-13T13:41:00.5615855 2022-08-31T22:50:07.5145569 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Yangzong Cidan 1 Hongyan Li 2 Yunqing Xuan 0000-0003-2736-8625 3 Hong Sun 4 Fang You 5 60997__25063__0e9e916094c949ef91276998f5573fef.pdf sustainability-14-10627.pdf 2022-08-31T22:51:36.8334317 Output 4651658 application/pdf Version of Record true © 2022 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
spellingShingle Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
Yunqing Xuan
title_short Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
title_full Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
title_fullStr Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
title_full_unstemmed Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
title_sort Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China
author_id_str_mv 3ece84458da360ff84fa95aa1c0c912b
author_id_fullname_str_mv 3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
author Yunqing Xuan
author2 Yangzong Cidan
Hongyan Li
Yunqing Xuan
Hong Sun
Fang You
format Journal article
container_title Sustainability
container_volume 14
container_issue 17
container_start_page 10627
publishDate 2022
institution Swansea University
issn 2071-1050
doi_str_mv 10.3390/su141710627
publisher MDPI AG
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
document_store_str 1
active_str 0
description The Second Songhua River Basin is located at the northern edge of the East Asian monsoonregion in China. The river basin has a large interannual rainfall-runoff variation often associated withfrequent droughts and floods. Therefore, the mid-long-term runoff prediction is of great significance.According to a review of the national and international literature, there are few studies on sunspots inthe prediction of medium- and long-term runoff. In this study, sunspots are selected as the influencingfactors of runoff based on the mechanism of astronomical factors; sensitivity analysis was used toidentify the time delay of sunspots’ influence on runoff and determine the prediction factor (relativenumber of sunspots in January and March). The BP (backpropagation) network is used to identifythe correlation between prediction factors and prediction items (monthly average inflow rate of theFengman Reservoir and the Baishan Reservoir in the flood season), and then the prediction model isconstructed. According to the test results of historical data and the actual forecast results, the forecastis working well, and the accuracy of qualitative forecasting is high.
published_date 2022-08-26T04:14:33Z
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