Article(id=1223201259180642976, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223201250133524577, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20221633, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1659888000000, receivedDateStr=2022-08-08, revisedDate=1662566400000, revisedDateStr=2022-09-08, acceptedDate=null, acceptedDateStr=null, onlineDate=1769563506168, onlineDateStr=2026-01-28, pubDate=1690214400000, pubDateStr=2023-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769563506168, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769563506168, creator=13701087609, updateTime=1769563506168, updator=13701087609, issue=Issue{id=1223201250133524577, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='7', pageStart='1', pageEnd='220', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769563504012, creator=13701087609, updateTime=1769563583713, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223201584469885927, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223201250133524577, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223201584469885928, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223201250133524577, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=98, endPage=101, ext={EN=ArticleExt(id=1223201259927229154, articleId=1223201259180642976, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Research on Stochastic Simulation Method of Multi-station Flood Series Based on Conditional Resampling, columnId=1222925283431272938, journalTitle=Water Resources and Power, columnName=HYDROLOGICAL FORECAST AND OPTIMAL SCHEDULING, runingTitle=null, highlight=null, articleAbstract=

Taking the self- and cross-correlation of the multi-station streamflow series of the main and tributary of the basin as the starting point, a multi-site flood series simulation method based on the conditional resampling theory was proposed, and simulate the flood series of Pingshan, Cuntan and Yichang station on the main stream of Changjiang River. The simulation results were compared with the results of the multi-station seasonal autoregressive model (MSAR) for verification and analysis. The results show that compared with the traditional model, the proposed method can not only satisfy the basic statistical characteristics of the runoff series and the higher-order self- and cross-correlation structures of the series, but also further consider the historical extreme flood characteristic, and could generate multi-station simulated flood scenarios with different design frequency.

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以流域干支流多站径流过程自、互相关性为切入点，提出了基于条件重采样理论的多站洪水过程模拟方法，并对长江流域干流屏山、寸滩与宜昌站洪水过程进行模拟延拓，将模拟结果与多站季节性自回归模型模拟结果进行了对比验证分析。结果表明，相对于传统模型，所提方法能在满足径流序列基本统计特性及序列高阶自互相关结构的同时，能进一步考虑历史极端洪水特征，生成满足不同设计频率的多站点多情景模拟径流过程。

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王权森（1993-），男，博士后，研究方向为水文水资源、智慧水利，E-mail：quansen_wang@163.com

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王权森（1993-），男，博士后，研究方向为水文水资源、智慧水利，E-mail：quansen_wang@163.com

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