Article(id=1223202685927670065, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20230215, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1676649600000, receivedDateStr=2023-02-18, revisedDate=1680537600000, revisedDateStr=2023-04-04, acceptedDate=null, acceptedDateStr=null, onlineDate=1769563846331, onlineDateStr=2026-01-28, pubDate=1703433600000, pubDateStr=2023-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769563846331, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769563846331, creator=13701087609, updateTime=1769563846331, updator=13701087609, issue=Issue{id=1223202678788965355, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='12', pageStart='1', pageEnd='228', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769563844630, creator=13701087609, updateTime=1769563913308, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223202966899901286, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223202966899901287, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=68, endPage=72, ext={EN=ArticleExt(id=1223202686288380236, articleId=1223202685927670065, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=The Improvement of SCS-CN and Its Application in Flood Prediction, columnId=1222925283431272938, journalTitle=Water Resources and Power, columnName=HYDROLOGICAL FORECAST AND OPTIMAL SCHEDULING, runingTitle=null, highlight=null, articleAbstract=

An accurate hydrological model with strong adaptability is crucial for predicting floods and preventing disasters. The antecedent soil moisture and rain intensity factors are considered to improve the SCS-CN runoff generation model. Then the new SCS-CN hydrological model is developed by adding the watershed concentration module. From the perspectives of different climate zones and magnitude floods, the new model is applied in four basins to flow simulation, which include semiarid basins of Hancun and Macun, and humid basins of Shenglihe and Gongcheng. The results demonstrate that new SCS-CN hydrological model has good applicability in both semi-arid and humid basins, with better performance in semi-arid basins. Generally, the model shows better accuracy in simulating floods of different magnitudes, especially for small and medium floods.

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精确、适用性强的水文模型是洪水预报的重要手段，是防灾减灾的有力支撑。考虑前期土壤湿度和雨强因子改进SCS-CN产流模型，并增加汇流模块开发出新型SCS-CN水文模型，从不同气候区、不同量级洪水等角度出发，在韩村、马村两个半干旱流域，胜利河、恭城两个湿润流域，对SCS-CN水文模型的流量模拟进行研究。结果表明，相对于新安江模型，SCS-CN水文模型在不同气候区均具有较好的适用性，在半干旱流域模拟效果更优；模型对各种量级洪水模拟精度整体较优，尤其对中低量级洪水的模拟效果最佳。

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^2.水利部水文气象灾害机理与预警重点实验室，江苏 南京 210044, bio={"content":"

孙彤（2001-），女，硕士研究生，研究方向为水文模型，E-mail：suntong_nuist@163.com

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孙彤（2001-），女，硕士研究生，研究方向为水文模型，E-mail：suntong_nuist@163.com

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