Article(id=1223278139342721638, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223278131956551924, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20221921, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1663171200000, receivedDateStr=2022-09-15, revisedDate=1673971200000, revisedDateStr=2023-01-18, acceptedDate=null, acceptedDateStr=null, onlineDate=1769581835827, onlineDateStr=2026-01-28, pubDate=1698163200000, pubDateStr=2023-10-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769581835827, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769581835827, creator=13701087609, updateTime=1769581835827, updator=13701087609, issue=Issue{id=1223278131956551924, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='10', 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=1769581834067, creator=13701087609, updateTime=1769584342407, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223288652869030422, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223278131956551924, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223288652869030423, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223278131956551924, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=19, endPage=22, ext={EN=ArticleExt(id=1223278139699237496, articleId=1223278139342721638, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Effect of DEM Resolution and Meteorological Data on Runoff SWAT Simulation of Yongcui River Small Watershed in Cold Region, columnId=1222925279849341011, journalTitle=Water Resources and Power, columnName=HYDROLOGY, WATER RESOURCES AND ENVIRONMENT, runingTitle=null, highlight=null, articleAbstract=

Due to the existence of snow, melting snow and frozen soil, the hydrological cycle in cold regions has its particularity. In order to probe into the hydrological law of small watershed in cold region and simulate the process of runoff formation, the hydrological data of Yongcuihe River basin from 1994 to 2015 were selected as the research area. The SWAT model for runoff simulation in cold region was constructed, and the applicability of DEM with different resolution, as well as three kinds of meteorological data, CMADS data set and CFSR data set, in Yongcuihe River basin was analyzed. The results show that the SWAT model can simulate the runoff process of Yongcuihe River. DEM resolution has a great impact on the extraction of watershed features, but has no obvious effect on runoff simulation. The applicability of different meteorological data has significant difference, the simulation effect of measured meteorological data is the best, the simulation effect of CMADS data set is better, and the simulation effect of CFSR data set is worse, which provides a reference for further study of small watershed in cold region.

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由于降雪、融雪及冻土层存在等因素，寒区水文循环过程具有特殊性。为探讨寒区小流域水文规律，模拟径流形成过程，以永翠河流域为例，选取流域1994~2015年总计22年的水文资料，构建适用于寒区流域径流模拟的SWAT模型，并分析不同分辨率DEM及实测气象数据、CMADS数据集、CFSR数据集三种气象数据在永翠河流域的适用性。结果表明，SWAT模型能较好地模拟永翠河流域径流过程，DEM分辨率对流域特征值提取影响较大但对径流模拟影响不明显；不同气象数据适用性差别显著，实测气象数据模拟效果最好，CMADS数据集模拟效果较好，CFSR数据集模拟效果差。结果为寒区小流域进一步研究提供了参考。

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张丽娜（1998-），女，硕士研究生，研究方向为产汇流理论，E-mail：1539860972@qq.com

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张丽娜（1998-），女，硕士研究生，研究方向为产汇流理论，E-mail：1539860972@qq.com

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