Article(id=1223210593302204781, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223210584024400210, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20212707, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1639065600000, receivedDateStr=2021-12-10, revisedDate=1646064000000, revisedDateStr=2022-03-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1769565731596, onlineDateStr=2026-01-28, pubDate=1687622400000, pubDateStr=2023-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769565731596, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769565731596, creator=13701087609, updateTime=1769565731596, updator=13701087609, issue=Issue{id=1223210584024400210, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='6', 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=1769565729385, creator=13701087609, updateTime=1769593153259, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1223325608164348105, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223210584024400210, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1223325608164348106, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223210584024400210, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=4, ext={EN=ArticleExt(id=1223210593600000397, articleId=1223210593302204781, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Influence of Climate Abrupt Change on Extreme Distribution of Staged Rainfall in Jiangxi Province Based on Genetic Algorithm, columnId=1222925279849341011, journalTitle=Water Resources and Power, columnName=HYDROLOGY, WATER RESOURCES AND ENVIRONMENT, runingTitle=null, highlight=null, articleAbstract=

In order to study the influence of climate change on rainfall extreme value distribution in main flood season, based on the daily rainfall data from 1960 to 2017 in Jiangxi Province, a variety of test methods were used to detect and test the abrupt change points. Genetic algorithm and Fisher's optimal segmentation method were used to stage the flood season before and after the climate abrupt change, and the extreme distribution of staged rainfall and design rainfall before and after the climate abrupt change were discussed. The results show that 1991 was the abrupt change year of precipitation in Jiangxi Province from 1960 to 2017, and it was necessary to pay more attention to the occurrence of extreme heavy rainfall in Guangchang and Poyang Lake regions. Genetic algorithm is suitable for the division and staging of flood season. After the abrupt climate change (1991-2017), the designed rainfall value in the main flood season of Jiangxi Province was greater than that before the abrupt climate change (1960-1990), and also greater than that in the whole period (1960-2017). When calculating the designed flood based on the designed rainfall, the influence of climate change on the designed rainfall value should be considered, and strengthen protection against floods.

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为了研究气候变化对江西省内主汛期降雨极值分布的影响,以江西省1960~2017年的逐日降雨资料为基础资料,采用多种检验方法检测突变点并对突变点进行检验,使用遗传算法与Fisher最优分割法对气候突变前后的汛期进行分期,并对气候突变前后分期降雨极值分布与设计降雨进行探讨。结果表明,1960~2017年江西省降雨量突变年为1991年,广昌与鄱阳湖区域需重点关注极端强降雨的发生;遗传算法适用于汛期划分与分期,气候突变后(1991~2017年)江西省主汛期设计降雨值大于气候突变前(1960~1990年),也大于整时段(1960~2017年)所得设计降雨值,在以设计降雨为基础推求江西省设计洪水时,需考虑气候变化对设计降雨值的影响,加强对洪水的防范。

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刘海明(1978-),男,博士、讲师,研究方向为管理科学与工程,E-mail:
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唐莉(1992-),女,博士、讲师,研究方向为水文学及水资源,E-mail:

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基于遗传算法的气候突变对江西省分期降雨极值分布的影响
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唐莉 a, b , 刘海明 b , 魏希 c , 闫中月 b , 杨冰冰 b
水电能源科学 | 水文水资源与环境 2023,41(6): 1-4
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水电能源科学 | 水文水资源与环境 2023, 41(6): 1-4
基于遗传算法的气候突变对江西省分期降雨极值分布的影响
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唐莉a, b , 刘海明b , 魏希c, 闫中月b, 杨冰冰b
作者信息
  • a.南昌工程学院江西省水安全与可持续发展软科学研究基地,江西 南昌 330099
  • b.南昌工程学院工商管理学院,江西 南昌 330099
  • c.南昌工程学院综合管理科,江西 南昌 330099
  • 唐莉(1992-),女,博士、讲师,研究方向为水文学及水资源,E-mail:

通讯作者:

刘海明(1978-),男,博士、讲师,研究方向为管理科学与工程,E-mail:
Influence of Climate Abrupt Change on Extreme Distribution of Staged Rainfall in Jiangxi Province Based on Genetic Algorithm
Li TANGa, b , Hai-ming LIUb , Xi WEIc, Zhong-yue YANb, Bing-bing YANGb
Affiliations
  • a.Jiangxi Provincial Soft Science Research Base of Water Security and Sustainable Development, Nanchang Institute of Technology, Nanchang 330099, China
  • b.School of Business Administration, Nanchang Institute of Technology, Nanchang 330099, China
  • c.Comprehensive Management Section, Nanchang Institute of Technology, Nanchang 330099, China
出版时间: 2023-06-25 doi: 10.20040/j.cnki.1000-7709.2023.20212707
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为了研究气候变化对江西省内主汛期降雨极值分布的影响,以江西省1960~2017年的逐日降雨资料为基础资料,采用多种检验方法检测突变点并对突变点进行检验,使用遗传算法与Fisher最优分割法对气候突变前后的汛期进行分期,并对气候突变前后分期降雨极值分布与设计降雨进行探讨。结果表明,1960~2017年江西省降雨量突变年为1991年,广昌与鄱阳湖区域需重点关注极端强降雨的发生;遗传算法适用于汛期划分与分期,气候突变后(1991~2017年)江西省主汛期设计降雨值大于气候突变前(1960~1990年),也大于整时段(1960~2017年)所得设计降雨值,在以设计降雨为基础推求江西省设计洪水时,需考虑气候变化对设计降雨值的影响,加强对洪水的防范。

气候变化  /  主汛期划分  /  降雨极值分布  /  江西省

In order to study the influence of climate change on rainfall extreme value distribution in main flood season, based on the daily rainfall data from 1960 to 2017 in Jiangxi Province, a variety of test methods were used to detect and test the abrupt change points. Genetic algorithm and Fisher's optimal segmentation method were used to stage the flood season before and after the climate abrupt change, and the extreme distribution of staged rainfall and design rainfall before and after the climate abrupt change were discussed. The results show that 1991 was the abrupt change year of precipitation in Jiangxi Province from 1960 to 2017, and it was necessary to pay more attention to the occurrence of extreme heavy rainfall in Guangchang and Poyang Lake regions. Genetic algorithm is suitable for the division and staging of flood season. After the abrupt climate change (1991-2017), the designed rainfall value in the main flood season of Jiangxi Province was greater than that before the abrupt climate change (1960-1990), and also greater than that in the whole period (1960-2017). When calculating the designed flood based on the designed rainfall, the influence of climate change on the designed rainfall value should be considered, and strengthen protection against floods.

climate change  /  flood season division  /  rainfall extreme value distribution  /  Jiangxi Province
唐莉, 刘海明, 魏希, 闫中月, 杨冰冰. 基于遗传算法的气候突变对江西省分期降雨极值分布的影响. 水电能源科学, 2023 , 41 (6) : 1 -4 . DOI: 10.20040/j.cnki.1000-7709.2023.20212707
Li TANG, Hai-ming LIU, Xi WEI, Zhong-yue YAN, Bing-bing YANG. Influence of Climate Abrupt Change on Extreme Distribution of Staged Rainfall in Jiangxi Province Based on Genetic Algorithm[J]. Water Resources and Power, 2023 , 41 (6) : 1 -4 . DOI: 10.20040/j.cnki.1000-7709.2023.20212707
  • 江西省教育厅科学技术研究项目(GJJ211945; GJJ201930)
2023年第41卷第6期
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doi: 10.20040/j.cnki.1000-7709.2023.20212707
  • 接收时间:2021-12-10
  • 首发时间:2026-01-28
  • 出版时间:2023-06-25
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  • 收稿日期:2021-12-10
  • 修回日期:2022-03-01
基金
江西省教育厅科学技术研究项目(GJJ211945; GJJ201930)
作者信息
    a.南昌工程学院江西省水安全与可持续发展软科学研究基地,江西 南昌 330099
    b.南昌工程学院工商管理学院,江西 南昌 330099
    c.南昌工程学院综合管理科,江西 南昌 330099

通讯作者:

刘海明(1978-),男,博士、讲师,研究方向为管理科学与工程,E-mail:
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2种不同金属材料的力学参数

Family
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Number of
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种数
Number of
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Percentage of
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Genus
种数
Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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