Article(id=1223202681649483968, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1223202678788965355, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20230325, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1678032000000, receivedDateStr=2023-03-06, revisedDate=1680451200000, revisedDateStr=2023-04-03, acceptedDate=null, acceptedDateStr=null, onlineDate=1769563845312, onlineDateStr=2026-01-28, pubDate=1703433600000, pubDateStr=2023-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769563845312, onlineIssueDateStr=2026-01-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769563845312, creator=13701087609, updateTime=1769563845312, 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=41, endPage=44, ext={EN=ArticleExt(id=1223202685847982490, articleId=1223202681649483968, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Identification of Key Factors and Critical Values for Production and Elimination of Water Bloom in Wuhan South Lake, columnId=1222925279849341011, journalTitle=Water Resources and Power, columnName=HYDROLOGY, WATER RESOURCES AND ENVIRONMENT, runingTitle=null, highlight=null, articleAbstract=

The identification of key influencing factors and their critical values for the prevention and control of water bloom in lakes is of great significance. Taking Wuhan South Lake as the study area, based on hydrological, water quality and meteorological monitoring data, Pearson Correlation Analysis, Gray Correlation Analysis and Principal Component Analysis were used to screen and identify key environmental factors with high correlation with chlorophyll a concentration, and the critical values of key environmental impact factors were analyzed by the Receiver Operating Characteristic (ROC) curve method. The results show that the CODMn, total phosphorus, total nitrogen, water temperature and air temperature had strong correlations with chlorophyll a concentration and were the key factors for water bloom outbreak, with the critical values of 6.25 mg/L, 0.146 mg/L, 0.725 mg/L, 27.05 ℃ and 22.35 ℃, respectively. It was found that the accuracy of the ROC curve method for solving the critical values of CODMn, total phosphorus, total nitrogen and other environmental factors with small daily variation was better than that of environmental factors with large daily variation such as air temperature and water temperature, and the ROC curve method has a greater advantage in determining the critical values of nutrient concentrations for water blooms in lakes.

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识别水华生消关键影响因子及其临界值对湖泊水华防控具有重要意义。以武汉市南湖为研究区,基于水文、水质和气象监测数据,采用皮尔逊相关分析、灰色关联分析、主成分分析方法,筛选并确定与叶绿素a浓度相关性较大的关键环境因子,利用受试者工作特征(ROC)曲线法分析关键环境影响因子的临界值。结果表明,CODMn、总磷、总氮、水温、气温与叶绿素a浓度具有较强的相关关系,是水华暴发的关键因子,其临界值分别为6.25 mg/L、0.146 mg/L、0.725 mg/L、27.05 ℃、22.35 ℃。研究发现,ROC曲线法对CODMn、总磷、总氮等日变幅较小环境因子临界值的求解精度优于气温、水温等日变幅较大环境因子,在湖泊水华暴发的营养盐浓度临界值确定方面具有较大优势。

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李建(1985-),男,教授级高级工程师,研究方向为水文水资源,E-mail:
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刘振旗(1998-),男,硕士研究生,研究方向为水文水资源,E-mail:

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武汉南湖水华生消关键因子识别及临界值
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刘振旗 1, 2 , 李建 1 , 江善虎 2 , 华一安 2 , 杨克非 3
水电能源科学 | 水文水资源与环境 2023,41(12): 41-44
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水电能源科学 | 水文水资源与环境 2023, 41(12): 41-44
武汉南湖水华生消关键因子识别及临界值
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刘振旗1, 2 , 李建1 , 江善虎2, 华一安2, 杨克非3
作者信息
  • 1.长江水资源保护科学研究所,湖北 武汉 430000
  • 2.河海大学水文水资源学院,江苏 南京 210000
  • 3.华北水利水电大学,河南 郑州 450000
  • 刘振旗(1998-),男,硕士研究生,研究方向为水文水资源,E-mail:

通讯作者:

李建(1985-),男,教授级高级工程师,研究方向为水文水资源,E-mail:
Identification of Key Factors and Critical Values for Production and Elimination of Water Bloom in Wuhan South Lake
Zhen-qi LIU1, 2 , Jian LI1 , Shan-hu JIANG2, Yi-an HUA2, Ke-fei YANG3
Affiliations
  • 1.Changjiang Water Resources Protection Institute, Wuhan 430000, China
  • 2.College of Hydrology and Water Resources, Hohai University, Nanjing 210000, China
  • 3.North China University of Water Resources and Electric Power, Zhengzhou 450000, China
出版时间: 2023-12-25 doi: 10.20040/j.cnki.1000-7709.2023.20230325
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识别水华生消关键影响因子及其临界值对湖泊水华防控具有重要意义。以武汉市南湖为研究区,基于水文、水质和气象监测数据,采用皮尔逊相关分析、灰色关联分析、主成分分析方法,筛选并确定与叶绿素a浓度相关性较大的关键环境因子,利用受试者工作特征(ROC)曲线法分析关键环境影响因子的临界值。结果表明,CODMn、总磷、总氮、水温、气温与叶绿素a浓度具有较强的相关关系,是水华暴发的关键因子,其临界值分别为6.25 mg/L、0.146 mg/L、0.725 mg/L、27.05 ℃、22.35 ℃。研究发现,ROC曲线法对CODMn、总磷、总氮等日变幅较小环境因子临界值的求解精度优于气温、水温等日变幅较大环境因子,在湖泊水华暴发的营养盐浓度临界值确定方面具有较大优势。

水华  /  关键环境因子  /  临界值  /  ROC曲线法

The identification of key influencing factors and their critical values for the prevention and control of water bloom in lakes is of great significance. Taking Wuhan South Lake as the study area, based on hydrological, water quality and meteorological monitoring data, Pearson Correlation Analysis, Gray Correlation Analysis and Principal Component Analysis were used to screen and identify key environmental factors with high correlation with chlorophyll a concentration, and the critical values of key environmental impact factors were analyzed by the Receiver Operating Characteristic (ROC) curve method. The results show that the CODMn, total phosphorus, total nitrogen, water temperature and air temperature had strong correlations with chlorophyll a concentration and were the key factors for water bloom outbreak, with the critical values of 6.25 mg/L, 0.146 mg/L, 0.725 mg/L, 27.05 ℃ and 22.35 ℃, respectively. It was found that the accuracy of the ROC curve method for solving the critical values of CODMn, total phosphorus, total nitrogen and other environmental factors with small daily variation was better than that of environmental factors with large daily variation such as air temperature and water temperature, and the ROC curve method has a greater advantage in determining the critical values of nutrient concentrations for water blooms in lakes.

water bloom  /  key environmental factors  /  critical value  /  ROC curve method
刘振旗, 李建, 江善虎, 华一安, 杨克非. 武汉南湖水华生消关键因子识别及临界值. 水电能源科学, 2023 , 41 (12) : 41 -44 . DOI: 10.20040/j.cnki.1000-7709.2023.20230325
Zhen-qi LIU, Jian LI, Shan-hu JIANG, Yi-an HUA, Ke-fei YANG. Identification of Key Factors and Critical Values for Production and Elimination of Water Bloom in Wuhan South Lake[J]. Water Resources and Power, 2023 , 41 (12) : 41 -44 . DOI: 10.20040/j.cnki.1000-7709.2023.20230325
  • 湖北省自然科学面上基金项目(2022CFB374)
  • 国家自然科学基金重点项目(U2040210)
2023年第41卷第12期
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文章信息
doi: 10.20040/j.cnki.1000-7709.2023.20230325
  • 接收时间:2023-03-06
  • 首发时间:2026-01-28
  • 出版时间:2023-12-25
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  • 收稿日期:2023-03-06
  • 修回日期:2023-04-03
基金
湖北省自然科学面上基金项目(2022CFB374)
国家自然科学基金重点项目(U2040210)
作者信息
    1.长江水资源保护科学研究所,湖北 武汉 430000
    2.河海大学水文水资源学院,江苏 南京 210000
    3.华北水利水电大学,河南 郑州 450000

通讯作者:

李建(1985-),男,教授级高级工程师,研究方向为水文水资源,E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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