Article(id=1241057211301032579, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241057209744945780, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728316800000, receivedDateStr=2024-10-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773820696902, onlineDateStr=2026-03-18, pubDate=1747670400000, pubDateStr=2025-05-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773820696902, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773820696902, creator=13701087609, updateTime=1773820696902, updator=13701087609, issue=Issue{id=1241057209744945780, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='5', pageStart='2369', pageEnd='2960', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773820696530, creator=13701087609, updateTime=1773820837005, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241057798994325889, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241057209744945780, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241057798994325890, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241057209744945780, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2816, endPage=2826, ext={EN=ArticleExt(id=1241057211540107914, articleId=1241057211301032579, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Spatial-temporal distribution characteristics of dissolved oxygen and its causes in Sihu Canal, columnId=1234106388083954308, journalTitle=China Environmental Science, columnName=Environmental Ecology, runingTitle=null, highlight=null, articleAbstract=

Hypoxia has become a prevalent phenomenon in the plain river network region. To reveal the causes of hypoxia in these regions, the Sihu Canal in the Hanjiang River Basin, one of China's most important freshwater aquaculture areas, was selected as a case study. The spatiotemporal variations in water quality, including dissolved oxygen(DO)and nutrients, were analyzed for the period 2010~2023, and the spatial distribution of nutrients in water and sediments were investigated. The impact of parameters such as water temperature, ammonia nitrogen, and flow on DO levels in the water was evaluated using a Random Forest model. The results indicated significant seasonal fluctuation in DO levels, which exhibited a 'V'-shaped pattern throughout the year. DO concentrations were relatively low during flood seasons, while during non-flood seasons the requirements for Class III surface water quality were generally satisfied. In 2021, severe hypoxia(DO<2mg/L)was observed, with the annual hypoxic days amounting to 79,116, and 96 at the Yunlianghu, Xinhecun, and Xintan sections respectively. Evident hypoxic zones were identified in the mid- and upstream sections of the Sihu Canal, where DO concentrations ranged from 2.61 to 3.22mg/L. From 2010 to 2023, the water quality of the Sihu Canal consistently ranged from Class IV to Class V, with occasional further deterioration recorded. The main parameters exceeding the standards were identified as DO, permanganate index, ammonia nitrogen, and total phosphorus. The total nitrogen and phosphorus contents in the sediments ranged from 857.70 to 2846.87mg/kg, and 545.99 to 2475.59mg/kg, respectively, indicating that the sediments were subjected to mild to moderate pollution, with tributaries being more polluted than the main canal. High accuracy in predicting DO levels was demonstrated by the Random Forest model, which yielded an R2 of 0.995 and an RMSE of 0.2085. Water temperature had a relative importance exceeding 35% in influencing DO levels, followed by pH, ammonia nitrogen, conductivity, turbidity, and flow. To mitigate the hypoxic conditions during flood seasons, it was recommended that the systematic management of the basin be strengthened, the water quality of shrimp-rice and aquaculture drainage systems be improved, and the operation and scheduling of pump stations be optimized.

, correspAuthors=Xian-qiang TANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Rui LI, Xian-qiang TANG, Yan-ping HU, Dan-yang WANG, Dong-fan GUO, Wen-liang ZHAI, Yong YANG), CN=ArticleExt(id=1241057214224462613, articleId=1241057211301032579, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=四湖总干渠溶解氧季节性异常特征与成因分析, columnId=1234106388268503686, journalTitle=中国环境科学, columnName=环境生态, runingTitle=null, highlight=null, articleAbstract=

平原水网地区水体溶解氧(DO)偏低已成为一个普遍的现象.为揭示平原水网地区溶解氧异常成因,以全国最重要的淡水养殖区汉江流域四湖总干渠为例,分析了2010~2023年四湖总干渠水质时空变化规律,调查监测了四湖总干渠DO、水体和沉积物中营养盐空间分布特征,采用随机森林模型等方法分析了水温、氨氮及流量等参数对水体溶解氧的影响.结果表明:四湖总干渠水体溶解氧(DO)存在明显的季节性波动,年内呈“V”型分布,汛期DO浓度相对较低,非汛期基本满足地表水Ⅲ类水要求.2021年四湖总干渠水体缺氧(DO<2mg/L)状况突出,运粮湖、新河村和新滩断面年缺氧天数分别为79,116和96d.汛期四湖总干渠在中上游河段存在明显的低氧区,DO浓度仅为2.61~3.22mg/L.自2010年以来四湖总干渠水质长期处于Ⅳ~劣Ⅴ类,主要超标因子为DO、高锰酸盐指数、氨氮、总磷.四湖总干渠沉积物总氮含量为857.70~2846.87mg/kg,TP含量为545.99~2475.59mg/kg,沉积物处于轻-中度污染状态,支渠污染重于干渠.随机森林模型能够较好的预测水体DO,拟合系数R2达0.995,均方根误差RMSE仅为0.2085.随机森林模型分析表明水温对DO影响相对重要性均超过35%,其他影响因素依次为pH值、氨氮、电导率、浊度、流量等.为改善四湖总干渠DO汛期异常状况,需加强流域系统治理,改善虾稻和水产养殖排水水质,优化泵站调度运行方式.

, correspAuthors=汤显强, authorNote=null, correspAuthorsNote=
* 责任作者,正高级工程师,
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黎睿(1990-),男,湖北竹溪人,高级工程师,硕士,主要从事流域水环境保护研究.发表论文20余篇..

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黎睿(1990-),男,湖北竹溪人,高级工程师,硕士,主要从事流域水环境保护研究.发表论文20余篇..

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黎睿(1990-),男,湖北竹溪人,高级工程师,硕士,主要从事流域水环境保护研究.发表论文20余篇..

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Limnology and Oceanography Letters20238(3):453-463., articleTitle=Extent,patterns,and drivers of hypoxia in the world's streams and rivers, refAbstract=null), Reference(id=1241057239629361994, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, doi=null, pmid=null, pmcid=null, year=2019, volume=41, issue=4, pageStart=421, pageEnd=425, url=null, language=null, rfNumber=[49], rfOrder=73, authorNames=陈帅, 莫彩芬, 李艳蔷, journalName=环境污染与防治, refType=null, unstructuredReference=陈帅,莫彩芬,李艳蔷,等. 洪湖水质时空特征及污染驱动力分析[J]. 环境污染与防治201941(4):421-425., articleTitle=洪湖水质时空特征及污染驱动力分析, refAbstract=null), Reference(id=1241057239763579734, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, doi=null, pmid=null, pmcid=null, year=2019, volume=41, issue=4, pageStart=421, pageEnd=425, url=null, language=null, rfNumber=[49], rfOrder=74, authorNames=Chen S, Mo C F, Li Y Q, journalName=Environmental Pollution & Control, refType=null, unstructuredReference=Chen SMo C FLi Y Q,et al. 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Environmental Pollution & Control201941(4):421-425., articleTitle=Spatio-temporal characterist ics of water quality and the pollution driving forces of Honghu Lake, refAbstract=null), Reference(id=1241057239914574690, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, doi=null, pmid=null, pmcid=null, year=2022, volume=41, issue=7, pageStart=1520, pageEnd=1530, url=null, language=null, rfNumber=[50], rfOrder=75, authorNames=陈玲, 范先鹏, 黄敏, journalName=农业环境科学学报, refType=null, unstructuredReference=陈玲,范先鹏,黄敏,等. 江汉平原稻虾轮作模式地表径流氮、磷流失特征[J]. 农业环境科学学报202241(7):1520-1530., articleTitle=江汉平原稻虾轮作模式地表径流氮、磷流失特征, refAbstract=null), Reference(id=1241057240065569648, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, doi=null, pmid=null, pmcid=null, year=2022, volume=41, issue=7, pageStart=1520, pageEnd=1530, url=null, language=null, rfNumber=[50], rfOrder=76, authorNames=Chen L, Fan X L, Huang M, journalName=Journal of Agro-Environment Science, refType=null, unstructuredReference=Chen LFan X LHuang M,et al. 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Natural Hazards and Earth System Sciences201919(11):2551-2564., articleTitle=Comparing the efficiency of hypoxia mitigation strategies in an urban,turbid tidal river via a coupled hydro-sedimentary–biogeochemical model, refAbstract=null)], funds=[Fund(id=1241057222986363522, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, awardId=2022YFC3201902, language=CN, fundingSource=国家重点研发专项(2022YFC3201902), fundOrder=null, country=null), Fund(id=1241057223183495827, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, awardId=CKSF2024327/SH, language=CN, fundingSource=中央级公益性科研院所基本科研业务费专项(CKSF2024327/SH), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241057214660670265, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, xref=1., ext=[AuthorCompanyExt(id=1241057214664864570, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, companyId=1241057214660670265, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.Basin Water Environmental Department, Yangtze River Scientific Research Institute, Wuhan 430010, China), AuthorCompanyExt(id=1241057214673253179, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, companyId=1241057214660670265, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.长江科学院流域水环境研究所,湖北 武汉 430010)]), AuthorCompany(id=1241057214799082308, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, xref=2., ext=[AuthorCompanyExt(id=1241057214807470917, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, companyId=1241057214799082308, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.Hubei Provincial Key Laboratory of Basin Water Resources and Ecological Environment Sciences, Yangtze River Scientific Research Institute, Wuhan 430010, China), AuthorCompanyExt(id=1241057214811665222, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, companyId=1241057214799082308, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.长江科学院流域水资源与生态环境科学湖北省重点实验室,湖北 武汉 430010)]), AuthorCompany(id=1241057214903939915, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, xref=3., ext=[AuthorCompanyExt(id=1241057214912328524, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, companyId=1241057214903939915, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.Irrigation and Drainage Experiment Station of the Four-Lake Engineering Administration Bureau, Jingzhou 434013, China), AuthorCompanyExt(id=1241057214924911440, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, companyId=1241057214903939915, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.湖北省荆州市四湖工程管理局排灌试验站,湖北 荆州 434013)])], figs=[ArticleFig(id=1241057219064688857, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=EN, label=Fig.1, caption=Location of main culvert gates and water quality monitoring sections of Sihu Canal, figureFileSmall=jAgSRUXGFy7qzRcZChIucQ==, figureFileBig=0JZgRm83v0lE0zRFaKIJAA==, tableContent=null), ArticleFig(id=1241057219211489515, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=CN, label=图1, caption=四湖总干渠主要涵闸、水质监测断面位置示意, figureFileSmall=jAgSRUXGFy7qzRcZChIucQ==, figureFileBig=0JZgRm83v0lE0zRFaKIJAA==, tableContent=null), ArticleFig(id=1241057219597365524, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=EN, label=Fig.2, caption=Characteristics of DO variations in national control sections of Sihu Canal, figureFileSmall=9Uh0+oLWHFB486aloqNpmQ==, figureFileBig=9b7j2goVM2q2ZpSJnXUETw==, tableContent=null), ArticleFig(id=1241057219932909865, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=CN, label=图2, caption=四湖总干渠国控断面DO变化特征

新滩断面由于设备维护检修,部分时段数据缺失

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箱线图字母表示断面之间DO的差异,P<0.05

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E2/E3、E2/E4和E3/E4分别表示波长250nm和365nm处吸光度的比值、波长250nm和400nm处吸光度的比值和波长300nm和400nm处吸光度的比值

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Main physicochemical parameters of Sihu Canal from 2021 to 2023

, figureFileSmall=null, figureFileBig=null, tableContent=
指标运粮湖新河村新滩
pH值6.87~8.16(7.46)7.00~7.69(7.36)7.03~7.96(7.34)
电导率(µS/cm)344.6~541.8(439.1)ab386.4~512.5(456.4)a314.1~522.7(424.7)b
浊度(NTU)13.8~126.3(43.4)a10.7~45.5(26.7)b11.6~195.9(52.3)a
CODMn(mg/L)2.88~8.26(4.70)b3.54~7.97(5.23)b4.23~11.20(6.56)a
NH3-N(mg/L)0.103~2.271(0.641)a0.238~0.991(0.502)a0.031~0.555(0.220)b
TP(mg/L)0.059~0.363(0.177)a0.098~0.223(0.151)ab0.057~0.305(0.124)b
TN(mg/L)1.17~4.00(2.39)1.39~2.98(2.21)1.10~3.50(2.27)
), ArticleFig(id=1241057222621459022, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=CN, label=表1, caption=

2021~2023年四湖总干渠水体主要理化参数

, figureFileSmall=null, figureFileBig=null, tableContent=
指标运粮湖新河村新滩
pH值6.87~8.16(7.46)7.00~7.69(7.36)7.03~7.96(7.34)
电导率(µS/cm)344.6~541.8(439.1)ab386.4~512.5(456.4)a314.1~522.7(424.7)b
浊度(NTU)13.8~126.3(43.4)a10.7~45.5(26.7)b11.6~195.9(52.3)a
CODMn(mg/L)2.88~8.26(4.70)b3.54~7.97(5.23)b4.23~11.20(6.56)a
NH3-N(mg/L)0.103~2.271(0.641)a0.238~0.991(0.502)a0.031~0.555(0.220)b
TP(mg/L)0.059~0.363(0.177)a0.098~0.223(0.151)ab0.057~0.305(0.124)b
TN(mg/L)1.17~4.00(2.39)1.39~2.98(2.21)1.10~3.50(2.27)
), ArticleFig(id=1241057222713733723, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=EN, label=Table 2, caption=

Total phosphorus, total nitrogen, and LOI in the sediments of Sihu Canal

, figureFileSmall=null, figureFileBig=null, tableContent=
位置TP(mg/kg)TN(mg/kg)LOI(%)
干渠上游1314.58±821.861132.73±491.765.49±1.99
中游876.12±189.801049.73±434.426.25±3.01
下游759.22±74.631688.63±1079.216.79±2.39
支渠1434.84±506.291567.27±192.506.47±1.90
), ArticleFig(id=1241057222856340079, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241057211301032579, language=CN, label=表2, caption=

四湖总干渠底质氮磷及有机质含量特征

, figureFileSmall=null, figureFileBig=null, tableContent=
位置TP(mg/kg)TN(mg/kg)LOI(%)
干渠上游1314.58±821.861132.73±491.765.49±1.99
中游876.12±189.801049.73±434.426.25±3.01
下游759.22±74.631688.63±1079.216.79±2.39
支渠1434.84±506.291567.27±192.506.47±1.90
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四湖总干渠溶解氧季节性异常特征与成因分析
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黎睿 1, 2 , 汤显强 1, 2, * , 胡艳平 1, 2 , 王丹阳 1, 2 , 郭栋帆 1 , 翟文亮 1, 2 , 杨勇 3
中国环境科学 | 环境生态 2025,45(5): 2816-2826
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中国环境科学 | 环境生态 2025, 45(5): 2816-2826
四湖总干渠溶解氧季节性异常特征与成因分析
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黎睿1, 2 , 汤显强1, 2, * , 胡艳平1, 2, 王丹阳1, 2, 郭栋帆1, 翟文亮1, 2, 杨勇3
作者信息
  • 1.长江科学院流域水环境研究所,湖北 武汉 430010
  • 2.长江科学院流域水资源与生态环境科学湖北省重点实验室,湖北 武汉 430010
  • 3.湖北省荆州市四湖工程管理局排灌试验站,湖北 荆州 434013
  • 黎睿(1990-),男,湖北竹溪人,高级工程师,硕士,主要从事流域水环境保护研究.发表论文20余篇..

通讯作者:

* 责任作者,正高级工程师,
Spatial-temporal distribution characteristics of dissolved oxygen and its causes in Sihu Canal
Rui LI1, 2 , Xian-qiang TANG1, 2, * , Yan-ping HU1, 2, Dan-yang WANG1, 2, Dong-fan GUO1, Wen-liang ZHAI1, 2, Yong YANG3
Affiliations
  • 1.Basin Water Environmental Department, Yangtze River Scientific Research Institute, Wuhan 430010, China
  • 2.Hubei Provincial Key Laboratory of Basin Water Resources and Ecological Environment Sciences, Yangtze River Scientific Research Institute, Wuhan 430010, China
  • 3.Irrigation and Drainage Experiment Station of the Four-Lake Engineering Administration Bureau, Jingzhou 434013, China
出版时间: 2025-05-20
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平原水网地区水体溶解氧(DO)偏低已成为一个普遍的现象.为揭示平原水网地区溶解氧异常成因,以全国最重要的淡水养殖区汉江流域四湖总干渠为例,分析了2010~2023年四湖总干渠水质时空变化规律,调查监测了四湖总干渠DO、水体和沉积物中营养盐空间分布特征,采用随机森林模型等方法分析了水温、氨氮及流量等参数对水体溶解氧的影响.结果表明:四湖总干渠水体溶解氧(DO)存在明显的季节性波动,年内呈“V”型分布,汛期DO浓度相对较低,非汛期基本满足地表水Ⅲ类水要求.2021年四湖总干渠水体缺氧(DO<2mg/L)状况突出,运粮湖、新河村和新滩断面年缺氧天数分别为79,116和96d.汛期四湖总干渠在中上游河段存在明显的低氧区,DO浓度仅为2.61~3.22mg/L.自2010年以来四湖总干渠水质长期处于Ⅳ~劣Ⅴ类,主要超标因子为DO、高锰酸盐指数、氨氮、总磷.四湖总干渠沉积物总氮含量为857.70~2846.87mg/kg,TP含量为545.99~2475.59mg/kg,沉积物处于轻-中度污染状态,支渠污染重于干渠.随机森林模型能够较好的预测水体DO,拟合系数R2达0.995,均方根误差RMSE仅为0.2085.随机森林模型分析表明水温对DO影响相对重要性均超过35%,其他影响因素依次为pH值、氨氮、电导率、浊度、流量等.为改善四湖总干渠DO汛期异常状况,需加强流域系统治理,改善虾稻和水产养殖排水水质,优化泵站调度运行方式.

溶解氧  /  缺氧  /  平原水网区  /  随机森林  /  四湖总干渠

Hypoxia has become a prevalent phenomenon in the plain river network region. To reveal the causes of hypoxia in these regions, the Sihu Canal in the Hanjiang River Basin, one of China's most important freshwater aquaculture areas, was selected as a case study. The spatiotemporal variations in water quality, including dissolved oxygen(DO)and nutrients, were analyzed for the period 2010~2023, and the spatial distribution of nutrients in water and sediments were investigated. The impact of parameters such as water temperature, ammonia nitrogen, and flow on DO levels in the water was evaluated using a Random Forest model. The results indicated significant seasonal fluctuation in DO levels, which exhibited a 'V'-shaped pattern throughout the year. DO concentrations were relatively low during flood seasons, while during non-flood seasons the requirements for Class III surface water quality were generally satisfied. In 2021, severe hypoxia(DO<2mg/L)was observed, with the annual hypoxic days amounting to 79,116, and 96 at the Yunlianghu, Xinhecun, and Xintan sections respectively. Evident hypoxic zones were identified in the mid- and upstream sections of the Sihu Canal, where DO concentrations ranged from 2.61 to 3.22mg/L. From 2010 to 2023, the water quality of the Sihu Canal consistently ranged from Class IV to Class V, with occasional further deterioration recorded. The main parameters exceeding the standards were identified as DO, permanganate index, ammonia nitrogen, and total phosphorus. The total nitrogen and phosphorus contents in the sediments ranged from 857.70 to 2846.87mg/kg, and 545.99 to 2475.59mg/kg, respectively, indicating that the sediments were subjected to mild to moderate pollution, with tributaries being more polluted than the main canal. High accuracy in predicting DO levels was demonstrated by the Random Forest model, which yielded an R2 of 0.995 and an RMSE of 0.2085. Water temperature had a relative importance exceeding 35% in influencing DO levels, followed by pH, ammonia nitrogen, conductivity, turbidity, and flow. To mitigate the hypoxic conditions during flood seasons, it was recommended that the systematic management of the basin be strengthened, the water quality of shrimp-rice and aquaculture drainage systems be improved, and the operation and scheduling of pump stations be optimized.

dissolved oxygen  /  hypoxia  /  plain river network region  /  random forest  /  Sihu Canal
黎睿, 汤显强, 胡艳平, 王丹阳, 郭栋帆, 翟文亮, 杨勇. 四湖总干渠溶解氧季节性异常特征与成因分析. 中国环境科学, 2025 , 45 (5) : 2816 -2826 .
Rui LI, Xian-qiang TANG, Yan-ping HU, Dan-yang WANG, Dong-fan GUO, Wen-liang ZHAI, Yong YANG. Spatial-temporal distribution characteristics of dissolved oxygen and its causes in Sihu Canal[J]. China Environmental Science, 2025 , 45 (5) : 2816 -2826 .
目前我国地表水环境质量持续向好,但仍有部分国控水质断面存在溶解氧(DO)等指标长期超标的情况.DO是评价水体自净能力和受污染程度的重要指标[1-3],当水体DO不足时,会影响水体污染物的生物化学反应过程,进而可能通过食物链累积等方式对人体产生有害影响.研究表明,鱼群的行为会随着DO浓度变化而改变[4],当DO<2mg /L时会导致鱼类窒息死亡,大多数藻类也无法存活[5].长期以来,人们一直认为水体缺氧主要发生在沿海水域[6]和深水湖库[7].近年来,研究发现河流往往有更多的缺氧事件[8],缺氧更可能发生在气候温暖、比降较低的河流中,尤其是那些平原水网地区的水体[9].
平原河网地区水体DO偏低的原因往往比较复杂,影响水体DO浓度的因素包括pH值、温度、电导率、营养物质浓度、大气复氧水平和水动力过程等[10].Zhi等[11]通过深度学习模型研究表明,美国河流日DO动态变化最主要的驱动因素是温度.南京市地表水溶解氧浓度夏季最低,水温和上游来水带入的耗氧污染物是外秦淮河溶解氧偏低的主要成因[3].丁淼等[12]基于三维荧光光谱分析和氮形态解析发现,夏季氨氮浓度高,是造成运河桐乡水源地DO不能稳定达标的首要原因.由气象和水文等多种因素驱动的内源性污染物很可能成为农业小流域水库耗氧污染短期变化的主要驱动因素[13].Xu等[14]通过向量自回归模型等分析方法发现,磷肥和降雨是长三角地区地表水中DO水平的关键驱动因素.华北平原河网区域10年的时间序列显示雨季时DO浓度较低,河岸缓冲区丧失、河流渠道化、污染排放和闸坝调控是影响DO浓度下降和水质恶化的主要因素[15].
即使在营养负荷较低的水流较缓的河流中,低氧状况也可能普遍存在[16].闸控河段会导致河道断流和缺氧,渠道异质性、堰闸的结构形式和启闭控制等均对DO浓度有重要影响[17].然而现有研究主要集中于分析水体中污染物的相互关系,较少关注沉积物、水体水动力条件等对水体DO的影响.四湖流域是湖北省水产养殖及水稻种植较为集中的区域[18],四湖总干渠是流域内主要的养殖用水来源和排水通道,鲜有研究关注四湖总干渠水体DO不达标情况,研究水体DO超标成因,有助于为区域水环境管理提供参考.
四湖总干渠位于汉江流域,起于荆州市沙市区观音垱镇习口闸,止于洪湖市新滩镇胡家湾村,流经沙市区、江陵县、潜江市、监利市、洪湖市,全长191km.四湖流域地势较为平坦,排涝渠、灌溉渠交错连接形成水网,部分渠道通过取水泵站与汉江、长江连通(图1).
四湖流域年平均降雨量约1200mm,降雨一般集中在5~10月,其降雨量约占全年降雨量的70%[19].根据荆州市水利工程专项普查结果,有154个水闸工程与四湖总干渠相连.上游以习家口节制闸控制,中游经福田寺防洪闸调控汇入洪湖,由洪湖小港闸等控制进入下游,至新滩口汇入长江.
于2023年6月和12月中旬,在四湖总干渠采集了水体及沉积物样品,采样断面如图1所示,所有样品均在断面中泓采集.现场采样使用水质多参数仪(YSI,EXO-2)测定水体温度、pH值、DO及电导率等指标.采用ADCP(M9)测量了水体流速及断面流量.参照《水和废水监测分析方法(第四版)》[20]分析了水体总磷(TP)、总氮(TN)、氨氮(NH3-N)、硝酸盐氮(NO3-N)、高锰酸盐指数(CODMn)等指标.以Milli-Q超纯水为参比,使用1cm光程比色皿,采用紫外可见光度计(岛津,UV-2600)分析了水体的光谱特征[21],扫描步长为1nm,扫描范围为190~700nm.沉积物样品冷冻干燥后研磨过100目筛,采用SMT法测定总磷,碱性过硫酸钾法测定总氮.以样品在550℃下灼烧3h的质量损失表征沉积物有机质含量[22],通过提取法分析了沉积物水溶解态氮磷[23].
在荆州市生态环境局收集了2010~2020年的历史水质监测资料,通过生态环境部地表水水质自动监测实时发布系统收集了2020~2023年运粮湖、新河村、新滩等3个国控断面水质监测数据.在荆州市水利部门收集了四湖总干渠控制闸流量、水位等水文资料.DO饱和度采用温度、气压修正经验公式计算[24].参照中国湖泊背景值(TN 690mg/kg,TP 543mg/kg),采用单因子指数法对底泥营养盐污染进行评价[25].
在剔除监测站点维护数据及异常值之后,采用R 3.5.1软件包Trend中的Mann-Kendall法分析溶解氧变化趋势,并用Pettitt突变点检验法得到DO明显变化的时间点.将通过多重共线性检验[26]之后的影响因素作为解释变量,DO浓度作为因变量,采用R语言randomForest程序包构建机器学习模型,评估影响因素重要性.首先对数据集进行拆分,取70%的数据集样本量作为训练集,剩余30%样本量作为测试集.为评估模型对水质拟合的准确性,利用验证点DO浓度的实测值和模型在训练集和测试集上的预测值,分别计算了决定系数R2以及均方误差RMSE.RMSE的值越小、R2越接近1,表明预测结果越准确[27].
四湖总干渠水体溶解氧存在明显的季节性波动特征,年内DO呈“V”型分布(图2).在汛期(4~10月)DO浓度相对较低,日均浓度仅为1.11~4.86mg/L,其中在6月下旬至7月上旬达到最小值,非汛期水体DO浓度相对较高,基本满足地表水Ⅲ类水DO浓度要求.DO饱和度也呈现同样的季节性变化趋势,汛期和非汛期DO饱和度范围分别为0.34%~85.98%和28.59%~102.16%.当水体DO浓度<2mg/L时,水体将出现严重的缺氧状况[28-29],2021年四湖总干渠水体缺氧状况尤为突出,运粮湖、新河村和新滩断面全年分别有79,116和96d处于缺氧状况(图2).从时间变化趋势上来看,四湖总干渠年缺氧时长显著降低,水体缺氧状况得到改善.从图2还可以看出,新滩断面的波动较为显著,其余断面的变化则相对缓和.
图3为汛期(4~10月)、非汛期(11月至翌年3月)运粮湖断面水体DO浓度典型昼夜变化过程.汛期DO浓度日变异系数可达12.91%,其昼夜波动显著高于非汛期.在汛期04:00~08:00时段DO浓度相对较低,随着白天光合作用复氧,在16:00达到一天中DO浓度峰值,随后DO浓度缓慢降低.
汛期四湖总干渠水体DO在中上游存在明显偏低现象,在中上游(东干渠汇入前)河段存在明显的低氧区(图4),DO浓度仅为2.61~3.22mg/L.而在新河村以下,水体DO水平逐渐恢复,至新滩断面水体溶解氧已达到8.76mg/L.这一发现与水质自动监测站同期监测结果一致,即水体DO浓度在空间上表现为运粮湖<新河村<新滩.
2021~2023年四湖总干渠水体pH值相对稳定,介于6.87~8.16之间.电导率平均为424.7~456.4μS/cm,中上游相对较高,而下游新滩断面相对较低.水体浊度则呈中游新河村断面相对较高,而上游和下游浊度相对较低(表1).在空间上CODMn自上游至下游呈逐渐升高趋势,水体氨氮和总磷则呈沿程降低趋势,总氮沿程无明显变化.根据《荆州市地表水环境质量月报》,自2010年以来四湖总干渠水质长期处于Ⅳ~劣Ⅴ类,主要超标因子为DO、CODMn、氨氮、总磷等,各评价因子中超标相对严重的指标是DO和氨氮,水体有机污染特征明显.在空间分布上,四湖总干渠上游至中游福田寺段水体污染严重,流经新滩口后水质得到改善[30].四湖总干渠水体氮浓度还呈现一定的季节性变化特征,即总氮和氨氮浓度自4月开始急剧上升,在9月之后开始快速下降,与农业生产过程施用氮肥较为一致[31],这一时间变化趋势与水体DO浓度变化也较为吻合.
四湖总干渠沉积物总氮含量为857.70~2846.87mg/kg,TP含量为545.99~2475.59mg/kg(表2),呈现明显的空间特征,从上游至下游总磷含量依次降低.总体上,四湖总干渠沉积物处于轻-中度污染状态,支渠污染重于干渠.
水温是影响水体DO浓度的重要因素,四湖总干渠水体DO与水温呈显著负相关关系(图5).水温会随着气温波动,自1971年以来荆州地区年平均气温由16.0℃显著升高至18.1℃,升温速率为每年0.0369℃(图5).4~10月四湖总干渠平均水温接近20℃(图6),有超过87.8%的DO监测值,低于60%饱和溶解度(图5).受气温升高影响,全球范围内普遍存在水体DO下降现象,据报道美国70%的河流存在缺氧状况,其中农业河流的变暖速度最慢,但溶解氧下降速率最快[8].在四湖总干渠DO随水温变化急剧下降(图5),其变化曲线斜率远高于水温对DO饱和度的影响,这表明除水温之外,水体DO还受到其他因素的影响.
四湖总干渠上游以灌溉为主兼顾防洪,而中下游则主要以防洪排涝为主,由此产生了地表水系循环与水动力的时空分布不匹配现象[32].每年4~10月因排水和灌溉需要,四湖流域内闸坝(泵站)运行,河道流量一般不低于30m3/s,在其他时期(11月至翌年3月)涵闸关闭,河道基本处于封闭状态,有些河渠甚至出现断流现象[33].以福田寺防洪闸为例,2022年全年闸上水位在25.22~27.27m之间波动,过闸流量为12.2~373m3/s,全年有130d处于关闭状态(图7).由于水闸长期处于关闭状态,水体连通性不足,水动力较弱,实测流速介于0.078~0.966m/s之间,污染物难以扩散交换,水体自然复氧能力减弱.
然而汛期水闸开放运行却加剧了水体缺氧,由图7(a)可知汛期四湖总干渠水体DO与过闸流量存在显著负相关关系(R2=0.2217,P<0.05).造成这一现象的原因可能是排涝站及涵闸运行使流域内大量污水汇入,非点源污染加重,水体中耗氧物质显著增加[34].汛期随着流量升高,水体CODMn呈线性增加趋势(图7),这表明流动的水体带来了更多的污染物.因此,汛期当过闸流量增加时,水体DO浓度反而降低,这一现象在其他研究中也有发现[35-36].
四湖总干渠水体DO随CODMn的增加呈显著降低趋势(图8),高锰酸盐指数的高低反映了水体有机污染物的水平,而水体有机物的降解过程中消耗了DO,因此这是DO降低的主要因素之一.四湖流域污水收集处理率相对较低,四湖流域年排放工业废水达4000多万t,排放生活污水8000多万t,农业生产施用的化肥、农药带来严重的面源污染[37].已有研究表明,残饵和代谢产物是养殖水体中有机质污染负荷的主要存在形式,是CODMn超标的主要原因[38].四湖总干渠水体DOM的吸光度比值E3/E4均小于3.5,E2/E3为1.58~2.06(图9),这表明水体DOM以胡敏酸为主,并且水体有机物主要来自于外源[39].
四湖总干渠水体DO浓度与NH3-N呈负相关关系,随着NH3-N浓度的升高,DO呈显著下降趋势,拟合曲线符合幂函数曲线(图8).氮的周转过程与DO的消耗高度耦合,是消耗水体DO的主要动力之一[40].在汛期,水体温度相对较高,微生物活性较强,硝化反应等对水体DO的消耗更为剧烈.而在非汛期,渠道内水量相对较少,水体对NH3-N等污染物的稀释作用较小,微生物活性减弱,因而水体DO随NH3-N浓度变化相对平缓.较低的DO浓度可直接抑制底泥-水体界面的硝化作用,减少NH3-N的消耗,厌氧菌分解有机物产生NH3-N,增加NH3-N的释放[30].运粮湖断面约78.2%的监测时段NH3-N浓度<1.00mg/L,这表明其对水体DO的消耗是有限的.
沉积物中溶解性有机质(DOM)的分解是影响水体DO浓度的主要因素之一[27],四湖总干渠沉积物LOI平均含量为5.49%~6.79%(表2),总体状况与太湖较为接近[41],参考太湖沉积物需氧量,四湖总干渠沉积物需氧量约为0.99μg/(cm2·h).
将水温、高锰酸盐指数、氨氮、总磷、总氮、浊度、电导率、流量等影响因素作为自变量,水体DO浓度作为因变量,分别构建广义相加模型、随机森林模型和多元线性回归模型,并以R2和RMSE为评价指标,比较了上述3种方法的预测效果.由图10可知,随机森林模型的拟合R2达到了0.995,显著高于其他模型,并且预测误差(RMSE)仅为0.2085,在所有模型中最小,因此可以采用随机森林模型分析四湖总干渠水体DO浓度的影响因素.
DO是水生生态系统健康状况的基本指标,已有研究表明pH值和温度是估算河流溶解氧的关键因素,而水位、温度、电导率和化学需氧量等对河流环境特征具有重要意义[42].进一步采用特征重要性排序,定量化评价了各因子对3个站点(运粮湖、新河村、新滩口)溶解氧的相对贡献(图11).相对重要性超过20%的指标有水温、pH值、氨氮、电导率、浊度、流量、总磷、总氮等.其中水温在3个断面的相对重要性分别为38.53%、46.71%和35.11%,这表明水温对四湖总干渠水体DO浓度有较大影响.水温除了通过影响水体DO饱和度之外,还会通过改变环境中微生物的活性,从而间接影响水中DO的消耗[43].Shi等[44]也发现,汛期微生物活性高,是水体溶解氧偏低的主要原因.
图11还可以看出除了水温之外,不同断面影响因素的相对重要性排序存在差异,在上游运粮湖断面pH值(36.1%)、氨氮(23.9%)等的相对重要性较高,而流量(18.93%)、高锰酸盐指数(17.89%)的相对重要性较低.在中游新河村断面氨氮(27.49%)、浊度(21.02%)的相对重要性较高,pH值(15.47%)、流量(14.71%)相对重要性较低.在下游新滩断面电导率(27.65%)、pH值(24.14%)和流量(23.73%)的相对重要性较高,高锰酸盐指数(15.41%)和总氮(14.39%)的相对重要性较低.这表明,在分析水体DO影响因素时,需要关注空间异质性的影响.
河流生态系统的新陈代谢参数显著受光照、水文条件、营养状况等的共同调控[45].由于营养物质的富集和温度的上升,许多闸控河流很容易出现富营养化和缺氧的情况[46].在四湖流域这一特定区域内,由于河流、湖泊与人工河渠的密集交织,水系结构复杂且边界模糊,加之区域产汇流过程受强烈人为活动干扰,限制了水体交换能力,削弱了水体的自净能力.此外,该区域缺乏自然集水区域,河湖岸线广泛被堤坝等水工建筑物包围,进一步加剧了自然水系的人工分割,使得水文参数(如流速、流量、水深)高度依赖于人工调控[47],为了维持一定水位需求,在非汛期闸坝关闭,污染物随水体一同滞留,而在汛期及排灌时段污染物则会随着水流迁移扩散.因此,水体DO浓度,随着流量升高呈降低趋势(图7),水动力的增加并没有如预期一样增加水体溶解氧浓度,这意味着水体好氧物质(CODMn等)是导致DO偏低的主要原因.
河流缺氧的发生是由河流内在属性(如河流比降)和流域环境特征(如土地利用)等决定的,它们相互作用以确定河道内的生化和物理条件[47]稻虾共作模式在四湖流域极为普遍.每年9~10月水稻收割后,稻田被改造为深水环境(40~50cm)以养殖小龙虾,并在次年春季(3~5月)进行饲料投喂[18].汛期作为水产快速生长期,饲料投加量显著增加,导致湖泊化学需氧量上升[49].稻虾共作农田成为氮磷的重要来源,其氮磷流失与相连河流的降水量、总氮和总磷浓度密切相关[50].相较于传统稻作模式,稻虾共作模式因水资源消耗量大及秸秆还田、饲料投入等因素,导致田面水中硝态氮、氨氮含量显著增加,加剧了水体富营养化的风险.
研究表明单独削减入污水排放量的措施对河流溶解氧的恢复十分有限[51].为了改善四湖总干渠水体DO汛期异常状况,需要加强流域系统治理,尤其是要加强对虾稻及水产养殖的尾水排放处理,拦截水面漂浮垃圾,减少污染物的输入通量,优化泵站闸坝的调度运行方式,尽量避免汛期污染物的集中排放.此外,对于四湖总干渠这种平原水网区域,闸坝拦截了氮磷等营养物质,增加了水体DO的消耗[36].在彻底阻断四湖总干渠污染源之前,通过增加过闸流量来改善水动力的方法,对水体DO浓度的改善可能收效甚微.
4.1 四湖总干渠水体DO浓度在时间上表现为非汛期较高,汛期较低的特征.在空间上,中上游DO浓度相对较低,而下游相对较高.
4.2 随机森林模型分析表明对水体DO浓度影响较大的环境因子为水温、pH值和氨氮.
  • 国家重点研发专项(2022YFC3201902)
  • 中央级公益性科研院所基本科研业务费专项(CKSF2024327/SH)
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2025年第45卷第5期
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  • 接收时间:2024-10-08
  • 首发时间:2026-03-18
  • 出版时间:2025-05-20
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  • 收稿日期:2024-10-08
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国家重点研发专项(2022YFC3201902)
中央级公益性科研院所基本科研业务费专项(CKSF2024327/SH)
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    1.长江科学院流域水环境研究所,湖北 武汉 430010
    2.长江科学院流域水资源与生态环境科学湖北省重点实验室,湖北 武汉 430010
    3.湖北省荆州市四湖工程管理局排灌试验站,湖北 荆州 434013

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2种不同金属材料的力学参数

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total species (%)

Genus
种数
Number of
species
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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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