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This study analysed the spatiotemporal characteristics of dissolved oxygen (DO) concentrations upstream and downstream of sluices during dry and wet years, using data from three automated water quality monitoring stations and field measurements along the Huangjiang River in Guangdong Province. Multiple statistical methods were employed to identify the relative contributions of key influencing factors to DO variability across years under different precipitation conditions. Upstream DO concentrations were generally higher in dry years ((8.02±0.10) mg/L) than in wet years ((7.26±0.08) mg/L). In contrast, DO levels in the downstream tidal section increased from (4.45±0.10) mg/L (dry year) to (7.33±0.09) mg/L (wet year), primarily due to improved water quality. Periodic fluctuations were observed in both years, with higher DO levels during the flood season and lower levels during the non-flood season throughout the river channel. Influenced by the gate control and different external inputs, DO fluctuations upstream and downstream were driven by different factors. Rainfall and water temperature explained 44% to 87% of the DO variability upstream. While ammonia nitrogen, and CODMn were the most influential factors downstream, accounting for 53% to 75% of the variability. Furthermore, the “lacustrine” upstream section was especially sensitive to climate variations. In this area, the loss of phytoplankton biomass caused by stormwater runoff was a major factor contributing to DO difference during dry and wet years. While DO downstream is more easily influenced by water pollutants, especially the significant decrease in oxygen-demanding substances.
, correspAuthors=Ju HUANG, Zhen WANG, 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=Xiao-yue JIN, Ju HUANG, Zhong-ya FAN, Lu HUANG, Qian-li LUO, Zhen WANG), CN=ArticleExt(id=1234106397395316967, articleId=1234106386687259396, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=闸控入海河流DO时空分布特征及其驱动因素, columnId=1234106388268503686, journalTitle=中国环境科学, columnName=环境生态, runingTitle=null, highlight=null, articleAbstract=
本文以广东省黄江河为研究对象,基于沿程3个水质自动监测站数据,分析枯水年(2021年)、丰水年(2023年)黄江河挡潮闸闸上与闸下河段DO的时空分布特征,并采用统计学方法,研究了DO变化的驱动因素及相对贡献.结果表明:闸上河段因水环境相对稳定,西闸断面DO呈现枯水年((8.02±0.10) mg/L)>丰水年((7.26±0.08) mg/L)特征;而闸下河段因水质改善,DO呈现枯水年((4.45±0.10) mg/L)<丰水年((7.33±0.09) mg/L)特征;枯、丰水年年内全河段DO均呈现汛期高、非汛期低的周期性变化规律.受闸坝作用及外源输入差异影响,闸上河段DO变化的主要驱动因素为降雨和水温,贡献度达到44%~87%;闸下河段DO变化的主要驱动因素则是氨氮和高锰酸盐指数,贡献度达到53%~75%.闸上“湖泊化”缓流河段DO更易受气候变化影响,尤其是暴雨径流引起的浮游植物流失是导致枯、丰水年DO差异的直接原因.而枯水年闸下感潮河段DO受外源污染输入及滞留影响显著,丰水年闸下河段耗氧物质的减少是DO提升的重要原因.
, correspAuthors=黄菊, 王振, authorNote=null, correspAuthorsNote=
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, authorsList=金晓玥, 黄菊, 范中亚, 黄露, 罗千里, 王振)}, authors=[Author(id=1234153437676499379, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=22xyjin@stu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1234153437777162678, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153437676499379, language=EN, stringName=Xiao-yue JIN, firstName=Xiao-yue, middleName=null, lastName=JIN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
1, 2, address=
1.Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention, Shantou University, Shantou 515063, China
2.Guangdong Key Laboratory of Water and Air Pollution Control, National Key Laboratory of Water Environment Simulation and Pollution Control, South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou 510535, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1234153439220003255, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153437676499379, language=CN, stringName=金晓玥, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
1, 2, address=
1.汕头大学,省市共建海洋灾害预警与防护广东省重点实验室,广东 汕头 515063
2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535, bio={"content":"
金晓玥(1999-),女,山东淄博人,汕头大学硕士研究生,从事流域水生态环境治理研究.22xyjin@stu.edu.cn.
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金晓玥(1999-),女,山东淄博人,汕头大学硕士研究生,从事流域水生态环境治理研究.22xyjin@stu.edu.cn.
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1.汕头大学,省市共建海洋灾害预警与防护广东省重点实验室,广东 汕头 515063)]), AuthorCompany(id=1234153437571641775, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, xref=2., ext=[AuthorCompanyExt(id=1234153437584224688, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535)])]), Author(id=1234153439278723513, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=huangju@scies.org, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1234153439345832379, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153439278723513, language=EN, stringName=Ju HUANG, firstName=Ju, middleName=null, lastName=HUANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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2.Guangdong Key Laboratory of Water and Air Pollution Control, National Key Laboratory of Water Environment Simulation and Pollution Control, South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou 510535, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1234153439425524156, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153439278723513, language=CN, stringName=黄菊, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1234153437571641775, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, xref=2., ext=[AuthorCompanyExt(id=1234153437584224688, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
2.Guangdong Key Laboratory of Water and Air Pollution Control, National Key Laboratory of Water Environment Simulation and Pollution Control, South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou 510535, China), AuthorCompanyExt(id=1234153437592613297, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535)])]), Author(id=1234153439496827326, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1234153439618462144, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153439496827326, language=EN, stringName=Zhong-ya FAN, firstName=Zhong-ya, middleName=null, lastName=FAN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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2.Guangdong Key Laboratory of Water and Air Pollution Control, National Key Laboratory of Water Environment Simulation and Pollution Control, South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou 510535, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1234153439685571009, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153439496827326, language=CN, stringName=范中亚, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
2, address=
2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1234153437571641775, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, xref=2., ext=[AuthorCompanyExt(id=1234153437584224688, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535)])]), Author(id=1234153439761068483, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1234153439882703301, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153439761068483, language=EN, stringName=Lu HUANG, firstName=Lu, middleName=null, lastName=HUANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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2, address=
2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1234153437571641775, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, xref=2., ext=[AuthorCompanyExt(id=1234153437584224688, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535)])]), Author(id=1234153440037892552, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1234153440121778634, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153440037892552, language=EN, stringName=Qian-li LUO, firstName=Qian-li, middleName=null, lastName=LUO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
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2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1234153437571641775, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, xref=2., ext=[AuthorCompanyExt(id=1234153437584224688, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
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2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535)])]), Author(id=1234153440344076749, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, orderNo=5, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zhenwang@stu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1234153440444740047, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, authorId=1234153440344076749, language=EN, stringName=Zhen WANG, firstName=Zhen, middleName=null, lastName=WANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
1, **, address=
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1.Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention, Shantou University, Shantou 515063, China), AuthorCompanyExt(id=1234153437470978478, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437454201260, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
1.汕头大学,省市共建海洋灾害预警与防护广东省重点实验室,广东 汕头 515063)]), AuthorCompany(id=1234153437571641775, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, xref=2., ext=[AuthorCompanyExt(id=1234153437584224688, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
2.Guangdong Key Laboratory of Water and Air Pollution Control, National Key Laboratory of Water Environment Simulation and Pollution Control, South China Institute of Environmental Science, Ministry of Ecology and Environment, Guangzhou 510535, China), AuthorCompanyExt(id=1234153437592613297, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, companyId=1234153437571641775, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=
2.生态环境部华南环境科学研究所,广东省水与大气污染防治重点实验室,国家水环境模拟与污染控制重点实验室,广东 广州 510535)])], figs=[ArticleFig(id=1234153441682059739, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Fig.1, caption=
Maps of study area and the sampling sites, figureFileSmall=ouYYOkdXp7b14787LC1wBQ==, figureFileBig=jRj/bHZUCAkkE2ITKM8qXg==, tableContent=null), ArticleFig(id=1234153441765945820, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=图1, caption=
研究区域及采样点位Z1,Z2,Z3分别代表中游站,西闸站,西闸下游站
, figureFileSmall=ouYYOkdXp7b14787LC1wBQ==, figureFileBig=jRj/bHZUCAkkE2ITKM8qXg==, tableContent=null), ArticleFig(id=1234153441887580637, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Fig.2, caption=
Average of dissolved oxygen in the dry-wet year and stage, figureFileSmall=I44ImXpRn9/RFOjLWlGZFA==, figureFileBig=/E1HMgjfi5lMt8QjlaHPMA==, tableContent=null), ArticleFig(id=1234153441958883806, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=图2, caption=
各站点DO枯、丰水年均值变化与汛期-非汛期变化柱状图上字母标记表示组内及组间显著性差异,相同字母表示无显著性差异,不同字母表示存在显著性差异
, figureFileSmall=I44ImXpRn9/RFOjLWlGZFA==, figureFileBig=/E1HMgjfi5lMt8QjlaHPMA==, tableContent=null), ArticleFig(id=1234153442025992671, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Fig.3, caption=
Average of environmental parameters in the dry and wet years, figureFileSmall=Z5Uwn64TWudRk3bKD+jMvg==, figureFileBig=xbbw/LHNeZpdaXo009HdfA==, tableContent=null), ArticleFig(id=1234153442088907232, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=图3, caption=
各站点各环境要素枯、丰水年均值变化柱状图上字母标记表示组内及组间显著性差异,相同字母表示无显著性差异,不同字母表示存在显著性差异
, figureFileSmall=Z5Uwn64TWudRk3bKD+jMvg==, figureFileBig=xbbw/LHNeZpdaXo009HdfA==, tableContent=null), ArticleFig(id=1234153442181181921, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Fig.4, caption=
Correlation coefficient between DO and environmental parameters, figureFileSmall=Tiq8mtfy+x6ce04dk8JFlw==, figureFileBig=NsAZ0HzvncGEMrjlpVwqGA==, tableContent=null), ArticleFig(id=1234153442269262306, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=图4, caption=
DO与各要素之间的相关性系数, figureFileSmall=Tiq8mtfy+x6ce04dk8JFlw==, figureFileBig=NsAZ0HzvncGEMrjlpVwqGA==, tableContent=null), ArticleFig(id=1234153443657576931, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Table 1, caption=
Average of DO and environmental parameters in wet and dry years
, figureFileSmall=null, figureFileBig=null, tableContent=
| 站点 | 年份 | DO(mg/L) | 总氮(mg/L) | 氨氮(mg/L) | 总磷(mg/L) | CODMn(mg/L) | 水温(℃) | pH值 | 电导率(µS/cm) | 浊度(NTU) | 降雨(mm) | 降雨天数(d) | 降雨天数(>10mm)(d) |
|---|
| 黄江中游 | 2021 | 7.41 | 0.35 | 0.06 | 0.04 | 4.50 | 26.33 | 7.23 | 462.58 | 17.05 | 1751.44 | 132 | 58 |
| 2023 | 6.36 | 1.24 | 0.19 | 0.09 | 3.93 | 26.06 | 7.40 | 573.26 | 35.60 | 3003.62 | 120 | 71 |
| 黄江西闸 | 2021 | 8.02 | 0.92 | 0.03 | 0.04 | 4.26 | 26.21 | 7.98 | 940.62 | 18.59 | 1751.44 | 132 | 58 |
| 2023 | 7.26 | 1.07 | 0.09 | 0.03 | 3.04 | 25.60 | 7.37 | 490.83 | 25.40 | 3003.62 | 120 | 71 |
| 黄江西闸 | 2021 | 4.45 | 2.85 | 0.97 | 0.17 | 6.00 | 26.05 | 7.69 | 22673.12 | 14.17 | 1751.44 | 132 | 58 |
| 下游 | 2023 | 7.33 | 3.62 | 0.26 | 0.03 | 4.15 | 26.51 | 7.74 | 14523.44 | 25.04 | 3003.62 | 120 | 71 |
), ArticleFig(id=1234153443733074404, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=表1, caption=
丰枯水年DO与其他因素均值
, figureFileSmall=null, figureFileBig=null, tableContent=
| 站点 | 年份 | DO(mg/L) | 总氮(mg/L) | 氨氮(mg/L) | 总磷(mg/L) | CODMn(mg/L) | 水温(℃) | pH值 | 电导率(µS/cm) | 浊度(NTU) | 降雨(mm) | 降雨天数(d) | 降雨天数(>10mm)(d) |
|---|
| 黄江中游 | 2021 | 7.41 | 0.35 | 0.06 | 0.04 | 4.50 | 26.33 | 7.23 | 462.58 | 17.05 | 1751.44 | 132 | 58 |
| 2023 | 6.36 | 1.24 | 0.19 | 0.09 | 3.93 | 26.06 | 7.40 | 573.26 | 35.60 | 3003.62 | 120 | 71 |
| 黄江西闸 | 2021 | 8.02 | 0.92 | 0.03 | 0.04 | 4.26 | 26.21 | 7.98 | 940.62 | 18.59 | 1751.44 | 132 | 58 |
| 2023 | 7.26 | 1.07 | 0.09 | 0.03 | 3.04 | 25.60 | 7.37 | 490.83 | 25.40 | 3003.62 | 120 | 71 |
| 黄江西闸 | 2021 | 4.45 | 2.85 | 0.97 | 0.17 | 6.00 | 26.05 | 7.69 | 22673.12 | 14.17 | 1751.44 | 132 | 58 |
| 下游 | 2023 | 7.33 | 3.62 | 0.26 | 0.03 | 4.15 | 26.51 | 7.74 | 14523.44 | 25.04 | 3003.62 | 120 | 71 |
), ArticleFig(id=1234153443825349093, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Table 2, caption=
Multiple Linear Regression for each site in wet and dry years
, figureFileSmall=null, figureFileBig=null, tableContent=
| 参数 | 黄江中游枯水年 | 黄江中游丰水年 | 黄江西闸枯水年 | 黄江西闸丰水年 | 黄江西闸下游枯水年 | 黄江西闸下游丰水年 |
|---|
| 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P |
|---|
| 降雨 | 42.73 | <0.001 | 3.14 | 0.032 | 34.44 | <0.001 | 31.08 | <0.001 | 6.49 | 0.001 | 2.30 | 0.014 |
| 氨氮 | 2.28 | <0.001 | 4.29 | 0.012 | 12.74 | <0.001 | 23.52 | <0.001 | 27.10 | <0.001 | 4.13 | 0.001 |
| 总磷 | 0.28 | <0.001 | 18.34 | <0.001 | 4.23 | <0.001 | 2.20 | <0.001 | 2.84 | 0.022 | 0.14 | 0.542 |
| 水温 | 43.14 | <0.001 | 48.21 | <0.001 | 25.23 | <0.001 | 13.29 | <0.001 | 37.54 | <0.001 | 8.44 | <0.001 |
| pH值 | 10.84 | <0.001 | 12.98 | <0.001 | 21.03 | <0.001 | 19.06 | <0.001 | 0.23 | 0.509 | 6.31 | <0.001 |
| CODMn | 0.18 | 0.004 | 1.73 | 0.111 | 0.26 | 0.035 | 0.18 | 0.022 | 23.15 | <0.001 | 52.03 | <0.001 |
| 总氮 | 0.07 | 0.080 | 7.19 | 0.001 | 0.002 | 0.857 | 0.41 | 0.001 | 0.0003 | 0.981 | 18.58 | <0.001 |
| 电导率 | 0.22 | 0.001 | 2.41 | 0.060 | 0.15 | 0.105 | 10.12 | <0.001 | 2.73 | 0.025 | 0.75 | 0.158 |
| 浊度 | 0.26 | 0.001 | 1.72 | 0.111 | 1.91 | <0.001 | 0.15 | 0.037 | 0.003 | 0.932 | 7.32 | <0.001 |
), ArticleFig(id=1234153443909235174, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=表2, caption=
各站点丰枯水年多元线性回归模型
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| 参数 | 黄江中游枯水年 | 黄江中游丰水年 | 黄江西闸枯水年 | 黄江西闸丰水年 | 黄江西闸下游枯水年 | 黄江西闸下游丰水年 |
|---|
| 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P | 贡献度(%) | P |
|---|
| 降雨 | 42.73 | <0.001 | 3.14 | 0.032 | 34.44 | <0.001 | 31.08 | <0.001 | 6.49 | 0.001 | 2.30 | 0.014 |
| 氨氮 | 2.28 | <0.001 | 4.29 | 0.012 | 12.74 | <0.001 | 23.52 | <0.001 | 27.10 | <0.001 | 4.13 | 0.001 |
| 总磷 | 0.28 | <0.001 | 18.34 | <0.001 | 4.23 | <0.001 | 2.20 | <0.001 | 2.84 | 0.022 | 0.14 | 0.542 |
| 水温 | 43.14 | <0.001 | 48.21 | <0.001 | 25.23 | <0.001 | 13.29 | <0.001 | 37.54 | <0.001 | 8.44 | <0.001 |
| pH值 | 10.84 | <0.001 | 12.98 | <0.001 | 21.03 | <0.001 | 19.06 | <0.001 | 0.23 | 0.509 | 6.31 | <0.001 |
| CODMn | 0.18 | 0.004 | 1.73 | 0.111 | 0.26 | 0.035 | 0.18 | 0.022 | 23.15 | <0.001 | 52.03 | <0.001 |
| 总氮 | 0.07 | 0.080 | 7.19 | 0.001 | 0.002 | 0.857 | 0.41 | 0.001 | 0.0003 | 0.981 | 18.58 | <0.001 |
| 电导率 | 0.22 | 0.001 | 2.41 | 0.060 | 0.15 | 0.105 | 10.12 | <0.001 | 2.73 | 0.025 | 0.75 | 0.158 |
| 浊度 | 0.26 | 0.001 | 1.72 | 0.111 | 1.91 | <0.001 | 0.15 | 0.037 | 0.003 | 0.932 | 7.32 | <0.001 |
), ArticleFig(id=1234153443993121255, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=EN, label=Table 3, caption=
DO under different rainfall at the Huangjiang West Sluice station in wet and dry years
, figureFileSmall=null, figureFileBig=null, tableContent=
| 项目 | 晴天 | 小雨 | 中雨 | 大雨 | 暴雨 | 大暴雨 |
|---|
| 枯水年天数(d) | 157 | 74 | 42 | 11 | 4 | 1 |
| 期间西闸断面DO(mg/L) | 9.07 | 7.03 | 6.35 | 6.22 | 6.16 | 5.06 |
| 丰水年天数(d) | 175 | 49 | 37 | 20 | 9 | 5 |
| 期间西闸断面DO(mg/L) | 7.93 | 7.01 | 5.81 | 5.61 | 5.44 | 5.09 |
| 枯丰水年西闸断面平均DO(mg/L) | 8.47 | 7.02 | 6.10 | 5.91 | 5.80 | 5.10 |
| 枯丰水年西闸断面平均浊度(NTU) | 17.74 | 19.62 | 27.50 | 27.77 | 31.31 | 33.57 |
), ArticleFig(id=1234153444064424424, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1234106386687259396, language=CN, label=表3, caption=
枯丰水年黄江西闸站不同降雨程度下DO浓度
, figureFileSmall=null, figureFileBig=null, tableContent=
| 项目 | 晴天 | 小雨 | 中雨 | 大雨 | 暴雨 | 大暴雨 |
|---|
| 枯水年天数(d) | 157 | 74 | 42 | 11 | 4 | 1 |
| 期间西闸断面DO(mg/L) | 9.07 | 7.03 | 6.35 | 6.22 | 6.16 | 5.06 |
| 丰水年天数(d) | 175 | 49 | 37 | 20 | 9 | 5 |
| 期间西闸断面DO(mg/L) | 7.93 | 7.01 | 5.81 | 5.61 | 5.44 | 5.09 |
| 枯丰水年西闸断面平均DO(mg/L) | 8.47 | 7.02 | 6.10 | 5.91 | 5.80 | 5.10 |
| 枯丰水年西闸断面平均浊度(NTU) | 17.74 | 19.62 | 27.50 | 27.77 | 31.31 | 33.57 |
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