Article(id=1200028549127173091, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1200028546686091752, articleNumber=null, orderNo=null, doi=10.12284/hyxb2024013, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1700323200000, receivedDateStr=2023-11-19, revisedDate=1706544000000, revisedDateStr=2024-01-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1764038701564, onlineDateStr=2025-11-25, pubDate=1709136000000, pubDateStr=2024-02-29, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1764038701564, onlineIssueDateStr=2025-11-25, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1764038701564, creator=13701087609, updateTime=1764038701564, updator=13701087609, issue=Issue{id=1200028546686091752, tenantId=1146029695717560320, journalId=1149651085930835976, year='2024', volume='46', issue='2', pageStart='1', pageEnd='130', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=0, articleOrder=1, issueType=-1, specialIssue=null, createTime=1764038700981, creator=13701087609, updateTime=1764060312216, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1200119190821634491, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1200028546686091752, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1200119190821634492, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1200028546686091752, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=93, endPage=106, ext={EN=ArticleExt(id=1200028549387219943, articleId=1200028549127173091, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Numerical simulation of the influence of biofilm on the dynamic geomorphological evolution of tidal flats, columnId=null, journalTitle=Haiyang Xuebao, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Tidal flats maintain a complex ecosystem, while its formation is driven by multi-factor interaction, including hydrodynamics, sediment transport, and biological processes. In particular, investigating tidal flat biological processes and elucidating their biological-physical effects are current research hotspots and challenges in the field of marine science. This study focused on intertidal biofilms, constructed a two-dimensional biomorphodynamic model which coupled biofilms with hydrodynamics, sediment transport, and bed level change, to explore the role of biofilms in sediment transport and geomorphological evolution. The biomorphodynamic model was validated using literature data, indicating that the constructed model can simulate the growth pattern and interannual variation of biofilms well. Model results show that tidal creeks with biofilm attachment are more fully extended towards the landward side, showing a branching distribution when hydrodynamics are weak, and biofilms were distributed on both sides of the intertidal zone. Through quantitative analysis of tidal creek morphology, it is found that the presence of biofilms promoted an increase in the number of tidal creek and their development in the vertical direction, while limiting the increase in their width. Compared to tidal flats without the influence of biofilms, the average depth of tidal creeks increases, the total area decreases, the total length increases, the average width decreases, and the overall volume increases. The research outcome of this study deepens the understanding of the role of biofilms on tidal flat evolution and provides a scientific basis for coastal zone protection and ecological restoration projects.

, correspAuthors=Zeng Zhou, authorNote=null, correspAuthorsNote=null, copyrightStatement=Haiyang Xuebao, 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=Mengjiao Liang, Yi Zhou, Heyue Zhang, Huan Li, Yanyan Kang, Dawei Wang, Zeng Zhou), CN=ArticleExt(id=1200028553103372327, articleId=1200028549127173091, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=生物膜对潮滩动力地貌演变影响的数值模拟研究, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

河口海岸潮滩湿地是一个复杂的生态系统,其地貌的形成和演变是水动力、泥沙输移和生物过程等多种因子相互作用的结果,特别是,探究潮滩生物过程并阐明其生物−物理效应是当前海洋科学领域研究的热点和难点。本文聚焦微生物生物膜,构建了耦合生物膜与水动力、沉积物输移、地貌演变的二维生物动力地貌模型,探究了生物膜在潮滩泥沙输移和地貌演变中发挥的作用。利用文献数据验证生物动力地貌模型,模型结果与文献数据吻合较好,表明所构建的模型可以较好地模拟出生物膜的增长规律及年际变化情况。结果表明,当水动力较弱时,在有生物膜作用的潮滩上,潮沟向陆侧延伸更充分,呈现出树杈状分布,潮间带区域的潮沟两侧分布有生物膜。通过对潮沟形态进行定量分析,发现生物膜的存在促进了潮沟数量增加,并向纵深方向发展,同时限制了其宽度的增加。相较于没有生物膜影响的潮滩,潮沟的平均深度增加,总面积减小,总长度增加,平均宽度减小,总体积增加。研究结果有助于加深对生物膜在潮滩地貌塑造中的作用机制认识,为海岸带保护与生态修复工程提供科学依据。

, correspAuthors=周曾, authorNote=null, correspAuthorsNote=
*周曾(1986—),男,江苏省句容市人,教授,主要从事河口海岸地貌学研究。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2024, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=wgyul8kHuVB3ziNwb4+A9w==, magXml=vTtJJlw7gieqP0/u0r1rzg==, pdfUrl=null, pdf=X4n9UzpFxHWmvoSgF1Njgw==, pdfFileSize=2274314, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=w4222rlggLz2+QzsTKEgIw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=HQE6C0+LiliCrgoEu3VvMw==, mapNumber=null, authorCompany=null, fund=null, authors=

梁梦娇(1997—),女,山东省菏泽市人,主要从事河口海岸水动力泥沙模拟研究。E-mail:

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梁梦娇(1997—),女,山东省菏泽市人,主要从事河口海岸水动力泥沙模拟研究。E-mail:

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different temperatures (b); different attenuation effects of water depth on light intensity (c), figureFileSmall=lU1D7lneG6aqzbJKTRgfPA==, figureFileBig=DjetT8Ce+/CobHAWoiMlBw==, tableContent=null), ArticleFig(id=1200138012710498567, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图3, caption=生物量年际变化不同泥沙组分(a);不同温度(b);水深对光照强度的不同衰减作用(c), figureFileSmall=lU1D7lneG6aqzbJKTRgfPA==, figureFileBig=DjetT8Ce+/CobHAWoiMlBw==, tableContent=null), ArticleFig(id=1200138012794384652, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Fig. 4, caption=Initial landform (a) and Initial profile (b), figureFileSmall=g4lTgHK5aOZ9WlpIUr1g5A==, figureFileBig=RjEDD2lLfkr4PtnoDNPsaQ==, tableContent=null), ArticleFig(id=1200138012869882128, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图4, caption=初始地形图(a)和初始剖面图(b), figureFileSmall=g4lTgHK5aOZ9WlpIUr1g5A==, figureFileBig=RjEDD2lLfkr4PtnoDNPsaQ==, tableContent=null), ArticleFig(id=1200138012978934039, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Fig. 5, caption=The tidal flats landforms (a–c) and biomass distribution (d–f) on tidal flats after 1 year, 3 years and 10 years under wave flow, respectively, figureFileSmall=4Z77d8Y1Yo3lHXdpMMIabQ==, figureFileBig=OSzXjTX+gSYj0pKDLTs7PA==, tableContent=null), ArticleFig(id=1200138013075403034, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图5, caption=波流作用下1年、3年和10年后潮滩地貌(a–c)和潮滩上生物量分布(d–f), figureFileSmall=4Z77d8Y1Yo3lHXdpMMIabQ==, figureFileBig=OSzXjTX+gSYj0pKDLTs7PA==, tableContent=null), ArticleFig(id=1200138013188649247, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Fig. 6, caption=The evolution process of tidal flat landform in the presence of biofilm (a–c) and the evolution process of tidal flat without biofilm (d–f), figureFileSmall=4uBYPSywAoREu0OiwKSFAg==, figureFileBig=6qOtW7pC/FW7GrGt0k2Nuw==, tableContent=null), ArticleFig(id=1200138013285118242, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图6, caption=生物膜存在时的潮滩地貌演变过程(a–c)和无生物膜存在时的潮滩演变过程(d–f), figureFileSmall=4uBYPSywAoREu0OiwKSFAg==, figureFileBig=6qOtW7pC/FW7GrGt0k2Nuw==, tableContent=null), ArticleFig(id=1200138013389975846, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Fig. 7, caption=The elevation change of the section perpendicular to the shoreline x = 5 km (a) and the elevation change of y = 10 km parallel to the shoreline section (b), figureFileSmall=4EikMD9quzk7Tw1r0LYjig==, figureFileBig=umSrrO1G32HCnxBmhuX5yQ==, tableContent=null), ArticleFig(id=1200138013503222059, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图7, caption=垂直于岸线断面x = 5 km高程变化情况(a)和平行于岸线断面y = 10 km高程变化情况(b), figureFileSmall=4EikMD9quzk7Tw1r0LYjig==, figureFileBig=umSrrO1G32HCnxBmhuX5yQ==, tableContent=null), ArticleFig(id=1200138013587108142, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Fig. 8, caption=Elevation changes of parallel shoreline section after 10 years for biofilm and non-biofilm tidal flat, figureFileSmall=JA2L8bNI98EAJVDcdcyZyQ==, figureFileBig=P/q3htNCBfnCz5wpF+hdxQ==, tableContent=null), ArticleFig(id=1200138013691965746, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图8, caption=生物膜潮滩和无生物膜潮滩10年后平行于岸线断面高程变化, figureFileSmall=JA2L8bNI98EAJVDcdcyZyQ==, figureFileBig=P/q3htNCBfnCz5wpF+hdxQ==, tableContent=null), ArticleFig(id=1200138013851349299, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Fig. 9, caption=Statistics of morphological parameters of tidal gully development with or without biofilm under the wave, figureFileSmall=Q4gN66gH3sgv7CSeaPThMA==, figureFileBig=ZXsSg5R7fGLJWJxveu7Akw==, tableContent=null), ArticleFig(id=1200138014040092984, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=图9, caption=波流作用下有无生物膜作用时潮沟发育的形态参数统计, figureFileSmall=Q4gN66gH3sgv7CSeaPThMA==, figureFileBig=ZXsSg5R7fGLJWJxveu7Akw==, tableContent=null), ArticleFig(id=1200138014182699323, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Table 1, caption=

Parameter setting and value

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 单位 取值范围 默认取值 含义 取值依据
μmax d–1 0.007 8~1.11 1.07 参考温度下的最大生长速率 Uehlinger等[34]
Labiod等[35]
Ks(以Chl a计) (mg/m2)–1 0.016 2~0.508 0.02 半饱和常数 Uehlinger等[34]
Labiod等[35]
I μE/(m2·s–1) 每日平均光强 Mariotti和Fagherazzi[29]
KI μE/(m2·s–1) 0.1~50 25 半饱和光系数 Boulêtreau等[36]
Io μE/(m2·s–1) 0~2 000 300 水面上的每日平均光强 Uehlinger等[34]
kd m–1 0.1~3 1.5 光强随水深的衰减系数 Lawson等[37]
β °C–1 –0.205~0.022 4 0.01 温度对生物膜发育的影响系数 Uehlinger等[34]
To °C 20 参考温度 Uehlinger等[34]
Tmax °C 33 最高温度 江苏盐城
Tmin °C –1 最低温度 江苏盐城
ε d–1 ~(0.001~0.1)u* 0.2 整体衰减系数 Uehlinger等[34]
Labiod等[35]
Xb(以Chl a计) mg/m2 4.4 × 10−5~1.68 1 最小生物量 Mariotti和Fagherazzi[29]
α(以Chl a计) Pa/(mg·m−2) 0.001~0.02 0.001 随生物膜生长τcr的增长系数 Le Hir等[33]
τcr,o Pa 0.05~1 0.2 无生物膜的泥沙临界起动切应力 Whitehouse等[38]
MC 0~1 0.5 某一泥沙组分下生物量变化的系数 Riechmüller等[32]
mct 0~1 0.5 底床中值粒径小于63 μm泥沙的总含量 Riechmülle等[32]
Dmin m 0~0.1 0.01 生物膜生存的平均高潮下的最小深度 Mariotti和Fagherazzi[39]
D m 河床高度与高潮位的差 根据模型设置计算取值
), ArticleFig(id=1200138014279168321, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=表1, caption=

参数设置及取值

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 单位 取值范围 默认取值 含义 取值依据
μmax d–1 0.007 8~1.11 1.07 参考温度下的最大生长速率 Uehlinger等[34]
Labiod等[35]
Ks(以Chl a计) (mg/m2)–1 0.016 2~0.508 0.02 半饱和常数 Uehlinger等[34]
Labiod等[35]
I μE/(m2·s–1) 每日平均光强 Mariotti和Fagherazzi[29]
KI μE/(m2·s–1) 0.1~50 25 半饱和光系数 Boulêtreau等[36]
Io μE/(m2·s–1) 0~2 000 300 水面上的每日平均光强 Uehlinger等[34]
kd m–1 0.1~3 1.5 光强随水深的衰减系数 Lawson等[37]
β °C–1 –0.205~0.022 4 0.01 温度对生物膜发育的影响系数 Uehlinger等[34]
To °C 20 参考温度 Uehlinger等[34]
Tmax °C 33 最高温度 江苏盐城
Tmin °C –1 最低温度 江苏盐城
ε d–1 ~(0.001~0.1)u* 0.2 整体衰减系数 Uehlinger等[34]
Labiod等[35]
Xb(以Chl a计) mg/m2 4.4 × 10−5~1.68 1 最小生物量 Mariotti和Fagherazzi[29]
α(以Chl a计) Pa/(mg·m−2) 0.001~0.02 0.001 随生物膜生长τcr的增长系数 Le Hir等[33]
τcr,o Pa 0.05~1 0.2 无生物膜的泥沙临界起动切应力 Whitehouse等[38]
MC 0~1 0.5 某一泥沙组分下生物量变化的系数 Riechmüller等[32]
mct 0~1 0.5 底床中值粒径小于63 μm泥沙的总含量 Riechmülle等[32]
Dmin m 0~0.1 0.01 生物膜生存的平均高潮下的最小深度 Mariotti和Fagherazzi[39]
D m 河床高度与高潮位的差 根据模型设置计算取值
), ArticleFig(id=1200138014430163268, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Table 2, caption=

Summary of model parameter settings

, figureFileSmall=null, figureFileBig=null, tableContent=
参数项 设置值
时间步长 0.3 min
谢才系数 65 m1/2/s
水平涡黏系数 1 m2/s
水平涡流扩散系数 10 m2/s
潮流边界条件 M2,S2
 粉砂 干容重 1 600 kg/m3
中值粒径 50 μm
底床厚度 5 m
 黏土 沉速 0.5 mm/s
临界起动切应力 0.2 N/m2
临界沉降切应力 1 000 N/m2
冲刷系数 5 × 10-4 kg/(m2·s)
底床厚度 10 m
), ArticleFig(id=1200138014551798086, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=表2, caption=

模型参数设置汇总表

, figureFileSmall=null, figureFileBig=null, tableContent=
参数项 设置值
时间步长 0.3 min
谢才系数 65 m1/2/s
水平涡黏系数 1 m2/s
水平涡流扩散系数 10 m2/s
潮流边界条件 M2,S2
 粉砂 干容重 1 600 kg/m3
中值粒径 50 μm
底床厚度 5 m
 黏土 沉速 0.5 mm/s
临界起动切应力 0.2 N/m2
临界沉降切应力 1 000 N/m2
冲刷系数 5 × 10-4 kg/(m2·s)
底床厚度 10 m
), ArticleFig(id=1200138014639878474, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Table 3, caption=

Hydrodynamic condition setting

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 单位 取值 含义
μmax d−1 0.9 参考温度下的最大生长速率
Ks(以Chl a计) (mg/m2)−1 0.02 半饱和常数
KI μE/(m2·s−1) 25 半饱和光系数
Io μE/(m2·s−1) 300 水面上的每日平均光强
kd m−1 1.5 光强随水深的衰减系数
β °C−1 0.022 4 温度对生物膜发育的影响系数
ε d−1 0.2 整体衰减系数
Xb(以Chl a计) mg/m2 1 最小生物量
α(以Chl a计) Pa/(mg·m−2) 0.001 6 随生物膜生长τcr的增长系数
To °C 20 参考温度
Tmax °C 33 最高温度
Tmin °C −1 最低温度
), ArticleFig(id=1200138014757318989, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=表3, caption=

水动力条件工况设置

, figureFileSmall=null, figureFileBig=null, tableContent=
变量 单位 取值 含义
μmax d−1 0.9 参考温度下的最大生长速率
Ks(以Chl a计) (mg/m2)−1 0.02 半饱和常数
KI μE/(m2·s−1) 25 半饱和光系数
Io μE/(m2·s−1) 300 水面上的每日平均光强
kd m−1 1.5 光强随水深的衰减系数
β °C−1 0.022 4 温度对生物膜发育的影响系数
ε d−1 0.2 整体衰减系数
Xb(以Chl a计) mg/m2 1 最小生物量
α(以Chl a计) Pa/(mg·m−2) 0.001 6 随生物膜生长τcr的增长系数
To °C 20 参考温度
Tmax °C 33 最高温度
Tmin °C −1 最低温度
), ArticleFig(id=1200138014891536719, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=EN, label=Table 4, caption=

Morphological parameters of tidal channel in the 10th year

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形态参数 无生物膜−潮沟 生物膜−潮沟 同比相差
潮间带下部 潮间带中部 潮滩 潮间带下部 潮间带中部 潮滩 潮间带下部 潮间带中部 潮滩
总体积/(106 m3 0.32 2.66 4.57 0.46 3.50 5.58 45.2% 31.6% 22.1%
总面积/(106 m2 0.27 2.44 4.12 0.32 2.22 3.83 19.8% −9.0% −7.0%
平均深度/m 1.19 1.09 1.11 1.44 1.57 1.46 21.2% 44.6% 31.5%
总长度/104 m 0.21 4.13 5.30 0.24 4.18 5.42 13.5% 1.1% 2.3%
平均宽度/m 127.45 59.20 77.87 134.53 53.26 70.70 5.6% −10.0% −9.2%
), ArticleFig(id=1200138015025754449, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1200028549127173091, language=CN, label=表4, caption=

第10年潮沟形态参数

, figureFileSmall=null, figureFileBig=null, tableContent=
形态参数 无生物膜−潮沟 生物膜−潮沟 同比相差
潮间带下部 潮间带中部 潮滩 潮间带下部 潮间带中部 潮滩 潮间带下部 潮间带中部 潮滩
总体积/(106 m3 0.32 2.66 4.57 0.46 3.50 5.58 45.2% 31.6% 22.1%
总面积/(106 m2 0.27 2.44 4.12 0.32 2.22 3.83 19.8% −9.0% −7.0%
平均深度/m 1.19 1.09 1.11 1.44 1.57 1.46 21.2% 44.6% 31.5%
总长度/104 m 0.21 4.13 5.30 0.24 4.18 5.42 13.5% 1.1% 2.3%
平均宽度/m 127.45 59.20 77.87 134.53 53.26 70.70 5.6% −10.0% −9.2%
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生物膜对潮滩动力地貌演变影响的数值模拟研究
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梁梦娇 1 , 周怡 2 , 张荷悦 2 , 李欢 2 , 康彦彦 3 , 王大伟 4 , 周曾 1, 2, *
海洋学报 | 论文 2024,46(2): 93-106
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海洋学报 | 论文 2024, 46(2): 93-106
生物膜对潮滩动力地貌演变影响的数值模拟研究
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梁梦娇1 , 周怡2, 张荷悦2, 李欢2, 康彦彦3, 王大伟4, 周曾1, 2, *
作者信息
  • 1.河海大学 水灾害防御全国重点实验室,江苏 南京 210098
  • 2.河海大学 江苏省海岸海洋资源开发与环境安全重点试验室,江苏 南京 210098
  • 3.河海大学 海洋学院,江苏 南京 210098
  • 4.河海大学 环境学院,江苏 南京 210098
  • 梁梦娇(1997—),女,山东省菏泽市人,主要从事河口海岸水动力泥沙模拟研究。E-mail:

通讯作者:

*周曾(1986—),男,江苏省句容市人,教授,主要从事河口海岸地貌学研究。E-mail:
Numerical simulation of the influence of biofilm on the dynamic geomorphological evolution of tidal flats
Mengjiao Liang1 , Yi Zhou2, Heyue Zhang2, Huan Li2, Yanyan Kang3, Dawei Wang4, Zeng Zhou1, 2, *
Affiliations
  • 1. The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing 210098, China
  • 2. Jiangsu Key Laboratory of Coast Ocean Resources Development and Environment Security, Hohai University, Nanjing 210024, China
  • 3. College of Oceanography, Hohai University, Nanjing 210098, China
  • 4. College of Environment, Hohai University, Nanjing 210098, China
出版时间: 2024-02-29 doi: 10.12284/hyxb2024013
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河口海岸潮滩湿地是一个复杂的生态系统,其地貌的形成和演变是水动力、泥沙输移和生物过程等多种因子相互作用的结果,特别是,探究潮滩生物过程并阐明其生物−物理效应是当前海洋科学领域研究的热点和难点。本文聚焦微生物生物膜,构建了耦合生物膜与水动力、沉积物输移、地貌演变的二维生物动力地貌模型,探究了生物膜在潮滩泥沙输移和地貌演变中发挥的作用。利用文献数据验证生物动力地貌模型,模型结果与文献数据吻合较好,表明所构建的模型可以较好地模拟出生物膜的增长规律及年际变化情况。结果表明,当水动力较弱时,在有生物膜作用的潮滩上,潮沟向陆侧延伸更充分,呈现出树杈状分布,潮间带区域的潮沟两侧分布有生物膜。通过对潮沟形态进行定量分析,发现生物膜的存在促进了潮沟数量增加,并向纵深方向发展,同时限制了其宽度的增加。相较于没有生物膜影响的潮滩,潮沟的平均深度增加,总面积减小,总长度增加,平均宽度减小,总体积增加。研究结果有助于加深对生物膜在潮滩地貌塑造中的作用机制认识,为海岸带保护与生态修复工程提供科学依据。

潮滩生物膜  /  数值模拟  /  潮滩地貌  /  潮沟系统

Tidal flats maintain a complex ecosystem, while its formation is driven by multi-factor interaction, including hydrodynamics, sediment transport, and biological processes. In particular, investigating tidal flat biological processes and elucidating their biological-physical effects are current research hotspots and challenges in the field of marine science. This study focused on intertidal biofilms, constructed a two-dimensional biomorphodynamic model which coupled biofilms with hydrodynamics, sediment transport, and bed level change, to explore the role of biofilms in sediment transport and geomorphological evolution. The biomorphodynamic model was validated using literature data, indicating that the constructed model can simulate the growth pattern and interannual variation of biofilms well. Model results show that tidal creeks with biofilm attachment are more fully extended towards the landward side, showing a branching distribution when hydrodynamics are weak, and biofilms were distributed on both sides of the intertidal zone. Through quantitative analysis of tidal creek morphology, it is found that the presence of biofilms promoted an increase in the number of tidal creek and their development in the vertical direction, while limiting the increase in their width. Compared to tidal flats without the influence of biofilms, the average depth of tidal creeks increases, the total area decreases, the total length increases, the average width decreases, and the overall volume increases. The research outcome of this study deepens the understanding of the role of biofilms on tidal flat evolution and provides a scientific basis for coastal zone protection and ecological restoration projects.

intertidal biofilms  /  numerical simulation  /  geomorphological evolution  /  tidal creeks system
梁梦娇, 周怡, 张荷悦, 李欢, 康彦彦, 王大伟, 周曾. 生物膜对潮滩动力地貌演变影响的数值模拟研究. 海洋学报, 2024 , 46 (2) : 93 -106 . DOI: 10.12284/hyxb2024013
Mengjiao Liang, Yi Zhou, Heyue Zhang, Huan Li, Yanyan Kang, Dawei Wang, Zeng Zhou. Numerical simulation of the influence of biofilm on the dynamic geomorphological evolution of tidal flats[J]. Haiyang Xuebao, 2024 , 46 (2) : 93 -106 . DOI: 10.12284/hyxb2024013
河口海岸潮滩是海陆交接的前沿地带,具有重要的社会、经济和生态价值[13]。潮滩湿地作为一个复杂的生态系统,其地貌的形成和演变受控于水动力、泥沙输移、生物过程等多种因子相互作用。在传统的潮滩地貌演变研究中,大多考虑水沙动力和地貌之间的相互反馈和演变进而达到某种平衡状态,这种经典的动力地貌学方法已成功用于潮滩地貌演变的模拟和预测[45]。随着对海岸动力地貌过程研究的逐渐深入,学界逐渐意识到生物在潮滩演化过程中扮演着不可忽视的角色,变化环境下泥沙供给、水动力和生物群落变化等关键生物−物理互馈过程直接影响着潮滩湿地的演化趋势[6]
潮滩生态系统中存在着大量微生物,它们分泌黏性的高分子聚合物(胞外聚合物,EPS)形成生物膜,可改变泥沙颗粒表面的化学、电荷特性及微观形态特征[7],在微观和宏观尺度上调节着海岸泥沙的运动特性。方红卫等[7]采用环扫电镜观察生物膜泥沙的形貌,发现生物膜形成后泥沙表面形貌起伏变少;Chen等[8]通过生物泥沙的培养试验,发现胞内聚合物桥连将改变泥沙的黏聚力。Andersen等[9]、de Deckere等[10]认为,生物膜之所以可以增强底床泥沙尤其是细颗粒泥沙的稳定性,一方面是由于生物膜覆盖在泥沙表面,有助于河床形成一个相对光滑的表面,同时还可以减小拖曳力。从宏观上来说,生物膜的附着提高了潮滩泥沙的抗侵蚀能力,对滩面稳定性有重要影响[1112],在塑造潮滩地貌演变中发挥着不可忽视的作用[1314]
虽然国内外学者已经通过多种手段证实了生物膜可影响泥沙运动特性,但是相关研究大多仍停留在微观尺度上,对于生物膜如何通过改变水沙响应关系在较大尺度上影响潮滩地貌演化的认识仍不清楚。鉴于此,本文以生物膜影响下的潮滩地貌系统为研究对象,通过建立二维潮滩生物动力地貌模型,耦合微生物生态过程和泥沙输移过程,分析生物膜在潮滩上的分布规律,探究生物膜对潮滩系统泥沙输移和地貌演变的影响,研究结果有助于加深对生物膜在潮滩地貌塑造中的作用机制认识,丰富新兴交叉学科“生物动力地貌学”的学科内涵。
本研究基于国际开源动力地貌模型Delft3D进行拓展研发,开发了潮滩生物膜模块,并与原模型的水动力模块、泥沙输运模块、地貌演变模块进行耦合,建立了考虑微生物生物膜的二维动力地貌模型,以下对模型进行简要介绍。
本文考虑的水动力包括潮流和波浪,以下分别进行介绍。
(1)潮流模块:
该模块是基于Boussinesq近似和静压假定的基础,求解不可压缩液体的Navier-Stokes方程。包括连续性方程和动量守恒方程。
①连续性方程:
$ \frac{{\partial \eta }}{{\partial t}} + \frac{{\partial hu}}{{\partial x}} + \frac{{\partial hv}}{{\partial y}} = 0 \text{,} $
②动量守恒方程:
$ \frac{{\partial u}}{{\partial t}} + v\frac{{\partial u}}{{\partial x}} + u\frac{{\partial u}}{{\partial y}} = - g\frac{{\partial \eta }}{{\partial x}} + \nu \left( {\frac{{{\partial ^2}u}}{{\partial {x^2}}} + \frac{{{\partial ^2}u}}{{\partial {y^2}}}} \right) - g\frac{{u\sqrt {{u^2} + {v^2}} }}{{{C^2}h}} \text{,} $
$ \frac{\partial\mathit{v}}{\partial t}+u\frac{\partial\mathit{v}}{\partial x}+\mathit{\mathit{v}}\frac{\partial\mathit{v}}{\partial y}=-g\frac{\partial\eta}{\partial y}+\mathit{\mathit{\nu}}\left(\frac{\partial^2\mathit{v}}{\partial x^2}+\frac{\partial^2\mathit{v}}{\partial y^2}\right)-g\frac{\mathit{v}\sqrt{u^2+\mathit{\mathit{v}}^2}}{C^2h}\text{,} $
式中, xy为笛卡尔坐标(单位:m);uvxy方向上的垂向平均流速(单位:m/s);t为时间(单位:s);h为水深(单位:m);η为相对于某个基准(比如平均海平面)的水位(单位:m);g为重力加速度(单位:m/s2);C为谢才系数(单位:m1/2/s);$\nu $为水平涡流黏性系数(单位:m2/s)。
(2)由潮流引起的底部切应力:
计算公式为:${\tau _c} = \rho g{u^2}/{C^2}$,式中,$\rho $为水的密度(kg/m3)。
(3)波浪模块:
该模块采用了基于Young 和Verhagen[1516]提出的公式,在Tao等[17]的论文中得到应用。该公式将无量纲风区($\chi = gF/{U^2_W}$)和无量纲水深($\delta = gh/{U^2_W}$)与无量纲波能量($ \varepsilon = {g^2}E/{U^4_W} $)及无量纲谱峰波频率($\varsigma = {U_W}{T_P}^{ - 1}/g$)联系起来,估算了给定风场下(例如:风区长度、风速和水深)波高和波周期。
$ \varepsilon = 3.64 \times {10^{ - 3}}{\left[ {\tanh {A_1}\tanh \left( {\frac{{{B_1}}}{{\tanh {A_1}}}} \right)} \right]^{1.74}}\text{,} $
$ \varsigma = 0.133{\left[ {\tanh {A_2}\tanh \left( {\frac{{{B_2}}}{{\tanh {A_2}}}} \right)} \right]^{ - 0.37}}\text{,} $
式中,${A_1} = 0.493{\delta ^{0.75}}$${B_1} = 3.13 \times {10^{ - 3}}{\chi ^{0.57}}$${A_2} = 0.331{\delta ^{1.01}}$${B_2} = 5.215 \times {10^{ - 4}}{\chi ^{0.73}}$${U_W}$是海拔10 m处的风速;F是风区长度;${T_P}$是峰波周期;E是波能,计算公式为$E = \rho g{H_S}^2/8$${H_S}$为有效波高)。在波浪传播过程中,波陡增加,波浪在浅水区域破碎,可以通过波浪破碎指标$\gamma = {H_S}/h$来判断。在本研究中,根据Roberts等[18]$\gamma $取为0.5。波浪破碎后,波高受水深限制,有效波高${H_S} = \gamma h$。波浪引起的底部切应力在波浪破碎时达到最大,然后随向岸水深的减小而减小[19]。根据线性波理论,底部最大波轨道速度为
$ u_{w,\ b}=\frac{\text{π}H_S}{T_p\sinh(kh)}\text{,} $
且由波浪引起的底床切应力为
$ \tau_{w,\ b}=\frac{1}{2}\rho f_wu_{w,\ b}^2\text{,} $
$ f_w=1.39\left[\frac{U_{w,\ b}T_p}{2\text{π}(D_{50}^{{\mathrm{mix}}}/12)}\right]^{-0.52}\text{,} $
式中,k是波数;fw是由Soulsby[20]文中定义的波浪摩擦因子;$D^{{\mathrm{mix}}}_{{50}} $是泥沙混合物的中值粒径。
潮流和波浪共同作用下的底床切应力的计算使用了Soulsby[20]的方法:
$ {\tau _{\max }} = {\tau _w} + {\tau _c}\left[ {1 + 1.2{{\left( {\frac{{{\tau _w}}}{{{\tau _c} + {\tau _w}}}} \right)}^{3.2}}} \right]. $
在计算泥沙输移时,黏性沙和非黏性沙的侵蚀、沉积和输移等物理过程往往使用不同的计算方法分开考虑。
(1)黏性沙
黏性沙的输移用带源汇项的对流扩散方程描述黏性沙的侵蚀淤积情况:
$ \frac{{\partial (ch)}}{{\partial t}} + \frac{{\partial (uch)}}{{\partial x}} = {Q_{{\mathrm{mud}},\;e}} - {Q_{{\mathrm{mud}},\;d}} ,$
式中,c为泥沙垂向平均浓度(单位:kg/m3);Qmud, eQmud, d分别代表黏性沙的侵蚀量和淤积量,二者通过Partheniades-Krone公式[21]来计算。
$ {Q_{{\mathrm{mud}},\;e}} = \left\{ \begin{array}{*{20}{ll}} {M_e}\left(\dfrac{\tau }{{{\tau _{{\mathrm{cr}},\;e}}}} - 1\right)&\tau > {\tau _{{\mathrm{cr}}\;e}} ,\\ 0&\tau \leqslant {\tau _{{\mathrm{cr}}\;e}} ,\end{array} \right. $
$ {Q_{{\mathrm{mud}},\;d}} = \left\{ {\begin{array}{*{20}{l}} {\omega _s}c\left(1 - \dfrac{\tau }{{{\tau _{{\mathrm{cr}},\;d}}}}\right)&\tau < {\tau _{{\mathrm{cr}},\;d}}, \\ 0&\tau \geqslant {\tau _{{\mathrm{cr}},\;d}} ,\end{array}} \right. $
式中,Me是冲刷系数[kg/(cm2·s)];ωs为泥沙沉降速度(单位:m/s);τcr, eτcr, d(单位:Pa)分别代表黏性沙的临界起动切应力和临界沉降切应力。在Delft3D模型中,运用了Winterwerp[22] 提出的连续沉降的概念,所以将τcr, d设置为默认值1 000 Pa,使得泥沙处于连续沉降的状态,因此式(12)可近似看为$ {Q_{{\mathrm{mud}},\;d}} = {\omega _s}c $
(2)非黏性沙
在二维模型中,非黏性沙使用Engelund和Hansen[23]的输移公式进行模拟。
$ |{\boldsymbol{S}} | = \frac{{0.05|{\boldsymbol {U}} {|^5}}}{{{g^{0.5}}{C^3}{\Delta ^2}{D_{50}}}} ,$
式中,$ {\boldsymbol{S}} $为总沉积物输移速率(单位:m2/s);${\boldsymbol{U}} $为流速(单位:m/s);D50为中值粒径。
考虑到底坡的影响,泥沙通量的大小根据Bagnold[24]的公式修正为
$ {{{\boldsymbol{S}}'}} = {\alpha _s} {\boldsymbol{S}} \text{,} $
$ \alpha_s=1+\alpha_{bs}\left\{\dfrac{\tan\left(\phi\right)}{\cos\left[\tan^{-1}\left(\dfrac{\partial z_b}{\partial s}\right)\right]\left[\tan\left(\phi\right)-\dfrac{\partial z_b}{\partial s}\right]}\right\}\text{,} $
式中,$ {{{\boldsymbol{S}}'}} $为被修正的沉积物输移速率(单位:m2/s);αbs为无因次系数,默认值取为1[5]$ \phi $为床层沉积物的内摩擦角,取为默认值30°[5]$ \partial {z_b}/\partial s $为纵向上的底坡。
通过引入一个正交的泥沙通量,进一步调整了沉积物通量$ {{{\boldsymbol{S}}'}} $的方向,以考虑横向底坡[25]
$ {S_n} = |{{{\boldsymbol{S}}'}} |{\alpha _{bn}}\frac{{{u_{cr}}}}{{|{\boldsymbol{U}} |}}\frac{{\partial {z_b}}}{{\partial n}} \text{,} $
式中,Sn的大小为正交泥沙通量(单位:m2/s),方向为向下倾斜;αbn为无因次系数,默认值取为1.5[5]$ \partial {z_b}/\partial n $为横向坡度(与流线方向正交)。
因此,泥沙通量Sr
$ {{{\boldsymbol{S}}_r}} = {{{\boldsymbol{S}}'}} + {{{\boldsymbol{S}}_n}} . $
地貌演变的控制方程为床面连续方程:
$ \left( {1 - \varphi } \right)\frac{{\partial {z_b}}}{{\partial t}} + \frac{{\partial {S_x}}}{{\partial x}} + \frac{{\partial {S_y}}}{{\partial y}} = 0 \text{,} $
式中,$z_b $为床面高程(m);$\varphi $为底床泥沙孔隙率;SxSy分别为xy方向上的泥沙通量(单位:m2/s)。
在地貌模型中,由于地貌时间尺度比水动力时间尺度大1~2个数量级,因此在模型中使用地貌加速因子(fmor)加速地貌演变[26]。将河床在一个水动力时间步长的变化量乘fmor,然后反馈到下一个时间步长,计算流场和波浪条件,实现用1年的水动力模拟fmor年后的地貌。
在分层模型中将初始底床分为一层冲淤层、若干层交换层和一层基础层,且每层的黏性沙和非黏性沙都按设定的比例均匀充分混合[27]。用前文中提到的泥沙输移公式计算一个水动力时间步长内的冲淤层的侵蚀或淤积。通过敏感性实验,本文模型中冲淤层和交换层厚度均取为0.2 m,共50层。在该模型中,冲淤层的厚度始终保持不变以保证其稳定性。
研究表明,生物膜大量分布在潮间带上部[28],在潮间带下部也有分布[14],潮间带是生物膜分布的主要区域。在盐城潮滩的野外观测中发现,生物膜大量分布在互花米草的前缘。向陆侧,在互花米草生长密度过大的区域,生物膜几乎没有分布;向海侧,生物膜有分布,但由于水深及淹没时间的因素影响,生物量差异较大。生物膜的分布范围为
$ X=\left\{\begin{array}{cc}0 & D\leqslant {D}_{\mathrm{min}},\\X &D > {D}_{\mathrm{min}},\end{array} \right. $
式中,$X $(单位:mg/m2)为Chl a生物量;当D > Dmin时按照式(24)计算,D为底床高度与高潮位的差(单位:m);Dmin为生物膜可以在平均高潮下生存的最小深度(单位:m)。
在本研究中,我们采用Mariotti和Fagherazzi[29]的方法,用叶绿素a含量代表生物膜的生物量(下文中均统一称之为生物量),且考虑到潮滩上生物膜的生长受季节性影响显著,且与潮滩细颗粒组分含量相关,所以在Mariotti和Fagherazzi[29]总结的简化公式的基础上进一步考虑温度、底床泥沙组分这两个要素,因此描述生物量季节性变化的公式为
$ \frac{{{\mathrm{d}}X}}{{{\mathrm{d}}t}} = \underbrace {{M_C}{\mu _{\max }}\frac{X}{{1 + {K_S}X}}}_{1a}\underbrace {\frac{I}{{I + {K_I}}}}_{1b}\underbrace {\exp \left[ {\beta \left( {T - {T_O}} \right)} \right]}_{1c} - \underbrace {\varepsilon \left( {X - {X_b}} \right)}_2 \text{,} $
式中,1$a $项刻画了生物量的对数增长;1$b $项考虑了光照强度对生物量的影响,其中I = Ioexp(kdd),d为水深;1c项描述了季节性温度变化对生物量的影响,2项表示生物量的正常衰减,式中各参数的含义及取值详见表1
温度变化考虑季节性差异,其公式来源于Nguyen等[30],如下:
$ T\left( t \right) = \frac{{{T_{\max }} - {T_{\min }}}}{2}\cos \left( {\frac{{2 {\text{π}} }}{{365t}}} \right) + \frac{{{T_{\max }} + {T_{\min }}}}{2} \text{,} $
式中,Tmax代表全年最高温度(单位:℃);Tmin代表全年最低温度(单位:℃)。
根据潮滩生物膜中微生物的优势种群不同,生物膜可以分为多种类型,主要有硅藻类生物膜、蓝藻类生物膜。硅藻类生物膜多分布于淤泥质潮滩,蓝藻类生物膜常见于砂质潮滩上[31]。本研究主要聚焦在硅藻生物膜上,考虑潮滩泥沙组分对其数量的影响。Riethmüller等[32]统计了滩面叶绿素含量采集点处的细颗粒组分(粒径小于63 μm)的含量和含水量,通过对其测量数据分析,总结了下面的关系式来反映泥沙组分对生物膜生长的影响效应。
$ {M_C} = \left\{ {\begin{array}{*{20}{c}} 0&{0 \leqslant mct \leqslant 10{\text{%}} }, \\ {0.35}&{10{\text{%}} < mct \leqslant 25{\text{%}} } ,\\ {0.6}&{25{\text{%}} < mct \leqslant 85{\text{%}} }, \\ 1&{mct > 85{\text{%}} } ,\end{array}} \right. $
式中,MC表示某一泥沙组分下生物量变化的系数;mct表示底床中值粒径小于63 μm泥沙的总含量。
生物量与泥沙临界起动切应力之间是一次线性关系[33],归结为以下公式[29]
$ {\tau _{{\mathrm{cr}}}} = {\tau _{{\mathrm{cr}},o}} + \alpha X \text{,} $
式中,τcr, o 为没有生物膜定殖时的泥沙临界起动切应力(单位:Pa);ατcr随生物膜生长τcr (单位:Pa)的增长系数。
在研发的生物膜模块中,根据现有文献,各参数的取值范围及默认取值如表1所示。
首先,依据前人研究结论,在生物动力地貌模型中有关生物膜做了以下3点假设[29]:(1)潮滩上生物膜均匀分布;(2)生物膜在临界切应力下,生物量不会发生损失;(3)高于临界切应力时,生物膜会完全被破坏,即“all or nothing”的破坏方式。
水动力模块中计算出的底部切应力(τ)作用到生物膜,并将水深(h)、床面高程(zb)及底床泥沙的中值粒径(D50)与生物量相关联,综合考虑环境因素,如温度、光照强度等,计算出生物量的大小;生物量通过改变泥沙的临界起动切应力(τcr)反馈回泥沙模块,引起地貌改变;地貌改变后重新计算水动力。本文的生物动力地貌模型通过此机制运行模拟生物量在潮滩上的分布及生物膜对潮滩地貌演变的影响。
生物膜对动力地貌过程的研究目前仍处于起步阶段,受限于潮滩生物膜实测数据的匮乏、生物膜特征的区域性差异等原因,本研究验证的方式是在不考虑外界水动力等物理环境因素影响,模拟生物量随时间变化情况,将增长曲线与室内培养实验结果进行比较。
(1)生物量增长速度
在本模型中,不考虑外界环境(如水动力、极端事件等)对生物膜生长过程的破坏,模拟生物量随时间变化情况如图1绿色曲线所示。
图1可知,生物量从0开始增加,在初期生长阶段,生物量的生长速率较小,然后随着模拟时间的增加,生物量的增长速率快速增加;在8 d左右,生长速率放缓并且随着时间的增加而减小,最后在20 d左右,生物量达到最大值,以Chl a计约为150 mg/m2。关于生物量的最值参考了Riethmüller等[32]与Zhu等[40]在潮滩上的实测数据取值。图中蓝色、红色的点表示Chen等[14] 通过实验室培养生物膜得出的实测值,虚线则表示拟合的生长曲线,其中蓝色、红色分别代表0~0.2 cm、0.2~0.5 cm深度所测生物量。由于对生物量表示单位不一致,所以仅对比生物量增长趋势,从图1中可以看出该模型中生物膜的增长曲线与实验室实测生长速度相似,在两周后达到稳定状态。
(2) 生物量及生物稳定性
生物量的年际变化情况如图2a所示,图中红点和红线为van der Wal等[28]研究中WES点所测生物量指标归一化差值植被指数 (NDVI)年际变化情况。从图中可以看出,初始温度为33°C,此时无其他可以破坏生物膜的条件存在,生物膜有较好的生长环境,因此生物量(以Chl a计)从初始值1 mg/m2快速增加到最高值,约为150 mg/m2,而后随温度的降低而减小,温度峰值与生物量的峰值出现的时间一致,并且生物量的变化与温度的变化趋势一致,模型结果表现出的季节性变化与van der Wal等[28]所测结果和前人研究基本一致[4142]
该模型用黏土组分的临界起动切应力表示生物稳定效应,方便把该效应量化。图2b刻画了生物膜生长后黏土组分的临界起动切应力(τcr)的变化情况,τcr的初始值为0.2 Pa,随之模拟时间的增加,该值在0.25~0.5 Pa之间变化,同时临界起动切应力的变化趋势与生物量同步。相较于Chen等[43]实验室测得τcr为0.258~0.33 Pa及Zhu等[40]野外观测中τcr为0.46 Pa,该模型的结果较为合理。
生物膜的生长受多种环境因子的影响,包括温度、光照、底床中黏性沙组分的占比以及水深,本文主要选取了沉积物组分、温度、光照强度3个环境参数进行敏感性分析,且模型均不考虑水动力等其他因素对生物膜的破坏作用。
野外观测中可以发现,硅藻生物膜多分布于淤泥质潮滩上,砂质潮滩上几乎不含有硅藻生物膜,因此在该部分设置3种工况(底床中黏土组分占比分别为25%,50%和90%)来模拟不同泥沙组分下的生物量,生物量年际变化情况如图3a所示。结果表明,生物量随黏土组分占比的提高而不断增加。当潮滩底质中黏土组分的占比仅有25%时,生物量(以Chl a计)最高只能达到60 mg/m2左右,而当黏土组分为90%时,生物量接近300 mg/m2,是前者的5倍。
温度也是影响硅藻生物膜生存和生长最重要的环境因子之一,对于硅藻生物膜来说,存在使其生长最快的适宜温度,超过一定温度后,硅藻细胞受到不可逆的损害导致生物膜无法生长,低于一定温度时,虽然不会造成硅藻的死亡,但是生长速度却受到了抑制。模型中与生物量有关的温度参数有最高温、最低温及温度对生物膜发育的影响系数β。在这部分的模型设置中,β表1中该项的最大参考值0.022 4,并设置两种工况:(1)最高温为33℃,最低温为–1℃;(2)最高温为27℃,最低温为7℃,结果如图3b所示。在第一种工况时,年内最大生物量(以Chl a计)约为150 mg/m2,最小为50 mg/m2,在第二种工况下年内最高生物量约为120 mg/m2,最小生物量约为70 mg /m2,生物量差距较小。所以,年内温度的最值虽然决定了生物量取值范围的上限和下限,但是在合理适宜的温度范围内,生物量之间的差距不是太大。
当生物膜淹水时,光照透过水到潮滩表层才能被利用,在光透过水到达潮滩表层时,光照强度会因为水的浊度等原因而被削弱。在模型中,水深对光照强度的衰减用系数kd表示, 模型设置了kd取0.5、1.5和3的3种工况,模拟淹水−露滩交替的区域内生物量的年际变化情况,过程如图3c所示。当kd取0.5时,生物量曲线较为光滑,随着kd取值的增加,生物量曲线出现锯齿状,很显然 kd 越大生物量曲线波动越剧烈;另外,生物量也会有所减小。这表明在淹水–露滩交替的区域,随着水深对光照强度的衰减系数kd的增加,生物膜对潮位的变化越敏感,表现为生物量随潮水上涨而减小,随潮位降低而增加。
为研究生物膜对潮滩−潮沟系统演变的影响,本文建立了二维生物膜−潮沟地貌模型,计算区域选为15 km × 10 km的矩形区域,初始地形由宽为7 km、坡度为0的平坡和宽为8 km、坡度为1.5‰的陡坡组成,并将模型划分为潮间带中部、潮间带下部及潮下带[44],初始地形如图4所示。考虑到模型的计算精度、计算时间以及模型结果的稳定性,经过敏感性分析,设置模型区域的网格大小为50 m × 50 m。
该模型具体参数设置如下:
(1)水动力参数设置
①计算时间步长设置
经过敏感性分析,在满足模型计算稳定性和精度要求,同时提高模型计算效率的同时,选取模型的计算时间步长为0.3 min。
②边界条件设置
模型的北边界设置为闭边界,为陆侧;东、西边界设置为纽曼边界。模型的开边界,无相位差;南边界设置为水位边界,主要考虑了M2和S2分潮,振幅分别为1.7 m和0.6 m,频率分别为28.985 5°/h和30°/h,相位均为0°;模型中设置风速为1 m/s,风区长度为5 000 m。
③底部糙率
糙率是反映对水流阻力影响的一个综合性无量纲数,糙率越大,对水流的阻力越大。本模型中忽略了水深对糙率的影响,模型区域内糙率统一取为定常数65 m1/2/s。
④水平涡黏系数
本模型中水平涡流扩散系数取为10 m2/s,水平涡黏系数取为1 m2/s[4]
(2)泥沙参数设置
在本模型中,同时考虑了黏性沙和非黏性沙,包括两种沉积物组分,即黏土和粉砂;两种沉积物的厚度分别为10 m和5 m,各组分含量比为2∶1。两种沉积物组分充分且均匀混合,构成了初始底床。对于黏土,其沉速为0.5 mm/s,无生物膜影响时的临界起动切应力为0.2 N/m2,冲刷系数为5 × 10−4 kg/(m2·s)[27, 45]。根据Winterwerp[22]提出的连续沉降理论,本模型将黏性沙的临界沉降切应力取一个极大值为1 000 N/m2,即不给泥沙设定临界沉降应力(泥沙沉降条件总能被满足)。
模型动力参数及边界条件设定如表2所示。
(3)地貌参数设置
为加快地貌演变的同时保证模型的结果更符合实际,经过敏感性分析,本模型中设置地貌加速因子fmor,地貌加速因子取为10。
(4)生物膜模块参数设置
在该章节中的生物膜模型中,生物膜模块相关参数的取值如表3所示。
模型中设置较小的风速为1 m/s,因此,波浪在潮滩上产生的底部切应力小于无生物膜覆盖黏性沙的临界起动切应力0.2 N/m2,所以认为潮滩上生物膜具有生长的环境。结合图5a图5c的潮滩地貌分析生物量,可以看出在第1年时,生物膜在潮滩上大量分布,在无潮沟发育的区域内,生物膜均匀覆盖,生物量最高(以Chl a计)可达到约为220 mg/m2;在8 km即平坡和陡坡的转折处,由于水深的急剧增加,生物量快速减小,在接近5 km时生物量为0。潮沟在转折处形成向海侧和陆侧发育,因此在8~11 km区域内,生物膜大量分布在潮沟两侧,潮沟内的生物量较小。由图5e图5f可见,潮沟外部生物量(以Chl a计)最高可达到220 mg/m2,在新发育的潮沟内侧生物量较小。
开敞式潮滩上潮沟系统的演变过程如图6所示。
图6中可以看出考虑生物膜是否存在对潮沟系统的发育和潮滩地貌有较大影响。首先,在潮沟演变的第0.5年,由于生物膜的存在,潮沟并未发展到11~15 km区域内,相反,在无生物膜潮滩上,11~15 km区域已经有一些较浅的潮沟形成。到第3年时,比较图6b图6e,虽然都有平行潮沟生成,但是潮滩地貌和潮沟系统确有明显的差异。生物膜存在的潮滩上,潮沟向陆侧发展,形成的潮汐通道更加明显,在潮滩上部形成了树杈状的潮沟;而无生物膜潮滩上,潮滩上部却形成相互平行的细窄长潮沟,数量多而密。另外还可以注意到,在12~15 km的区域内,无生物膜潮滩上潮沟两侧的高程明显高于生物膜潮滩,但是在7~12 km区域内恰恰相反,这是由于生物膜的覆盖增加了泥沙的临界起动切应力,附近潮沟外的泥沙更不易起动,以至于输移向陆侧落淤的泥沙量更小。在演变的第10年,潮沟系统发育得更加完整,生物膜潮滩上的潮沟继续向陆侧延伸,潮沟前端继续分叉产生新的潮沟;但是无生物膜潮滩上,陆边界处的高程增加,潮沟发生后移。由此可以看出,生物膜可以促使潮沟系统向陆侧的发育。
图7a图7b分别表示生物膜潮滩上垂直于岸线断面(x = 5 km)和平行于岸线断面(y = 10 km)的高程变化情况。在x = 5 km断面上,演变初期在距离海边界8 km处潮滩被侵蚀,潮滩上部略有淤积。第3年时,9~12 km范围被剧烈冲刷,潮滩上部由于淤积床面高程增加;在第3年到第10年内,潮滩上部的高程变化较小,说明该时间内潮沟发育的过程较为缓慢。通过图7b看出在演变初期(第0.5年)潮沟已经开始形成,随着时间的增加,潮沟内侧的侵蚀和外侧的淤积均有所增强,潮沟的宽深比继续减小,潮沟的冲刷作用更强烈。在第3~10年期间,潮沟冲淤的位置基本不变,说明此时该断面上的潮沟发育已经稳定,水动力条件不变的情况下不会发生摆动。
图8表示10年后生物膜潮滩和无生物膜潮滩两个断面上的高程变化情况。在y = 10 km断面(图8a)上,生物膜潮滩上潮沟两侧发生淤积,高程平均为0.3 m;无生物膜潮滩整体呈现出侵蚀,表明当生物膜存在时,促进了y = 10 km断面高程增加。且两类潮滩在y = 12 km断面(图8b)上均发生淤积,由此可见,生物膜存在时,潮滩上的淤积范围更广。此外,该断面上,无生物膜潮沟的特点是潮沟的深度小,潮沟宽度大,而在生物膜覆盖的潮滩上,该断面上发育的潮沟具有数量多且密,潮沟深度大,潮沟宽度小的特点。
y = 12 km断面(图8b)上,两种不同类型的潮滩都发生了不同程度的淤积,生物膜潮滩上该断面的最大高程在1.5 m左右,而无生物膜潮滩上断面高程最大约为1.8 m。不考虑生物膜时,潮沟深度最大为2 m,而生物膜存在时潮沟的深度最大可达到4 m,是前者的2倍。在该断面处,两个潮滩上潮沟均表现出数量多且密集的特点,区别在于生物膜潮滩上所发育出来的潮沟深度更大。
潮间带第10年潮沟形态参数统计见表4,在潮间带下部,生物膜潮滩上潮沟的各项参数均大于无生物膜的潮滩,表明潮间带下部分布的生物膜对该区域的潮沟发育具有促进作用,对潮沟总体积的促进作用最大,使其增加45.2%,平均宽度的增幅较小,为5.6%。在潮间带中部,生物膜更多地促进了潮沟的平均深度和体积的增加,总长度仅相差1.1%,而潮沟总面积和平均宽度均减小,分别减小了9.0%和10.0%。
生物膜潮沟系统和无生物膜潮沟系统的各形态参数定量统计结果如图9所示,在演变初期(0~2年),生物膜潮滩与非生物膜潮滩上的潮沟总体积相差不大,生物膜潮滩上的潮沟总面积、总长度略小于无生物膜潮滩,而潮沟较深。在第2~10年的演变过程中,对于潮沟总体积、总面积和平均深度3项参数,生物膜潮沟系统的增长速度明显快于无生物膜潮沟系统,潮沟深度和体积的差距逐渐增大。对两种类型的潮滩来说,在演变的中后期,潮沟的总面积的增长速度放缓,而潮沟的总体积和平均深度还在快速增长,在该时间内,潮沟体积的增加主要是由于潮沟还在继续加深。
将以上5项潮沟形态参数统计成表4,很显然,生物膜潮滩上潮沟的总面积较无生物膜潮滩减小7.0%,平均深度增加31.5%,潮沟总体积增加22.1%。在生物膜作用下,潮沟的总长度持续增加,10年后潮沟的总长度较无生物膜潮沟系统增加2.26%,潮沟的平均宽度却小于无生物膜潮沟系统,二者相差9.2%。
综上可以说明,总体来说,在该水动力条件下,潮沟演变初期,生物膜的生物黏结作用抑制了潮沟面积增加,促进了潮沟向纵向深度发展;中后期,潮沟的发育过程以潮沟的加深为主,而宽度和长度较为稳定。最后可以得出,生物膜对潮沟系统发育过程的作用主要表现为减小潮沟的平均宽度,延长潮沟的总长度,潮沟总面积整体小于无生物膜潮滩,同时潮沟的深度大幅增加,从而潮沟的体积也得到增加。
本文通过在开源模型Delft3D中将生物膜作用耦合进传统的水沙动力地貌模型中,模拟了开敞式生物膜潮滩的演变过程。然而,真实环境中的生物地貌过程更为复杂,各种生物之间相互作用(例如,底栖动物对生物膜的破坏、植物与生物膜相互作用等),以及生物膜对水动力和底床泥沙组分等因素复杂的响应机制。并且各地潮滩和水生环境具有显著的独特性,因此,将完整的生物地貌复刻到数值模型中是一个极大的挑战。
生物膜覆盖在潮滩上,其生长与潮滩环境的变化息息相关。以硅藻类生物膜为例来分析对其变化至关重要的因素。首先,硅藻作为潮滩上生产者的一分子,需要足够的阳光进行光合作用,因此,光照是硅藻生长的限制因素[28]。生物膜与底栖动物在潮滩上共存,底栖动物的活动(例如,螃蟹的生物活动)阻碍了生物膜的生长甚至会对生物膜产生较大的破坏[29, 46]。同时水深也是一个重要影响因素,水深会对光照强度产生不同程度的衰减效应,水深过大则不满足生物膜增长的光照条件[34]。温度在一定程度上驱动着生物量的变化,呈现出季节性变化特征,总体来说,夏多冬少[28]。一部分学者研究表明春秋多,夏季少则是因为底栖动物的活动导致[4748]。其次,作为生物膜的生长基质,底床泥沙组分也决定了生物量的大小。van der Wal等[28]的研究表明,相较于砂质潮滩,淤泥质潮滩上代表生物量的指标归一化差值植被指数 (NDVI)更高。最后潮滩上的水动力作用不容小视,极端天气的出现将导致底栖藻类生物量大规模减少。潮滩的淹没时间也是控制生物量大小的一个因素,潮间带上部生物量更大,另外海平面上升也会影响到生物膜的空间分布及大小[28]
由于生物量的影响因素众多且预测较难,现有的生物量数值模型并不能把所有的影响因素一一量化计算。例如,底床泥沙组分与生物量之间的数学关系如何,现在还未有研究明确指出,并且由于研究地点的独特和复杂性,也无法有较为通用的关系用于生物量预测的数学模型中。可见,为了使模型结果更贴近实际,在后续的模型研究中,有必要进一步改进底床泥沙粒度组成与生物量的关系。Gerbersdorf和Wieprecht[49]指出生物稳定性表现为提高了泥沙的临界起动切应力,从Riethmüller等[32]实测、Widdows等[50]水槽实验及Le Hir等[33]的研究中可以看出生物膜对泥沙临界起动切应力的影响目前只能总结为一次线性关系,相关参数对研究地点的依赖性较高。另外由于实地测量带来的困难导致现在数据缺乏,给数值模型的验证带来了一定的困难。因此,未来的模型要在预测的精确性上得到提高,不仅需要在现有的模型基础上考虑增加更多的影响因子作用,还需要将影响因子和生物稳定性的作用较为精确的定量化,同时以研究地点的野外实测数据为辅助,得到更能用于该地的生物动力地貌模型。
潮滩地貌演变是多种因子相互作用的结果,生物膜作为潮滩系统中的重要生物因子,对泥沙输移和潮滩地貌塑造有着不可忽视的影响。本文在传统的地貌模型中加入生物膜作用,论证了生物动力地貌模型对生物量的模拟能力,对沉积物组分、温度、光照几种主要环境因子进行了模型的敏感性分析,分析了生物膜对潮沟系统的影响。具体结论如下:
(1)不考虑外界环境对生物膜的破坏作用时,本文开发的生物膜模块可以模拟出生物量的对数增长曲线,与前人实验室结果类似;并且生物量随温度增减,年际变化呈现为余弦变化曲线。
(2)在该生物膜模型中,底床中黏土组分的占比提高,生物量会快速增加;温度的最值决定了生物量的最值;随着光照随水深的衰减系数这一参数增加,生物膜对水深变化的敏感度增加,生物量随潮位产生较大的波动。
(3)生物膜影响了潮滩地貌塑造及潮沟系统的发育,主要表现为:生物膜的存在加大了泥沙淤积的范围,促进了潮滩向陆侧的延伸。生物膜潮滩的潮间带下部潮沟各项形态参数得到增加,而潮间带中部潮沟总面积和平均宽度有小幅度减小。总体来说生物膜潮滩上潮沟数量多的同时更深更长,但是宽度有所减小。
本研究开发了水动力、生物膜和泥沙耦合的动力地貌模块,考虑生物膜在潮滩演变中的作用,结果有助于加深对生物膜在潮滩地貌塑造中作用机制的认识。本研究在模拟过程中仅探讨了较弱的水动力作用,未加入风暴潮这一极端条件对生物膜的破坏;此外,模型仅考虑生物膜在表层分布,而实际潮滩中生物膜在垂向也有分布,未来的研究中可以在此基础上进一步改进,进而更加深入地掌握生物膜和多种动力因子共同作用对潮滩地貌和潮沟系统的影响。
  • 中央高校基本科研业务费专项资金项目(B230201061)
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2024年第46卷第2期
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doi: 10.12284/hyxb2024013
  • 接收时间:2023-11-19
  • 首发时间:2025-11-25
  • 出版时间:2024-02-29
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  • 收稿日期:2023-11-19
  • 修回日期:2024-01-30
基金
中央高校基本科研业务费专项资金项目(B230201061)
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    1.河海大学 水灾害防御全国重点实验室,江苏 南京 210098
    2.河海大学 江苏省海岸海洋资源开发与环境安全重点试验室,江苏 南京 210098
    3.河海大学 海洋学院,江苏 南京 210098
    4.河海大学 环境学院,江苏 南京 210098

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*周曾(1986—),男,江苏省句容市人,教授,主要从事河口海岸地貌学研究。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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