Article(id=1211297763975893793, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211297760624644861, articleNumber=null, orderNo=null, doi=10.12284/hyxb2023005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1655136000000, receivedDateStr=2022-06-14, revisedDate=1660492800000, revisedDateStr=2022-08-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1766725491756, onlineDateStr=2025-12-26, pubDate=1675180800000, pubDateStr=2023-02-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766725491756, onlineIssueDateStr=2025-12-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766725491756, creator=13701087609, updateTime=1766725491756, updator=13701087609, issue=Issue{id=1211297760624644861, tenantId=1146029695717560320, journalId=1149651085930835976, year='2023', volume='45', issue='2', pageStart='1', pageEnd='150', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766725490957, creator=13701087609, updateTime=1766734526247, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1211335657419567924, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211297760624644861, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1211335657419567925, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211297760624644861, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=98, endPage=109, ext={EN=ArticleExt(id=1211297764219163440, articleId=1211297763975893793, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Qualitative comparative analysis on grain-size parameters of derived from graphic and moment methods: a case study of the surficial sediment of coastal beaches of Qiongzhou Strait, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

Little research attention has been paid to comparison of the descriptive terms used in graphical method and moment method for grains-size parameters, although some work has been done on comparison of the numerical values and mutual conversion equations. In this paper, 105 surface sediments from 22 sections of 15 beaches on both sides of the Qiongzhou Strait are selected as typical research objects. The grain-size parameter results are obtained by the Folk & Ward graphic method and Friedman moment method respectively. The regression relationship of quantitative results is constructed and the similarities and differences of qualitative results are compared. Combined with the previous research results, this paper further discusses the comparability of the results of the two methods, and analyzes the possible impact of the differences between the two methods on the extraction and use of sediment particle size information. The results show that: (1) in terms of quantitative results, the average particle size and sorting coefficient calculated by graphic method and moment method have strong correlation (R2 ≥ 0.951), while the skewness and kurtosis show moderate correlation (R2 = 0.586) and uncorrelation (R2 = 0.011), indicating that the correlation between the quantitative results of particle size parameters calculated by the two methods is not stable, which is basically consistent with the previous research results; (2) as far as qualitative results are concerned, there is a large deviation between the results of graphic method and moment method. The proportion of inconsistent sorting coefficient, skewness and kurtosis is 30.48%, 55.24% and 71.43% respectively, which deviates from the correlation of quantitative results to a certain extent, indicating that the correlation degree of quantitative results can not be fully used to indicate the consistency degree of qualitative term results. Since it is the goal of grain-size parameter analysis method to reveal the differences of sediments to the greatest extent, it is necessary to fully consider the characteristics of grain-size distribution curve when choosing which method to calculate grain-size parameters. This paper provides a typical case of comparing the results of graphical method and moment method for grain-size parameters of beach sediments. The research results help to improve the understanding of the differences, causes and scientific use of grain-size parameter analysis methods.

, correspAuthors=Qiong Xia, Jieping Tang, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2023 Pratacultural Science. All rights reserved., 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=Gaocong Li, Rongxin Liang, Changliang Tong, Huaqiang Wang, Qiong Xia, Zhiqiang Li, Jieping Tang), CN=ArticleExt(id=1211297765464871791, articleId=1211297763975893793, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=图解法和矩值法粒度参数的定性对比:以琼州海峡岸滩表层沉积物为例, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

前人已开展了大量的关于图解法和矩值法数值结果的相关性分析和相互转换方程的确定工作,但针对定性结果的对比仍较为罕见。本文选取了琼州海峡两岸15个海滩22条断面105个表层沉积物为典型研究对象,分别采用Folk和Ward图解法和Friedman矩值法获取粒度参数结果,构建定量结果的回归关系和对比定性结果的异同。结合前人的研究成果,本文进一步探讨了两种方法结果的可对比性,并分析两种方法的方法差异对沉积物粒度信息提取及使用造成的可能影响。研究结果表明:(1)就定量结果而言,图解法和矩值法计算的平均粒径和分选系数具有强相关性(R2 ≥ 0.951),而偏态和峰态则表现为中等相关(R2 = 0.586)和不相关(R2 = 0.011),表明图解法和矩值法计算粒度参数定量结果之间的相关性并不稳定,这与前人的研究结果基本一致;(2)就定性结果而言,图解法和矩值法的结果之间存在较大偏差,分选系数、偏态和峰态不一致的占比分别达30.48%、55.24%和71.43%,这与定量结果的相关性存在一定程度的偏差,表明定量结果的相关性程度并不能完全用于指示定性术语结果的一致性程度。鉴于最大化地揭示沉积物的差异是粒度参数分析方法追寻的目标,在选择何种方法计算粒度参数时需充分考虑沉积物粒径概率分布曲线的特征。本文提供了一个以海滩沉积物为研究对象的图解法和矩值法粒度参数结果对比的典型案例,研究结果有助于提升对粒度参数分析方法的差异、原因和科学使用等方面的认识。

, correspAuthors=夏琼, 唐杰平, authorNote=null, correspAuthorsNote=
*夏琼(1987-),女,广东省湛江市人,博士,主要从事海洋科学研究。E-mail: ;
唐杰平(1987-),男,江苏省南京市人,博士,主要从事海洋沉积动力学研究。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2023, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=MUC12Bh34JpBZWEwxKmLvw==, magXml=RJjKEZKbxl3L+JixI0FHew==, pdfUrl=null, pdf=k0ZtNDCSZmm0gpeoU6JN7g==, pdfFileSize=1711650, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=WSJdnk9pK4KZ290gix6SOw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=eVLaublWGk+tNv3V3TZuSg==, mapNumber=null, authorCompany=null, fund=null, authors=

李高聪(1987-),男,广东省梅州市人,博士,主要从事海洋地质学研究。E-mail:

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caption=图解法(GM)和矩值法(MM)粒度参数的数值结果及其线性拟合方程, figureFileSmall=nPOaxL2dp+IRYVDs/5Wqaw==, figureFileBig=R7sAUmqCsBSFQIeyPl+AJQ==, tableContent=null), ArticleFig(id=1215304198267261847, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Fig. 2, caption=Comparison of the physical descriptive terms obtained using the graphic method (GM) and the moment method (MM), figureFileSmall=fQCVB+VwnJS5OR7WhKtJwQ==, figureFileBig=gAOqxyFP0Rjnxc670fPNiQ==, tableContent=null), ArticleFig(id=1215304198380508059, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=图2, caption=图解法(GM)和矩值法(MM)粒度参数定性描述术语结果对比, figureFileSmall=fQCVB+VwnJS5OR7WhKtJwQ==, figureFileBig=gAOqxyFP0Rjnxc670fPNiQ==, tableContent=null), ArticleFig(id=1215304198506337184, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Fig. 3, caption=Grain-size distribution curves of the different sorting descriptive terms (graphic method result VS moment method result)

Different color lines indicate different samples

, figureFileSmall=6+wqQvH0/xclgq2CQMRaIw==, figureFileBig=TvzMEE7SMKDbwfOHhkQBYw==, tableContent=null), ArticleFig(id=1215304198602806181, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=图3, caption=不同分选系数定性结果对应的沉积物粒径概率分布曲线(图解法结果VS矩值法结果)

不同颜色线条指示不同样品

, figureFileSmall=6+wqQvH0/xclgq2CQMRaIw==, figureFileBig=TvzMEE7SMKDbwfOHhkQBYw==, tableContent=null), ArticleFig(id=1215304198724441004, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Fig. 4, caption=Grain-size distribution curves of the different skewness descriptive terms (graphic method result VS moment method result)

Different color lines indicate different samples

, figureFileSmall=8bf++1S3SBGSpqk1DzoXGQ==, figureFileBig=SonKnDGpJzOTZ9HZj2Hepg==, tableContent=null), ArticleFig(id=1215304198812521392, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=图4, caption=不同偏态定性结果对应的沉积物粒径概率分布曲线(图解法结果VS矩值法结果)

不同颜色线条指示不同样品

, figureFileSmall=8bf++1S3SBGSpqk1DzoXGQ==, figureFileBig=SonKnDGpJzOTZ9HZj2Hepg==, tableContent=null), ArticleFig(id=1215304198904796085, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Fig. 5, caption=Grain-size distribution curves of the different kurtosis descriptive terms (graphic method result vs moment method result)

Different color lines indicate different samples

, figureFileSmall=tc+/L1tTF5manYDNp9VBpA==, figureFileBig=1m0278V5bMf2XlZpQP1L7Q==, tableContent=null), ArticleFig(id=1215304198997070780, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=图5, caption=不同峰态定性结果对应的沉积物粒径概率分布曲线(图解法结果VS矩值法结果)

不同颜色线条指示不同样品

, figureFileSmall=tc+/L1tTF5manYDNp9VBpA==, figureFileBig=1m0278V5bMf2XlZpQP1L7Q==, tableContent=null), ArticleFig(id=1215304199093539777, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 1, caption=

Equations of grain-size parameters for the graphic and moment mothods

, figureFileSmall=null, figureFileBig=null, tableContent=
粒度参数图解法[5]矩值法[7]
注:D5D16、D25、D50、D75、D84、D95分别对应概率累积曲线上5%、16%、25%、50%、75%、84%和95%的粒径;Xi为粒级组的中值,fi为各粒级范围的百分比含量,$ \sigma $为分选系数的结果。
平均粒径(Φ)${ \displaystyle\frac{{D}_{16}+{D}_{50}+{D}_{84}}{3} }$${ \displaystyle\frac{\displaystyle\sum _{i}^{n}{X}_{i}{f}_{i}}{100} }$
分选系数${ \displaystyle\frac{{D}_{84}-{D}_{16}}{4}+\displaystyle\frac{{D}_{95}-{D}_{5}}{6.6}} $${ {\left[\displaystyle\frac{ \displaystyle\sum _{i}^{n}{ {f}_{i}({X}_{i}-\stackrel{—}{X})^{2} } }{100}\right]}^{1/2} }$
偏态${ \displaystyle\frac{{D}_{84}+{D}_{16}-{2D}_{50}}{2({D}_{84}-{D}_{16})}+\displaystyle\frac{{D}_{95}+{D}_{5}-{2D}_{50}}{2({D}_{95}-{D}_{5})}} $${ \displaystyle\frac{ \displaystyle\sum _{i}^{n}{({X}_{i}-\stackrel{—}{X})^{3} }{f}_{i} }{100{\sigma }^{3} } }$
峰态${ \displaystyle\frac{{D}_{95}-{D}_{5}}{2.44({D}_{75}-{D}_{25})}} $${ \displaystyle\frac{ \displaystyle\sum _{i}^{n}{({X}_{i}-\stackrel{—}{X})^{4} }{f}_{i} }{100{\sigma }^{4} } }$
), ArticleFig(id=1215304199190008773, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表1, caption=

图解法和矩值法粒度参数的计算方程

, figureFileSmall=null, figureFileBig=null, tableContent=
粒度参数图解法[5]矩值法[7]
注:D5D16、D25、D50、D75、D84、D95分别对应概率累积曲线上5%、16%、25%、50%、75%、84%和95%的粒径;Xi为粒级组的中值,fi为各粒级范围的百分比含量,$ \sigma $为分选系数的结果。
平均粒径(Φ)${ \displaystyle\frac{{D}_{16}+{D}_{50}+{D}_{84}}{3} }$${ \displaystyle\frac{\displaystyle\sum _{i}^{n}{X}_{i}{f}_{i}}{100} }$
分选系数${ \displaystyle\frac{{D}_{84}-{D}_{16}}{4}+\displaystyle\frac{{D}_{95}-{D}_{5}}{6.6}} $${ {\left[\displaystyle\frac{ \displaystyle\sum _{i}^{n}{ {f}_{i}({X}_{i}-\stackrel{—}{X})^{2} } }{100}\right]}^{1/2} }$
偏态${ \displaystyle\frac{{D}_{84}+{D}_{16}-{2D}_{50}}{2({D}_{84}-{D}_{16})}+\displaystyle\frac{{D}_{95}+{D}_{5}-{2D}_{50}}{2({D}_{95}-{D}_{5})}} $${ \displaystyle\frac{ \displaystyle\sum _{i}^{n}{({X}_{i}-\stackrel{—}{X})^{3} }{f}_{i} }{100{\sigma }^{3} } }$
峰态${ \displaystyle\frac{{D}_{95}-{D}_{5}}{2.44({D}_{75}-{D}_{25})}} $${ \displaystyle\frac{ \displaystyle\sum _{i}^{n}{({X}_{i}-\stackrel{—}{X})^{4} }{f}_{i} }{100{\sigma }^{4} } }$
), ArticleFig(id=1215304199336809418, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 2, caption=

Physical descriptive terms and their ranges applied to numerical values for grain-size parameters of the graphical and moment methods

, figureFileSmall=null, figureFileBig=null, tableContent=
粒度参数定性描述术语数值范围
图解法[5]矩值法[7]
注:“−”代表无数据。
分选分选极好< 0.35< 0.35
分选好0.35~0.500.35~0.50
分选较好0.50~0.700.50~0.70
分选中等0.70~1.000.70~1.00
分选较差1.00~2.001.00~2.00
分选差2.00~4.002.00~4.00
分选极差> 4.00> 4.00
偏态极负偏–1.0~–0.3< −1.30
负偏–0.3~–0.1−0.30~–0.43
近对称–0.1~0.1–0.43~0.43
正偏0.1~0.30.43~1.30
极正偏0.3~1.0> 1.30
峰态很平坦< 0.67< 1.70
平坦0.67~ 0.901.70~2.55
中等0.90~1.112.55~3.70
尖锐1.11~1.503.70~7.40
很尖锐1.50~3.00> 7.40
非常尖锐> 3.00
), ArticleFig(id=1215304199450055633, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表2, caption=

图解法和矩值法粒度参数的定性描述术语及其数值范围

, figureFileSmall=null, figureFileBig=null, tableContent=
粒度参数定性描述术语数值范围
图解法[5]矩值法[7]
注:“−”代表无数据。
分选分选极好< 0.35< 0.35
分选好0.35~0.500.35~0.50
分选较好0.50~0.700.50~0.70
分选中等0.70~1.000.70~1.00
分选较差1.00~2.001.00~2.00
分选差2.00~4.002.00~4.00
分选极差> 4.00> 4.00
偏态极负偏–1.0~–0.3< −1.30
负偏–0.3~–0.1−0.30~–0.43
近对称–0.1~0.1–0.43~0.43
正偏0.1~0.30.43~1.30
极正偏0.3~1.0> 1.30
峰态很平坦< 0.67< 1.70
平坦0.67~ 0.901.70~2.55
中等0.90~1.112.55~3.70
尖锐1.11~1.503.70~7.40
很尖锐1.50~3.00> 7.40
非常尖锐> 3.00
), ArticleFig(id=1215304199521358809, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 3, caption=

Characteristic values of grain-size parameters for the numerical values of graphic method (GM) and moment method (MM)

, figureFileSmall=null, figureFileBig=null, tableContent=
粒度参数计算方法最小值最大值平均值标准偏差
平均粒径
GM–0.373.172.160.66
MM–0.373.142.100.68
分选系数GM0.311.560.620.27
MM0.341.620.690.27
偏态GM–0.490.460.070.16
MM–3.102.500.061.10
峰态GM0.662.481.130.25
MM1.9522.877.674.33
), ArticleFig(id=1215304199626216412, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表3, caption=

图解法(GM)和矩值法(MM)粒度参数数值结果特征值统计表

, figureFileSmall=null, figureFileBig=null, tableContent=
粒度参数计算方法最小值最大值平均值标准偏差
平均粒径
GM–0.373.172.160.66
MM–0.373.142.100.68
分选系数GM0.311.560.620.27
MM0.341.620.690.27
偏态GM–0.490.460.070.16
MM–3.102.500.061.10
峰态GM0.662.481.130.25
MM1.9522.877.674.33
), ArticleFig(id=1215304199697519586, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 4, caption=

Distribution matrix for the sorting descriptive terms obtained using the graphic method (GM) and the moment method (MM) (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
MMGM
分选极好分选好分选较好分选中等分选较差
分选极好2.860.000.000.000.00
分选好3.8122.860.000.000.00
分选较好0.9513.3316.190.000.00
分选中等0.000.007.6219.050.00
分选较差0.000.000.004.768.57
), ArticleFig(id=1215304199819154408, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表4, caption=

图解法(GM)和矩值法(MM)分选系数术语的分布矩阵(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
MMGM
分选极好分选好分选较好分选中等分选较差
分选极好2.860.000.000.000.00
分选好3.8122.860.000.000.00
分选较好0.9513.3316.190.000.00
分选中等0.000.007.6219.050.00
分选较差0.000.000.004.768.57
), ArticleFig(id=1215304199911429101, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 5, caption=

Distribution matrix for the skewness descriptive terms obtained using the graphic method (GM) and the moment method (MM) (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
MMGM
极负偏负偏近对称正偏极正偏
极负偏1.906.670.000.950.00
负偏0.005.7119.050.000.00
近对称0.000.0018.1011.430.95
正偏0.000.000.9518.101.90
极正偏0.000.000.0013.330.95
), ArticleFig(id=1215304200028869617, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表5, caption=

图解法(GM)和矩值法(MM)偏态术语的分布矩阵(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
MMGM
极负偏负偏近对称正偏极正偏
极负偏1.906.670.000.950.00
负偏0.005.7119.050.000.00
近对称0.000.0018.1011.430.95
正偏0.000.000.9518.101.90
极正偏0.000.000.0013.330.95
), ArticleFig(id=1215304200125338615, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 6, caption=

Distribution matrix for the kurtosis descriptive terms obtained using the graphic method (GM) and the moment method (MM) (%)

, figureFileSmall=null, figureFileBig=null, tableContent=
MMGM
很平坦平坦中等尖锐很尖锐
很平坦0.000.000.000.000.00
平坦0.952.860.000.000.00
中等0.002.863.811.900.00
尖锐0.001.9025.7117.142.86
很尖锐0.000.0022.8612.384.76
), ArticleFig(id=1215304201408795642, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表6, caption=

图解法(GM)和矩值法(MM)峰态术语的分布矩阵(%)

, figureFileSmall=null, figureFileBig=null, tableContent=
MMGM
很平坦平坦中等尖锐很尖锐
很平坦0.000.000.000.000.00
平坦0.952.860.000.000.00
中等0.002.863.811.900.00
尖锐0.001.9025.7117.142.86
很尖锐0.000.0022.8612.384.76
), ArticleFig(id=1215304201501070332, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=EN, label=Table 7, caption=

Regression equations and their coefficients of determination for the grain size parameters computed by the graphic method (GM) and moment method (MMFr or MMMc)

, figureFileSmall=null, figureFileBig=null, tableContent=
对比方法序号沉积环境平均粒径分选系数偏态峰态参考文献
斜率R2斜率R2斜率R2斜率R2
注:“−”代表无数据。
GM- MMFr1黄土高原西部黄土古土壤和风成砂1.010.9991.000.9471.140.3843.060.941[15]
2东沙群岛以东陆坡区沉积物0.940.9950.900.9783.110.7323.560.725[16]
3中沙群岛以东深海盆地沉积物0.950.9860.900.9912.010.7262.600.697[16]
4长江口外近海海域表层沉积物0.9980.9560.1790.411[22]
5钱塘江河口中高潮滩泥质纹层1.060.9991.520.8980.300.8770.260.970[17]
6钱塘江河口中高潮滩砂质纹层1.050.9741.420.8750.090.1560.200.718[17]
7西台吉乃尔盐湖沉积物0.9970.8700.3280.273[18]
8岱海稳定湖相沉积物1.050.9911.120.9590.230.6320.150.622[21]
9洛川典型风成黄土1.050.9871.050.8110.350.8040.110.391[21]
10秦安孙嘉剖面红黏土1.050.9991.260.9540.200.4990.140.742[21]
11酒泉盆地火烧沟河湖相沉积物1.050.9950.970.7240.460.8400.240.617[21]
12胶州湾表层沉积物0.990.9981.070.9662.300.8011.710.597[12]
13江苏潮滩表层沉积物0.970.9980.780.9494.140.3903.750.065[12]
14珠江水下三角洲表层沉积物0.970.9980.970.9712.160.7882.840.791[12]
15湛江南三岛海滩表层沉积物1.040.9791.010.8213.210.2074.190.035[12]
16北部湾陆架表层沉积物0.990.9940.970.9851.920.8442.400.816[12]
17海南潟湖表层沉积物0.970.9980.850.9442.620.4163.240.537[12]
18琼州海峡两岸海滩表层沉积物0.980.9960.970.9515.200.5861.860.011本研究
GM-MMMc19山东半岛月湖和荣成湾沉积物0.9980.9850.7710.248[14]
20宜昌莲沱河河道沉积物1.050.9950.960.9070.470.1300.430.494[23]
21福建泉州湾表层沉积物0.940.9660.830.6314.240.1461.200.084[19]
22金沙江上游雪隆囊溃坝堆积物(上游)0.720.9480.930.8241.890.7576.910.822[20]
23金沙江上游雪隆囊溃坝堆积物(中游)0.920.9940.890.9591.730.8152.470.942[20]
24金沙江上游雪隆囊溃坝堆积物(下游)0.990.9911.450.9012.250.4914.660.580[20]
25湛江南三岛海滩表层沉积物1.040.9791.010.8210.130.0670.040.159[11]
), ArticleFig(id=1215304201614316544, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211297763975893793, language=CN, label=表7, caption=

图解法(GM)和矩值法(MMFr或MMMc)粒度参数回归方程的斜率和拟合优度(R2)统计表

, figureFileSmall=null, figureFileBig=null, tableContent=
对比方法序号沉积环境平均粒径分选系数偏态峰态参考文献
斜率R2斜率R2斜率R2斜率R2
注:“−”代表无数据。
GM- MMFr1黄土高原西部黄土古土壤和风成砂1.010.9991.000.9471.140.3843.060.941[15]
2东沙群岛以东陆坡区沉积物0.940.9950.900.9783.110.7323.560.725[16]
3中沙群岛以东深海盆地沉积物0.950.9860.900.9912.010.7262.600.697[16]
4长江口外近海海域表层沉积物0.9980.9560.1790.411[22]
5钱塘江河口中高潮滩泥质纹层1.060.9991.520.8980.300.8770.260.970[17]
6钱塘江河口中高潮滩砂质纹层1.050.9741.420.8750.090.1560.200.718[17]
7西台吉乃尔盐湖沉积物0.9970.8700.3280.273[18]
8岱海稳定湖相沉积物1.050.9911.120.9590.230.6320.150.622[21]
9洛川典型风成黄土1.050.9871.050.8110.350.8040.110.391[21]
10秦安孙嘉剖面红黏土1.050.9991.260.9540.200.4990.140.742[21]
11酒泉盆地火烧沟河湖相沉积物1.050.9950.970.7240.460.8400.240.617[21]
12胶州湾表层沉积物0.990.9981.070.9662.300.8011.710.597[12]
13江苏潮滩表层沉积物0.970.9980.780.9494.140.3903.750.065[12]
14珠江水下三角洲表层沉积物0.970.9980.970.9712.160.7882.840.791[12]
15湛江南三岛海滩表层沉积物1.040.9791.010.8213.210.2074.190.035[12]
16北部湾陆架表层沉积物0.990.9940.970.9851.920.8442.400.816[12]
17海南潟湖表层沉积物0.970.9980.850.9442.620.4163.240.537[12]
18琼州海峡两岸海滩表层沉积物0.980.9960.970.9515.200.5861.860.011本研究
GM-MMMc19山东半岛月湖和荣成湾沉积物0.9980.9850.7710.248[14]
20宜昌莲沱河河道沉积物1.050.9950.960.9070.470.1300.430.494[23]
21福建泉州湾表层沉积物0.940.9660.830.6314.240.1461.200.084[19]
22金沙江上游雪隆囊溃坝堆积物(上游)0.720.9480.930.8241.890.7576.910.822[20]
23金沙江上游雪隆囊溃坝堆积物(中游)0.920.9940.890.9591.730.8152.470.942[20]
24金沙江上游雪隆囊溃坝堆积物(下游)0.990.9911.450.9012.250.4914.660.580[20]
25湛江南三岛海滩表层沉积物1.040.9791.010.8210.130.0670.040.159[11]
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图解法和矩值法粒度参数的定性对比:以琼州海峡岸滩表层沉积物为例
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李高聪 1, 2, 3 , 梁荣鑫 1 , 仝长亮 2, 3, 4 , 王华强 5 , 夏琼 1, * , 李志强 1 , 唐杰平 1, *
海洋学报 | 论文 2023,45(2): 98-109
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海洋学报 | 论文 2023, 45(2): 98-109
图解法和矩值法粒度参数的定性对比:以琼州海峡岸滩表层沉积物为例
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李高聪1, 2, 3 , 梁荣鑫1, 仝长亮2, 3, 4, 王华强5, 夏琼1, * , 李志强1, 唐杰平1, *
作者信息
  • 1 广东海洋大学 海洋技术系,广东 湛江 524088
  • 2 海南省地质测试研究中心,海南 海口 570206
  • 3 海南省海洋地质资源与环境重点实验室,海南 海口 570206
  • 4 海南省海洋地质调查研究院,海南 海口 570206
  • 5 交通运输部 南海航海保障中心广州海事测绘中心,广东 广州 510320
  • 李高聪(1987-),男,广东省梅州市人,博士,主要从事海洋地质学研究。E-mail:

通讯作者:

*夏琼(1987-),女,广东省湛江市人,博士,主要从事海洋科学研究。E-mail: ;
唐杰平(1987-),男,江苏省南京市人,博士,主要从事海洋沉积动力学研究。E-mail:
Qualitative comparative analysis on grain-size parameters of derived from graphic and moment methods: a case study of the surficial sediment of coastal beaches of Qiongzhou Strait
Gaocong Li1, 2, 3 , Rongxin Liang1, Changliang Tong2, 3, 4, Huaqiang Wang5, Qiong Xia1, * , Zhiqiang Li1, Jieping Tang1, *
Affiliations
  • 1Department of Marine Technology, Guangdong Ocean University, Zhanjiang 524088, China
  • 2Hainan Geology Detection and Research Centre of Hainan Province, Haikou 570206, China
  • 3Laboratory of Marne Geology Resources and Environment of Hainan Province, Haikou 570206, China
  • 4Marine Geological Institute of Hainan Province, Haikou 570206, China
  • 5The Guangzhou Hydrographic Center of the Navigation Guarantee Center for South China Sea, Ministry of Transport, Guangzhou 510320, China
出版时间: 2023-02-01 doi: 10.12284/hyxb2023005
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前人已开展了大量的关于图解法和矩值法数值结果的相关性分析和相互转换方程的确定工作,但针对定性结果的对比仍较为罕见。本文选取了琼州海峡两岸15个海滩22条断面105个表层沉积物为典型研究对象,分别采用Folk和Ward图解法和Friedman矩值法获取粒度参数结果,构建定量结果的回归关系和对比定性结果的异同。结合前人的研究成果,本文进一步探讨了两种方法结果的可对比性,并分析两种方法的方法差异对沉积物粒度信息提取及使用造成的可能影响。研究结果表明:(1)就定量结果而言,图解法和矩值法计算的平均粒径和分选系数具有强相关性(R2 ≥ 0.951),而偏态和峰态则表现为中等相关(R2 = 0.586)和不相关(R2 = 0.011),表明图解法和矩值法计算粒度参数定量结果之间的相关性并不稳定,这与前人的研究结果基本一致;(2)就定性结果而言,图解法和矩值法的结果之间存在较大偏差,分选系数、偏态和峰态不一致的占比分别达30.48%、55.24%和71.43%,这与定量结果的相关性存在一定程度的偏差,表明定量结果的相关性程度并不能完全用于指示定性术语结果的一致性程度。鉴于最大化地揭示沉积物的差异是粒度参数分析方法追寻的目标,在选择何种方法计算粒度参数时需充分考虑沉积物粒径概率分布曲线的特征。本文提供了一个以海滩沉积物为研究对象的图解法和矩值法粒度参数结果对比的典型案例,研究结果有助于提升对粒度参数分析方法的差异、原因和科学使用等方面的认识。

粒度参数  /  海滩沉积物  /  图解法和矩值法  /  定量和定性对比  /  琼州海峡两岸

Little research attention has been paid to comparison of the descriptive terms used in graphical method and moment method for grains-size parameters, although some work has been done on comparison of the numerical values and mutual conversion equations. In this paper, 105 surface sediments from 22 sections of 15 beaches on both sides of the Qiongzhou Strait are selected as typical research objects. The grain-size parameter results are obtained by the Folk & Ward graphic method and Friedman moment method respectively. The regression relationship of quantitative results is constructed and the similarities and differences of qualitative results are compared. Combined with the previous research results, this paper further discusses the comparability of the results of the two methods, and analyzes the possible impact of the differences between the two methods on the extraction and use of sediment particle size information. The results show that: (1) in terms of quantitative results, the average particle size and sorting coefficient calculated by graphic method and moment method have strong correlation (R2 ≥ 0.951), while the skewness and kurtosis show moderate correlation (R2 = 0.586) and uncorrelation (R2 = 0.011), indicating that the correlation between the quantitative results of particle size parameters calculated by the two methods is not stable, which is basically consistent with the previous research results; (2) as far as qualitative results are concerned, there is a large deviation between the results of graphic method and moment method. The proportion of inconsistent sorting coefficient, skewness and kurtosis is 30.48%, 55.24% and 71.43% respectively, which deviates from the correlation of quantitative results to a certain extent, indicating that the correlation degree of quantitative results can not be fully used to indicate the consistency degree of qualitative term results. Since it is the goal of grain-size parameter analysis method to reveal the differences of sediments to the greatest extent, it is necessary to fully consider the characteristics of grain-size distribution curve when choosing which method to calculate grain-size parameters. This paper provides a typical case of comparing the results of graphical method and moment method for grain-size parameters of beach sediments. The research results help to improve the understanding of the differences, causes and scientific use of grain-size parameter analysis methods.

grain-size parameters  /  beach sediment  /  graphic and moment methods  /  quantitative and qualitative comparison  /  both sides of Qiongzhou Strait
李高聪, 梁荣鑫, 仝长亮, 王华强, 夏琼, 李志强, 唐杰平. 图解法和矩值法粒度参数的定性对比:以琼州海峡岸滩表层沉积物为例. 海洋学报, 2023 , 45 (2) : 98 -109 . DOI: 10.12284/hyxb2023005
Gaocong Li, Rongxin Liang, Changliang Tong, Huaqiang Wang, Qiong Xia, Zhiqiang Li, Jieping Tang. Qualitative comparative analysis on grain-size parameters of derived from graphic and moment methods: a case study of the surficial sediment of coastal beaches of Qiongzhou Strait[J]. Haiyang Xuebao, 2023 , 45 (2) : 98 -109 . DOI: 10.12284/hyxb2023005
粒度分布特征是沉积物的基本性质之一,也是获取沉积物类型、粒径输运趋势、水动力强度和沉积环境演变信息的重要途径[1-4]。刻画沉积物粒度的分布信息方式之一是采用4个粒度参数,即平均粒径、分选系数、偏态和峰态,分别表征了沉积物粒径的粗细、均匀性、对称性和相对集中的程度[5-8]。计算粒度参数的方法主要分为图解法和矩值法两大类。前者是基于沉积物粒径分析的结果,绘制出粒径频率分布累积曲线,随后在曲线上读取几个特征点对应的粒径值,最后利用较为简单的统计学公式求取粒度参数[5-6]。后者则是将平均粒径、分选系数、偏态和峰态分别定义为沉积物的全体粒径概率分布数据的一、二、三和四阶矩函数[7-8]。在众多的算法当中,使用较多的为Folk和Ward图解法和Friedman矩值法,它们也是沉积学和海洋地质学领域研究人员常用的沉积物粒度分布和统计集成软件“GRADISTAT”所采用的分析方法[9-10]
从信息提取的角度而言,最大化地揭示沉积物的差异是粒度参数分析方法追寻的目标。目前,图解法和矩值法均采用定量和定性两类指标来刻画沉积物粒度参数的异同,两者一般配套使用。前者是指采用特定统计学公式计算沉积物样品各粒度参数的数值结果,而后者指采用系列术语对定量结果的特定数值范围进行定性描述,旨在更好地揭示各粒度参数的分布特征。需指出的是,图解法和矩值法采用相同的定性术语来刻画沉积物的分选系数、偏态和峰态,但使用不同的统计方程来计算相关参数的定量结果。可以推理,相同的描述术语意味着通过两种方法获得的相同定性结果之间应具有一定的可比性。前人的研究指出,实现这一可比性的前提是图解法和矩值法的定量结果之间具有较强的相关性和较为稳定的数学转换关系[10-12]。针对这一问题,前人已针对不同沉积环境(黄土古土壤、风成砂、盐湖、河道、堰塞湖溃坝堆积物、潮滩、海滩、潟湖、海湾、水下三角洲、大陆架、大陆坡和深海盆地等)的沉积物样品开展了大量的对比分析工作[11-23]。尽管如此,前人的研究主要集中在两种方法的定量结果之间的关系的对比上,而针对定性结果的分析则较为罕见,亟需开展基于定量和定性结果的系统对比工作。
针对图解法和矩值法粒度参数的定性结果是否具有可比性的问题,本文选取了琼州海峡两岸的海滩沉积物为典型研究对象,分别采用Folk和 Ward图解法[5]和Friedman矩值法[8],计算粒度参数的数值,确定粒度参数的定性术语,分析定量结果的回归关系,对比定性结果的异同。在此基础上,与前人的定量结果相比较,系统探讨不同沉积环境沉积物图解法和矩值法粒度参数的定量关系,分析图解法和矩值法结果产生差异的原因,并探讨了图解法和矩值法方法差异对沉积物粒度信息提取及使用的可能影响。
本文的研究对象为2021年7月27日至31日在琼州海峡两岸15个海滩的表层(取表层5 cm)沉积物样品。琼州海峡北岸采样点包括白沙湾、大塘、青安湾、赤坎和下塘5个海滩,共计包含9条断面的27个样品。琼州海峡南岸的采样海滩有10个,从东到西依次为桂林洋、希尔顿、假日、金沙湾、澄迈、沙土湾、博铺港、佳才村、光村和新村海滩,共计包含13条断面的78个样品。每条断面均参照潮上带,潮间带和潮下带的分布位置采样。
沉积物样品的粒度测试在华东师范大学河口海岸学国家重点实验室完成。首先,让样品充分混合后用挖勺取适量样品加入100 mL烧杯中,并加入体积分数为10%的盐酸,静置24 h,去除样品中的碳酸钙成分;其次,加入纯水至杯满后静置12 h,去除上清液后加入纯水至杯满,用pH试纸检查溶液是否为中性,若为酸性,则重复上述操作直至溶液呈中性;第三,加入10 mL过氧化氢,静置48 h去除样品中有机质成分;第四,加入纯水清洗样品中的过氧化氢残留,沉降后去除上清液,重复清洗直至溶液呈中性;第五,将样品放至烘箱,设定80℃进行12 h以上的烘干,去除样品中水分;最后,将处理好的样品放入多功能粒径和粒形分析仪(德国莱驰科技研发的Camsizer X2)进行粒度粒形测试。Camsizer X2主要基于动态图像分析原理提取沉积物的精确粒度粒形信息,其测量范围为0.6 μm至8 mm。
基于粒度测试的结果,本文拟采用Folk 和 Ward图解法和Friedman矩值法研究海滩样品的粒度参数,包括平均粒径、分选系数、偏态和峰态4个参数。在计算时,图解法需获取沉积物样品粒度分布数据中累积含量为5%、16%、25%、50%、75%、84%和95%的特征粒径数据D5D16D25D50D75D84D95[4]。本文通过Matlab程序中的插值功能获得各样品上述特征值的具体数值。矩值法则将粒度测试的粒径频率数据结果直接作为输入数据。表1展示了两类方法的计算公式,表2为两种方法计算出不同粒度参数数值结果指示的定性描述术语参照标准。
图解法的平均粒径的值域为–0.37~3.17,平均值为2.16, 标准偏差为0.66。矩值法的平均粒径的值域为–0.37~3.14,平均值为2.10,标准偏差为0.68。因此,就平均粒径而言,两种方法的计算结果几乎一致。分选系数与平均粒径的情况类似,两种方法计算结果比较接近。分选系数的值域范围为0.31~1.62,平均值为0.62~0.69,标准偏差为0.27。图解法计算偏态的标准偏差较小,仅为0.16;偏态的值域为–0.49~0.46,平均值为0.07。矩值法计算偏态的标准偏差较大,数值达1.10;其值域为–3.10~2.50,平均值为0.06。与偏态结果相似,图解法计算峰态的标准偏差数值(0.25)要比矩值法计算结果(4.33)明显小。前者的值域和平均值分别为0.66~2.48和1.13,后者的为1.95~22.87和7.67。表3列出上述结果。
图1展示了通过图解法和矩值法计算获得的研究区沉积物样品4个粒度参数的数值结果及其线性拟合方程结果。两种方法计算的平均粒径结果非常接近,其线性拟合方程的斜率(0.98)和拟合优度(R2 =0.996)均接近1,截距(–0.02)接近0。分选系数的结果与平均粒径一致。其拟合方程的斜率(0.97)和拟合优度(R2 =0.951)均接近1,截距(0.09)亦接近0。偏态结果的拟合程度一般,其拟合优度仅为0.586,斜率和截距分别为5.2和–0.33。峰态结果的拟合程度极弱(R2 = 0.011),其斜率和截距分别为1.86和5.57。因此,两种方法计算得到的平均粒径和分选系数结果强相关且可认为是相等的,而偏态的结果中等相关,峰态结果则没有相关性。
图2展示了通过图解法和矩值法计算获得的3个粒度参数的定性描述术语结果。就分选系数而言,两种方法在73个样品中给出了一致的判定结果(图2a浅绿色区域),32个样品结果不一致(图2a粉色区域)。47个样品图解法和矩值法偏态结果一致(图2b浅绿色区域);另外58个则不一致(图2b粉色和黄色区域)。30个样品峰态结果一致(图2c浅绿色区域),另外75个样品则不一致(图2c粉色和黄色区域)。因此,依据两种方法判定的定性描述术语结果在3个粒度参数中均存在较大差异。
就分选系数而言,两种方法在69.52%的样品中判定一致,其中包含2.86%的分选极好、22.86%的分选好、16.19%的分选较好、19.05%的分选中等和8.57%的分选较差;其余30.48%均属于图解法结果比矩值法结果分选情况更好的类型(表4)。
就偏态而言,44.76%的样品图解法和矩值法偏态结果一致,其中包括1.90%的极负偏、5.71%的负偏、18.10%的近对称、18.10%的正偏和0.95%的极正偏;其余的14.29%个样品属于图解法结果比矩值法结果更负偏的类型,40.95%的样品则术语图解法结果比矩值法结果更正偏的类型(表5)。
就峰态而言,28.57%的样品的结果一致,其中2.86%的平坦、3.81%的中等、17.14%的尖锐和4.76%的很尖锐;其余66.67%的样品属于图解法结果比矩值法结果更平坦的类型,4.76%的样品则属于图解法结果比矩值法结果更尖锐的类型(表6)。
本研究分析了琼州海峡两岸15个海滩的105个表层沉积物关于两种方法数值结果的数值转换关系。结果表明,图解法和矩值法计算的平均粒径(R2 = 0.996)和分选系数(R2 = 0.951)结果强相关,偏态结果(R2 = 0.586)中等相关,而峰态结果(R2 = 0.011)则没有相关性。仅通过本文的案例分析不能说明上述结果是否在其他研究区具有普适性,但将其与前人的研究成果进行对比可缩小这一问题的解空间。表7显示了通过文献资料法收集的图解法和矩值法粒度参数结果之间回归方程的斜率和拟合优度(R2)的统计表。在对比的过程中,研究人员分析的图解法是指Folk 和 Ward(1957)提出的图解法(GM)[5],而矩值法则可分为Friedman(1962)提出的矩值法(MMFr[8]和McManus(1988)提出的矩值法(MMMc[9]两种。上述工作提供了大量的两类方法结果之间数值关系的斜率和拟合优度数据,可与本文的结果一起探讨两者之间的数值转换关系。
就GM-MMFr关系而言,平均粒度和分选系数均具有较强的相关性,偏态和峰态的相关性在不同沉积环境的沉积物样品结果中差异较大。平均粒径的斜率值域为0.94~1.06,拟合优度值域为0.974~0.999,表明两种方法的计算结果几乎一致。分选系数的斜率和拟合优度的值域也分别达到了0.78~1.52和0.724~0.991,表明两种方法的结果也较为接近,可通过简单的数学关系相互转换,但拟合效果要比前者差一些。偏态和峰态的结果中分别有约1/2和1/3的沉积环境拟合效果较好(R2 > 0.7),但它们的斜率相差较大(0.20 < 斜率 < 3.56),表明两种方法计算结果之间的数学转换关系具有一定的不稳定性。其余偏态和峰态结果的拟合优度则相对较小,呈中等、弱或不相关关系(0.011 < R2 < 0.697)。在所有统计数据中,仅有不到1/4的沉积环境(东沙群岛以东陆坡区沉积物、钱塘江河口中高潮滩泥质纹层、珠江水下三角洲表层沉积物和北部湾陆架表层沉积物)的4个粒度参数的两种方法结果之间均具有强相关关系,另外超过3/4的沉积环境沉积物样品则表现为平均粒径和分选系数强相关,而偏态和峰态2个中仅有1个或0个粒度参数呈强相关。
就GM-MMMc关系而言,平均粒径和分选系数总体上具有较强的相关性,而偏态和峰态的相关性在不同沉积环境中发生变化。由于MMFr矩值法和MMMc矩值法具有同样的平均粒径和分选系数计算公式,则两者的结果可直接比较。大部分沉积环境的平均粒径和分选系数结果与GM-MMFr关系对比分析中的沉积环境一致;它们的平均粒径的斜率值域为0.72~1.05,拟合优度值域为0.948~0.998,而分选系数的斜率值域为0.83~1.45,拟合优度值域为0.821~0.985。特殊的在于金沙江上游雪隆囊溃坝堆积物(上游)的平均粒径的斜率仅为0.72,福建泉州湾表层沉积物的分选系数拟合优度值仅为0.631,扩展了GM-MMFr关系中平均粒径和分选系数结果的斜率和拟合优度的数值范围。偏态中分别有约1/2的沉积环境拟合效果较好(R2 > 0.7),斜率较为接近(1.73和1.89)。峰态中有约1/3的沉积环境拟合效果较好,但斜率相差较大(2.47和6.91),其余的拟合优度均小于0.6。在所有统计数据中,仅有2个沉积环境(福建泉州湾表层沉积物和金沙江上游雪隆囊溃坝堆积物(上游))的4个粒度参数的两种方法结果之间均具有强相关关系。除个别外,其他沉积环境的平均粒径和分选系数具有强相关关系,而偏态和峰态2个粒度参数中仅有1个或0个呈强相关关系(0.067 < R2 < 0.7171)。因此,图解法和矩值法计算粒度参数定量结果之间的相关性并不稳定。
前人已开展了大量的关于两类方法数值结果的相关性分析和相互转换方程的确定工作(表7),但针对定性结果的对比分析较为罕见[11-12]。针对这一不足,本文对比分析了琼州海峡两岸15个海滩表层沉积物样品关于图解法和矩值法定量和定性术语结果的异同情况。结果表明,定性术语结果在分选系数(30.48%)、偏态(47.14%)和峰态(65.71%)中均存在较大比重的不一致性(图2表4表5表6)。假若图解法和矩值法能够获得较为一致的定性结果,两种方法定量结果之间的强、中等和弱相关应与定性结果的高、中等和低一致性相对应。显然,琼州海峡两岸的海滩表层沉积物的情况与上述推理存在一定程度的偏差,这就表明图解法和矩值法的定性术语结果是不完全对等的。
上述偏差产生的原因与两种方法采用的计算公式的差异和沉积物粒径概率分布曲线的特征有关[12, 24]。就计算公式而言,图解法的输入参数较少,即D5D16D25D50D75D84D95共7个特征值,而矩值法则将粒径分析软件所提供的全部粒径及其占比数据作为输入(本文的情况是160对特征值)。两者的共性是均考虑了位于概率累积曲线5%~95%的粒径的影响,但后者不仅加密了5%~95%之间其他粒径的影响,还考虑了前后各占比5%的粒径的影响,从而能更加精细地刻画不同沉积物之间的差异。前人指出,若沉积物粒径概率分布曲线服从正态分布规律,图解法和矩值法的定量结果之间应具有较强的相关性;若分布曲线不属于正态分布,两者结果的相关性将随阶矩的增加而变化较大,原因是后者的算法对两头末端的5%更加敏感[12, 14, 17, 24]
这一推理是否适用于两种方法的定性结果,本文试图通过琼州海峡两岸海滩沉积物的案例分析来解答。这些海滩沉积物具有典型的海滩砂的粒径概率分布曲线特征,即绝大多数样品都具有单峰的曲线分布特征(图3)。当沉积物粒径概率分布曲线服从或近似服从正态分布时,图解法和矩值法分选系数的定性结果较为一致或近似(图3a图3e);而当情况属于服从非正态分布时,一部分样品表现为一致(图3f图3h图3j),而另一部分样品则表现为图解法结果比矩值法结果分选情况更好(图3g图3i)。就偏态而言,当分布曲线服从或近似服从正态分布时,图解法和矩值法的结果亦较为一致或近似(图4e);而当情况服从非正态分布时,一部分样品表现为一致(图4a图4c图4i图4m),一部分样品则表现为图解法结果比矩值法结果更负偏(图4f图4j图4k图4l),而另一部分则表现为图解法结果比矩值法结果更正偏(图4b图4d图4g图4h)。就峰态而言,当沉积物粒径概率分布曲线服从或近似服从正态分布时,图解法和矩值法的结果较为一致或近似(图5e图5i图5k);而当情况属于服从非正态分布时,一部分样品表现为一致(图5b图5l),一部分样品则表现为图解法结果比矩值法结果更平坦(图5a图5c图5d图5f图5g图5j),而少部分表现为图解法结果比矩值法结果更尖锐(图5h)。因此,图解法和矩值法定量结果的相关性程度并不能完全用于指示两者定性术语结果的一致性。
图解法和矩值法分别给出了定量化和定性化粒度参数的计算方程和描述术语。但采用何种方法才能更加有效地揭示出沉积物之间的差异取决于各自方程对特定研究区沉积物粒径概率分布曲线的敏感程度。平均粒径指示了粒径频率分布的中心趋势,可用于反映沉积物的平均动能。前文研究表明,图解法和矩值法计算的平均粒径的定量结果之间具有强相关性,且其斜率也接近1(0.92~1.05),表明两种方法的计算结果几乎一致。因此,图解法和矩值法的方法差异不会对基于平均粒径的信息提取造成影响。分选系数则指示了沉积物颗粒的均匀程度,可用于揭示将具有相似特征的颗粒从复杂环境中筛选出来的动力过程。表7显示了图解法和矩值法计算得到的分选系数的定量结果之间同样具有强相关关系。值得注意的是,两者间的斜率同样也存在一定程度的波动情况,其值域范围为0.78~1.52。基于数值越大,分选效果则变差的逻辑,本文推理:当两者的斜率小于1时,图解法方程对沉积物之间分选效果的差异更为敏感;而当斜率大于1时,矩值法方程则更敏感。
偏态和峰态描述了沉积物粒径频率曲线的不对称程度和频率曲线两端的分选与中间部分分选的比率,分别可用于反映沉积过程中能量的变异情况和用于判断沉积环境以及追溯物源。在表7中的25个案例中,图解法和矩值法的偏态和峰态的定量结果之间的相关性并不稳定,即使相关性较强,斜率的数值也变化较大(0.14~6.91),表明两方法结果之间并不存在普适的相互转换关系。然而,图解法和矩值法获得的粒度参数结果之间具有稳定的数值转换关系是确定矩值法的定性描述术语值域范围的重要前提。相关性不稳定意味着采用目前的Folk和Ward图解法和Friedman矩值法分别确定的定性术语结果之间失去了相互比较的基础。对于两种方法计算结果具有强相关性的研究区而言,重新确定矩值法的粒度参数的定性术语数值范围是重建两者定性结果可比性的有效渠道[12, 24]。但新建立的关系是否适用于其他区域或研究领域(如沉积物输运特征分析[25-26]、物源分析[27-28]、环境变化分析[29-31]),则需要开展进一步的研究工作。对于两种方法的定量结果之间表现为中等和弱相关关系的研究区而言,在理论上矩值法应能更有效地揭示沉积物偏态或峰态的信息,原因在于该方法充分考虑了沉积物粒径概率分布曲线的整体情况。
(1)图解法和矩值法计算的平均粒径和分选系数数值较为一致。平均粒径的值域为–0.37~3.17,标准偏差为0.66~0.68。分选系数值域为0.31~1.62,标准偏差为0.27。图解法计算的偏态值域为–0.49~0.46,标准偏差为0.16;矩值法结果为–3.10~2.50,标准偏差达1.10。图解法计算的峰态值域为0.66~2.48,标准偏差为0.25;矩值法结果为1.95~22.87,标准偏差达4.33。
(2)就数值结果的相关性而言,图解法和矩值法计算的平均粒径和分选系数结果强相关(R2 ≥ 0.951),而偏态和峰态的结果则表现为中等相关(R2 = 0.586)和不相关(R2 = 0.011)。这一结果与前人的研究结果相符,即平均粒度和分选系数均具有较强的相关性(0.999 ≥ R2 ≥ 0.724),而偏态和峰态的相关性则在不同沉积环境的沉积物样品结果中差异较大(0.970 ≥ R2 ≥ 0.035)。
(3)就定性结果而言,图解法和矩值法的分选系数存在30.48%不一致的情况,而偏态和峰态不一致的分别占比为55.24%和71.43%。因此,图解法和矩值法的定性术语结果存在一定程度的不可对比性。
  • 国家自然科学基金(42176167);广东省科技厅科技基础条件建设项目(2021B1212110005);2022年海南省自然科学基金(422RC800);海南省海洋地质资源与环境重点实验室开放课题重点课题 (HNHYDZZYHJKF015);湛江市创新创业团队引育“领航计划”(211207157080994)。
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2023年第45卷第2期
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doi: 10.12284/hyxb2023005
  • 接收时间:2022-06-14
  • 首发时间:2025-12-26
  • 出版时间:2023-02-01
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  • 收稿日期:2022-06-14
  • 修回日期:2022-08-15
基金
国家自然科学基金(42176167);广东省科技厅科技基础条件建设项目(2021B1212110005);2022年海南省自然科学基金(422RC800);海南省海洋地质资源与环境重点实验室开放课题重点课题 (HNHYDZZYHJKF015);湛江市创新创业团队引育“领航计划”(211207157080994)。
作者信息
    1 广东海洋大学 海洋技术系,广东 湛江 524088
    2 海南省地质测试研究中心,海南 海口 570206
    3 海南省海洋地质资源与环境重点实验室,海南 海口 570206
    4 海南省海洋地质调查研究院,海南 海口 570206
    5 交通运输部 南海航海保障中心广州海事测绘中心,广东 广州 510320

通讯作者:

*夏琼(1987-),女,广东省湛江市人,博士,主要从事海洋科学研究。E-mail: ;
唐杰平(1987-),男,江苏省南京市人,博士,主要从事海洋沉积动力学研究。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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