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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2023.1220331</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Sediment transport trend and its influencing factors in coastal bedrock island sea areas-a case study of Chudao island, China</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Zhou</surname>
<given-names>Yadi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2306563"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Hu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1937281"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yan</surname>
<given-names>Yuru</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>School of Marine Science and Technology, Tianjin University</institution>, <addr-line>Tianjin</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Observation and Research Station of East China Coastal Zone, Ministry of Natural Resources</institution>, <addr-line>Nantong</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Xingsen Guo, University College London, United Kingdom</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Zhenhao Wang, First Institute of Oceanography, MNR, China; Jialing Hao, Hohai University, China; Piyali Chowdhury, Centre for Environment, Fisheries and Aquaculture Science (CEFAS), United Kingdom</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Hu Wang, <email xlink:href="mailto:hu.wang@tju.edu.cn">hu.wang@tju.edu.cn</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>11</day>
<month>07</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>10</volume>
<elocation-id>1220331</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>05</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>26</day>
<month>06</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Zhou, Wang and Yan</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Zhou, Wang and Yan</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Coastal bedrock islands sea areas have a unique natural environment, frequent human activities, and complex sedimentary dynamic processes. In this paper, we select the Chudao Island sea area off the coast of Shandong Peninsula, China, as a typical research area to investigate the sediment transport trends and influencing factors by means of high-precision bathymetric survey, high-density sediment sampling, grain-size trend analysis and hydrodynamic numerical modeling. Results and analysis indicate that the grain size parameters including mean grain-size, sorting coefficient and skewness are zonal distributed, roughly parallel to the isobaths. While the overall sediment transport trend is from island shore to sea, with several convergence centers near the loop centers of bottom flow and at the edge of the agriculture area. The near-bottom flow velocity is primary factor that controlling the significance of sediment transport trend, while the flow decides the general patterns of sediment transport trend and sediment distribution. Submarine topography can either directly transport sediments down its slope, or indirectly affect the direction of sediment transport by constraining the near-bottom flow from shallow to deep waters. Besides the natural factors of bottom flow and submarine topography, human activities represented by aquaculture also affect the sediment transport trend in coastal bedrock island sea areas. First, the increased sedimentation rate caused by organic matters and the diffusion of scallop fragments may cause sediment coarsening. Second, the artificial aquaculture facilities can reduce flow velocity and therefore hinder the initiation, suspension and transport of sediment near the aquaculture areas. Our methods and findings provide high-resolution details to insight into the sediment transport trends to improve the understanding of the modern sediment dynamics in small-scale coastal bedrock island sea areas and provide reference for corresponding engineering and agriculture activities.</p>
</abstract>
<kwd-group>
<kwd>sediment transport</kwd>
<kwd>grain size trend analysis</kwd>
<kwd>hydrodynamic numerical modeling</kwd>
<kwd>coastal bedrock island sea areas</kwd>
<kwd>bathymetric survey and sediment sampling</kwd>
</kwd-group>
<counts>
<fig-count count="7"/>
<table-count count="0"/>
<equation-count count="5"/>
<ref-count count="70"/>
<page-count count="12"/>
<word-count count="5734"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Coastal Ocean Processes</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The bedrock coast, which is mainly composed of rocks, takes up nearly 75% of the world&#x2019;s coast (<xref ref-type="bibr" rid="B49">Rosser et&#xa0;al., 2005</xref>). The length of bedrock coast, 5,000 km, also accounts for about 30% of the total coastline of China (<xref ref-type="bibr" rid="B59">Wang and Aubrey, 1987</xref>). The bedrock coast, which is characterized by steep topography, interlaced headlands and bays, and various erosion and accumulation landforms, develops many famous deep-water harbors. Bedrock islands, which usually develop adjacent to bedrock coasts, are widely distributed in China&#x2019;s coasts, e.g., Liaodong Peninsula, Shandong Peninsula, and the coast south of Hangzhou Bay, accounting for about 90% of the total islands of China. In this study, we focus on the sea areas adjacent to bedrock coasts and with bedrock islands therein. These sea areas not only are typical regions of strong land-sea interaction due to its complex submarine topography and its variable hydrodynamic and sediment dynamics (<xref ref-type="bibr" rid="B17">French and Burningham, 2009</xref>), but also have severe interaction between the nature marine environment and human activities resulting from an increasing coastal engineering and marine aquaculture.</p>
<p>Marine sediments are the loose substances deposited at the bottom of seawater over the basement rock (<xref ref-type="bibr" rid="B51">Singer, 1984</xref>). The distribution, thickness, type and property of sediments are complex and changeable due to various water depth, seabed topography, hydrodynamics, physical and chemical properties of sea water, and marine biological activities. Sediments, which may have strong interactions with ocean hydrodynamics such as waves, tides, storm surges, and currents, can be initiated, suspended, deposited, and transported, and thus in turn shape and change the topography of seafloor. The calculation of sediment transport rate is essential to marine sedimentary dynamics (<xref ref-type="bibr" rid="B3">Bakhtyar et&#xa0;al., 2009</xref>), among which the research ideas can be mainly classified into two categories. The first investigates sediment transport and source-sink characteristics through the inherent properties of sediments such as grain size, magnetism, mineral components, etc., in which sediment sampling and corresponding analysis are applied (<xref ref-type="bibr" rid="B1">Andrews et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B61">Wang et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B64">Yu et&#xa0;al., 2019b</xref>). The second approach believes that sediment transport is mainly caused by the hydrodynamic-induced incipient motion and suspension of sediment, through which the characteristics and trends of sediment transport are mainly investigated based on numerical models of hydrodynamics and sediment dynamics (<xref ref-type="bibr" rid="B64">Yu et&#xa0;al., 2019b</xref>). Sediment transport trend, which is a stable transport trend of sediments formed under the long-term action of various factors including hydrodynamics, provenance, biological activities, contains important information for interpreting the evolution of sedimentary environment, sediment dynamic process and material migration.</p>    <p>Particle size, also known as grain size, which represents the size of sediment particles, are one of the main parameters of sediment. <xref ref-type="bibr" rid="B38">McCave (1978)</xref> defined the plane difference of grain size parameters as grain-size trend. In order to extract the grain-size trend information, <xref ref-type="bibr" rid="B39">McLaren (1981)</xref> and <xref ref-type="bibr" rid="B40">McLaren and Bowles (1985)</xref> developed a one-dimensional model and concluded that the sediment transport trends were related to the spatial variation of grain size parameters of mean grain-size, sorting coefficient and skewness. <xref ref-type="bibr" rid="B18">Gao and Collins (1991</xref>; <xref ref-type="bibr" rid="B19">1992)</xref> proposed a two-dimensional grain size trend analysis (GSTA) model based on McLaren model. Since then, more scholars have successively developed improved models based on GSTA. For example, <xref ref-type="bibr" rid="B33">Le Roux (1994)</xref> used a modified vector analysis procedure to determine the transmission vectors, while <xref ref-type="bibr" rid="B34">Le Roux and Rojas (2007)</xref> used the gradient between the central site and surrounding sites to define vector magnitudes, and considered kurtosis together with mean grain-size, sorting coefficient, and skewness for the first time. Moreover, <xref ref-type="bibr" rid="B7">Chang et&#xa0;al. (2001)</xref> improved the average length test method, while <xref ref-type="bibr" rid="B47">Poizot et&#xa0;al. (2008)</xref> used the geostatistical method to determine the characteristic distance of sampling sites. <xref ref-type="bibr" rid="B46">Poizot and Mear (2010)</xref> developed GisedTrend, a GSTA plugin of the QGIS project that considering the effect of obstacles (natural or artificial) in computing vector fields. GSTA has been widely used in various marine sedimentary environments such as estuaries (<xref ref-type="bibr" rid="B14">Duc et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B65">Yu et&#xa0;al., 2019a</xref>; <xref ref-type="bibr" rid="B11">Chu et&#xa0;al., 2020</xref>), coasts (<xref ref-type="bibr" rid="B45">Pedreros et&#xa0;al., 1996</xref>; <xref ref-type="bibr" rid="B60">Wang et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B32">Kawakami et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B52">Sinha et&#xa0;al., 2021</xref>), bays (<xref ref-type="bibr" rid="B31">Jia et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B50">S&#xe1;nchez and Carriquiry, 2011</xref>; <xref ref-type="bibr" rid="B70">Zheng et&#xa0;al., 2016</xref>), and continental shelves (<xref ref-type="bibr" rid="B56">Vanwesenbeeck and Lanckneus, 2000</xref>; <xref ref-type="bibr" rid="B4">Balsinha et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B20">Gao and Collins, 2014</xref>). However, due to the limitation of sediment sampling density, to the authors&#x2019; knowledge, this method has rarely been used for high-resolution insight into the sediment transport trends in small scale sea areas, especially in coastal bedrock island sea areas with more complex topography, sediment sources, hydrodynamics, and human activities.</p>
<p>The specific way to explore sediment transport is to embed sediment dynamic module into ocean numerical model. The sediment dynamic process, which is mainly influenced by the incipient motion, suspension, transport and deposition, has long been studied by means of field observations, model tests, and corresponding theoretical and numerical models (<xref ref-type="bibr" rid="B62">Wang et&#xa0;al., 2018</xref>). These kinds of studies, for example, sediment transport along the Amazon continental shelf (<xref ref-type="bibr" rid="B41">Molinas et&#xa0;al., 2020</xref>), the suspension transport of river-influent sediments in the Bohai Sea, Yellow Sea and East China Sea (<xref ref-type="bibr" rid="B67">Zeng et&#xa0;al., 2015</xref>), and the origin of muddy sediment areas in the Yellow Sea Trough and the Okinawa Trough (<xref ref-type="bibr" rid="B6">Bian et&#xa0;al., 2013</xref>), usually focus on large-scale and long-term sediment transport. The numerical models, which have the characteristics of multiple assumption and simplification, numerous model parameters, and some values of model parameters are difficult to determine, are mainly concerned with the large space-scale and long time-scale seawater movement and sediment transport. In the meanwhile, the physical process of the sediment movement module is quite complex in shallow water sea area, especially in bedrock island sea areas. Therefore, the above-mentioned models are inadequate to explore the details of sediment transport in small space scale coastal sea areas.</p>
<p>In this paper, we select the Chudao Island sea area off the coast of Shandong Peninsula, China, as a typical research area, to give deep insight into the sediment transport trends and its influencing factors of small space scale bedrock island sea areas based on high-precision bathymetric survey, high-density sediment sampling, grain-size trend analysis and hydrodynamic numerical modeling. Through which we hope to improve the understanding of the modern sediment dynamic process of coastal bedrock island sea area and provide reference for corresponding engineering and aquatic activities.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Study area</title>
<p>The study area, as the national shallow sea comprehensive test site of China (<xref ref-type="bibr" rid="B35">Li et&#xa0;al., 2017</xref>), is located in the Yellow Sea, north of the coast of Weihai, with Chudao Island at the southern side (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Chudao Island is a 0.82&#xa0;km long and 0.21&#xa0;km wide bedrock island 3.7&#xa0;km from the coastline of Shandong peninsula, which is surrounded with rugged coastline and steep bank slope. The average water depth is 30 to 60&#xa0;m, and presents a generally high-low-high topography from south to north. An east-west directional trench, which is about 2.5&#xa0;km long and 1&#xa0;km wide, with maximum water depth 70&#xa0;m (<xref ref-type="bibr" rid="B69">Zhang et&#xa0;al., 2020a</xref>), locates in the north of Chudao Island.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Map of the Chudao Island sea area with sediment sampling sites (black dots), tide station (blue lozenge), aquaculture areas (the area filled by black slashes) and multi-beam echo sounder (MBES) track lines (red lines).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g001.tif"/>
</fig>
<p>The hydrodynamic in the study area was characterized by the irregular semidiurnal tide and east-west reciprocating flow (<xref ref-type="bibr" rid="B5">Bi et&#xa0;al., 2019</xref>). The tide difference has a maximum value of 3.08&#xa0;m and a mean value of 1.73&#xa0;m. The northward and eastward wave account for about 58.5% and 37% of the total (<xref ref-type="bibr" rid="B27">Han et&#xa0;al., 2020</xref>).</p>
<p>Kelp and scallop raft aquaculture occupy large areas in the northwest of the study area and small areas on the east and west sides of Chudao Island (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The breeding cycle of kelp is generally from November to May or June of the following year, which takes up more than half of the whole year. The length of kelp can grow to 4 to 5&#xa0;m when it is harvested in June and July. The scallop species, Chlamys farreri, which have a shell height of 6 to 7&#xa0;cm and a shell length of about 7&#xa0;cm at maturity, is mainly breeding from May to November.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Field work and laboratory analysis</title>
<p>Fieldwork including small spacing sediment sampling and full-coverage bathymetry survey were carried out in November and December 2018, through which the grain size parameter data obtained by laboratory grain-size analysis are used for sediment trend analysis, while the bathymetry data are used to explore the effects of seabed topography on sediment transport trends. A total of 229 surface sediment samples were collected, with grid of 250&#xa0;m &#xd7; 500&#xa0;m (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), sampling thickness between 20~30 cm, using a clam sampler (type DDC1-2, volume 0.025 m&#xb2;, Beijing Jinyang Wanda Technology Co., Ltd.). The navigation and positioning were executed by Global Navigation Satellite System (H32, plane positioning accuracy &#xb1; 8&#xa0;+&#xa0;1&#xd7;10<sup>-6</sup> D, Guangzhou Hi-Target Satellite Navigation Technology Co., Ltd.). The positions were measured twice during sediment sampling process, with one when the vessel arrived at the planned station and the other when the sampler reached the seabed. Repeated sampling was performed if the mass of the sample was less than 300&#xa0;g. The sea conditions are calm during the sampling period, neither high waves nor strong winds had been recorded in Novermber and the beginning of December of 2018.</p>    <p>The collected sediment samples were brought to the laboratory for grain-size analysis using sieving-densitometer method. For a sediment sample, the part of grain size less than 0.075&#xa0;mm is used by densitometer method, and the part of grain size larger than 0.075&#xa0;mm is used by sieving method. The specific steps of the test are referred to Standard for geotechnical testing method (<xref ref-type="bibr" rid="B54">Standard of P. R. China, GB/T 50123-2019, 2019</xref>). The mean grain-size, sorting coefficient and skewness were calculated based on the grain size distribution curve as follows (<xref ref-type="bibr" rid="B16">Folk and Ward, 1957</xref>):</p>
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</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>M</italic>
<sub>z</sub>, <italic>&#x3c3;</italic>
<sub>i</sub>, and <italic>S</italic>
<sub>ki</sub> are the mean grain-size, sorting coefficient and skewness, with <italic>&#x3c6;</italic>
<sub>5</sub>, <italic>&#x3c6;</italic>
<sub>16</sub>, <italic>&#x3c6;</italic>
<sub>50</sub>, <italic>&#x3c6;</italic>
<sub>84</sub>, <italic>&#x3c6;</italic>
<sub>95</sub> the grain size corresponding to the cumulative percentage content of 5%, 16%, 50%, 84% and 95%.</p>
<p>Full-coverage bathymetry survey was carried out by a multi-beam echo sounder system (R2 SONIC 2024, R2Sonic Limited Liability Company, USA) with operating frequency 400 kHz, range resolution 1.25&#xa0;cm and sector angle of 120&#xb0;~140&#xb0;. A total of 36 main survey lines with line spacing 100&#xa0;m and 7 check lines perpendicular to the main survey line were carried out. Global Navigation Satellite System (H32), fiber optic gyrocompass and motion sensor (Octans III, iXSea Ltd., France), sound velocity profiler (MiniSVP, Valeport Ltd., UK) and automatic water gauge (DCX-25PVDF, Druckmesstechnik AG, Switzerland) were applied accordingly to obtain the positioning, attitude, sound velocity profile and sea level data. The CARIS HIPS and SIPS (V10.1, Teledyne Technologies Incorporated, Canada) software were used to process the MBES data to get the water depth and topography of the study area.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Grain-size trend analysis</title>
<p>
<xref ref-type="bibr" rid="B40">McLaren and Bowles (1985)</xref> found that there were two cases for the net sediment transport trends, that is, Case 1: finer, better sorted and more negatively skewed; Case2: coarser, better sorted and more positively skewed. GSTA was provided by <xref ref-type="bibr" rid="B18">Gao and Collins (1991)</xref> based on McLaren&#x2019;s model. The first step of GSTA is to define trend vectors for a grid of sampling sites by comparing the grain size parameters of each sample site with its neighbors in any direction. A characteristic distance (<italic>D</italic>
<sub>cr</sub>) is specified to identify whether the sites are adjacent. If either a Case 1 or a Case 2 trend is identified between the two sites, a dimensionless trend vector of unit length is defined for two neighboring sites. For each sampling site, there may be more than one unit-length vector.</p>
<p>Then, the trend vectors at each sampling site are obtained by composing the multi-vectors into a single vector:</p>
<disp-formula>
<label>(4)</label>
<mml:math display="block" id="M4">
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mover accent="true">
<mml:mi>R</mml:mi>
<mml:mo>&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mi>n</mml:mi>
</mml:munderover>
</mml:mstyle>
<mml:mover accent="true">
<mml:mi>r</mml:mi>
<mml:mo>&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>n</italic> is the number of trend vectors identified for the site, <inline-formula>
<mml:math display="inline" id="im1">
<mml:mrow>
<mml:mover accent="true">
<mml:mi>r</mml:mi>
<mml:mo>&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> is a trend vector, and <inline-formula>
<mml:math display="inline" id="im2">
<mml:mrow>
<mml:mover accent="true">
<mml:mi>R</mml:mi>
<mml:mo>&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> is the sum of the trend vectors. Finally, an averaging procedure is applied to remove noise included in the vectors at each site, as:</p>
<disp-formula>
<label>(5)</label>
<mml:math display="block" id="M5">
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mrow>
<mml:mtext>av</mml:mtext>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mrow>
<mml:mi>K</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:mfrac>
<mml:mrow>
<mml:mo>[</mml:mo>
<mml:mrow>
<mml:mover accent="true">
<mml:mi>R</mml:mi>
<mml:mo>&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>+</mml:mo>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mi>k</mml:mi>
</mml:munderover>
</mml:mstyle>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
<mml:mo>]</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im3">
<mml:mrow>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mi>j</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> is a summed trend vector obtained on the basis of eq. (4) at a neighboring site, and <italic>K</italic> is the total number of such sites. The vectors <inline-formula>
<mml:math display="inline" id="im4">
<mml:mrow>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mrow>
<mml:mtext>av</mml:mtext>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="true">&#x2192;</mml:mo>
</mml:mover>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> can be defined as transport vectors to describe the main sediment transport pathways. Since the sampling sites are regular and uniform with a rectangular grid of 250&#xa0;m &#xd7; 500&#xa0;m, the characteristic distance <italic>D</italic>
<sub>cr</sub> is set as 250 <inline-formula>
<mml:math display="inline" id="im5">
<mml:mrow>
<mml:msqrt>
<mml:mn>5</mml:mn>
</mml:msqrt>
</mml:mrow>
</mml:math>
</inline-formula> m.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Hydrodynamic analysis</title>
<p>Tidal currents and waves are the main factors controlling sediment transport in coastal waters (<xref ref-type="bibr" rid="B23">George et&#xa0;al., 2018</xref>). The sediment grain-size trend is mainly formed under the long-term reciprocating action of periodic tidal currents rather than the random changeable waves (<xref ref-type="bibr" rid="B2">Armstrong et&#xa0;al., 2022</xref>). Therefore, this study focuses on the simulation of tidal currents.</p>
<p>The Coastal and Regional Ocean Community model (CROCO) is a three-dimensional nonlinear baroclinic primitive equation model based on the Regional Ocean Modeling System (ROMS) (<xref ref-type="bibr" rid="B30">Huang et&#xa0;al., 2021</xref>), which can simulate multiple-scale sea water movement. In the CROCO model, a time-splitting method is used to generate two different time steps, in which the short time steps is used to advance the surface elevation and barotropic momentum, while a large time step is used for tracers and baroclinic momentum. The curvilinear orthogonal coordinate system and Arakawa C staggered grid are adopted in the horizontal direction to increase the resolution of the specific area, while the S coordinate system is used in the vertical direction to improve the resolution at the thermocline and the bottom boundary layer.</p>
<p>The horizontal resolution of the model is 1/1200&#xb0;, while the vertical water column is meshed into 6 levels. The shoreline with resolution 1&#x2032; is from the Global Self-consistent Hierarchical High-resolution Shorelines (GSHHS) provided by the National Geophysical Data Center (NGDC) of U.S. The topography with resolution 1&#x2032; is from the Gridded Global Relief Data Collection (ETOPO1) with resolution 1&#x2032; provided by NGDC. The initial temperature and salinity data are from the World Ocean Atlas 2009 (WOA09) published by NGDC. The open boundary is forced by ten tidal constituents including M<sub>2</sub>, S<sub>2</sub>, N<sub>2</sub>, K<sub>2</sub>, K<sub>1</sub>, O<sub>1</sub>, P<sub>1</sub>, Q<sub>1</sub>, M<sub>f</sub>, and M<sub>m</sub>, in which the harmonic constants are obtained from the Oregon State University Tidal Inversion Software (OTIS). The short time step and the large time step are set as 2 and 120 s, respectively. The model is operated normally after it is integrated forward to a stable state, with the duration covering the whole year of 2018 that consistent with time of the sediment sampling.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Topography features</title>
<p>As shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>, the water depth of the study area is mainly between 25.0&#xa0;m and 60.0&#xa0;m, with an average of 36.7&#xa0;m and a maximum of 70&#xa0;m. The seafloor is rugged in the north of the island, while the water depth drastically increases to more than 60.0&#xa0;m at an east-west trench north of the island. The trench has dense isobaths and steep slope around it, among which the slope is steeper in the north-south direction with a maximum 5.2&#xb0; than that in the east-west direction. The water depth gradually becomes shallow north of the trench, forming the flattest area within the study area.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>The three-dimensional topographic map of the study area.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g002.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Sediment distribution and grain size characteristics</title>
<p>The continuous distribution of <italic>M</italic>
<sub>z</sub> <italic>&#x3c3;</italic>
<sub>i</sub>, <italic>S</italic>
<sub>ki</sub>, which are obtained by interpolating the parameters of discrete point with a kriging method (<xref ref-type="bibr" rid="B43">Oliver and Webster, 1990</xref>). The mean grain-size <italic>M</italic>
<sub>z</sub>, which is mainly affected by material supply, transport capacity, and the depositional environment, can directly reflect the size of the sediment particle and the strength of hydrodynamics of the environment (<xref ref-type="bibr" rid="B57">Visher, 1969</xref>). The sorting coefficient <italic>&#x3c3;</italic>
<sub>i</sub>, which represents the uniformity of sediment, is also an indicator of hydrodynamics and sediment transport trend. The skewness <italic>S</italic>
<sub>ki</sub> describes the degree of symmetry of sediment grain size distribution. As shown in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, the surficial sediments are mainly muddy silt, with mean grain-size 4.9~6.2 <italic>&#x3c6;</italic>, average value 5.03 <italic>&#x3c6;</italic> and maximum value 0.79 <italic>&#x3c6;</italic> (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>). The sorting coefficient <italic>&#x3c3;</italic>
<sub>i</sub> ranges from 0.014 to 2.206 with an average value of 0.077, most of which are excellent (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). The skewness <italic>S</italic>
<sub>ki</sub> shows a decrease pattern from south to the north, from island to sea, with all positive skew ranging from 0.07 to 0.97 (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). Generally, the three grain size parameters show an obvious feature of zonal distribution. The area with larger <italic>M</italic>
<sub>z</sub> (&lt;2 <italic>&#x3c6;</italic>), poor sorting, and strong positive <italic>S</italic>
<sub>ki</sub> concentrates around the bedrock island, where rocks and gravels are common seen from the samples. While to the north, <italic>M</italic>
<sub>z</sub> gradually transitions to a broad northern area with <italic>&#x3c6;</italic>=5, <italic>&#x3c3;</italic>
<sub>i</sub> becomes better away from the island, and <italic>S</italic>
<sub>ki</sub> decreases to minimum.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Spatial distribution of mean grain-size <bold>(A)</bold>, sorting coefficient <bold>(B)</bold>, Skewness <bold>(C)</bold>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g003.tif"/>
</fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Sediment grain-size trends</title>
<p>In <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>, the vector direction represents the net sediment transport direction, while the vector length represents the significance of the grain-size trend.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Sediment grain size trends calculated by Gao-Collins grain size trend analysis (GSTA) model.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g004.tif"/>
</fig>
<p>Despite the southward transport trend of small areas in the northwest and northeast, the overall sediment transport trend of the study area is from island shore to sea and from south to north. In addition, there are four convergence centers in the study area and show different transport patterns. The transport trend is more significant on the southern side than that on the northern side of A and B (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>), indicating a clear shore-to-sea transport trend at the east and west of the Chudao Island. A counterclockwise sediment transport trend at C is discovered although C is located at the edge of the study area and the edge effect caused by the lack of information may affect the accuracy of the results. An inconspicuous sediment convergence center D locates at the west of the Chudao Island, where eastward and westward vectors meet.</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Near-bottom flow field</title>
<p>Since the erosion, transport and deposition of sediments are most closely related to the near-bottom flow velocity, the flow velocity of the bottommost layer (the sixth layer) in the model is particularly exported from the CROCO model to characterize the hydrodynamic factors. <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref> shows the comparison of tidal level simulated by numerical model and the value observed by the Chudao tide station (with location illustrated in <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), in which the time is from November 11 to December 1, 2018 including an astronomical tide. As can be seen that not only the calculated tide level variation trend but also its values are in good agreement with the observed ones. The correlation coefficient (<italic>R</italic>
<sup>2</sup>) of the simulated and observed tide level is 98.42% (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>
<bold>)</bold>, which proves the reliability of the presented model.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Comparison between the simulated and observed tide fluctuation.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g005.tif"/>
</fig>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>The correlation between the simulated and observed tide level (<italic>L</italic>s refers to tide level simulated by CROCO; <italic>L</italic>o refers to tide level observed by tide station; <italic>R</italic>
<sup>2</sup> refers to the correlation coefficient).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g006.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<sec id="s4_1">
<label>4.1</label>
<title>Influence of near-bottom flow field on sediment transport trends</title>
<p>The overall sediment transport trend in the study area, that is, from the island shore to the sea (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>), is generally consistent with the direction of annual-averaged near-bottom flow (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). The disturbance of seabed caused by near-bottom water flow is the direct driving force of sediment transport (<xref ref-type="bibr" rid="B21">Gardner et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B13">Du et al., 2021</xref>), so the direction and velocity of near-bottom flow correspond well with the direction and the significance of sediment transport trends (<xref ref-type="bibr" rid="B26">Gunsolus and Binns, 2018</xref>). The locations of the two bottom flow loops at the east and west of the study area (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>) corresponds well with the convergence centers of grain-size trend A and B (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>), indicating that the flow direction controls the direction of sediment transport. Moreover, the average bottom velocity (0.149&#xa0;m/s) in the west of the study area is greater than that (0.136&#xa0;m/s) in the east (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). Correspondingly, the sediment transport trend in the west of the study area is also more significant than that in the east (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>), indicating the controlling effect of flow velocity on the potential quantity of sediment transport. However, it should also be noted that the sediment convergence centers A and B deviate slightly from the positions of the two loops. The convergence center C is located at the junction of the east-west loop, with northwestward flow on its west side and northeastward flow on its east side, which is not completely consistent with the sediment transport directions of west-northwestward on the west side and southwestward on the northeast side. What is more, the bottom flow loop on the east side of Chudao Island does not form a sediment convergence center. This demonstrates that the sediment transport trend may also be influenced by other factors besides the near-bottom flow field.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Annual average near-bottom flow field simulated by CROCO. The direction of the vector indicates the flow direction, the length of the vector and the contours represent the flow velocity.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-10-1220331-g007.tif"/>
</fig>
<p>The hydrodynamic conditions are weak as the average bottom flow velocity of the entire study area is only about 0.1&#xa0;m/s (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). The fine-grained sediments are brought from nearshore to offshore areas by the weak bottom currents, most of which are settled in the trench valley, while the coarse-grained sediments are left nearshore. Therefore, the sediment in the southern part of the study area is coarse-grained, while the sediment located in the trench north of Chudao Island is finer-grained. The coarser sediment size in the north of the trench is because the weak bottom flow cannot drive the nearshore fine-grained sediment over the steep slope. This is consistent with the mean grain-size of sediment from south to north showing a &#x201c;coarse-fine-coarse&#x201d; striped distribution presented in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>.</p>
<p>To summarize, the near-bottom flow field is the primary factor that controlling the sediment transport trend in coastal bedrock islands sea area. The greater the bottom flow velocity is, the more obvious the sediment transport trend is. The direction of bottom flow decides the general patterns of sediment transport although small deviations may exist in specific areas. Besides, sediment transport impacted by the near-bottom flow field shapes the sediment distribution characteristics in coastal bedrock islands sea area.</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Influence of submarine topography on sediment transport trends</title>
<p>The submarine topography is varied in the study area with steep slope around the Chudao island, then deep trench connected with flat plain from south to north (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). The near-bottom current basically points in the direction from shallow to deep waters. The general sediment transport trend is from the southern island shore and the northern flat area to the trench, which is consistent with the topography from shallow to deep. In fact, bottom flow (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>), which indicates the sediment transport direction, is also influenced by the topography, because the local flow field is usually constrained by submarine topography and tends to flow from shallow to deep water areas. The existing distribution characteristics of sediment grain size parameters are the result of long-term sediment transport. The mean grain-size, sorting coefficient and skewness (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>) in the study area are zonal distributed, roughly parallel to the isobaths (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>), which also indicates the controlling effect of submarine topography on the long-term sediment transport trend. In addition, the sediment convergence center A (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>) is not coincided with the center of the bottom flow loop, however, it locates northwest of the loop center where densest isobaths and most dramatic topography changes exist. This indicates that rapid decline of seafloor topography can cause certain amount of sediment to be transported down the slope. Actually, previous researches have revealed that the surficial sediment would slowly move down along the seabed slope due to its own gravity (<xref ref-type="bibr" rid="B15">Eschard, 2001</xref>; <xref ref-type="bibr" rid="B29">Hsiung and Yu, 2013</xref>), the steeper the slope is, the faster and the larger volume of sediments would transport on a long-term scale. It can also be seen that (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>), unlike the general trend of sediment transport from shore to sea, the sediment around Chudao Island is transported in all directions with the island as the center. This is because the water depth around the island decreases drastically, which leads to the sediment around the island transports in the direction of downward slope. Therefore, the main difference in sediment transport trend between coastal bedrock island sea area and traditional bedrock coast is that the presence of the island in makes itself a discrete center of sediment transport, and the sediment around the island transports seaward.</p>
<p>Under the influence of submarine topography, sediment in the coastal bedrock island sea areas mainly transports from shore to sea, making it difficult to silt up near shore. Due to the presence of islands, tides and waves are strongly dissipated before reaching the shoreline (<xref ref-type="bibr" rid="B42">Ogawa et&#xa0;al., 2011</xref>). In addition, the bedrock coast is resistant to erosion and has stable geological conditions. All of these conditions meet the requirements of harbor site selection, so the coastal bedrock island sea area is suitable for the construction of harbors, docks and other coastal engineering.</p>
<p>Thus, in the coastal bedrock island sea areas, the topography can either directly transport sediments down its slope or indirectly affect the sediment transport by constraining the near-bottom flow, making the sediment generally transports from shallow to deep waters. In the coastal bedrock island sea area, the sediment around the island is transported seaward with the island as the center, which is the main difference from the sediment transport trend of the traditional bedrock coasts.</p>
</sec>
<sec id="s4_3">
<label>4.3</label>
<title>Influence of aquaculture on sediment transport trends</title>
<p>Near the considerable aquaculture area (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), the mean grain-size (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>) of the sediment increase, and the near-bottom flow velocity (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>), indicating that human activities such as aquaculture will also affect the sediment transport trend in coastal bedrock island sea area besides natural factors (<xref ref-type="bibr" rid="B63">Wood and Widdows, 2002</xref>). Aquaculture facilities including net cages and rafts is widely deployed in China coasts, particularly in bedrock island sea areas (<xref ref-type="bibr" rid="B66">Yu et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B9">Chen et&#xa0;al., 2018</xref>) such as our study area. However, these aquaculture facilities have certain impact on sediment transport in shallow waters even to water depth 200&#xa0;m (<xref ref-type="bibr" rid="B44">Pawar et&#xa0;al., 2001</xref>; <xref ref-type="bibr" rid="B53">Srithongouthai and Tada, 2017</xref>; <xref ref-type="bibr" rid="B8">Chaves et&#xa0;al., 2020</xref>).</p>
<p>The mean grain-size becomes coarse near the aquaculture area rather than the trench (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>), which may be due to the increased sedimentation rate of organic matter induced by aquaculture-produced residual bait and feces. For example, to our common knowledge, the unidirectional eastward near-bottom flow cannot form sediment convergence center at D, however, the sediment convergence center D does exist. This is probably due to the sediment at D is fine, but the sediment east of D is coarsened by the aquaculture and west of D is also coarse, which presents the transport trend from the east and west to the convergence center. In addition, the diffusion of scallop fragments caused by water flow also contributes to the sediment coarsening near the aquaculture area, the time for sediment sampling was from November to December 2018, just when the kelp and scallops in the aquaculture area were ripe and large in size. Similarly, sediment coarsening induced by the dispersal of mussel fragments were also found in Marlborough Bay, New Zealand (<xref ref-type="bibr" rid="B28">Hartstein, 2005</xref>), while sedimentation rates were also increased by the mussel and kelp aquaculture activities (<xref ref-type="bibr" rid="B58">Walker and Grant, 2009</xref>; <xref ref-type="bibr" rid="B37">Liu et&#xa0;al., 2016</xref>). The aggregation of macroalgae and the artificial aquaculture facilities (<xref ref-type="bibr" rid="B22">Gaylord et&#xa0;al., 2007</xref>) can change the local hydrodynamics especially reduce the flow velocity to a certain extent (<xref ref-type="bibr" rid="B48">Rosman et&#xa0;al., 2007</xref>). For example, the averaged near-bottom flow on the east side of the sediment convergence center C (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>) is only 0.05&#xa0;m/s, which is 62% lower than that of 0.13&#xa0;m/s in other surrounding areas. Similarly, the flow velocity at Sungo Bay and Heini Bay off Shandong Peninsula, China, also as bedrock island sea areas, have been observed to be reduced by 54% (<xref ref-type="bibr" rid="B24">Grant and Bacher, 2001</xref>) and 21% (<xref ref-type="bibr" rid="B68">Zhang et&#xa0;al., 2020b</xref>) as well due to the influence of shellfish and kelp aquaculture.</p>
<p>Reduced flow velocity and weakened sediment transport can exacerbate the enrichment of pollutants and eutrophication of water in aquaculture areas (<xref ref-type="bibr" rid="B10">Chor et&#xa0;al., 2022</xref>), resulting in the death of farmed scallops and fish and the frequent occurrence of algal blooms (<xref ref-type="bibr" rid="B12">Cui et&#xa0;al., 2018</xref>), harming the economic and environmental benefits. The impact of aquaculture on flow field and sediment transport can be mitigated by reducing stocking densities (<xref ref-type="bibr" rid="B55">Tang et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B25">Gretchen, 2018</xref>) and netting weights (<xref ref-type="bibr" rid="B36">Liu et&#xa0;al., 2008</xref>), allowing for the dilution of enriched pollutants and nutrient salts.</p>
<p>Thus, aquaculture may affect the material source, the deposition and transportation rate of sediments, and thus make influence on the sediment transport of coastal bedrock island sea area. First, the aquaculture waste and the accelerating on sedimentation rate can increase the mean grain-size of sediment. Second, the artificial aquaculture facilities would reduce the movement of seawater, slow down the flow velocity, and thus hinder the initiation, suspension of sediments, resulting in a sediment coarsening and a significant reduction of sediment transport. The accelerated sediment deposition and weakened transport can cause pollutant and nutrient enrichment, which can be mitigated by rational planning of aquaculture density and configuration of aquaculture facilities. This will enable the sustainable development of aquaculture industry while protecting the ecological environment of the coastal bedrock island sea areas.</p>
</sec>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusions</title>
<p>In this paper, the Chudao Island sea area off the coast of Shandong Peninsula, China, with complex topography and aquaculture activities, was chosen to investigate sediment transport trends. Multiple methods including high-precision bathymetric survey, high-density sediment sampling, grain-size trend analysis and hydrodynamic numerical modeling were used to explore the effects of natural factors and human activities on sediment transport and give some new insights into the sediment dynamic process in the less reported small-scale bedrock island sea area. Conclusions are drawn as follows.</p>
<p>The grain size parameters including mean grain-size, sorting coefficient and skewness are zonal distributed, roughly parallel to the isobaths. While the overall sediment transport trend is from island shore to sea, with several convergence centers near the loop centers of bottom flow and at the edge of the agriculture area. This result is consistent with the distribution of near-bottom flow field and submarine topographic features, indicates that the validity of grain size trend analysis to small-scale coastal bedrock island sea area has been confirmed.</p>
<p>In coastal bedrock island sea areas, near-bottom flow field is the primary factor controlling the sediment transport trend, that is, the greater the bottom flow velocity is, the more significant the sediment transport trend is. The flow direction of bottom flow decides the general patterns of sediment transport although small deviations may exist in specific areas. Submarine topography can either directly transport sediments down its slope, or indirectly influence the direction of sediment transport by constraining the near-bottom flow field, making the sediment transport direction generally from shallow to deep waters. In the coastal bedrock island sea areas, the water depth around the island decreases drastically, leading to a divergence sediment transport trend away from the island down the slope. Besides the natural factors of bottom flow and submarine topography, human activities represented by aquaculture will also affect the sediment transport trend in coastal bedrock island sea areas. First, the increased sedimentation rate caused by organic matters and the diffusion of scallop fragments may cause sediment coarsening. Second, the artificial aquaculture facilities can reduce flow velocity and therefore hinder the initiation, suspension and transport of sediment near the aquaculture areas.</p>
<p>Sediment transport trend analysis like our study combined with high-precision observation and numerical modeling is appropriate to understand the sediment distribution features affected by hydrodynamic and submarine topography, nearshore sediment silting and enrichment of pollutants in aquaculture areas. Through which we will enhance the knowledge towards sediment dynamic process of coastal bedrock island sea area and providing reference for coastal engineering and agriculture activities.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>YZ, HW, and YY contributed to Conceptualization and design of the study. HW and YZ performed the investigation. YY provided experimental materials. YZ performed the statistical analysis and data visualization, wrote the original draft of the manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This research is supported by the Open Fund of Observation and Research Station of East China Coastal Zone, Ministry of Natural Resources (ORSECCZ2022206) and National Natural Science Fund of China (41702307).</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/article/10.3389/fmars.2023.1220331/full#supplementary-material">https://www.frontiersin.org/article/10.3389/fmars.2023.1220331/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table_1.xlsx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
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