Dynamics of Dual‐Mode Bedload Transport With Three‐Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis
Bedload transport often exhibits dual‐mode behavior due to interactions of spatiotemporal controlling factors with the migrating three‐dimensional bedforms (characterized by the fully developed patterns in the bed, such as alternate bars, pools, and clusters). This study explores dual‐mode bedload t...
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description | Bedload transport often exhibits dual‐mode behavior due to interactions of spatiotemporal controlling factors with the migrating three‐dimensional bedforms (characterized by the fully developed patterns in the bed, such as alternate bars, pools, and clusters). This study explores dual‐mode bedload transport based on experimental measurements and develops Einstein's exponential‐based model to characterize large fluctuations of bedload sediment discharge. The particle waiting time, particle flux, and bed elevation are measured in a series of well‐controlled laboratory experiments. Flume experiments show that the waiting time distribution of sediments gives a bimodal characteristic, two distinct modes can be identified from the measured data. This study encapsulates this dual‐mode bedload transport behavior in a hyperexponential distribution of sediment resting times and introduces it into the continuous time random walk (CTRW) framework. Considering the scaling limit of the thin/heavy‐tailed CTRW processes, a single‐rate mass transfer (SRMT) and fractional‐derivative SRMT (F‐SRMT) models are obtained, and the model parameters are determined from the hyperexponential distribution. Further analyses reveal that the dual‐mode bedload transport behavior is controlled by mass exchange between the mobile and immobile zones, and a dimensionless index η can quantify the intensity of dual‐mode behavior. Applications show that the dual‐mode bedload transport models are much more accurate in characterizing bedload transport in a mixed‐size gravel bed than the traditional exponential‐based model, and the nonlocal movement of bedload sediments is significant in the mixed‐size gravel bed. Further investigations will focus on the applicability test of the dual‐mode models to other flow regimes and conditions.
Plain Language Summary
Sediment transport caused by particles rolling and sliding as well as saltation on riverbeds is called bedload transport. Bedload transport is highly complex due to the complexity of the flow and bedform in natural rivers. Bedforms are commonly classified in terms of their characteristic longitudinal scales, and a three‐dimensional (3‐D) bedform represents the bed with fully developed patterns such as alternate bars, pools, and clusters. Traditional models in quantifying bedload transport may differ from field data by 1–4 orders of magnitude, especially for the migrating 3‐D bedforms. In this study, flume experiments reveal that the waiting time |
doi_str_mv | 10.1029/2022JF006882 |
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Plain Language Summary
Sediment transport caused by particles rolling and sliding as well as saltation on riverbeds is called bedload transport. Bedload transport is highly complex due to the complexity of the flow and bedform in natural rivers. Bedforms are commonly classified in terms of their characteristic longitudinal scales, and a three‐dimensional (3‐D) bedform represents the bed with fully developed patterns such as alternate bars, pools, and clusters. Traditional models in quantifying bedload transport may differ from field data by 1–4 orders of magnitude, especially for the migrating 3‐D bedforms. In this study, flume experiments reveal that the waiting time distribution of bedload sediments shows a significant bimodal characteristic (two bumps can be distinguished by the probability distribution curve) when transporting along the 3‐D riverbeds, and two modes can be identified from the experimental data. The observed dual‐mode bedload transport behavior is encapsulated by a mixture (hyperexponential) distribution after collecting two exponential distributions of sediment resting times. The stochastic and deterministic models are developed to characterize the observed dual‐mode bedload transport behavior, providing a tractable way for quantifying large fluctuations in the bedload transport rate due to the presence of dual‐mode dynamics in sediment movement.
Key Points
Probability density functions of the particle waiting time measured in the flume experiments exhibit a bimodal feature
A novel formula of resting time is developed to characterize the observed dual‐mode bedload transport behavior in experiments
Experimental observations guide the development of stochastic and deterministic models for dual‐mode bedload transport</description><identifier>ISSN: 2169-9003</identifier><identifier>EISSN: 2169-9011</identifier><identifier>DOI: 10.1029/2022JF006882</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Bars (landforms) ; Bed forms ; Bed load ; Bedforms ; bedload transport ; Clusters ; Complexity ; CTRW ; Distribution ; dual‐mode behavior ; Dynamics ; Encapsulation ; Experiments ; Fluctuations ; Flumes ; Gravel ; Gravel beds ; heavy‐tailed dynamics ; hyperexponential distribution ; Laboratory experimentation ; Laboratory experiments ; Mass transfer ; Modelling ; Particle settling ; Pools ; Probability distribution ; Probability theory ; Random walk ; River beds ; Riverbeds ; Rivers ; Saltation ; Scaling ; Sediment ; Sediment discharge ; Sediment movement ; Sediment transport ; Sedimentary structures ; Sediments ; Stochasticity ; Subcritical flow ; Tranquil flow ; Transport phenomena ; Transport rate ; waiting time</subject><ispartof>Journal of geophysical research. Earth surface, 2023-03, Vol.128 (3), p.n/a</ispartof><rights>2023. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3302-c58004513ca1c9968d18cc1f6403f556c6cb756cd6a053c6f97d4cfab5e5e7693</citedby><cites>FETCH-LOGICAL-a3302-c58004513ca1c9968d18cc1f6403f556c6cb756cd6a053c6f97d4cfab5e5e7693</cites><orcidid>0000-0001-8726-4663 ; 0000-0003-1209-9434 ; 0000-0003-0121-0950 ; 0000-0002-8422-3871</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2022JF006882$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2022JF006882$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,11514,27924,27925,45574,45575,46468,46892</link.rule.ids></links><search><creatorcontrib>Li, ZhiPeng</creatorcontrib><creatorcontrib>Kiani Oshtorjani, Mehrdad</creatorcontrib><creatorcontrib>Chen, Dong</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>Sun, HongGuang</creatorcontrib><title>Dynamics of Dual‐Mode Bedload Transport With Three‐Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis</title><title>Journal of geophysical research. Earth surface</title><description>Bedload transport often exhibits dual‐mode behavior due to interactions of spatiotemporal controlling factors with the migrating three‐dimensional bedforms (characterized by the fully developed patterns in the bed, such as alternate bars, pools, and clusters). This study explores dual‐mode bedload transport based on experimental measurements and develops Einstein's exponential‐based model to characterize large fluctuations of bedload sediment discharge. The particle waiting time, particle flux, and bed elevation are measured in a series of well‐controlled laboratory experiments. Flume experiments show that the waiting time distribution of sediments gives a bimodal characteristic, two distinct modes can be identified from the measured data. This study encapsulates this dual‐mode bedload transport behavior in a hyperexponential distribution of sediment resting times and introduces it into the continuous time random walk (CTRW) framework. Considering the scaling limit of the thin/heavy‐tailed CTRW processes, a single‐rate mass transfer (SRMT) and fractional‐derivative SRMT (F‐SRMT) models are obtained, and the model parameters are determined from the hyperexponential distribution. Further analyses reveal that the dual‐mode bedload transport behavior is controlled by mass exchange between the mobile and immobile zones, and a dimensionless index η can quantify the intensity of dual‐mode behavior. Applications show that the dual‐mode bedload transport models are much more accurate in characterizing bedload transport in a mixed‐size gravel bed than the traditional exponential‐based model, and the nonlocal movement of bedload sediments is significant in the mixed‐size gravel bed. Further investigations will focus on the applicability test of the dual‐mode models to other flow regimes and conditions.
Plain Language Summary
Sediment transport caused by particles rolling and sliding as well as saltation on riverbeds is called bedload transport. Bedload transport is highly complex due to the complexity of the flow and bedform in natural rivers. Bedforms are commonly classified in terms of their characteristic longitudinal scales, and a three‐dimensional (3‐D) bedform represents the bed with fully developed patterns such as alternate bars, pools, and clusters. Traditional models in quantifying bedload transport may differ from field data by 1–4 orders of magnitude, especially for the migrating 3‐D bedforms. In this study, flume experiments reveal that the waiting time distribution of bedload sediments shows a significant bimodal characteristic (two bumps can be distinguished by the probability distribution curve) when transporting along the 3‐D riverbeds, and two modes can be identified from the experimental data. The observed dual‐mode bedload transport behavior is encapsulated by a mixture (hyperexponential) distribution after collecting two exponential distributions of sediment resting times. The stochastic and deterministic models are developed to characterize the observed dual‐mode bedload transport behavior, providing a tractable way for quantifying large fluctuations in the bedload transport rate due to the presence of dual‐mode dynamics in sediment movement.
Key Points
Probability density functions of the particle waiting time measured in the flume experiments exhibit a bimodal feature
A novel formula of resting time is developed to characterize the observed dual‐mode bedload transport behavior in experiments
Experimental observations guide the development of stochastic and deterministic models for dual‐mode bedload transport</description><subject>Bars (landforms)</subject><subject>Bed forms</subject><subject>Bed load</subject><subject>Bedforms</subject><subject>bedload transport</subject><subject>Clusters</subject><subject>Complexity</subject><subject>CTRW</subject><subject>Distribution</subject><subject>dual‐mode behavior</subject><subject>Dynamics</subject><subject>Encapsulation</subject><subject>Experiments</subject><subject>Fluctuations</subject><subject>Flumes</subject><subject>Gravel</subject><subject>Gravel beds</subject><subject>heavy‐tailed dynamics</subject><subject>hyperexponential distribution</subject><subject>Laboratory experimentation</subject><subject>Laboratory experiments</subject><subject>Mass transfer</subject><subject>Modelling</subject><subject>Particle settling</subject><subject>Pools</subject><subject>Probability distribution</subject><subject>Probability theory</subject><subject>Random walk</subject><subject>River beds</subject><subject>Riverbeds</subject><subject>Rivers</subject><subject>Saltation</subject><subject>Scaling</subject><subject>Sediment</subject><subject>Sediment discharge</subject><subject>Sediment movement</subject><subject>Sediment transport</subject><subject>Sedimentary structures</subject><subject>Sediments</subject><subject>Stochasticity</subject><subject>Subcritical flow</subject><subject>Tranquil flow</subject><subject>Transport phenomena</subject><subject>Transport rate</subject><subject>waiting time</subject><issn>2169-9003</issn><issn>2169-9011</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kUtOwzAQhiMEEhV0xwEssaXgR-PY7ErbFKpWSFDEMnIdh7pK42A7KtlxAzgjJ8FVEWLFbGY0_uafh6PoDMFLBDG_whDjaQohZQwfRB2MKO9xiNDhbwzJcdR1bg2DsZBCuBN9jNpKbLR0wBRg1Ijy6_1zbnIFblReGpGDhRWVq4314Fn7FVisrFKBGemNqpw2lSjBoPTKVsKHImEdmOsXK3x4AroCj81SWu21DFxamu01GL_Vyu6qvQOiysGuW9AIQq3T7jQ6KkTpVPfHn0RP6XgxvO3N7id3w8GsJwiBuCdjBmE_RkQKJDmnLEdMSlTQPiRFHFNJ5TIJLqcCxkTSgid5XxZiGatYJZSTk-h8r1tb89oo57O1acISpctwwhHijBEaqIs9Ja1xzqoiq8PowrYZgtnu6tnfqwec7PGtLlX7L5tNJw9p-JcEk285Z4YG</recordid><startdate>202303</startdate><enddate>202303</enddate><creator>Li, ZhiPeng</creator><creator>Kiani Oshtorjani, Mehrdad</creator><creator>Chen, Dong</creator><creator>Zhang, Yong</creator><creator>Sun, HongGuang</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0001-8726-4663</orcidid><orcidid>https://orcid.org/0000-0003-1209-9434</orcidid><orcidid>https://orcid.org/0000-0003-0121-0950</orcidid><orcidid>https://orcid.org/0000-0002-8422-3871</orcidid></search><sort><creationdate>202303</creationdate><title>Dynamics of Dual‐Mode Bedload Transport With Three‐Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis</title><author>Li, ZhiPeng ; Kiani Oshtorjani, Mehrdad ; Chen, Dong ; Zhang, Yong ; Sun, HongGuang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3302-c58004513ca1c9968d18cc1f6403f556c6cb756cd6a053c6f97d4cfab5e5e7693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Bars (landforms)</topic><topic>Bed forms</topic><topic>Bed load</topic><topic>Bedforms</topic><topic>bedload transport</topic><topic>Clusters</topic><topic>Complexity</topic><topic>CTRW</topic><topic>Distribution</topic><topic>dual‐mode behavior</topic><topic>Dynamics</topic><topic>Encapsulation</topic><topic>Experiments</topic><topic>Fluctuations</topic><topic>Flumes</topic><topic>Gravel</topic><topic>Gravel beds</topic><topic>heavy‐tailed dynamics</topic><topic>hyperexponential distribution</topic><topic>Laboratory experimentation</topic><topic>Laboratory experiments</topic><topic>Mass transfer</topic><topic>Modelling</topic><topic>Particle settling</topic><topic>Pools</topic><topic>Probability distribution</topic><topic>Probability theory</topic><topic>Random walk</topic><topic>River beds</topic><topic>Riverbeds</topic><topic>Rivers</topic><topic>Saltation</topic><topic>Scaling</topic><topic>Sediment</topic><topic>Sediment discharge</topic><topic>Sediment movement</topic><topic>Sediment transport</topic><topic>Sedimentary structures</topic><topic>Sediments</topic><topic>Stochasticity</topic><topic>Subcritical flow</topic><topic>Tranquil flow</topic><topic>Transport phenomena</topic><topic>Transport rate</topic><topic>waiting time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, ZhiPeng</creatorcontrib><creatorcontrib>Kiani Oshtorjani, Mehrdad</creatorcontrib><creatorcontrib>Chen, Dong</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>Sun, HongGuang</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Environment Abstracts</collection><jtitle>Journal of geophysical research. Earth surface</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, ZhiPeng</au><au>Kiani Oshtorjani, Mehrdad</au><au>Chen, Dong</au><au>Zhang, Yong</au><au>Sun, HongGuang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamics of Dual‐Mode Bedload Transport With Three‐Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis</atitle><jtitle>Journal of geophysical research. Earth surface</jtitle><date>2023-03</date><risdate>2023</risdate><volume>128</volume><issue>3</issue><epage>n/a</epage><issn>2169-9003</issn><eissn>2169-9011</eissn><abstract>Bedload transport often exhibits dual‐mode behavior due to interactions of spatiotemporal controlling factors with the migrating three‐dimensional bedforms (characterized by the fully developed patterns in the bed, such as alternate bars, pools, and clusters). This study explores dual‐mode bedload transport based on experimental measurements and develops Einstein's exponential‐based model to characterize large fluctuations of bedload sediment discharge. The particle waiting time, particle flux, and bed elevation are measured in a series of well‐controlled laboratory experiments. Flume experiments show that the waiting time distribution of sediments gives a bimodal characteristic, two distinct modes can be identified from the measured data. This study encapsulates this dual‐mode bedload transport behavior in a hyperexponential distribution of sediment resting times and introduces it into the continuous time random walk (CTRW) framework. Considering the scaling limit of the thin/heavy‐tailed CTRW processes, a single‐rate mass transfer (SRMT) and fractional‐derivative SRMT (F‐SRMT) models are obtained, and the model parameters are determined from the hyperexponential distribution. Further analyses reveal that the dual‐mode bedload transport behavior is controlled by mass exchange between the mobile and immobile zones, and a dimensionless index η can quantify the intensity of dual‐mode behavior. Applications show that the dual‐mode bedload transport models are much more accurate in characterizing bedload transport in a mixed‐size gravel bed than the traditional exponential‐based model, and the nonlocal movement of bedload sediments is significant in the mixed‐size gravel bed. Further investigations will focus on the applicability test of the dual‐mode models to other flow regimes and conditions.
Plain Language Summary
Sediment transport caused by particles rolling and sliding as well as saltation on riverbeds is called bedload transport. Bedload transport is highly complex due to the complexity of the flow and bedform in natural rivers. Bedforms are commonly classified in terms of their characteristic longitudinal scales, and a three‐dimensional (3‐D) bedform represents the bed with fully developed patterns such as alternate bars, pools, and clusters. Traditional models in quantifying bedload transport may differ from field data by 1–4 orders of magnitude, especially for the migrating 3‐D bedforms. In this study, flume experiments reveal that the waiting time distribution of bedload sediments shows a significant bimodal characteristic (two bumps can be distinguished by the probability distribution curve) when transporting along the 3‐D riverbeds, and two modes can be identified from the experimental data. The observed dual‐mode bedload transport behavior is encapsulated by a mixture (hyperexponential) distribution after collecting two exponential distributions of sediment resting times. The stochastic and deterministic models are developed to characterize the observed dual‐mode bedload transport behavior, providing a tractable way for quantifying large fluctuations in the bedload transport rate due to the presence of dual‐mode dynamics in sediment movement.
Key Points
Probability density functions of the particle waiting time measured in the flume experiments exhibit a bimodal feature
A novel formula of resting time is developed to characterize the observed dual‐mode bedload transport behavior in experiments
Experimental observations guide the development of stochastic and deterministic models for dual‐mode bedload transport</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2022JF006882</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0001-8726-4663</orcidid><orcidid>https://orcid.org/0000-0003-1209-9434</orcidid><orcidid>https://orcid.org/0000-0003-0121-0950</orcidid><orcidid>https://orcid.org/0000-0002-8422-3871</orcidid></addata></record> |
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subjects | Bars (landforms) Bed forms Bed load Bedforms bedload transport Clusters Complexity CTRW Distribution dual‐mode behavior Dynamics Encapsulation Experiments Fluctuations Flumes Gravel Gravel beds heavy‐tailed dynamics hyperexponential distribution Laboratory experimentation Laboratory experiments Mass transfer Modelling Particle settling Pools Probability distribution Probability theory Random walk River beds Riverbeds Rivers Saltation Scaling Sediment Sediment discharge Sediment movement Sediment transport Sedimentary structures Sediments Stochasticity Subcritical flow Tranquil flow Transport phenomena Transport rate waiting time |
title | Dynamics of Dual‐Mode Bedload Transport With Three‐Dimensional Alternate Bars Migration in Subcritical Flow: Experiments and Model Analysis |
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