Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions

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dc.citation.articleNumbere2020WR027199
dc.citation.issueNumber11
dc.citation.journalTitleWater Resources Research
dc.citation.volumeNumber56
dc.contributor.authorDong, Tian Y.
dc.contributor.authorNittrouer, Jeffrey A.
dc.contributor.authorMcElroy, Brandon
dc.contributor.authorIl'icheva, Elena
dc.contributor.authorPavlov, Maksim
dc.contributor.authorMa, Hongbo
dc.contributor.authorMoodie, Andrew J.
dc.contributor.authorMoreido, Vsevolod M.
dc.date.accessioned2020-12-16T22:09:03Z
dc.date.available2020-12-16T22:09:03Z
dc.date.issued2020
dc.description.abstractChannel bifurcations control the distribution of water and sediment in deltas, and the routing of these materials facilitates land building in coastal regions. Yet few practical methods exist to provide accurate predictions of flow partitioning at multiple bifurcations within a distributary channel network. Herein, multiple nodal relations that predict flow partitioning at individual bifurcations, utilizing various hydraulic and channel planform parameters, are tested against field data collected from the Selenga River delta, Russia. The data set includes 2.5 months of time‐continuous, synoptic measurements of water and sediment discharge partitioning covering a flood hydrograph. Results show that width, sinuosity, and bifurcation angle are the best remotely sensed, while cross‐sectional area and flow depth are the best field measured nodal relation variables to predict flow partitioning. These nodal relations are incorporated into a graph model, thus developing a generalized framework that predicts partitioning of water discharge and total, suspended, and bedload sediment discharge in deltas. Results from the model tested well against field data produced for the Wax Lake, Selenga, and Lena River deltas. When solely using remotely sensed variables, the generalized framework is especially suitable for modeling applications in large‐scale delta systems, where data and field accessibility are limited.
dc.identifier.citationDong, Tian Y., Nittrouer, Jeffrey A., McElroy, Brandon, et al.. "Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions." <i>Water Resources Research,</i> 56, no. 11 (2020) Wiley: https://doi.org/10.1029/2020WR027199.
dc.identifier.doihttps://doi.org/10.1029/2020WR027199
dc.identifier.urihttps://hdl.handle.net/1911/109751
dc.language.isoeng
dc.publisherWiley
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
dc.titlePredicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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