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

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dc.citation.articleNumbere2020WR027199en_US
dc.citation.issueNumber11en_US
dc.citation.journalTitleWater Resources Researchen_US
dc.citation.volumeNumber56en_US
dc.contributor.authorDong, Tian Y.en_US
dc.contributor.authorNittrouer, Jeffrey A.en_US
dc.contributor.authorMcElroy, Brandonen_US
dc.contributor.authorIl'icheva, Elenaen_US
dc.contributor.authorPavlov, Maksimen_US
dc.contributor.authorMa, Hongboen_US
dc.contributor.authorMoodie, Andrew J.en_US
dc.contributor.authorMoreido, Vsevolod M.en_US
dc.date.accessioned2020-12-16T22:09:03Zen_US
dc.date.available2020-12-16T22:09:03Zen_US
dc.date.issued2020en_US
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.en_US
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.en_US
dc.identifier.doihttps://doi.org/10.1029/2020WR027199en_US
dc.identifier.urihttps://hdl.handle.net/1911/109751en_US
dc.language.isoengen_US
dc.publisherWileyen_US
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.en_US
dc.titlePredicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditionsen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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