Water Resources Research, volume 56, issue 11
Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions
Dong Tian Y
1
,
Nittrouer J. A.
1
,
McElroy B. J.
2
,
Il’icheva Elena
3, 4
,
Pavlov Maksim
3
,
Ma Hongbo
1
,
Moodie Andrew J.
1
,
Moreido V. M.
5
,
Moreido Vsevolod M
5
2
Department of Geology and Geophysics University of Wyoming Laramie WY USA
|
Publication type: Journal Article
Publication date: 2020-11-01
Journal:
Water Resources Research
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 5.4
ISSN: 00431397, 19447973
Water Science and Technology
Abstract
Channel 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.
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Citations by publishers
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Wiley
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9 publications, 45%
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Frontiers Media S.A.
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Frontiers Media S.A.
1 publication, 5%
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Springer Nature
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Springer Nature
1 publication, 5%
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Taylor & Francis
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Taylor & Francis
1 publication, 5%
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The Open Journal
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The Open Journal, 1, 5%
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1 publication, 5%
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Dong T. Y. et al. Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions // Water Resources Research. 2020. Vol. 56. No. 11.
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Dong T. Y., Nittrouer J. A., McElroy B. J., Il’icheva E., Pavlov M., Ma H., Moodie A. J., Moreido V. M., Moreido V. M. Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions // Water Resources Research. 2020. Vol. 56. No. 11.
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TY - JOUR
DO - 10.1029/2020wr027199
UR - https://doi.org/10.1029%2F2020wr027199
TI - Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions
T2 - Water Resources Research
AU - Dong, Tian Y
AU - Nittrouer, J. A.
AU - McElroy, B. J.
AU - Il’icheva, Elena
AU - Pavlov, Maksim
AU - Ma, Hongbo
AU - Moodie, Andrew J.
AU - Moreido, Vsevolod M
AU - Moreido, V. M.
PY - 2020
DA - 2020/11/01 00:00:00
PB - Wiley
IS - 11
VL - 56
SN - 0043-1397
SN - 1944-7973
ER -
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@article{2020_Dong,
author = {Tian Y Dong and J. A. Nittrouer and B. J. McElroy and Elena Il’icheva and Maksim Pavlov and Hongbo Ma and Andrew J. Moodie and Vsevolod M Moreido and V. M. Moreido},
title = {Predicting Water and Sediment Partitioning in a Delta Channel Network Under Varying Discharge Conditions},
journal = {Water Resources Research},
year = {2020},
volume = {56},
publisher = {Wiley},
month = {nov},
url = {https://doi.org/10.1029%2F2020wr027199},
number = {11},
doi = {10.1029/2020wr027199}
}
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