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.
River deltas are home to large populations and can be composed of complex channel networks which convey flows of matter to the shoreline. Knowledge of flow within individual channels is needed to quantify the distribution of discharge across the delta, and thus its sustainability over time. Due to a lack of field measurements at the local channel scale, researchers leverage remote sensing data to estimate the partitioning of flow. We compare data from 15 river deltas to discharge partitioning estimates based on channel network graphs derived from remote sensing imagery. We quantify errors in the common width‐based method and test alternative partitioning techniques to find that width‐based discharge partitioning is universally applicable, suggesting that absent any site‐specific information, discharge partitioning by average channel width is an appropriate approach. We also provide networks, streamflow measurements, and flux partitioning estimates for 28 delta networks as the Discharge In Distributary NeTworks (DIDNT) dataset.
more » « less- Award ID(s):
- 1719670
- NSF-PAR ID:
- 10370347
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 49
- Issue:
- 14
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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