Testing Nodal Point Relations by Tracking Sediment Through a Bifurcation on the Jefferson River, MT, USA
Year: 2026
Type: article
Abstract: River bifurcations control water and sediment distribution in fluvial systems, but the physical mechanisms governing sediment partitioning remain poorly validated in natural rivers. We present a comprehensive field test of nodal point relations using radio frequency identification (RFID) tracking of 376 gravel clasts through a meandering river bifurcation in Montana, USA. The study bifurcation features key characteristics for testing existing theory: upstream channel curvature, a 40‐cm bed ramp at the shallower bifurcate entrance, and unequal branch geometry. During the 2017 flood season, we recovered 202 (out of 376) clasts transported through the bifurcation, which divided nearly equally between bifurcate arms. Statistical analysis reveals that sediment partitioning is primarily controlled by upstream transverse position and longitudinal deployment distance, while grain size, shape, and mass show no significant influence. Calibrated Delft3D modeling combined with theoretical nodal point relations demonstrates that for curved bifurcations, helical flow and non‐uniform incoming sediment push sediment in opposite directions. The nodal point relation that accounts for non‐uniform incoming sediment distribution due to curvature best predicts the observed sediment delivery to the northern arm. Our results provide critical field validation showing that curvature‐induced sorting begins well upstream of the bifurcation node, and the two curvature effects (helical flow deflection and non‐uniform incoming sediment distribution) must both be included for accurate predictions. These findings advance our understanding of bifurcation mechanics and provide guidance for improving theoretical models and river restoration designs.
DOI: 10.1029/2025jf008799
Institutions: Indiana University, Utah State University, Chevron (United States)
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,070
Funder: National Science Foundation
OpenAlex ID: W7148788396
