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May 13, 2026Water Resources Research0 citationsOpen Access

Refinement of a Framework for Moving Aircraft River Velocimetry (MARV) and Application to Particle Tracking Along Alaskan Rivers

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CLCarl J. LegleiterPKPaul J. KinzelMLMark Laker

Key Points

  • The study aims to refine the framework of Moving Aircraft River Velocimetry (MARV) and assess its functionality for particle tracking in river systems.
  • Utilized data from two new sites to assess MARV's accuracy compared to field measurements
  • Evaluated different configurations of image sequences to enhance velocity estimates
  • Demonstrated MARV's applicability in driving particle tracking models for river dynamics
  • MARV yielded velocity estimates with a correlation of up to 0.87 compared to field measurements
  • Optimal configuration of MARV involved a long window with short jumps between sequences
  • Initial simulations indicated that channel morphology and flow velocity significantly impact particle travel time and fate, while diffusion plays a smaller role.

Abstract

Abstract Information on river velocities enhances understanding flood hazards, evaluating habitat conditions, and predicting the transport of floating materials. In this follow‐up study, we used data from two new sites, one with a more complex morphology and the other with a lower suspended sediment concentration, to provide further evidence that Moving Aircraft River Velocimetry (MARV) can yield accurate velocity estimates ( up to 0.87 when compared to field measurements) for long segments of large, turbid rivers. The MARV workflow is packaged in freely available software and is robust to implementation details; neither buffering to mitigate edge effects nor a new approach to aggregating velocity vectors improved performance. MARV was not sensitive to parameters used to establish overlapping image sequences, but combining a long window with a short jump between consecutive windows was the optimal configuration. Although accuracy varied from one cross section to the next, agreement between remotely sensed velocities and those measured in the field was independent of position within a frame range. As an initial step toward application of the approach to help address practical problems, we showed how MARV can drive particle tracking models. Our first‐order simulations suggest that channel morphology and flow velocity are the primary controls on travel time and particle fate, with diffusive processes playing a lesser role. Although MARV can be used to characterize an instantaneous flow field, a more comprehensive framework that accounts for other physical processes would be required to model specific types of events like oil spills.

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Cite This Study

Legleiter et al. (2026) studied this question.

synapsesocial.com/papers/6a04153d79e20c90b4444ff9https://doi.org/10.1029/2025wr043181
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