Remote Sensing of Riverbank Migration Using Particle Image Velocimetry

Chadwick, A. J.; Greenberg, Evan; Ganti, Vamsi

doi:10.1029/2023jf007177

Cited by 5 publications

(10 citation statements)

References 112 publications

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“…For example, differences in area‐based mobility between braided and meandering rivers could highlight important differences in floodplain turnover. Area‐based metrics can also be used alongside centerline‐, vector‐ and pixel‐based methods that only quantity bank migration (Chadwick et al., 2023; Rowland et al., 2016; Sylvester et al., 2019) to tease apart relative contributions of bank‐scale, reach‐scale and floodplain‐scale processes to floodplain erosion and planform change.…”

Section: Discussionmentioning

confidence: 99%

“…This is problematic because multi‐thread channels are pervasive worldwide and constitute some of the world's largest river systems (Galeazzi et al., 2021; Latrubesse, 2008). Existing morphology‐independent methods are only designed to quantify bank‐scale migration and ignore reach and floodplain scale processes like channel‐bend cutoff and avulsion (e.g., Chadwick et al., 2023). There is a crucial need for planform‐independent remote sensing methods that can integrate reach‐ and floodplain‐scale river mobility, especially since these are the scales over which we expect natural environmental gradients and anthropogenic climate change to impact rivers.…”

Section: Introductionmentioning

confidence: 99%

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A Generalized Area‐Based Framework to Quantify River Mobility From Remotely Sensed Imagery

Greenberg,

Chadwick,

Ganti

2023

JGR Earth Surface

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Rivers are the primary conduits of water and sediment across Earth’s surface. In recent decades, rivers have been increasingly impacted by climate change and human activities. The availability of global‐coverage satellite imagery provides a powerful avenue to study river mobility and quantify the impacts of these perturbations on global river behavior. However, we lack remote sensing methods for quantifying river mobility that can be generally applied across the diversity of river planforms (e.g., meandering, braided) and fluvial processes (e.g., channel migration, avulsion). Here, we upscale area‐based methods from laboratory flume experiments to build a generalized remote sensing framework for quantifying river mobility. The framework utilizes binary channel‐mask time series to determine time‐ and area‐integrated rates and scales of river floodplain reworking and channel‐thread reorganization. We apply the framework to numerical models to demonstrate that these rates and scales are sensitive to specific river processes (channel migration, channel‐bend cut‐off, and avulsion). We then apply the framework to natural migrating and avulsing rivers with meandering and braided planforms. Results show that our area‐based framework provides an objective and accurate means to quantify river mobility at reach‐ to floodplain‐scales, which is largely insensitive to spatial and temporal biases that can arise in traditional mobility metrics. Our work provides a framework for investigating global controls on river mobility, testing hypotheses about river response to environmental gradients, and quantifying the timescales of terrestrial organic carbon cycling.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Generalized Area‐Based Framework to Quantify River Mobility From Remotely Sensed Imagery

Greenberg,

Chadwick,

Ganti

2023

JGR Earth Surface

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“…Notably, PIV specializes in capturing vectors related to gradual bank migration while effectively ignoring those associated with abrupt morphological changes, such as avulsion or the sudden opening and closing of anabranches. This characteristic is supported by both laboratory Chadwick, Steel, Williams-Schaetzel, et al, 2022) and remote sensing evidence (Chadwick et al, 2023) and differentiates PIV from other channel-tracking algorithms such as dynamic time warping (Lisiecki & Lisiecki, 2002), demon (Thirion, 1998), and SCREAM (Rowland et al, 2016)-which yield erroneous migration vectors in areas associated with abrupt morphological changes (Chadwick, Steel, Williams-Schaetzel, et al, 2022;Sylvester et al, 2019). To address the current data limitations on applying topography-based PIV, emerging methods including Light Detection and Ranging and Unmanned Aerial Vehicle (UAV)-enabled techniques could provide more efficient and frequent topographic measurements.…”

Section: Water Resources Researchmentioning

confidence: 90%

“…10.1029/2023WR035229 would cause erroneous migration vectors (Figure 9a) (Chadwick et al, 2023). Yet in some field settings amenable to image-based PIV, the application of topography-based PIV can be used to independently measure the motion of channel threads.…”

Section: Water Resources Researchmentioning

confidence: 99%

“…PIV works by cross‐correlating small sub‐images, known as interrogation areas, in successive images to determine the best‐fit displacement between image pairs (Keane & Adrian, 1992; Westerweel, 1997). This method has been used to track the motion of channel centerlines from satellite images (Chadwick et al., 2023; Jarriel et al., 2021) and track the motion of riverbanks in laboratory deltas from overhead photographs (Chadwick, Steel, Passalacqua, & Paola, 2022; Chadwick, Steel, Williams‐Schaetzel, et al., 2022). Importantly, PIV does not track channel thread displacements that exceed the width of the largest interrogation area (Nogueira et al., 2001; Sciacchitano, 2019; Westerweel, 1997).…”

Section: Introductionmentioning

confidence: 99%

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Topography‐Based Particle Image Velocimetry of Braided Channel Initiation

Wang,

Limaye,

Chadwick

2024

Water Resources Research

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River channels shape landscapes through gradual migration and abrupt avulsion. Measuring the motion of braided rivers, which have multiple channel threads, is particularly challenging, limiting predictions for landscape evolution and fluvial architecture. To address this challenge, we extended the capabilities of image‐based particle image velocimetry (PIV)—a technique for tracking channel threads in images of the surface—by adapting it to analyze topographic change. We applied this method in a laboratory experiment where a straight channel set in non‐cohesive sediment evolved into a braided channel under constant water and sediment fluxes. Topography‐based PIV successfully tracked the motion of channel threads if displacements between observations were less than the channel‐thread width, consistent with earlier results from image‐based PIV. We filtered spurious migration vectors with magnitudes less than the elevation grid spacing, or with high uncertainties in magnitude and/or direction. During braided channel initiation, migration rates varied with the channel planform development, showing an increase as incipient meanders developed, a decrease during the transitional braiding phase, and consistently low values during the established braiding phase. In this experimental setup, migration rates varied quasi‐periodically along stream at the half scale of initial meander bends. Lateral migration with respect to the mean flow direction was much more pronounced than streamwise migration, accounting for approximately 80% of all detected motion. Results demonstrate that topography‐based PIV has the potential to advance predictions for bank erosion and landscape evolution in natural braided rivers as well as bar preservation and stratigraphic architecture in geological records.

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Vegetation enhances curvature-driven dynamics in meandering rivers

Finotello,

Ielpi,

Lapôtre

et al. 2024

Nat Commun

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Stabilization of riverbanks by vegetation has long been considered necessary to sustain single-thread meandering rivers. However, observation of active meandering in modern barren landscapes challenges this assumption. Here, we investigate a globally distributed set of modern meandering rivers with varying riparian vegetation densities, using satellite imagery and statistical analyses of meander-form descriptors and migration rates. We show that vegetation enhances the coefficient of proportionality between channel curvature and migration rates at low curvatures, and that this effect wanes in curvier channels irrespective of vegetation density. By stabilizing low-curvature reaches and allowing meanders to gain sinuosity as channels migrate laterally, vegetation quantifiably affects river morphodynamics. Any causality between denser vegetation and higher meander sinuosity, however, cannot be inferred owing to more frequent avulsions in modern non-vegetated environments. By illustrating how vegetation affects channel mobility and floodplain reworking, our findings have implications for assessing carbon stocks and fluxes in river floodplains.

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Remote Sensing of Riverbank Migration Using Particle Image Velocimetry

Abstract: River channels are inherently mobile. Their movement across floodplains is responsible for shaping Earth's lowland ecosystems and landscapes (

Cited by 5 publications

References 112 publications

A Generalized Area‐Based Framework to Quantify River Mobility From Remotely Sensed Imagery

A Generalized Area‐Based Framework to Quantify River Mobility From Remotely Sensed Imagery

Topography‐Based Particle Image Velocimetry of Braided Channel Initiation

Vegetation enhances curvature-driven dynamics in meandering rivers

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