THE SECRET LIVES OF MEANDER BENDS

Mapping meander migration over decades is usually performed at coarse time intervals where the initial and final channel positions are established from maps, aerial photographs, satellite imagery, etc. Trajectories of meander planform evolution are thus often poorly resolved due to a combination of insufficient historic data and slow migration. Large and active meandering tropical rivers, observed by Landsat satellite imagery collected worldwide every 18 days at 30 meter resolution since 1984, potentially occupy a “sweet spot” of observational resolution where more than three decades of imagery capture significant portions of meander bend lifetimes at sub-annual time resolution. This study leverages Landsat imagery to resolve annual planform dynamics of over 1,300 km of the Ucayali River in Peru.

Each available Landsat image is classified, and annual bankfull-resolving composites are created by combining individual images. Binary channel masks are derived from the annual composites, and these annual masks are used to quantify planform changes. A comprehensive Matlab toolbox was developed to extract banklines and centerlines, compute widths, curvatures, and angles, and quantify planform changes via centerline migration and erosion/accretion. The toolbox was applied to binary masks of the Ucayali River to quantify changes in width, identify hotspots of migration, and map 57 cutoffs over 30 years of evolution. The analysis captures variability from the reach-scale, where climate may control average migration rates, to the bend-scale where local flow conditions and channel morphology affect meander migration. Intermediate-scale variability is also observed that corresponds to cutoff events that, in some cases, induce accelerated migration rates up- and downstream across many bends. This study demonstrates the vast potential locked within Landsat archives to identify multi-scale controls on meander migration, observe the co-evolution of width, curvature, discharge, and migration, and discover and develop new geomorphic insights such as accelerated migrations due to cutoff.