Towards a Global Assessment of Bar Push Versus Bank Pull using Remote Sensing and Cloud Computing.

Abstract

Rivers and floodplains are hotspots of biodiversity that support a large and growing number of people with food, water, nutrients, and transportation. Within these floodplains, the dynamic interplay of erosion on the outer banks and sedimentation on the inner banks propels lateral channel migration, resulting in the creation of intricate and sinuous meandering river landscapes. A key question in river meandering research concerns the ongoing debate regarding the primary driver of lateral river migration. Is it initiated by outer-bank erosion, leading to localized inner-bank deposition (the process known as ‘bank pull’), or is it inner sedimentation that initially diverts the flow, subsequently triggering outer-bank erosion (‘bar push’)? This study introduces an innovative methodology that combines extensive time series analysis of remote sensing imagery with cloud computing to discern the prevalence of bar push versus bank pull across vast sections of the global river network. The methodology involves analyzing each image to pinpoint the precise timing of pixels undergoing erosion and/or sedimentation. For each river bend, we compare the years in which the outer bank undergoes erosion with the years in which the inner bank experiences sedimentation, thereby determining the predominant process—erosion and bank pull, or sedimentation and bar push. Additionally, we explore whether these processes change over time and whether they are correlated with factors such as river sediment load, bank vegetation, river curvature, and other relevant physiographic metrics. By extending this methodology to diverse rivers worldwide, we systematically test the bar push versus bank pull theories in a variety of real environmental settings. This unprecedented, large-scale analysis advances our understanding of meandering rivers and their complex dynamics.