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Successful management of flooding and erosion hazards on floodplains depends on our ability to predict a river channel's shape and the lifespan during which it will continue to flow. Recent progress has improved our understanding of what sets the lifespan and width of single‐thread channels; the next challenge is to extend this knowledge to braided channels and their interwoven sub‐channels (threads). In this study, we investigate the lifespan and width of braided channel threads in a large experimental data set, coupled with particle‐image velocimetry‐derived measurements of riverbank erosion and accretion. We find that, unlike single‐thread channels, braided channels in the experiment do not exhibit an equilibrium between bank erosion and accretion. Instead, bank erosion outpaces lateral accretion, causing individual threads to widen and infill until they are abandoned. Thread lifespan is limited to the time it takes for threads to triple their width: tripling of the width yields enough bank material to aggrade more than half the channel depth, at which point flow is rerouted to a narrower thread. In consequence the width of active threads is limited to three times their initial width. Threshold channel theory accurately predicts the median thread width, which is roughly double the initial width and two‐thirds the limiting width. The results are consistent with existing field data and suggest that differential bank migration is sufficient to explain why braided channels show greater width variability and higher width‐to‐depth ratios than their single‐thread counterparts.

 

The morphology of deltas is determined by the spatial extent and variability of the geomorphic processes that shape them. While in some cases resilient, deltas are increasingly threatened by natural and anthropogenic forces, such as sea level rise and land use change, which can drastically alter the rates and patterns of sediment transport. Quantifying process patterns can improve our predictive understanding of how different zones within delta systems will respond to future change. Available remotely sensed imagery can help but appropriate tools are needed for pattern extraction and analysis. We present a method for extracting information about the nature and spatial extent of active geomorphic processes across deltas from ten parameters quantifying the geometry of each of 1239 islands and the channels around them using machine learning. The method consists of a two-step unsupervised machine learning algorithm that clusters islands into spatially continuous zones based on the ten morphological metrics extracted from remotely sensed imagery. By applying this method to the Ganges–Brahmaputra–Meghna Delta, we find that the system can be divided into six major zones. Classification results show that active fluvial island construction and bar migration processes are limited to relatively narrow zones along the main Ganges River and Brahmaputra and Meghna corridors, whereas zones in the mature upper delta plain, with smaller fluvial distributary channels stand out as their own morphometric class. The classification also shows good correspondence with known gradients in the influence of tidal energy with distinct classes for islands in the backwater zone and in the purely tidally-controlled region of the delta. Islands at the delta front, under the mixed influence of tides, fluvial-estuarine construction, and local wave reworking have their own characteristic shape and channel configuration. The method does not distinguish between islands with embankments (polders) and natural islands in the nearby mangrove forest (Sundarbans), suggesting that human modifications have not yet altered the gross geometry of the islands beyond their previous natural morphology. These results demonstrate that machine learning and remotely sensed imagery are useful tools for identifying the spatial patterns of geomorphic processes across delta systems. 

Deltaic river networks naturally reorganize as interconnected channels move to redistribute water, sediment, and nutrients across the delta plain. Network change is documented in decades of satellite imagery and laboratory experiments, but our ability to measure and understand channel movements is limited: existing methods are difficult to employ efficiently and struggle to distinguish between gradual movements (channel migration) and abrupt shifts in river course (channel avulsions). Here, we present a method to extract channel migration from plan‐view imagery using particle image velocimetry (PIV). Although originally designed to track particles moving in a fluid, PIV can be adapted to track channels moving on the delta surface, based on input estimates of channel width, migration timescale, and maps of the wet‐dry interface. Results for a delta experiment show that PIV‐derived vector fields accurately capture channel‐bank movements, as compared to manually drawn maps and an independent image‐registration technique. Unlike other methods, PIV targets the process of channel migration, excluding changes associated with channel avulsions and overbank flow. PIV‐derived migration rates from the experiment span an order of magnitude and are reduced under lower sediment supply and during sea‐level rise, supporting recent models. Together, results indicate that PIV offers a fast and reliable way to measure channel migration in river networks, that channel migration rates under non‐cohesive conditions can displace channels a distance comparable to their width in the time needed to aggrade ∼10% of the channel depth, and that migration direction is ∼60% orthogonal to mean flow direction and ∼40% flow‐parallel overall.

 

Arising from the non‐uniform dispersal of sediment and water that build deltaic landscapes, morphological change is a fundamental characteristic of river delta behavior. Thus, sustainable deltas require mobility of their channel networks and attendant shifts in landforms. Both behaviors can be misrepresented as degradation, particularly in context of the “stability” that is generally necessitated by human infrastructure and economies. Taking the Ganges‐Brahmaputra‐Meghna Delta as an example, contrary to public perception, this delta system appears to be sustainable at a system scale with high sediment delivery and long‐term net gain in land area. However, many areas of the delta exhibit local dynamics and instability at the scale at which households and communities experience environmental change. Such local landscape “instability” is often cited as evidence that the delta is in decline, whereas much of this change simply reflects the morphodynamics typical of an energetic fluvial‐delta system and do not provide an accurate reflection of overall system health. Here we argue that this disparity between unit‐scale sustainability and local morphodynamic change may be typical of deltaic systems with well‐developed distributary networks and strong spatial gradients in sediment supply and transport energy. Such non‐uniformity and the important connections between network sub‐units (i.e., fluvial, tidal, shelf) suggest that delta risk assessments must integrate local dynamics and sub‐unit connections with unit‐scale behaviors. Structure and dynamics of an integrated deltaic network control the dispersal of water, solids, and solutes to the delta sub‐environment and thus the local to unit‐scale sustainability of the system over time.

 

At a global scale, delta morphologies are subject to rapid change as a result of direct and indirect effects of human activity. This jeopardizes the ecosystem services of deltas, including protection against flood hazards, facilitation of navigation, and biodiversity. Direct manifestations of delta morphological instability include river bank failure, which may lead to avulsion, persistent channel incision or aggregation, and a change of the sedimentary regime to hyperturbid conditions. Notwithstanding the in‐depth knowledge developed over the past decades about those topics, existing understanding is fragmented, and the predictive capacity of morphodynamic models is limited. The advancement of potential resilience analysis tools may proceed from improved models, continuous observations, and the application of novel analysis techniques. Progress will benefit from synergy between approaches. Empirical and numerical models are built using field observations, and, in turn, model simulations can inform observationists about where to measure. Information theory offers a systematic approach to test the realism of alternative model concepts. Once the key mechanism responsible for a morphodynamic instability phenomenon is understood, concepts from dynamic system theory can be employed to develop early warning indicators. In the development of reliable tools to design resilient deltas, one of the first challenges is to close the sediment balance at multiple scales, such that morphodynamic model predictions match with fully independent measurements. Such a high ambition level is rarely adopted and is urgently needed to address the ongoing global changes causing sea level rise and reduced sediment input by reservoir building.