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1. Dominant process zones in a mixed fluvial-tidal delta are morphologically distinct

   Perignon, M.; Adams, J.; Overeem, I.; Passalacqua, P. (April 2020, Earth surface dynamics discussions)

   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. 

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2. Global rates and patterns of channel migration in river deltas

   https://doi.org/10.1073/pnas.2103178118  

   Jarriel, Teresa; Swartz, John; Passalacqua, Paola (November 2021, Proceedings of the National Academy of Sciences)

   River deltas are dynamic systems whose channels can widen, narrow, migrate, avulse, and bifurcate to form new channel networks through time. With hundreds of millions of people living on these globally ubiquitous systems, it is critically important to understand and predict how delta channel networks will evolve over time. Although much work has been done to understand drivers of channel migration on the individual channel scale, a global-scale analysis of the current state of delta morphological change has not been attempted. In this study, we present a methodology for the automatic extraction of channel migration vectors from remotely sensed imagery by combining deep learning and principles from particle image velocimetry (PIV). This methodology is implemented on 48 river delta systems to create a global dataset of decadal-scale delta channel migration. By comparing delta channel migration distributions with a variety of known external forcings, we find that global patterns of channel migration can largely be reconciled with the level of fluvial forcing acting on the delta, sediment flux magnitude, and frequency of flood events. An understanding of modern rates and patterns of channel migration in river deltas is critical for successfully predicting future changes to delta systems and for informing decision makers striving for deltaic resilience. 

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3. Stable ≠ Sustainable: Delta Dynamics Versus the Human Need for Stability

   https://doi.org/10.1029/2021EF002121  

   Passalacqua, P.; Giosan, L.; Goodbred, S.; Overeem, I. (July 2021, Earth's Future)

   Abstract 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. 

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4. Modeling the dynamics of sediment transport, tides, and sea-level rise: Implications for the resilience of coastal Bengal.

   Tasich, C.M.; Gilligan, J.M.; Hornberger, G.M. (January 2024, Proceedings of the 2023 Winter Simulation Conference)

   Corlu, C.G.; Hunter, S.R.; Lam, B.; Onggo, S.; Shortle, J.; Biller, B. (Ed.)

   The coastal zone of the Ganges-Brahmaputra-Meghna (GBM) Delta is widely recognized as one of the most vulnerable places to sea-level rise (SLR), with around 57 million people living within 5m of sea level. Sediment transported by the Ganges, Brahmaputra, and Meghna rivers has the potential to raise the land and offset SLR. There is significant uncertainty in future sediment supply and SLR, which raises questions about the sustainability of the delta. We present a simple model, driven by basic physics, to estimate the evolution of the landscape under different conditions at low computational cost. Using a single tuning parameter, the model can match observed rates of land aggradation. We find a strong negative feedback, which robustly brings land elevation into equilibrium with changing sea level. We discuss how this model can be used to investigate the dynamics of sediment transport and the sustainability of the GBM Delta. 

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5. Image-based machine learning for monitoring the dynamics of deltaic islands in the Atchafalaya River Delta Complex between 1991 and 2019

   https://doi.org/10.1016/j.jhydrol.2023.129814  

   Yang, Jiangjie; Dai, Zhijun; Lou, Yaying; Mei, Xuefei; Fagherazzi, Sergio (August 2023, Journal of Hydrology)

   Deltaic islands are distinct hydro-environmental zones with global significance in food security, biodiversity conservation, and fishery industry. These islands are the fundamental building blocks of many river deltas. However, deltaic islands are facing severe challenges due to intensive anthropogenic activities, sea level rise, and climate change. In this study, dynamic changes of deltaic islands in Wax Lake Delta (WLD) and Atchafalaya Delta (AD), part of the Atchafalaya River Delta Complex (ARDC) in Louisiana, USA, were quantified based on remote sensing images from 1991 to 2019 through a machine learning method. Results indicate a significant increase in deltaic islands area for the whole ARDC at a rate of 1.29 km2/yr, with local expansion rates of 0.60 km2/yr for WLD and 0.69 km2/yr for AD. All three parts of the WLD naturally prograded seaward, with the western part (WP) and central part (CP) expanding southwestward to the sea, while the eastern part (EP) prograding southeastwards. Differently from WLD, the three parts of AD irregularly expanded seaward under the impacts of anthropogenic activities. The WP and CP of the AD expanded respectively northwestwards and southwestwards, while the EP remained stable. Different drivers dominate the growth of deltaic islands in the WLD and AD. Specifically, fluvial suspended sediment discharge and peak flow events were responsible for the shift in the spatial evolution of WLD, while dredging and sediment disposal contributed to the expansion of AD. Tropical storms with different intensity and landing locations caused short-term deltaic island erosion or expansion. Tropical storms mainly generated erosion on the deltaic islands of the WLD, while causing transient erosion or siltation on the deltaic islands of the AD. In addition, high-intensity hurricanes that made landfall east of the deltas caused more erosion in the AD. Finally, sea level rise, at the current rate of 8.17 mm/yr, will not pose a threat to the deltaic island of WLD, while the eastern part of AD may be at risk of drowning. This study recognizes the complexity of factors influencing the growth of deltaic islands, suggesting that quantitative studies on the deltaic island extent are of critical for the restoration and sustainable management of the Mississippi River Delta and other deltas around the world. 

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