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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 Brahmaputramore »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.« less
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 decisionmore »makers striving for deltaic resilience.

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3. Monsoon Dynamics in the Ganges-Brahmaputra-Meghna Basin

   https://doi.org/10.3390/CHyCle-2017-04865  

   Curtis, Scott ; Crawford, Thomas ; Munshi, Khaled ; Paul, Bimal ( September 2017 , The 1st Electronic Conference on Hydrological Cycle (CHyCle-2017))

   A recently funded US National Science Foundation project seeks to investigate monsoon variability within the Ganges-Brahmaputra-Meghna (GBM) river basin as a potential predictor for annual shoreline erosion rates in the lower coastal delta region. Many previous studies have examined the interannual variability of South Asian precipitation either within political boundaries or across large spans of latitudes and longitudes, but few have taken a more hydrologic approach by analyzing the atmospheric-oceanic forcings that lead to precipitation falling only within the GBM basin. The temporal climate patterns would likely be different from previous studies and are hypothesized to have a more direct effect on outlet discharge and erosion rates. In the present study, mean monsoon precipitation (June-July-August-September) for the 2,309 0.25° grid boxes of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) was extracted using geospatial methods. A Principal Component (PC) analysis was performed over the period 1983 to 2015. The first PC explains 88.7% of the variance and resembles climatology with the center of action over Bangladesh. The eigenvector shows a downward trend consistent with studies reporting a recent decline in monsoon rainfall. The second PC explains 2.9% of the variance and concentrates rainfall inmore »the western portion of the basin. The 2nd component has greater temporal variability than the 1st component and an apparent decadal cycle. An analysis of global precipitation indicates that the rainfall patterns obtained within the GBM are localized. Surface and upper-air atmospheric height fields suggest the 2nd PC pattern is forced by a Rossby wave train stemming from the North Atlantic.« less
4. Application of electrical resistivity to map the stratigraphy and salinity of fluvio-deltaic aquifers: case studies from Bangladesh reveal promises and pitfalls

   Micaela N. Pedrazas, M. Bayani ( July 2021 , Ground water)

   Fluvio-deltaic aquifers are the primary source of drinking water for the people of Bangladesh. Such aquifers, which comprise the Ganges-Brahmaputra-Meghna Delta, are extremely hydrogeologically heterogeneous. Because of widespread groundwater quality issues in Bangladesh, it is crucial to know the hydrostratigraphic architecture and hydrochemistry of the aquifers as some units are contaminated whereas others are safe. Geophysical methods provide a potentially effective and non-invasive method for extensive characterization of these aquifers. This study applies and investigates the limitations of using electrical resistivity imaging (ERI) for mapping the hydrostratigraphy and salinity of an aquifer-aquitard system adjacent to the Meghna River. Some ER sections showed excellent correlation between resistivity and grain size. These suggest that ERI is a powerful tool for mapping internal aquifer architecture and their boundaries with finer-grained aquitards which clearly appear as low ER zones. However, in parts of some ER sections, variations in electrical properties were determined by porewater resistivity. In these cases, low ER was indicative of brine and did not indicate the presence of finer-grained materials such as silt or clay. Accordingly, the following hydrostratigraphic zones with different resistivities were detected: (1) aquifers saturated with fresh ground water, (2) a regional silt/clay aquitard, and (3) a deepermore »brine-saturated formation. In addition, shallow silt/clay pockets were detected close to the river and below the vadose zone. ERI is thus a promising technique for mapping aquifers versus aquitards. However, the observations are easily confounded by porewater salinity. In such cases, borehole information and groundwater salinity measurements are necessary for ground-truthing.« less
5. Shoreline Change Analysis along Rivers and Deltas: A Systematic Review and Bibliometric Analysis of the Shoreline Study Literature from 2000 to 2021

   https://doi.org/10.3390/geosciences12110410  

   Rahman, Munshi Khaledur ; Crawford, Thomas W. ; Islam, Md Sariful ( November 2022 , Geosciences)

   Globally, coastal zones, rivers and riverine areas, and deltas carry enormous values for ecosystems, socio-economic, and environmental perspectives. These often highly populated areas are generally significantly different from interior hinterlands in terms of population density, economic activities, and geophysical and ecological processes. Geospatial technologies are widely used by scholars from multiple disciplines to understand the dynamic nature of shoreline changes globally. In this paper, we conduct a systematic literature review to identify and interpret research patterns and themes related to shoreline change detection from 2000 to 2021. Two databases, Web of Science and Scopus, were used to identify articles that investigate shoreline change analysis using geospatial technique such as remote sensing and GIS analysis capabilities (e.g., the Digital Shoreline Analysis System (DSAS). Between the years 2000 and 2021, we initially found 1622 articles, which were inspected for suitability, leading to a final set of 905 articles for bibliometric analysis. For systematic analysis, we used Rayyan—a web-based platform used for screening literature. For bibliometric network analysis, we used the CiteSpace, Rayyan, and VOSviewer software. The findings of this study indicate that the majority of the literature originated in the USA, followed by India. Given the importance of protecting the communities livingmore »in the riverine areas, coastal zones, and delta regions, it is necessary to ask new research questions and apply cutting-edge tools and technology, such as machine learning approach and GeoAI, to fill the research gaps on shoreline change analysis. Such approaches could include, but are not limited to, centimeter level accuracy with high-resolution satellite imagery, the use of unmanned aerial vehicles (UAV), and point cloud data for both local and global level shoreline change and analysis.« less