Bankline Assessment of Shibsa-Passur River by Satellite Imagery and Hydrodynamic Modeling using Delft3D
The Sundarbans, a prolific mangrove wetland ecosystem part of the world's largest delta formed by the Ganges, Brahmaputra, and Meghna rivers, contribute immensely to coastal stability and protection. In deltaic mangroves such as the Sundarbans, recurrent...
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| Main Authors: | , , , |
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| 格式: | Article |
| 語言: | 英语 |
| 出版: |
Research and Development Wing, MIST
2025
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| 主題: | |
| 在線閱讀: | http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/862 |
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| 總結: | The Sundarbans, a prolific mangrove wetland ecosystem part of the world's largest delta formed by the Ganges, Brahmaputra, and Meghna rivers, contribute immensely to coastal stability and protection. In deltaic mangroves such as the Sundarbans, recurrent erosion and accretion caused by the transportation of unconsolidated sediments by rivers, interact with flow velocity and bed shear to generate continuous morphological dynamics. This study analyzed the bankline migration patterns of the Shibsa and Passur rivers within the Bangladesh portion of the Sundarbans using satellite imagesand assessed their hydrodynamic behavior by developing a two-dimensional model using Delft3D. This study utilized Landsat and Sentinel images from 2009-2021 to identify critical erosion and deposition zones applyingthe DSAS tool of ArcGIS. A two-dimensional hydrodynamic model was then developed and calibrated to simulate flow velocity, bed shear stress, and water levels in these critical zones. The model was validated against limited available water level data. Six critical zones were identified, with four erosion-prone and two deposition-prone areas. The model results indicated increased velocities and bed shear stresses in the erosion zones relative to non-critical areas, while the deposition zones experienced reduced velocities and bed shear stresses. The study reveals that the high values of velocity and bed shear stressesare responsible for the morphological changesof erosion, thus emphasizing the significance of close monitoring with remotely sensed images. |
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