Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods
The 2020 Monsoon floods submerged two-thirds of Bangladesh, profoundly affecting the stable char areas along the Padma River. This study addresses the under-explored link between Monsoonal flood hydrology and river morphological changes, introducing a novel approach that integrates one-dimensional s...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2024.2399668 |
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| author | Aishia Fyruz Aishi Abul Kashem Faruki Fahim |
| author_facet | Aishia Fyruz Aishi Abul Kashem Faruki Fahim |
| author_sort | Aishia Fyruz Aishi |
| collection | DOAJ |
| description | The 2020 Monsoon floods submerged two-thirds of Bangladesh, profoundly affecting the stable char areas along the Padma River. This study addresses the under-explored link between Monsoonal flood hydrology and river morphological changes, introducing a novel approach that integrates one-dimensional steady flow hydraulic modeling, dual-sensor satellite imagery analysis (Sentinel-1 SAR and Sentinel-2 optical), and multiple machine learning techniques to assess flood impacts on bank erosion in the most affected reaches. Multiple linear regression (MLR), random forest (RF), artificial neural networks (ANN), and support vector machines (SVM) along with other statistical analyses, were employed to elucidate relationships between hydraulic variables and bank erosion. Results indicated a gradual decrease in river discharge-related variables from July to October, with peak erosion in July, primarily along the right banks and concave areas. In analyzing the relationships between hydraulic variables and bank erosion, the ANN model outperformed others, identifying flow area, stream power, and shear stress as the most influential predictors through importance analysis. This integrated approach offers a transferable framework for analyzing flood-induced bank erosion, enhancing riverbank erosion understanding crucial for flood risk management strategies in Bangladesh and similar river systems worldwide. |
| format | Article |
| id | doaj-art-29d0975dc93c4a8f9773f0f9b97a1f7e |
| institution | DOAJ |
| issn | 1947-5705 1947-5713 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geomatics, Natural Hazards & Risk |
| spelling | doaj-art-29d0975dc93c4a8f9773f0f9b97a1f7e2025-08-20T02:50:29ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132024-12-0115110.1080/19475705.2024.2399668Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floodsAishia Fyruz Aishi0Abul Kashem Faruki Fahim1Department of Meteorology, University of Dhaka, Dhaka, BangladeshDepartment of Disaster Science and Climate Resilience, University of Dhaka, Dhaka, BangladeshThe 2020 Monsoon floods submerged two-thirds of Bangladesh, profoundly affecting the stable char areas along the Padma River. This study addresses the under-explored link between Monsoonal flood hydrology and river morphological changes, introducing a novel approach that integrates one-dimensional steady flow hydraulic modeling, dual-sensor satellite imagery analysis (Sentinel-1 SAR and Sentinel-2 optical), and multiple machine learning techniques to assess flood impacts on bank erosion in the most affected reaches. Multiple linear regression (MLR), random forest (RF), artificial neural networks (ANN), and support vector machines (SVM) along with other statistical analyses, were employed to elucidate relationships between hydraulic variables and bank erosion. Results indicated a gradual decrease in river discharge-related variables from July to October, with peak erosion in July, primarily along the right banks and concave areas. In analyzing the relationships between hydraulic variables and bank erosion, the ANN model outperformed others, identifying flow area, stream power, and shear stress as the most influential predictors through importance analysis. This integrated approach offers a transferable framework for analyzing flood-induced bank erosion, enhancing riverbank erosion understanding crucial for flood risk management strategies in Bangladesh and similar river systems worldwide.https://www.tandfonline.com/doi/10.1080/19475705.2024.2399668Bangladeshmonsoon floodsriverbank erosionHEC-RASPadmarandom forest |
| spellingShingle | Aishia Fyruz Aishi Abul Kashem Faruki Fahim Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods Geomatics, Natural Hazards & Risk Bangladesh monsoon floods riverbank erosion HEC-RAS Padma random forest |
| title | Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods |
| title_full | Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods |
| title_fullStr | Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods |
| title_full_unstemmed | Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods |
| title_short | Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods |
| title_sort | analyzing the association between the hydrodynamics and bank erosion along the padma river 2020 monsoon floods |
| topic | Bangladesh monsoon floods riverbank erosion HEC-RAS Padma random forest |
| url | https://www.tandfonline.com/doi/10.1080/19475705.2024.2399668 |
| work_keys_str_mv | AT aishiafyruzaishi analyzingtheassociationbetweenthehydrodynamicsandbankerosionalongthepadmariver2020monsoonfloods AT abulkashemfarukifahim analyzingtheassociationbetweenthehydrodynamicsandbankerosionalongthepadmariver2020monsoonfloods |