- 1Lamont-Doherty Earth Observatory, Columbia University, NY, USA
- 2Department of Geological Sciences, University of Colorado at Boulder, CO, USA
- 3Department of Geology and Geophysics, Louisiana State University, LA, USA
- 4Department of Earth and Environmental Sciences, Vanderbilt University, TN, USA
- 5Scripps Institution of Oceanography, University of California San Diego, CA, USA
Coastal regions face a cascading sustainability crisis due to rising sea levels, stronger storms, land loss, salinization, and ecosystem collapse. These risks are particularly severe in densely populated lowland river deltas, which are highly sensitive to effective sea-level rise that combines eustatic ocean levels, subsidence, and tidal amplification. The Ganges-Brahmaputra Delta (GBD) in Bangladesh is such a region, characterized by geomorphic dynamism and rapid land-use changes associated with agriculture and urbanization, highlighting the critical need for accurate surface elevation change measurements.
In this study, we process Sentinel-1 datasets spanning 2014-2024 and derive a 30-meter resolution InSAR velocity field over coastal Bangladesh, sufficient to resolve differences between villages and fields. We incorporate a high-resolution (5-meter) Worldview DEM referenced to ICESat-2 altimeter data and implement a suite of innovative InSAR algorithms to enhance pixel recovery in coastal areas, improve atmospheric noise mitigation, and refine time series retrieval.
By integrating InSAR-derived deformation measurements with ground observations, including RSET-MH, continuous GNSS, and campaign-based GNSS resurveys of geodetic monuments, we identify higher subsidence rates in areas of active sedimentation, such as rice fields and mangrove forests, compared to urban areas containing buildings with deep foundations, revealing the influence of surface landscape on the observed deformation. We demonstrate that seasonal deformation, driven by elastic loading and poroelastic effects, can be distinguished and separated through a combination of the retrieved InSAR time series and continuous GNSS time series.
Additionally, we validate InSAR observations using a poroelastic model for coastal subsidence that incorporates shallow (<10 m depth) geomorphic and land-use processes often excluded from modern models, finding strong agreement between model predictions and observed data. This study not only advances the assessment of sea-level rise risks for the densely populated GBD but also establishes a transferable framework for addressing challenges across vulnerable coastal communities worldwide.
How to cite: Shen, L., Chadwick, A. J., Steckler, M. S., Tiampo, K. F., Wilson, C., Goodbred, S. L., and Oryan, B.: High-resolution mapping of coastal subsidence in the Ganges-Brahmaputra Delta using advanced InSAR and ground observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7642, https://doi.org/10.5194/egusphere-egu25-7642, 2025.
