2024 CSDMS meeting-053
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A predictive model for delta subsidence
Austin Chadwick,
(He/Him),Lamont-Doherty Earth Observatory, Columbia University New York, NY New York, United States. achadwick@ldeo.columbia.edu
Suzana J. Camargo, Lamont-Doherty Earth Observatory, Columbia University New York New York, United States. suzana.camargo@columbia.edu
Michael S. Steckler, Lamont-Doherty Earth Observatory, Columbia University New York New York, United States. steckler@ldeo.columbia.edu
Densely populated coastal deltas worldwide face cascading flood and salinization hazards associated with sea-level rise, storm surges, dwindling sediment supplies, and land subsidence. One of the greatest hurdles to hazard prediction stems from quantifying the land-subsidence component, which exhibits significant spatial and temporal variations across any given delta. Here, we present a delta-subsidence model capable of quantifying these variations. The model is built upon fundamental principles of effective stress, conservation of mass, and Darcy flow; as well as constitutive relations for porosity and edaphic factors (e.g. roots, burrows). For an input sediment column and deposition rate, we quantify the depth-profile of vertical land motion over time, allowing for direct comparison with field observations spanning various depths, timescales, and methods (e.g., GPS stations; Rod-surface-elevation tables; C14 and OSL ages). Preliminary results demonstrate the model can accurately resolve decadal-scale subsidence patterns on the Ganges-Brahmaputra delta, including subsidence hotspots associated with fine-grained lithologies, buried Pleistocene paleovalleys, and river embankments constructed in the 1950’s. This predictive subsidence model can improve assessments of coastal flood hazards on the Ganges-Brahmaputra and other deltas worldwide; and help inform ongoing billion-dollar restoration efforts facing crucial decisions as to where and when coastal barriers, sediment diversions, and settlement relocations will be implemented in the coming century.
