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Densely populated coastal deltas worldwide … 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.will be implemented in the coming century. +
A predictive model for delta subsidence +
New York, NY +
United States +
Lamont-Doherty Earth Observatory, Columbia University +
New York +
achadwick@ldeo.columbia.edu +
Austin +
Lamont-Doherty Earth Observatory, Columbia University +
Chadwick +
6505211630 +
Image: +
2) Vegetation as ecogeomorphic features +
2) Introduction & Building with Google Earth Engine: Batteries Included +
3) New features and basic usage of the GeoClaw software for depth-averaged flow +
New York +
United States +
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16:53:39, 25 March 2024 +
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16:53:39, 25 March 2024 +
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