Present-day vertical land motions (VLM) of the Chesapeake Bay region derived from robust network imaging of global navigation satellite system (GNSS) observations
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Scientific Reports
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The Chesapeake Bay region (defined as longitudes − 78° to -74° and latitudes 36.5° to 40°) experiences the highest rates of relative sea-level rise (RSLR) on the Atlantic Coast. Regional land subsidence influences RSLR, however quantified rates of vertical land motions (VLM) are inconsistent in published solutions. For 5 years from 2019 to 2023, new Global Navigation Satellite System (GNSS) campaign data were collected at over 60 sites across the Chesapeake Bay region annually. These data were processed and combined with continuous GNSS data (120 stations) from the region covering the same time-period using GAMIT-GLOBK to produce 3D velocities and their associated uncertainties. We use the Robust Network Imaging algorithm to interpolate GNSS-derived VLM to produce a new regional VLM solution of the Chesapeake Bay region. We find that land subsidence is ubiquitous throughout the region with rates varying from − 2.97 to -0.40 mm/yr. In major cities across the Chesapeake Bay region, VLM rates are − 1.1 ± 1.6 mm/yr (1-sigma) for Washington DC, -0.8 ± 1.4 mm/yr for Baltimore, MD, -2.4 ± 0.5 mm/yr for Ocean City, MD, and − 2.3 ± 1.0 mm/yr for Hampton, VA. When we compare our VLM rates with a geodetic-based solution from 1974, we observe meaningful shifts in the locations and rates of maximum subsidence. The results of this work underscore that regular monitoring of VLM and can be used to improve projections of relative sea-level changes as well as the associated coastal hazards for communities in the Chesapeake Bay region.
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This article was originally published in Scientific Reports. The version of record is available at: https://doi.org/10.1038/s41598-025-32348-5
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Williams, K., Stamps, D.S., Duda, J. et al. Present-day vertical land motions (VLM) of the Chesapeake Bay region derived from robust network imaging of global navigation satellite system (GNSS) observations. Sci Rep 16, 2435 (2026). https://doi.org/10.1038/s41598-025-32348-5
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Except where otherwised noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International

