2022
DOI: 10.1002/essoar.10511192.1
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Disruptive Role of Vertical Land Motion in Future Assessments of Climate Change-Driven Sea Level Rise and Coastal Flooding Hazards in the Chesapeake Bay.

Abstract: Rising sea levels pose significant challenges to coastal communities and ecosystems (IPCC, 2021). The global sea level rose by 0.

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Cited by 3 publications
(4 citation statements)
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References 32 publications
(48 reference statements)
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“…5e,f), assuming linearly continuous subsidence. This observation is notable because it brings land subsidence to the fore of coastal-hazard discussions and highlights it as a crucial index in coastal disaster resilience design 20 .…”
Section: Land Subsidence Is a Critical Driver Of Coastal Hazardsmentioning
confidence: 95%
See 2 more Smart Citations
“…5e,f), assuming linearly continuous subsidence. This observation is notable because it brings land subsidence to the fore of coastal-hazard discussions and highlights it as a crucial index in coastal disaster resilience design 20 .…”
Section: Land Subsidence Is a Critical Driver Of Coastal Hazardsmentioning
confidence: 95%
“…Generally, higher standard deviation values represent areas of lower precision. The observed lower precision in some pixels may be attributed to lower interferometric phase signal-to-noise ratio caused by surface vegetation, nonlinearity in the rates between the ALOS and Sentinel-1 observation periods owing to aquifer recharge and depletion, a limited number of GNSS stations used for the adjustment and a comparatively higher standard deviation of the GNSS station in the particular regions 20,27,28 . Furthermore, we validate the VLM rates using 756 GNSS stations (US Atlantic coast: 218; US Gulf coast: 157; US Pacific coast: 381) from the Nevada Geodetic Laboratory 62 and Shirzaei et al 48 .…”
Section: Vlm Datamentioning
confidence: 99%
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“…Generally, we note higher χ 2 values in areas with noted higher standard deviations. This could be attributed to several factors: the nonlinearities in surface deformation rates observed between the ALOS-1 and Sentinel-1 periods, the sparse distribution of GNSS stations, and the comparatively higher standard deviation observed at these GNSS stations in these areas ( 76 ). The final VLM utilized in this study is shown in Fig.…”
Section: Methodsmentioning
confidence: 99%