Subtle Land Subsidence Elevates Future Storm Surge Risks Along the Gulf Coast of the United States
Ke Wang, Jingyi Chen, Eirik Valseth, Gordon Wells, Srinivas Bettadpur, Cathleen E. Jones, Clint Dawson
Abstract
Abstract We developed a robust InSAR processing strategy that can effectively mitigate severe decorrelation noise in a large volume of InSAR data. We mapped the average land subsidence rate (2017–2020) over the 131,572 km 2 Upper Texas and Louisiana coasts from Sentinel‐1 data, with ∼2 mm/yr accuracy based on independent GPS and tide gauge validation at 189 locations. The improved InSAR observations reveal widespread subsidence that was previously undetected in coastal wetlands and rural areas with small communities. Our InSAR surface deformation map is at the spatial scale that overlaps with the scale of hydrodynamic model grids. This allows us to integrate InSAR observations into operational storm surge models to analyze future flooding risks due to relative sea level change. We found that these subtle millimeter‐to‐centimeter subsidence features can substantially increase hurricane‐induced inundation, and passive flood mapping (known as the “bathtub” approach) can lead to inaccurate flood risk predictions.