Imaging Vertical Deformation Along the Coast of the Pacific Northwest

The Pacific Northwest (PacNW) is characterized by a complex vertical land motion driven by tectonic, geological, and anthropogenic processes. Dominated by the Cascadia subduction zone, the region exhibits diverse deformation patterns resulting from interseismic locking, episodic tremor and slip (ETS), detachment, and underplating, compounded by glacial isostatic adjustment (GIA) and human activities such as groundwater extraction and infrastructure development. Historical events, such as the 1700 Cascadia earthquake, highlight the catastrophic interplay between tectonic subsidence and coastal flooding. Accurately quantifying vertical land motion (VLM) is essential for assessing coastal vulnerabilities in the context of sea level rise and investigating geophysical mechanisms responsible for these signals. Advances in interferometric synthetic aperture radar (InSAR) have significantly improved VLM measurement capabilities, offering high spatial resolution over large areas. However, dense vegetation in the PacNW leads to phase decorrelation, posing challenges and limiting the reliability of InSAR measurements in this region. In this study, we employ the network-based phase-gradient stacking (NPG-Stacking) method, which integrates phase gradient stacking with network adjustment, to address these limitations. Using this approach, we generate vertical deformation velocity maps with a 200 m resolution along the PacNW coast for the period 2017–2023, derived from C-band Sentinel-1 data. We compare these results with historical tide gauge records and repeated leveling data to evaluate the time dependence of current vertical velocities. Additionally, we incorporate hazard assessments for critical infrastructure and vulnerable communities and further discuss the interplay of GIA and tectonic motion in this region. The resulting deformation field provides valuable insights for assessing hazards, supporting risk mitigation strategies, and potentially enhancing our understanding of the driving forces behind long-wavelength deformation patterns.