Alexandra Christensen (Jet Propulsion Laboratory, California Institute of Technology, USA); Michael Denbina (Jet Propulsion Laboratory, USA); Pascal Matte (Environment and Climate Change Canada, Canada); Ali Payandeh (Jet Propulsion Laboratory, California Institute of Technology, USA); Cecilia Lopez-Gamundi (Jet Propulsion Laboratory, California Institute of Technology, USA)

River deltas and estuaries are dynamic transitional zones at the land-ocean interface where freshwater, tides, sediment, and nutrients interact, shaping ecosystems that are both ecologically rich and highly vulnerable to climate change and anthropogenic disturbance. The Surface Water and Ocean Topography (SWOT) satellite mission offers unprecedented opportunities to monitor water surface elevation and hydrodynamics in these complex environments. However, extracting actionable information from SWOT’s novel Ka-band radar interferometric measurements—especially in low-slope, tidally influenced coastal regions—requires new approaches tailored to the complex geomorphology and hydrology of deltas and estuaries.

In this study, we developed and applied a framework that aggregates SWOT measurements onto a delta-specific river network graphs to extract hydrodynamic parameters and validate numerical hydrodynamic models in global river deltas and estuaries. The graphs organize SWOT’s pixel cloud (PixC) data along channels to allow for a robust non-stationary harmonic analysis (i.e. NS_Tide), which reconstructs hourly tidal constituents from the sparse SWOT measurements. The tidal reconstruction is then used to validate numerical models that are further leveraged to quantify channel-wetland connectivity, which is essential for understanding how water and salinity move across deltaic landscapes. This approach captures temporal variability in tidal dynamics and enables estimation of tidal range and hydroperiod—the duration and frequency of inundation in adjacent wetlands. These parameters are critical for assessing habitat viability, salinity gradients and biogeochemical fluxes.

We applied this methodology across a range of representative coastal systems, including: the Guayas River delta (Ecuador), the Komo River estuary (Gabon), the St. Lawrence estuary (Canada), the Langebaan Lagoon (South Africa), and the Mississippi River Delta (USA). These sites span a spectrum of tidal regimes, channel geometries, and wetland types, offering a comparative view of SWOT’s performance across diverse hydro-geomorphological contexts. We evaluated SWOT-derived water levels against in-situ gauges, model outputs, and ancillary remote sensing data, and we assessed the coherence of tidal signals along river-to-ocean transects.

Our results demonstrate that SWOT reliably resolves tidal amplitudes and phases in most estuarine channels, enabling consistent estimation of hydroperiod in adjacent wetlands. SWOT’s performance is modulated by regional morphology, including tidal range, channel geometry, vegetation, and bathymetric complexity. SWOT’s capacity to detect water surface slopes and variations diminishes in areas with dense vegetation cover, highly fragmented marshes and narrow tidal creeks. Nevertheless, the aggregated PixC-based approach significantly enhances signal quality by reducing noise and increasing spatial-temporal sampling density. The tidal constituents extracted with NS_Tide show strong agreement with in-situ tidal observations, mostly when SWOT accuracy is significantly larger than tidal range. The approach developed here provides a robust framework for leveraging SWOT data in coastal settings, opening new possibilities for long-term monitoring productivity of coastal wetlands, and their vulnerability to sea-level rise, land subsidence, and reduced freshwater discharge, as well as for identifying thresholds where salinity intrusion may begin to impact ecosystem health and function.