Suranjana Chatterjee (Auburn University, United States); Emma Marzolf (The Jones Center at Ichauway, United States); Steven Brantley (The Jones Center at Ichauway, United States); John Beck (The University of Alabama in Huntsville, United States)

Geographically isolated wetlands (GIWs), which are not connected to a river, lake or ocean, are widespread and provide many societal benefits, including flood prevention, wildlife habitat, and water quality improvement. This project explores the potential of SWOT observations used with other water-focused satellite missions to monitor and improve understanding of GIWs. The first objective of our project, which will be discussed in the presentation, is to compare SWOT raster and pixel cloud data to field-measured water surface elevation and inundated area. We upgraded and expanded an existing monitoring network of 20 GIWs on the Dougherty Plain of Southwest Georgia, USA. The monitored wetlands range in size from (70 m)2 – (350 m)2 or 0.5 – 12 ha when full. A range of wetland vegetation types are represented, including grass and sedge marshes, cypress-gum swamp, and open water with occasional free-floating vegetation coverage. The contributing areas of the GIWs include a mix of forested and agricultural land covers. Water level is measured in the deepest part of the wetland at 15-minute intervals with HOBO water level recorders. We developed bathymetric maps by merging sonar depth readings with ground-based and airborne lidar that provide precise depth-area-volume relationships for these wetlands. Inundated area is determined in a subset of two to three GIWs on the date of each SWOT pass by walking wetted perimeter with a high-resolution (sub-meter) GPS. SWOT level-2 raster-derived water surface elevations were extracted for the raster cells containing the deepest point of three large GIWs and compared to field-measured water level over a one-year period during which the wetlands experienced a large range of variability in water level. Results showed that the raster product is affected by data quality issues leading to frequent overestimation of peak water levels and poor capture of seasonal drawdown periods, with SWOT-reported elevations exceeding field observations by up to 6 meters. This highlights limitations in vegetated or low-coherence conditions. Given these limitations, ongoing work is developing methods for estimating GIW water level and inundated area with SWOT Pixel Cloud Level 2 data. We developed scripts to retrieve and process pixel cloud data over the study wetlands. Initial analyses showed that a large proportion of pixels within wetland boundaries were classified as “land” or transitional types (e.g., land-near-water), especially along vegetated margins, though water was detected through both herbaceous and forested wetland vegetation. These findings demonstrate both the potential and limitations of SWOT for monitoring small inland wetlands. Ongoing work will develop a hybrid framework combining bathymetric modeling, field validation, and pixel filtering to improve wetland hydroperiod estimation.