Characterizing hydrologic changes of the Great Dismal Swamp using SAR/InSAR

- Hydrologic changes of the Great Dismal Swamp were studied using SAR/InSAR.
- SMAP was explored to find relationship between soil moisture and water table.
- C-/L-band SAR backscatter coefficient has high correlation with groundwater level.
- InSAR coherence helps delineate flooded areas subject to run-off events.
- Temporal InSAR measurements have a close correlation with water table.

The Great Dismal Swamp (GDS), one of the largest, northernmost peatlands on the Atlantic Coastal Plain, is underlain by a thick water-logged organic soil layer (peat) made up of dead and decaying plant material. The peatland functions as a main sink for a large amount of soil derived organic carbon. The disturbance of this wetland has negatively impacted the ecosystem and contributed to climate change through the release of the stored greenhouse gases. Surface water level and soil moisture conditions are critical information about peatlands, but monitoring these hydrologic changes has been a challenging task. With a lack of in situ soil moisture measurements, we first explored yearlong Soil Moisture Active Passive (SMAP) data to find the close relationship (R-squared value: 0.80) between soil moisture and groundwater table from March 2015 to March 2016. Based on synthetic aperture radar (SAR) backscattering returns and interferometric SAR (InSAR) phase measurements from C-band Radarsat-1 and L-band ALOS PALSAR datasets, we then analyzed the hydrologic changes in the peatlands. We compared averaged C/L-band SAR backscattering intensity (mid 1998-early 2008 for Radarsat-1, late 2006-early 2011 for ALOS PALSAR) with groundwater level changes and found that the SAR backscattering is significantly responsive (R-squared value: 0.76 and 0.67 for Radarsat-1 and ALOS PALSAR, respectively) to soil moisture changes through a three-way correlated relationship of soil moisture, groundwater level, and SAR intensity. Using InSAR coherence observations, we delineated the inundated area (western and northern regions of GDS) during the wet season, subject to double-bounce backscattering. We measured the relative water level changes in the inundated areas through the InSAR phase measurements, and estimated the groundwater level changes corresponding to soil moisture changes using time-series InSAR analysis. Our comprehensive study has demonstrated that time-series SAR backscattering returns and InSAR analysis can be used to gauge soil moisture conditions and to monitor the hydrologic and vegetation changes in the GDS.