Regional-scale hydrological monitoring of wetlands with Sentinel-1 InSAR observations: Case study of the South Florida Everglades

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Wetland is a very fragile ecosystem that provides important services to a large variety of flora and fauna species, as well as for humans. As wetland depends on water availability, protecting this important ecosystem requires careful hydrological monitoring. The Sentinel-1 mission, featuring a wide swath coverage, high temporal observations and open data policy, provides unprecedented opportunity for high spatio-temporal resolution water level change mapping over regional-wide wetland areas. In this study, we assess Sentinel-1 InSAR observations for routine water level change measurements over the entire south Florida Everglades wetlands. The study utilizes 91 Sentinel-1 images acquired over a three-year period (Sep 2016 to Nov 2019) and generates routine 12-days Interferograms and correspondingly 30 m spatial resolution water level change maps over the entire Everglades. The high spatial resolution interferograms detect hydrological signals induced by both natural- and human-induced flow, including tides, gate operations, and canal overflow; all these cannot be detected by terrestrial measurements. The large number of both InSAR and ground-based gauge observations allow us to quantify the overall accuracy of the Sentinel-1 InSAR measurements, which is 3.9 cm for the entire wetland area, but better for smaller hydrological units within the Everglades. Our study reveals that the tropospheric delay for individual interferograms can be very large, as much as 30 cm (~10 fringes). When applying tropospheric corrections to all three years of Sentinel-1 InSAR observations, the overall accuracy level improved by 13% to 3.4 cm. Although our study is focused on the Everglades, its implications in term of the suitability of Sentinel-1 observations for space-based hydrological monitoring of wetlands and the derived accuracy level are applicable to other wetlands with similar vegetation types, located all over the world.

Liao-et-al-RSE-2020-supp.pdf (7957 kB)
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