Oceanography The Official Magazine of
The Oceanography Society
Volume 26 Issue 03

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Volume 26, No. 3
Pages 64 - 69

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Remote-Sensing Monitoring of Tide Propagation Through Coastal Wetlands

By Shimon Wdowinski , Sang-Hoon Hong , Amanda Mulcan , Brian Brisco, and  
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Article Abstract

Tide propagation through coastal wetlands is a complex phenomenon affected by vegetation, channels, and tidal conditions. Generally, tidal flow is studied using stage (water level) observations, which provide good temporal resolution, but they are acquired in limited locations. Here, a remote-sensing technique, wetland InSAR (interferometric synthetic aperture radar), is used to detect tidal flow in vegetated coastal environments over broad spatial scales. The technique is applied to data sets acquired by three radar satellites over the western Everglades in south Florida. Interferometric analysis of the data shows that the greatest water-level changes occur along tidal channels, reflecting a high velocity gradient between fast horizontal flow in the channel and the slow flow propagation through the vegetation. The high-resolution observations indicate that the tidal flushing zone extends 2–3 km on both sides of tidal channels and can extend 3–4 km inland from the end of the channel. The InSAR observations can also serve as quantitative constraints for detailed coastal wetland flow models.

Citation

Wdowinski, S., S.-H. Hong, A. Mulcan, and B. Brisco. 2013. Remote-sensing monitoring of tide propagation through coastal wetlands. Oceanography 26(3):64–69, https://doi.org/10.5670/oceanog.2013.46.

References
    Buckley, S.M., P.A. Rossen, and P. Persaud. 2000. ROI_PAC documentation: Repeat orbit interferometry package. Available online at: http://www.earth.ox.ac.uk/~timw/roi_pac/ROI_PAC_doc.pdf (accessed July 11, 2013).
  1. Burgmann, R., Rosne, P.A. and E.J. Fielding. 2000. Synthetic aperture radar interferometry to measure Earth’s surface topography and its deformation. Annual Review of Earth and Planetary Sciences 28:169–209, https://doi.org/10.1146/annurev.earth.28.1.169.
  2. Cloude, S.R., and E. Pottier. 1996. A review of target decomposition theorems in radar polarimetry. IEEE Transactions on Geoscience and Remote Sensing 34:498–518, https://doi.org/10.1109/36.485127.
  3. Gondwe, B.R.N., S.H. Hong, S. Wdowinski, and P. Bauer-Gottwein. 2010. Hydrologic dynamics of the ground-water-dependent Sian Ka’an Wetlands, Mexico, derived from InSAR and SAR data. Wetlands 30(1):1–13, https://doi.org/10.1007/s13157-009-0016-z.
  4. Holtermann, P., H. Burchard, and T. Jennerjahn. 2009. Hydrodynamics of the Segara Anakan lagoon. Regional Environmental Change 9(4):245–258, https://doi.org/​10.1007/s10113-008-0075-3.
  5. Hong, S.H., S. Wdowinski, and S.W. Kim. 2010. Evaluation of TerraSAR-X observations for wetland InSAR application. IEEE Transactions on Geoscience and Remote Sensing 48(2):864–873, https://doi.org/10.1109/TGRS.2009.2026895.
  6. Kim, J.W., Z. Lu, H. Lee, C.K. Shum, C.M. Swarzenski, T.W. Doyle, and S.H. Baek. 2009. Integrated analysis of PALSAR/Radarsat-1 InSAR and ENVISAT altimeter data for mapping of absolute water level changes in Louisiana wetlands. Remote Sensing of Environment 113(11):2,356–2,365, https://doi.org/10.1016/j.rse.2009.06.014
  7. Kim, S.-W., S. Wdowinski, A. Amelung, T.H. Dixon, and J.-S. Won. 2013. Interferometric coherence analysis of the Everglades wetlands, South Florida. IEEE Transactions on Geoscience and Remote Sensing 51:1–15, https://doi.org/10.1109/TGRS.2012.2231418.
  8. Kwoun, O.I., and Z. Lu. 2009. Multi-temporal RADARSAT-1 and ERS backscattering signatures of coastal wetlands in southeastern Louisiana. Photogrammetric Engineering and Remote Sensing 75(5):607–617.
  9. Mazda, Y., N. Kanazawa, and E. Wolanski. 1995. Tidal asymmetry in mangrove creeks. Hydrobiologia 295:51–58, https://doi.org/​10.1007/BF00029110.
  10. Schalles, J.F., C.M. Hladik, A.A. Lynes, and S.C. Pennings. 2013. Landscape estimates of habitat types, plant biomass, and invertebrate densities in a Georgia salt marsh. Oceanography 26(3):88–97, https://doi.org/​10.5670/oceanog.2013.50.
  11. Simard, M., K.Q. Zhang, V.H. Rivera-Monroy, M.S. Ross, P.L. Ruiz, E. Castaneda-Moya, R.R. Twilley, and E. Rodriguez. 2006. Mapping height and biomass of mangrove forests in Everglades National Park with SRTM elevation data. Photogrammetric Engineering and Remote Sensing 72(3):299–311.
  12. Wdowinski, S., F. Amelung, F. Miralles-Wilhelm, T.H. Dixon, and R. Carande. 2004. Space-based measurements of sheet-flow characteristics in the Everglades wetland, Florida. Geophysical Research Letters 31, L15503, https://doi.org/​10.1029/2004GL020383.
  13. Wdowinski, S., and S. Eriksson. 2009. Geodesy in the 21st Century. Eos, Transactions, American Geophysical Union 90(18):153–155, https://doi.org/10.1029/2009EO180001.
  14. Wdowinski, S., S.W. Kim, F. Amelung, T.H. Dixon, F. Miralles-Wilhelm, and R. Sonenshein. 2008. Space-based detection of wetlands’ surface water level changes from L-band SAR interferometry. Remote Sensing of Environment 112(3):681–696, https://doi.org/10.1016/​j.rse.2007.06.008.
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