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A regional algorithm for investigating the Patos Lagoon coastal plume using Aqua/MODIS and oceanographic data

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Abstract

Located in the south of Brazil, the Patos Lagoon is the world’s largest choked lagoon. The extensive mud deposits that surround its estuary indicate a substantial transport of suspended matter to the continental shelf by its plume. This study aims to develop a regional algorithm for estimating the total suspended matter of the Patos Lagoon coastal plume using remote sensing data combined with oceanographic measurements. We develop a polynomial correlating total suspended matter with the reflectance of the 667-nm-centered band of the Moderate-Resolution Imaging Spectroradiometer (MODIS), aboard the Aqua satellite. We use the satellite-based estimates to investigate the development and fate of the plume and to quantify the exchange processes between the estuary and the coastal zone. The seasonal averaged total amount of suspend matter exported by the plume ranged between values in the order of 106 and 107 ton. The plume shows a residual displacement to the south of the estuary mouth, though it can be transiently displaced northwards under the influence of strong southerly winds. The river discharge determines the plume’s suspended matter transport, whereas the wind shapes its form and determines its spreading. The plume’s variability shows well-marked cycles with semi-annual and quasi-annual frequencies, which could be identified by EOF and wavelet analyses.

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References

  1. J.E. Salisbury, J.W. Campbell, L.D. Meeker, C. Vörösmarty, Eos Trans. 82, 221 (2001)

    Article  Google Scholar 

  2. L.A. Cifuentes, L.E. Schemel, J.H. Sharp, Estuar. Coast. Shelf Sci. 30, 411 (1990)

    Article  Google Scholar 

  3. P.H. Doering, R.H. Chamberlain, J. Am. Water Resour. Assoc. 35, 793 (1999)

    Article  Google Scholar 

  4. I. Grabemann, H. Kühle, B. Kunze, A. Müller, Mixing Estuaries Coast. Seas 50, 291 (2013)

    Article  Google Scholar 

  5. R.L. Miller, B.A. Mckee, E.J. D’Sa (eds.), in Remote Sensing of Coastal Aquatic Environments: Technologies, Techniques and Applications (Springer, Dordrecht, Netherlands, 2005), pp. 259–276

  6. R. Li, Y.J. Kaufman, B. Gao, C.O. Davis, IEEE Trans. Geosci. Remote Sens. 41, 559 (2003)

    Article  Google Scholar 

  7. R.L. Miller, B.A. McKee, Remote Sens. Environ. 93, 259 (2004)

    Article  Google Scholar 

  8. L.J. Calliari, J.C. Winterwerp, E. Fernandes, D. Cuchiara, S.B. Vinzon, M. Sperle, K.T. Holland, Cont. Shelf Res. 29, 515 (2009)

    Article  Google Scholar 

  9. B. Kjerfve, in Estuarine Variability, ed. By D.A. Wolfe (Academic Press, Orlando, 1986), pp. 63–81

  10. C. Hartmann, P.F.C. Harkot, Rev. Bras. Geociênc. 20, 329 (1990)

    Google Scholar 

  11. H.A. Oliveira, E.H.L. Fernandes, O.O. Möller, G.L. Collares, Rev. Bras. Recur. Hidricos 20, 34 (2015)

    Google Scholar 

  12. N. Krusche, J.M.B. Saraiva, M.S. Reboita, in Normais Climatológicas Provisórias de 1991 a 2000 Para Rio Grande, RS (Ed. Universitária/UFSM, Santa Maria, 2002)

  13. O.O. Moller, J.A. Lorenzzentti, J. Stech, M.M. Math, Cont. Shelf Res. 16, 335 (1996)

    Article  Google Scholar 

  14. E.H.L. Fernandes, I. Mariño-Tapia, K.R. Dyer, O.O. Möller, Ocean Dyn. 54, 348 (2004)

    Article  Google Scholar 

  15. B.A. Franz, E.J. Kwiatkowska, G. Meister, C.R. McClain, Proc. SPIE 6677, 66770Q (2007)

    Article  Google Scholar 

  16. A. Savtchenko, D. Ouzounov, S. Ahmad, J. Acker, G. Leptoukh, J. Koziana, D. Nickless, Adv. Sp. Res. 34, 710 (2004)

    Article  Google Scholar 

  17. R.B. Sharp, Pestic. Sci. 5, 197 (1974)

    Article  Google Scholar 

  18. J.D.H. Strickland, T.R. Parsons, in Fisheries Research Board of Canada, 2nd edn. (Bulletin 167, Ottawa, 1972)

    Google Scholar 

  19. W.J. Emery, R.E. Thompson, in Data Analysis Methods in Physical Oceanography (Elsevier Science, 1998)

  20. F. Shen, W. Verhoef, Y. Zhou, M.S. Salama, X. Liu, Estuar. Coast. 33, 1420 (2010)

    Article  Google Scholar 

  21. A.C. Vaz, O.O. Möller Jr., T.L. de Almeida, Atlântica 28, 13 (2006)

    Google Scholar 

  22. W.C. Marques, E.H. Fernandes, I.O. Monteiro, O.O. Möller, Cont. Shelf Res. 29, 556 (2009)

    Article  Google Scholar 

  23. S.P. Dinnel, W.W. Schroeder, W.J. Wiseman, J. Coast. Res. 6, 789 (1990)

    Google Scholar 

  24. E.N. de Oliveira, B.A. Knoppers, J.A. Lorenzzetti, P.R.P. Medeiros, M.E. Carneiro, W.F.L. de Souza, Brazilian J. Oceanogr. 60, 283 (2012)

    Article  Google Scholar 

  25. X. Zhang, F. Hu, J. Zhang, D. Tang, Int. J. Remote Sens. 35, 37 (2014)

    Google Scholar 

  26. I.D. Soares, O.O. Möller, Cont. Shelf Res. 21, 1785 (2001)

    Article  Google Scholar 

  27. W.C. Marques, E.H.L. Fernandes, B.C. Moraes, O.O. Möller, A. Malcherek, J. Geophys. Res. Oceans 115, 1 (2010)

    Google Scholar 

  28. V.H. Kourafalou, O. Lie-Yauw, J.D. Wang, T.N. Lee, J. Geophys. Res. 101, C2 (1996)

    Google Scholar 

  29. J.A. Warrick, P.M. DiGiacomo, S.B. Weisberg, N.P. Nezlin, M. Mengel, B.H. Jones, J.C. Ohlmann, L. Washburn, E.J. Terrill, K.L. Farnsworth, Cont. Shelf Res. 27, 19 (2007)

    Article  Google Scholar 

  30. L. Xie, L.J. Pietrafesa, J. Coast. Res. 15, 4 (1999)

    Google Scholar 

  31. Z. Chen, C. Hu, F. Muller-Karger, Remote Sens. Environ. 109, 207 (2007)

    Article  Google Scholar 

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Acknowledgements

The authors are grateful to: the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) under contracts: 456292/2013-6 and 305885/2013-8, and to the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under contract: 77/2010 CII/CGPE/DPB/CAPES. Further acknowledgments go to the Brazilian National Water Agency and to the American National Oceanic and Atmospheric Administration for supplying the fluvial discharge and wind datasets, respectively; and to the National Aeronautics and Space Administration for maintaining and distributing the MODIS/Aqua dataset. Although some data were taken from governmental databases, this paper is not necessarily representative of the views of the government.

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Authors and Affiliations

  1. Institute of Mathematics, Statistics and Physics, Federal University of Rio Grande, Avenida Itália, km 8, Rio Grande, Rio Grande do Sul, 96201-900, Brazil

    Juliana Costi & Wiliam Correa Marques

  2. Institute of Oceanography, Federal University of Rio Grande, Rio Grande, Rio Grande do Sul, Brazil

    Bruno Correa Moraes

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  1. Juliana Costi
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  2. Bruno Correa Moraes
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  3. Wiliam Correa Marques
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Correspondence to Juliana Costi.

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Costi, J., Moraes, B.C. & Marques, W.C. A regional algorithm for investigating the Patos Lagoon coastal plume using Aqua/MODIS and oceanographic data. Mar Syst Ocean Technol 12, 166–177 (2017). https://doi.org/10.1007/s40868-017-0032-4

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