Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 14 2 2010 10.5194/hess-14-351-2010 http://www.hydrol-earth-syst-sci.net/14/351/2010/ http://www.hydrol-earth-syst-sci.net/14/351/2010/hess-14-351-2010.html http://www.hydrol-earth-syst-sci.net/14/351/2010/hess-14-351-2010.pdf 351 364 2010-02-22 A contribution to understanding the turbidity behaviour in an Amazon floodplain E. Alcântara enner@dsr.inpe.br E. Novo J. Stech J. Lorenzzetti C. Barbosa A. Assireu A. Souza Brazilian Institute for Space Research, Remote Sensing Division, P.O. Box 12227-010, São José dos Campos, SP, Brazil Brazilian Institute for Space Research, Image Processing Division, P.O. Box 12227-010, São José dos Campos, SP, Brazil ETEP Faculdades, P.O. Box 12242-800, São José dos Campos, SP, Brazil Observations of turbidity provide quantitative information about water quality. However, the number of available in situ measurements for water quality determination is usually limited in time and space. Here, we present an analysis of the temporal and spatial variability of the turbidity of an Amazon floodplain lake using two approaches: (1) wavelet analysis of a turbidity time series measured by an automatic monitoring system, which should be improved/simplified, and (2) turbidity samples measured in different locations and then interpolated using an ordinary Kriging algorithm. The spatial and temporal variability of turbidity are clearly related to the Amazon River flood pulses in the floodplain. When the water level in the floodplain is rising or receding, the exchange between the Amazon River and the floodplain is the major driving force in turbidity variability. At high-water levels, turbidity variability is controlled by Lake Bathymetry. When the water level is low, wind action and Lake Morphometry are the main causes of turbidity variability. The combined use of temporal and spatial data shows a good potential for better understanding of the turbidity behaviour in a complex aquatic system such as the Amazon floodplain. Alcântara, E. H.: Analysis of turbidity in Curuai floodplain through the integration of telemetric and MODIS/Terra image data (MSc. Dissertation), INPE: São José dos Campos, Brazil, 220~pp., 2006 (in Portuguese). Alcântara, E. H., Stech, J. L., Novo, E. M. L. M., Shimabukuro, Y. E., and Barbosa, C. C. F.: Turbidity in the Amazon floodplain assessed through a spatial regression model applied to fraction images derived from MODIS/Terra. IEEE Trans. Geo. Rem. Sens. 46, 2895–2905, 2008. Alcântara, E. H., Barbosa, C. C. F., Stech, J. L., Novo, E. M. L. M., and Shimabukuro, Y. E.: Improving the spectral unmixing algorithm to map water turbidity distributions. Environ. Modell. Softw., 24, 1051–1061, 2009. Barbosa, C. C. F.: Sensoriamento remoto da dinâmica de circulação da água do sistema planície de Curuai/ Rio Amazonas (PhD. Thesis), INPE: São José dos Campos, Brazil, 255~pp., 2005. Barroux, G.: Bio-geochemical study of a lake system from the Amazonian floodplain: the case of "Lago Grande de Curuaí", Pará-Brazil (PhD Thesis), UPS: Toulouse, France , 304~pp., 2006 (in French). Bellehumeur, C., Marcotte, D., and Legendre, P.: Estimation of regionalized phenomena by geostatistical methods: lake acidity on the Canadian Shield, Environ. Geol., 39, 211–220, 2000. Bonnet, M. P., Barroux, G., Martinez, J. M., Seyler, F., Moreira-Turcq, P., Cochonneau, G., Melack, J. M., Boaventura, G., Maurice-Bourgoin, L., León, J. G., Roux, E., Calmant, S., Kosuth, P., Guyot, J. L., and Seyler, P.: Floodplain hydrology in an Amazon floodplain lake (Lago Grande de Curuaí), J. Hydrol., 349, 18–30, 2008. Booth, J. G., Miller, R. L., McKee, B. A., and Leathers, R. A.: Wind-induced bottom sediment resuspension in a microtidal coastal environment, Cont. Shelf Res., 20, 785–806, 2000. Burrough, P. A.: GIS and Geostatistics: Essential partners for spatial analysis. Environ. Ecol. Stat. 8, 361–377, 2001. Burrough, P. A. and Mcdonnell, R. A.: Principles of geographical information systems, 2rd Ed., Oxford University Press, New York, USA, 356~pp., 1998. Carper, G. L. and Bachmann, R. W.: Wind resuspension of sediments in a prairie lake, Can. J. Fish. Aquat. Sci. 41, 1763–1767, 1984. CERC: Shore protection manual, 1rd Ed, US Army Coastal Engineering Center, Viksburg, USA, 603~pp., 1984. Cózar, A., Gálvez, J. A., Hull, V., García, C. M., and Loiselle, S. A.: Sediment resuspension by Wind in a shallow lake of Esteros Del Iberá (Argentina): a model based on turbidimetry, Ecol. Model. 186, 63–76, 2005. De Leo, G. A. and Ferrari, I.: Disturbance and diversity in a river zooplankton community: a neutral model analysis, Coenoses., 8, 121–129, 1993. Dekker, A. G., Vos, R. J., and Peters, S. W. M.: Analytical algorithms for lake water TSM estimation for retrospective analyses of TM and SPOT sensor data, Int. J. Remote Sens. 23, 15–35, 2002. Farge, M.: Wavelet transforms and their applications to turbulence, Annu. Rev. Fluid Mech. 24, 395–457, 1992. George, D. G.: The airborne remote sensing of phytoplankton chlorophyll in the lakes and tarns of the English Lake District, Int. J. Remote Sens. 18, 1961–1975, 1997. Goovaerts, P.: Geostatistics for natural resources evaluation, Oxford University Press, New York, USA, 483~pp., 1997. Grinsted, A., Moore, J. C., and Jevrejeva, S.: Application of the cross wavelet transform and wavelet coherence to geophysical time series, Nonlinaer Proc. Geoph. 11, 561–566, 2004. Han, L. and Rundquist, D. C.: The impact of a wind-roughened water surface on remote measurements of turbidity, Int. J. Remote Sens. 19, 195–201, 1998. Hedger, R. D., Atkinson, P. M., and Malthus, T. J.: Optimizing sampling strategies for estimating mean water quality in lakes using geostatistical techniques with remote sensing, Lakes & Reservoirs, Res. Manage., 6, 279–288, 2001. Isaaks, E. H. and Srivastava, M. R.: An introduction to applied geostatistics, Oxford University Press, New York, USA, 561~pp., 1989. Jerosch, K., Schlüter, M., and Pesch, R.: Spatial analysis of marine categories information using indicator Kriging applied to georeferenced video mosaics of the deep-sea Håkon Mosby Mud Volcano, Ecol. Inform., 1, 391–406, 2006. Junk, W. J.: The Central Amazon Floodplain: ecology of a pulsing system, 1rd Ed., Springer Verlag, Berlin, Germany, 525~pp., 1997. Justus, C. G. and Mikhail, A.: Height variation of wind speed and wind distribution statistics, Geophys. Res. Lett., 3, 264–264, 1976. Kirk, J. T. O.: Light and photosynthesis in aquatic environments, 1rd Ed., Cambridge University Press, Cambridge, USA, 401~pp., 1983. Kumar, P. and Foufoula-Georgiou, E.: Wavelet analysis for geophysical application, Rev. Geophys., 35, 385–412, 1997. Lima, I. B. T., Carvalho, J. C., Ramos, F. M., Rosa, R. R., Sych, R. A., and Novo, E. L. M. M.: Detecting climatic and tidal influence on the Amazon River level by wavelet analysis, Int. Ver. The., 29, 1785–1788, 1995. Lou, J., Schwab, D. J., Beletsky, D., and Hawley, N.: A model of sediment resuspension and transport dynamics in southern Lake Michigan, J. Geophys. Res., 105, 6591–6610, 2000. Maia, P. D., Maurice, L., Cossa, D., Portugal, R. A., Etcheber, H., Souza, J. R., Guimarães, E. M., and Boaventura, G. R.: Is the Curuai floodplain (Middle Amazon, Brazil) an efficient trap for particulate mercury?, Geophys. Res. Abstr., 10, 12238, 2008. Martinez, J.-M. and Le-Toan, T.: Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data, Remote Sens. Environ. 108, 209–223, 2006. Maraun, D. and Kurths, J.: Cross wavelet analysis: significance testing and pitfalls, Nonlinear Proc. Geophy., 11, 505–514, 2004. Massei, N., Dupont, J. P., Mahler, B. J., Laignel, B., Fournier, M., Valdes, D., and Ogier, S.: Investigating transport properties and turbidity dynamics of a karst aquifer using correlation, spectral, and wavelet analyses, J. Hydrol., 329, 244–257, 2006. Maurice-Bourgoin, L., Bonnet, M. P., Martinez, J. M., Kosuth, P., Cochonneau, G., Moreira-Turcq, P., Guyot, J. L., Vauchel, P., Filizola, N., and Seyler, P.: Temporal dynamics of water and sediment exchanges between the Curuaí floodplain and the Amazon River, Brazil, J. Hydrol., 335, 140–156, 2007. Meade, R. H., Dunne, T., Richey, J. E., Santos, U. M., and Salati, E.: Storage and remobilization of suspended sediment in the lower Amazon River of Brazil, Science, 228, 488–490, 1985. Moreira-Turcq, P. F., Jouanneau, B., Turcq, B., Seyler, P., Weber, O., and Guyot, J. L.: Carbon sedimentation at Lago Grande de Curuaí, a floodplain lake in the low Amazon region: insight into sedimentation rates, Palaeogeogr. Palaeocl., 214, 27–70, 2004. Meyers, S. D., Kelly, B. G., and O'Brien, J. J.: An introduction to wavelet analysis in Oceanography and Meteorology: with application to the dispersion of Yanai Waves, Mon. Weather Rev., 121, 2858–2866, 1993. Mertes, L. A. K., Dunne, T., and Martinelli, L. A.: Channel-floodplain geomorphylogy along the Solimões-Amazon River, Brazil, GSA Bulletin, 108, 1089–1107, 1996. Miquelis, A., Rougier, C., and Pourriot, R.: Impact of turbulence and turbidity on the grazing rate of the rotifer Brachionus calyciflorus (Pallas), Hydrobiologia, 386, 203–211, 1998. Newcombe, C. P. and Jensen, J. O. T.: Channel suspended sediment and fisheries: a synthesis for quantitative assessment of risk and impact, N. Am. J. Fish. Manage., 16, 693–727, 1996. Novo, E. L. M. M., Barbosa, C. C. F., Freitas, R. M., Shimabukuro, Y. E., Melack, J. M., and Pereira-Filho, W.: Seasonal changes in chlorophyll distribution in Amazon floodplain lakes derived from MODIS images, Limnology, 7, 153–161, 2006. Press, W. H., Teukolsky, S. A., Vetterling, W. T., and Flannery, B. P.: Numerical recipes in fortran 77: the art of scientific computing. Vol. 1 of Fortran numerical recipes, Cambridge University Press, UK, 933~pp., 1992. Roozen, F. C. J. M., Van-Geest, G. J., Ibelings, B. W., Roijackers, R., Scheffer, M., and Buijse, A. D.: Lake age and water level affect the turbidity of floodplain lakes along the lower Rhine, Freshwater Biol., 48, 519–531, 2003. Stech, J. L. and Lorenzzetti, J. A.: The response of the south Brazil bight to the passage of wintertime cold fronts, J. Geophys. Res., 97, 9507–9520, 1992. Stech, J. L., Lima, I. B. T., Novo, E. M. L. M., Silva, C. M., Assireu, A. T., Lorenzzetti, J. A., Carvalho, J. C., Barbosa, C. C. F., and Rosa, R. R.: Telemetric Monitoring System for meteorological and limnological data acquisition, Verh. Internat. Verein. Limnol. 29, 1747–1750, 2006. Stevens, C. and Imberger, J.: The initial response of a stratified lake to a surface shear stress, J. Fluid Mech. 312, 39–66, 1996. Tundisi, J. G., Matsumura-Tundisi, T., Arantes-Junior, J. D., Tundisi, J. E. M., Manzini, N. F., and Ducrot, R.: The response of Carlos Botelho (Lobo, Broa) reservoir to the passage of cold fronts as reflected by physical, chemical and biological variables, Braz. J. Biol., 64, 177–186, 2004. Torrence, C. and Compo, G. P.: A Practical Guide to Wavelet Analysis, B. Am. Meteorol. Soc., 79, 61–78, 1998. Torrence, C. and Webster, P.: Interdecadal changes in the ENSO-Monsoon system, J. Climate. 12, 2679–2690, 1999. Tyler, A. N., Svab, E., Preston, E., Présing, M., and Kovács, W. A.: Remote sensing of the water quality of shallow lakes: A mixture modelling approach to quantifying phytoplankton in water characterized by high-suspended sediment, Int. J. Remote. Sens., 27, 1521–1537, 2006. Valdés-Galicia, J. F. and Velasco, V. M.: Variations of mid-term periodicities in solar activity physical phenomena, Adv. Space Res., 41, 297–305, 2008. Wetzel, R. G.: Limnology – Lake and River Ecosystems, 3rd Ed., Academic Press, San Diego, USA, 1006~pp., 2001. Zhang, Y., Pulliainen, J. T., Koponen, S. S., and Hallikainen, M. T.: Water quality retrievals from combined Landsat TM data and ERS-2 data in the Gulf of Finland, IEEE Trans. Geosci. Remote, 41, 622–629, 2003.