Editorial Office:
Management:
R. S. Oyarzabal
Technical Support:
D. H. Diaz
M. A. Gomez
W. Abrahão
G. Oliveira
Publisher by Knobook Pub
doi: 10.6062/jcis.2008.01.01.0006(Free PDF)
Enner H. Alcântara
The objective of this paper is to study the turbidity behavior in an Amazon Floodplain Lake. Observations of turbidity provide quantitative information about water quality conditions. However, the number of available in situ measurements of water quality characteristics is usually limited, especially temporal series variables and synoptic coverage of extensive water body. In order to contribute to the study of turbidity we present two approaches: (i) the first is based on wavelet analysis of a turbidity time series measured by an automatic monitoring system; (ii) the second is based on spatially distributed turbidity samples analized by Ordinary Kriging algorithm. The main results are: the space/time turbidity variability is related to Amazon river flood pulse in the floodplain; during the rising and receding water stages, the water exchange between Amazon river and floodplain is the major driven force in turbidity variability; during the high water level, the lake bathymetry controls turbidity variability; and during the low water level, the wind intensity and lake morphometry are the main causes of turbidity variability. The joint use of temporal and spatial data showed a great potential for understanding the turbidity behavior in a complex aquatic system, like the Amazon floodplain.
Turbidity, Amazon Floodplain, Geostatistics, Spatial Modeling, Limnology.
ALCÂNTARA EH. 2006. Análise da Turbidez na Planície de Inundação de Curuaí (PA, Brasil) Integrando Dados Telemétricos e Imagens MODIS/Terra. (MSc. Dissertation) - Instituto Nacional de Pesquisas Espaciais - (INPE), São José dos Campos, Brazil.
ALCÂNTARA EH, STECH JL, NOVO EMLM, SHIMABUKURO YE &BARBOSA CCF. (in press ). Turbidity in the Amazon floodplain assessed through a spatial regression model applied to fraction images derived from MODIS/Terra. IEEE Transactions on Geoscience and Remote Sensing.
BARBOSA CCF. 2005. Sensoriamento remoto da dinâmica de circulação da água do sistema planície de Curuai/Rio Amazonas. (Ph.D. Thesis) - Instituto Nacional de Pesquisas Espaciais - (INPE), São José dos Campos, Brazil.
BELLEHUMEUR C, MARCOTTE D & LEGENDRE P. 2000. Estimation of regionalized phenomena by geostatistical methods: lake acidity on the Canadian Shield. Environmental Geology, 39: 211-220.
BONNET MP, BARROUX G, MARTINEZ JM, SEYLER F, MOREIRATURCQ P, COCHONNEAU G, MELACK JM, BOAVENTURA G, MAURICEBOURGOIN L, LEÓN JG, ROUX E, CALMANT S, KOSUTH P, GUYOT JL & SEYLER P. 2008. Floodplain hydrology in an Amazon floodplain lake (Lago Grande de Curuaí). Journal of Hydrology, 349: 18-30. doi: 10.1016/j.jhydrol.2007.10.055
BOOTH JG, MILLER RL, McKEE BA & LEATHERS RA. 2000. Windinduced bottom sediment resuspension in a microtidal coastal environment. Continental Shelf Research, 20: 785-806. doi: 10.1016/S0278-4343(00)00002-9
BOURGOIN LM, BONNET MP, MARTINEZ JM, KOSUTH P, COCHONNEAU G, MOREIRA-TURCQ ??, GUYOT JL, VAUCHEL P, FILIZOLA N &SEYLER P. 2007. Temporal dynamics of water and sediment exchanges between the Curuaí floodplain and the Amazon River, Brazil. Journal of Hydrology, 335: 140-156. doi: 10.1016/j.jhydrol.2006.11.023
BURROUGH PA. & McDONNELL RA. 1998. Principles of geographical information systems. New York: Oxford University Press.
BURROUGH PA. 2001. GIS and Geostatistics: Essential partners for spatial analysis. Environmental and Ecological Statistics, 8: 361-377. doi: 10.1023/A:1012734519752
CARPER GL & BACHMANN RW. 1984. Wind resuspension of sediments in a prairie lake. Can. J. Fish. Aquat. Sci., 41: 1763-1767. doi: 10.1139/f84-217
CÓZAR A, GÁLVEZ JA, HULL V, GARCÍA CM & LOISELLE SA. 2005. Sediment resuspension by Wind in a shallow lake of Esteros Del Iberá (Argentina): a model based on turbidimetry. Ecological Modelling, 186:63-76. doi: 10.1016/j.ecolmodel.2005.01.020
DAUBECHIES I. 1990. The wavelet transform, time-frequency location and signal analysis. IEEE Transactions on Information Theory, 36:961-1005. doi: 10.1109/18.57199
DEKKER AG, VOS RJ & PETERS SWM. 2002. Analytical algorithms for lake water TSM estimation for retrospective analyses of TM and SPOT sensor data. International Journal of Remote Sensing, 23: 15-35. doi: 10.1080/01431160010006917
FARGE M. 1992. Wavelet transforms and their applications to turbulence. Ann. Rev. Fluid Mech., 24: 395-457. doi: 10.1146/annurev.fl.24.010192.002143
GAUCHEREL C. 2002. Use of wavelet transform for temporal characterisation of remote watersheds. Journal of Hydrology, 269: 101-121. doi: 10.1016/S0022-1694(02)00212-3
GEORGE DG. 1997. The airborne remote sensing of phytoplankton chlorophyll in the lakes and tarns of the English Lake District. International Journal of Remote Sensing, 18: 1961-1975. doi: 10.1080/014311697217972
GLASGOW HB, BURKHOLDER JM, REED RE, LEWITUS AJ & KLEINMANN JE. 2004. Real-time remote monitoring of water quality: a review of current applications, and advancements in sensor, telemetry, and computing technologies. Journal of Experimental Marine Biology and Ecology, 300: 409-448. doi: 10.1016/j.jembe.2004.02.022
GOOVAERTS P. 1997. Geostatistics for natural resources evaluation. New York: Oxford University Press.
HEDGER RD, ATKINSON PM & MALTHUS TJ. 2001. Optimizing sampling strategies for estimating mean water quality in lakes using geostatistical techniques with remote sensing. Lakes & Reservoirs: Research and Management, 6: 279-288. doi: 10.1046/j.1440-1770.2001.00159.x
ISAAKS EH & SRIVASTAVA MR. 1989. An introduction to applied geostatistics. New York: Oxford University Press, 561 p.
JEROSCH K, SCHLUTERM& PESCH R. 2006. Spatial analysis of marine categories information using indicator Kriging applied to georeferenced video mosaics of the deep-sea Hâkon Mosby Mud Volcano. Ecological Informatics, 1: 391-406. doi: 10.1016/j.ecoinf.2006.05.003
JUNK WJ. 1997. The Central Amazon Floodplain: ecology of a pulsing system. Berlin: Springer Verlag.
KUMAR P & FOUROULA-GEORGIOU E. 1997. Wavelet analysis for geophysical application. Reviews of Geophysics, 35: 385-412.
MASSEI N, DUPONT JP, MAHLER BJ, LAIGNEL B, FOURNIER M, VALDES D & OGIER S. 2006. Investigating transport properties and turbidity dynamics of a karst aquifer using correlation, spectral, and wavelet analyses. Journal of Hydrology, 329: 244-257. doi: 10.1016/j.jhydrol.2006.02.021
MEYERS SD, KELLY BG & OBRIEN JJ. 1993. An introduction to wavelet analysis in Oceanography and Meteorology: with application to the dispersion of Yanai Waves. Mon. Wea. Rev., 121: 2858-2866.
MOREIRA-TURCQ PF, JOUANNEAU B, TURCQ B, SEYLER P, WEBER O & GUYOT JL. 2004. Carbon sedimentation at Lago Grande de Curuaí, a floodplain lake in the low Amazon region: insight into sedimentation rates. Palaeogeography, Palaeoclimatology, Palaeoecology, 214: 27-70. doi: 10.1016/j.palaeo.2004.06.013
NAKKEN M. 1999. Wavelet analysis of rainfall-runoff variability isolating climatic from anthropogenic patterns. Environmental Modelling & Software, 14: 283-295. doi: 10.1016/S1364-8152(98)00080-2
LOU J, SCHWAB DJ, BELETSKY D & HAWLEY N. 2000. A model of sediment resuspension and transport dynamics in southern Lake Michigan. Journal of Geophysical Research, 105: 6591-6610. doi: 10.1029/1999JC900325
STECH JL, LIMA IBT, NOVO EMLM, SILVA CM, ASSIREU AT, LORENZZETTI JA, CARVALHO JC, BARBOSA CCF & ROSA RR. 2006. Telemetric Monitoring System for meteorological and limnological data acquisition. Verh. Internat. Verein. Limnol., 29: 1747-1750.
TYLER AN, SVAB E, PRESTON E, PRŽESING M & KOVŽACS WA. 2006. Remote sensing of the water quality of shallow lakes: A mixture modelling approach to quantifying phytoplankton in water characterized by high-suspended sediment. International Journal of Remote Sensing, 27: 1521-1537. doi: 10.1080/01431160500419311
TORRENCE C & COMPO GP. 1998. A Practical Guide to Wavelet Analysis. Bull. Amer. Meteor. Soc., 79: 61-78.
U.S. ARMY COASTAL ENGINEERING CENTER - CERC. 1984. Shore protection manual. 41: pp. 603.
ZHANG Y, PULLIAINEN JT, KOPONEN SS & HALLIKAINEN MT. 2003. Water quality retrievals from combined Landsat TM data and ERS-2 data in the Gulf of Finland. IEEE Transactions on Geoscience and Remote Sensing, 41: 622-629. doi: 10.1109/TGRS.2003.808906