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Granulometry of Mangrove Sediments

  • Gautam Kumar Das
Chapter
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Part of the Coastal Research Library book series (COASTALRL, volume 11)

Abstract

The grain size analyses of estuarine sediments give an idea of the depositional environment in the estuaries. Values of graphic mean size, median, standard deviation, kurtosis and skewness are determined from the cumulative curves drawn by plotting size values. The statistical size parameters of the Sunderbans estuarine sediments indicate that the estuarine banks, flanks of the mid channel bars and point bars where depositional energy is low, are characterised by muddy sediments.

Keywords

Sunderbans estuary Grain size Mean Median Standard deviation Kurtosis Skewness Cumulative curves 

References

  1. Benson DJ (1981) Textural analyses with Texus Instruments 59 programmable calculator. J Sediment Petrol 51(2):61–62CrossRefGoogle Scholar
  2. Blott SJ, Pye K (2001) GRADISTAT: a grain size distribution and statistics package for the analysis of unconsolidated sediments. Earth Surf Process Landf 26:1237–1248CrossRefGoogle Scholar
  3. Coulter Electronics, Inc. (1989) Coulter Multisizer AccuComp color software: reference manual. HialeahGoogle Scholar
  4. Das GK (2009) Grain size analysis of some beach sands from the Indian Coasts. Geogr Rev India 71(1):10–18Google Scholar
  5. Davis RAD (1983) Depositional systems. Prentice-Hall, INC., Englewood CliffsGoogle Scholar
  6. Folk RL, Ward W (1957) Brazos River bar – a study of the significance of grain size parameters. J Sediment Petrol 27:3–26CrossRefGoogle Scholar
  7. Fuller AO (1961) Size characteristics of shallow marine sands from Cape of Good Hope, South Africa. J Sediment Petrol 31:256–261CrossRefGoogle Scholar
  8. Jones SB, Simpkin P (1970) A computer program for the calculation of hydrometer size analyses. Mar Geol 9:23–29CrossRefGoogle Scholar
  9. Kane WT, Hubert JF (1962) FORTRAN program for the calculation of grain-size textural parameters on the IBM 1620 computer. Sedimentology 2:87–90CrossRefGoogle Scholar
  10. Krumbien PD (1938) Size frequency distributions and the normal phi curve. J Sediment Petrol 8:84–90Google Scholar
  11. Krumbein WC, Pettijhon FJ (1938) Manual of sedimentary petrography. D. Appleton – Century, New YorkGoogle Scholar
  12. Muerdter DR, Dauphin JP, Steele G (1981) An interactive computerized system for grain size analysis of silt using electro-resistance. J Sediment Petrol 51:647–650CrossRefGoogle Scholar
  13. Poppe LJ, Eliason AH, Fredericks JJ (1985) APSAS: an automated particle-size analysis system. U.S. Geological Survey Circular 963Google Scholar
  14. Rigler JK, Collins MB, Williams SJ (1981) A high – precision digital recording sedimentation tower for sands. J Sediment Petrol 51:642–644CrossRefGoogle Scholar
  15. Sawyer MB (1977) Computer program for the calculation of grain-size statistics by the method of moments. U.S. Geological Survey Open File Report, pp 77–580Google Scholar
  16. Schlee J (1966) A modified Woods Hole rapid sediment analyzer. J Sediment Petrol 30:403–413Google Scholar
  17. Schlee J, Webster J (1967) A computer program for grain-size data. Sedimentology 8:45–54CrossRefGoogle Scholar
  18. Spencer DW (1963) The interpretation of grain size distribution curves of clastic sediments. J Sediment Petrol 33:180–190Google Scholar
  19. Syvitski JPM, Asprey KW, Clattenburg DA (1991) Principles, design and calibration of settling tubes. In: Syvitski JPM (ed) Principles, methods and applications of particle size analysis. Cambridge University Press, New York, pp 3–21CrossRefGoogle Scholar
  20. Visher GS (1969) Grain size distributions and depositional processes. J Sediment Petrol 39(3):1074–1106Google Scholar
  21. Zeigler JM, Whitney GG Jr, Hayes CR (1960) Woods Hole rapid sediment analyzer. J Sediment Petrol 30:490–495Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gautam Kumar Das
    • 1
  1. 1.Department of Chemical EngineeringJadavpur UniversityKolkataIndia

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