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Ocean Dynamics

, Volume 55, Issue 1, pp 2–9 | Cite as

Synergy of satellite remote sensing and numerical modeling for monitoring of suspended particulate matter

  • Andrey Pleskachevsky
  • Gerhard Gayer
  • Jochen Horstmann
  • Wolfgang Rosenthal
Original paper

Abstract

Monitoring and modeling of the distribution of suspended particulate matter (SPM) is an important task, especially in coastal environments. Several SPM models have been developed for the North Sea. However, due to waves in shallow water and strong tidal currents in the southern part of the North Sea, this is still a challenging task. In general there is a lack of measurements to determine initial distributions of SPM in the bottom sediment and essential model parameters, e.g., appropriate exchange coefficients. In many satellite-borne ocean color images of the North Sea a plume is visible, which is caused by the scattering of light at SPM in the upper ocean layer. The intensity and length of the plume depends on the wave and current climate. It is well known that the SPM plume is especially obvious shortly after strong storm events. In this paper a quasi-3-D and a 3-D SPM transport model are presented. Utilizing the synergy of satellite-borne ocean color data with numerical models, the vertical exchange coefficients due to currents and waves are derived. This results in models that for the first time are able to reproduce the temporal and spatial evolution of the plume intensity. The SPM models consist of several modules to compute ocean dynamics, the vertical and horizontal exchange of SPM in the water column, and exchange processes with the seabed such as erosion, sedimentation, and resuspension. In the bottom layer, bioturbation via benthos and diffusion processes is taken into account.

Keywords

Suspended particulate matter Transport model Exchange processes Synergy of modelling and remote sensing Ocean colour remote sensing 

Notes

Acknowledgements

The authors would like to thank the Federal Maritime and Hydrographic Agency of Germany (BSH) and the German Weather Service (DWD) for providing wave, wind, and SPM bottom data. Special thanks to R. Doerffer from the GKSS Research Center and to A. Neumann, M. Hetscher, and H. Krawczyk from the German Aerospace Center for providing the ocean surface SPM concentration data derived from satellite-borne ocean color data. We would also like to thank S. Dick from the BSH for the fruitful discussions on SPM transport modeling.

References

  1. Albrecht H (1993) Kontamination der Sedimente, In: Geht es der Nordsee besser? SDN-Colloquium October 1992, Schriftenreihe der Schutzgemeinschaft Deutsche Nordseeküste e.V., ISSN 0943-9552, pp 59–82Google Scholar
  2. Bouws E, Günther H, Rosenthal W, Vincent CL (1985) Similarity of the wind wave spectrum in finite depth water. 1 Spectral form. J Geo Res 90(C1):975–986Google Scholar
  3. Casuli V, Gattani E (1994) Stability, accuracy and efficiency of a semi-implicit method for three-dimensional shallow water flow. Computers Math Applic 27(4):99–112Google Scholar
  4. Doerffer R, Fischer J (1994) Concentrations of chlorophyll, suspended matter and gelbstoff in case-II waters derived from satellite coastal zone colour scanner data with inverse modelling methods. J Geoph Res 99:745–7466Google Scholar
  5. Dyer KR, Moffat TJ (1998) Fluxes of suspended matter in the East Anglian plume southern North Sea. Continental Shelf Res 18:1311–1331Google Scholar
  6. Günther H, Rosenthal W, Weare TJ, Worthington BA, Hasselman K, Ewig JA (1979) A hybrid parametrical wave prediction model. J Geoph Res 84:5727–5738Google Scholar
  7. Günther H, Hasselmann S, Janssen PAEM (1992) The WAM Model Cycle-4.0, user manual, Deutsche Klimarechenzentrum, Technical ReportGoogle Scholar
  8. Hetscher M, Krawczyk H, Neumann A, Walzel T, Zimmermann G (1998) Capabilities for the retrieval of coastal water constituents (case II) using multispectral satellite data. Int Symposium on Remote Sensing, Barcelona, Spain. Proc. SPIE, 3496Google Scholar
  9. Holligan PM, Aarup T, Groom SB (1989) The North Sea satellite colour atlas. Continental Shelf Research 9:665–765Google Scholar
  10. Irion G, Müller G (1990) Lateral distribution and sources of sediment-associated heavy metals in the North Sea. In: Ittekot V, Kempe S, Michaelis W, Spitzy A (eds) Facets of modern biogeochemistry. Springer, Berlin Heidelberg New York, pp 175–201Google Scholar
  11. Müller-Navarra SH, Huber K, Komo H (1999) Model simulations of the transport of Odra flood water through the Szczecin Lagoon into the Pomerian Bight in July/August 1997. Acta Hydrochim Hydrobiol 27(5):364–373Google Scholar
  12. Odd NVM, Murphy DG (1992) Calibration of a 20-km grided 3D model simulating a representative annual cycle of mud transport, particulate pollutants in the North Sea. Wallingford HR, Report SR 292, p 15Google Scholar
  13. Pleskachevsky A, Horstmann J, Gayer G, Rosenthal W (2002) Synergy of remote sensing and numerical modeling for suspended matter transport monitoring. In: Proceedings of Symposium of the International Geoscience and Remote Sensing Toronto, CanadaGoogle Scholar
  14. Pohlmann T, Puls W (1994) Currents and transport in water. In: Sündermann J (ed.) Circulation and contaminant fluxes in the North Sea. Springer Berlin Heidelberg New York, pp 345–402Google Scholar
  15. Puls W, Doerffer R, Sündermann J (1994) Numerical simulation and satellite observations of suspended matter in the North Sea. IEEE J Oceanic Eng 19(1):3–9Google Scholar
  16. Puls W, Pohlmann T, Sündermann J (1997) Suspended particulate matter in the southern North Sea: application of a numerical model to extend NERC North Sea project data interpretation. Dt Hydr Z 49(2/3):307–327Google Scholar
  17. Soulsby R (1997) Dynamics of marine sands. A manual for practical application. Thomas Telford Services Ltd, LondonGoogle Scholar
  18. ZISCH (1988) Zirkulation und Schadstoffumsatz in der Nordsee. BMBF Project, MFU 0545, Final Report, p 323Google Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • Andrey Pleskachevsky
    • 1
  • Gerhard Gayer
    • 1
  • Jochen Horstmann
    • 1
  • Wolfgang Rosenthal
    • 1
  1. 1.Institute for Coastal ResearchGKSS Research CenterGeesthachtGermany

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