| The multicoloured North Sea |
Funder identifier: T4/DD/44 (Other contract id)
Period: December 1996 till March 1999
Status: Completed
Thesaurus terms Chlorophylls; Eutrophication; Models; Nutrients (mineral); Remote sensing; Suspended matter
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| Institutes (2) |
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- Koninklijk Belgisch Instituut voor Natuurwetenschappen; Departement Beheer van het Mariene Ecosysteem; Beheerseenheid Mathematisch Model Noordzee en Schelde-estuarium; Brussel (KBIN-BMM), more
- Belgian Science Policy (BELSPO), more, sponsor
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| Abstract |
The main goals of the proposal are to take advantage of the information available from ocean colour remote sensing satellites, to calibrate them in function of the specificities of the Belgian coastal waters, to use them in conjunction with biological models, and so to bring in elements of scientific answers to the debate presently held between riparian North Sea states about eutrophication problems, their geographical extension and the actions that have to be taken.
The proposal is composed of two main research packages:
* In the first part we will develop state-of-the-art algorithms to extract chlorophyll, suspended matter and gelbstoff concentration from the measurements that will be made by the Sea-viewing Wide Field-of-view Sensor (SeawiFs) to be launched by NASA in early 1997 (we will also use the public domain remotely sensed AHVRR data, processed to give "turbidity index"). These algorithms will be specifically tailored to the Belgian coastal zone and calibrated, i.e. the free constants of (possibly modified) algorithms developed by NASA and other groups will be determined using seaborne measurements. The most promising algorithms will then be compared to available in situ measurements so that their accuracy can be quantified.
* The best of them will be applied to a series of SeawiFs images, approximately covering a one-year period. The observed spatial structures of chlorophyll will be interpreted using numerical simulations made with a coupled physical/biological model in order to explain these distributions in terms of physical and biological processes and to improve the model validation. |
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